Microphysical Processes - Radar Profiles#
import datetime as dt
import matplotlib.pyplot as plt
import numpy as np
import xarray as xr
import radarpolarimetry as rp
Preparation#
zlevels = rp.visdict14["ZH"]["ticks"]
zdrlevels = rp.visdict14["ZDR"]["ticks"]
rholevels = rp.visdict14["RHO"]["ticks"]
kdplevels = rp.visdict14["KDP"]["ticks"]
philevels = rp.visdict14["PHI"]["ticks"]
levels = lambda x: dict(levels=x, cbar_kwargs=dict(ticks=x))
Event 1#
Vertical Profile - VP#
22.06.2011 09:00 - 14:30 UTC
scan: ‘vertical_scan’
zh_offset: -2.5
zdr_offset: -0.8
zh_offset = -2.5
zdr_offset = -0.8
start_time = dt.datetime(2011, 6, 22, 9)
stop_time = dt.datetime(2011, 6, 22, 14, 30)
delta = stop_time - start_time
loc = "boxpol"
scan = "vertical_scan"
Open dataset (VP)#
reindex_angle = dict(start_angle=0, stop_angle=360, angle_res=1.0, direction=1)
sweep_vp_1 = rp.load_timeseries_sweep(
start_time, delta, scan, reindex_angle=reindex_angle
)
display(sweep_vp_1)
loading 66 files
<xarray.Dataset> Size: 2GB
Dimensions: (time2: 66, azimuth: 360, range: 2000)
Coordinates:
* azimuth (azimuth) float64 3kB 0.5 1.5 2.5 ... 357.5 358.5 359.5
elevation (azimuth) float64 3kB dask.array<chunksize=(360,), meta=np.ndarray>
time (time2, azimuth) datetime64[ns] 190kB dask.array<chunksize=(1, 360), meta=np.ndarray>
* range (range) float32 8kB 12.5 37.5 ... 4.996e+04 4.999e+04
longitude float64 8B 7.072
latitude float64 8B 50.73
altitude float64 8B 99.5
Dimensions without coordinates: time2
Data variables: (12/18)
KDP (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
PHIDP (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
DBZH (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
DBZV (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
RHOHV (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
DBTH (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
... ...
sweep_mode (time2) <U20 5kB 'azimuth_surveillance' ... 'azimuth_s...
sweep_number (time2) int64 528B 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0
prt_mode (time2) <U7 2kB 'not_set' 'not_set' ... 'not_set'
follow_mode (time2) <U7 2kB 'not_set' 'not_set' ... 'not_set'
sweep_fixed_angle (time2) float64 528B 90.0 90.0 90.0 ... 90.0 90.0 90.0
nyquist_velocity (time2) object 528B None None None ... None None None
Attributes:
source: gamic
pulse_width: 1xarray.Dataset
- time2: 66
- azimuth: 360
- range: 2000
- azimuth(azimuth)float640.5 1.5 2.5 ... 357.5 358.5 359.5
- standard_name :
- ray_azimuth_angle
- long_name :
- azimuth_angle_from_true_north
- units :
- degrees
- axis :
- radial_azimuth_coordinate
array([ 0.5, 1.5, 2.5, ..., 357.5, 358.5, 359.5], shape=(360,))
- elevation(azimuth)float64dask.array<chunksize=(360,), meta=np.ndarray>
- standard_name :
- ray_elevation_angle
- long_name :
- elevation_angle_from_horizontal_plane
- units :
- degrees
- axis :
- radial_elevation_coordinate
Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Dask graph 1 chunks in 325 graph layers Data type float64 numpy.ndarray - time(time2, azimuth)datetime64[ns]dask.array<chunksize=(1, 360), meta=np.ndarray>
- standard_name :
- time
Array Chunk Bytes 185.62 kiB 2.81 kiB Shape (66, 360) (1, 360) Dask graph 66 chunks in 195 graph layers Data type datetime64[ns] numpy.ndarray - range(range)float3212.5 37.5 ... 4.996e+04 4.999e+04
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 25.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 12.5
array([1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04], shape=(2000,), dtype=float32) - longitude()float647.072
- long_name :
- longitude
- units :
- degrees_east
- standard_name :
- longitude
array(7.071663)
- latitude()float6450.73
- long_name :
- latitude
- units :
- degrees_north
- positive :
- up
- standard_name :
- latitude
array(50.73052)
- altitude()float6499.5
- long_name :
- altitude
- units :
- meters
- standard_name :
- altitude
array(99.5)
- KDP(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - PHIDP(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - DBZH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - DBZV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - RHOHV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - DBTH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - DBTV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - VRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - VRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - WRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - WRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - ZDR(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - sweep_mode(time2)<U20'azimuth_surveillance' ... 'azim...
array(['azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance', 'azimuth_surveillance'], dtype='<U20') - sweep_number(time2)int640 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) - prt_mode(time2)<U7'not_set' 'not_set' ... 'not_set'
array(['not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set'], dtype='<U7') - follow_mode(time2)<U7'not_set' 'not_set' ... 'not_set'
array(['not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set'], dtype='<U7') - sweep_fixed_angle(time2)float6490.0 90.0 90.0 ... 90.0 90.0 90.0
array([90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90.]) - nyquist_velocity(time2)objectNone None None ... None None None
- standard_name :
- nyquist_velocity
- units :
- m s-1
array([None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None], dtype=object)
- source :
- gamic
- pulse_width :
- 1
sweep_vp_1 = sweep_vp_1.set_coords("sweep_mode")
sweep_vp_1["sweep_mode"] = sweep_vp_1["sweep_mode"][0]
sweep_vp_1 = sweep_vp_1.wrl.georef.georeference()
sweep_vp_1 = sweep_vp_1.assign_coords(height=sweep_vp_1.z.mean("azimuth"))
display(sweep_vp_1)
<xarray.Dataset> Size: 2GB
Dimensions: (time2: 66, azimuth: 360, range: 2000)
Coordinates: (12/16)
* azimuth (azimuth) float64 3kB 0.5 1.5 2.5 ... 357.5 358.5 359.5
elevation (azimuth) float64 3kB dask.array<chunksize=(360,), meta=np.ndarray>
time (time2, azimuth) datetime64[ns] 190kB dask.array<chunksize=(1, 360), meta=np.ndarray>
* range (range) float32 8kB 12.5 37.5 ... 4.996e+04 4.999e+04
x (azimuth, range) float64 6MB 2.092e-05 ... -0.08315
y (azimuth, range) float64 6MB 0.002397 0.00719 ... 9.528
... ...
height (range) float64 16kB 112.0 137.0 ... 5.006e+04 5.009e+04
sweep_mode <U20 80B 'azimuth_surveillance'
longitude float64 8B 7.072
latitude float64 8B 50.73
altitude float64 8B 99.5
crs_wkt int64 8B 0
Dimensions without coordinates: time2
Data variables: (12/17)
KDP (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
PHIDP (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
DBZH (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
DBZV (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
RHOHV (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
DBTH (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
... ...
ZDR (time2, azimuth, range) float32 190MB dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
sweep_number (time2) int64 528B 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0
prt_mode (time2) <U7 2kB 'not_set' 'not_set' ... 'not_set'
follow_mode (time2) <U7 2kB 'not_set' 'not_set' ... 'not_set'
sweep_fixed_angle (time2) float64 528B 90.0 90.0 90.0 ... 90.0 90.0 90.0
nyquist_velocity (time2) object 528B None None None ... None None None
Attributes:
source: gamic
pulse_width: 1xarray.Dataset
- time2: 66
- azimuth: 360
- range: 2000
- azimuth(azimuth)float640.5 1.5 2.5 ... 357.5 358.5 359.5
- standard_name :
- ray_azimuth_angle
- long_name :
- azimuth_angle_from_true_north
- units :
- degrees
- axis :
- radial_azimuth_coordinate
array([ 0.5, 1.5, 2.5, ..., 357.5, 358.5, 359.5], shape=(360,))
- elevation(azimuth)float64dask.array<chunksize=(360,), meta=np.ndarray>
- standard_name :
- ray_elevation_angle
- long_name :
- elevation_angle_from_horizontal_plane
- units :
- degrees
- axis :
- radial_elevation_coordinate
Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Dask graph 1 chunks in 325 graph layers Data type float64 numpy.ndarray - time(time2, azimuth)datetime64[ns]dask.array<chunksize=(1, 360), meta=np.ndarray>
- standard_name :
- time
Array Chunk Bytes 185.62 kiB 2.81 kiB Shape (66, 360) (1, 360) Dask graph 66 chunks in 195 graph layers Data type datetime64[ns] numpy.ndarray - range(range)float3212.5 37.5 ... 4.996e+04 4.999e+04
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 25.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 12.5
array([1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04], shape=(2000,), dtype=float32) - x(azimuth, range)float642.092e-05 6.275e-05 ... -0.08315
- axis :
- X
- long_name :
- Easting
- standard_name :
- projection_x_coordinate
- units :
- metre
array([[ 2.09158767e-05, 6.27474452e-05, 1.04578767e-04, ..., 8.30702793e-02, 8.31116231e-02, 8.31529666e-02], [ 6.27412588e-05, 1.88223222e-04, 3.13704446e-04, ..., 2.49185534e-01, 2.49309553e-01, 2.49433571e-01], [ 1.04547529e-04, 3.13641664e-04, 5.22734567e-04, ..., 4.15224884e-01, 4.15431540e-01, 4.15638195e-01], ..., [-1.04547529e-04, -3.13641664e-04, -5.22734567e-04, ..., -4.15224884e-01, -4.15431540e-01, -4.15638195e-01], [-6.27412588e-05, -1.88223222e-04, -3.13704446e-04, ..., -2.49185534e-01, -2.49309553e-01, -2.49433571e-01], [-2.09158767e-05, -6.27474452e-05, -1.04578767e-04, ..., -8.30702793e-02, -8.31116231e-02, -8.31529666e-02]], shape=(360, 2000)) - y(azimuth, range)float640.002397 0.00719 ... 9.524 9.528
- axis :
- Y
- long_name :
- Northing
- standard_name :
- projection_y_coordinate
- units :
- metre
array([[2.39672207e-03, 7.19014504e-03, 1.19835398e-02, ..., 9.51891118e+00, 9.52364870e+00, 9.52838620e+00], [2.39599201e-03, 7.18795485e-03, 1.19798895e-02, ..., 9.51601162e+00, 9.52074770e+00, 9.52548376e+00], [2.39453210e-03, 7.18357515e-03, 1.19725900e-02, ..., 9.51021340e+00, 9.51494660e+00, 9.51967976e+00], ..., [2.39453210e-03, 7.18357515e-03, 1.19725900e-02, ..., 9.51021340e+00, 9.51494660e+00, 9.51967976e+00], [2.39599201e-03, 7.18795485e-03, 1.19798895e-02, ..., 9.51601162e+00, 9.52074770e+00, 9.52548376e+00], [2.39672207e-03, 7.19014504e-03, 1.19835398e-02, ..., 9.51891118e+00, 9.52364870e+00, 9.52838620e+00]], shape=(360, 2000)) - z(azimuth, range)float64112.0 137.0 ... 5.006e+04 5.009e+04
- standard_name :
- height_above_ground
- units :
- metre
array([[ 111.99999977, 136.99999931, 161.99999885, ..., 50036.9990844 , 50061.99908605, 50086.99908946], [ 111.99999977, 136.99999931, 161.99999885, ..., 50036.9990844 , 50061.99908605, 50086.99908946], [ 111.99999977, 136.99999931, 161.99999885, ..., 50036.9990844 , 50061.99908605, 50086.99908946], ..., [ 111.99999977, 136.99999931, 161.99999885, ..., 50036.9990844 , 50061.99908605, 50086.99908946], [ 111.99999977, 136.99999931, 161.99999885, ..., 50036.9990844 , 50061.99908605, 50086.99908946], [ 111.99999977, 136.99999931, 161.99999885, ..., 50036.9990844 , 50061.99908605, 50086.99908946]], shape=(360, 2000)) - gr(azimuth, range)float640.002397 0.00719 ... 9.524 9.529
- standard_name :
- distance_from_radar
- units :
- metre
array([[2.39681334e-03, 7.19041883e-03, 1.19839961e-02, ..., 9.51927364e+00, 9.52401134e+00, 9.52874902e+00], [2.39681334e-03, 7.19041883e-03, 1.19839961e-02, ..., 9.51927364e+00, 9.52401134e+00, 9.52874902e+00], [2.39681334e-03, 7.19041883e-03, 1.19839961e-02, ..., 9.51927364e+00, 9.52401134e+00, 9.52874902e+00], ..., [2.39681334e-03, 7.19041883e-03, 1.19839961e-02, ..., 9.51927364e+00, 9.52401134e+00, 9.52874902e+00], [2.39681334e-03, 7.19041883e-03, 1.19839961e-02, ..., 9.51927364e+00, 9.52401134e+00, 9.52874902e+00], [2.39681334e-03, 7.19041883e-03, 1.19839961e-02, ..., 9.51927364e+00, 9.52401134e+00, 9.52874902e+00]], shape=(360, 2000)) - rays(azimuth, range)float640.5 0.5 0.5 ... 359.5 359.5 359.5
- standard_name :
- ray_azimuth_angle
- long_name :
- azimuth_angle_from_true_north
- units :
- degrees
- axis :
- radial_azimuth_coordinate
array([[ 0.5, 0.5, 0.5, ..., 0.5, 0.5, 0.5], [ 1.5, 1.5, 1.5, ..., 1.5, 1.5, 1.5], [ 2.5, 2.5, 2.5, ..., 2.5, 2.5, 2.5], ..., [357.5, 357.5, 357.5, ..., 357.5, 357.5, 357.5], [358.5, 358.5, 358.5, ..., 358.5, 358.5, 358.5], [359.5, 359.5, 359.5, ..., 359.5, 359.5, 359.5]], shape=(360, 2000)) - bins(azimuth, range)float3212.5 37.5 ... 4.996e+04 4.999e+04
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 25.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 12.5
array([[1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04], [1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04], [1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04], ..., [1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04], [1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04], [1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04]], shape=(360, 2000), dtype=float32) - height(range)float64112.0 137.0 ... 5.006e+04 5.009e+04
- standard_name :
- height_above_ground
- units :
- metre
array([ 111.99999977, 136.99999931, 161.99999885, ..., 50036.9990844 , 50061.99908605, 50086.99908946], shape=(2000,)) - sweep_mode()<U20'azimuth_surveillance'
array('azimuth_surveillance', dtype='<U20') - longitude()float647.072
- long_name :
- longitude
- units :
- degrees_east
- standard_name :
- longitude
array(7.071663)
- latitude()float6450.73
- long_name :
- latitude
- units :
- degrees_north
- positive :
- up
- standard_name :
- latitude
array(50.73052)
- altitude()float6499.5
- long_name :
- altitude
- units :
- meters
- standard_name :
- altitude
array(99.5)
- crs_wkt()int640
- crs_wkt :
- PROJCRS["AEQD centered at 50.73052N 7.071663E",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Azimuthal Equidistant",ID["EPSG",1125]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- AEQD centered at 50.73052N 7.071663E
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
array(0)
- KDP(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - PHIDP(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - DBZH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - DBZV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - RHOHV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - DBTH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - DBTV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - VRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - VRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - WRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - WRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - ZDR(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 2000) (1, 360, 2000) Dask graph 66 chunks in 199 graph layers Data type float32 numpy.ndarray - sweep_number(time2)int640 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) - prt_mode(time2)<U7'not_set' 'not_set' ... 'not_set'
array(['not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set'], dtype='<U7') - follow_mode(time2)<U7'not_set' 'not_set' ... 'not_set'
array(['not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set'], dtype='<U7') - sweep_fixed_angle(time2)float6490.0 90.0 90.0 ... 90.0 90.0 90.0
array([90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90.]) - nyquist_velocity(time2)objectNone None None ... None None None
- standard_name :
- nyquist_velocity
- units :
- m s-1
array([None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None], dtype=object)
- source :
- gamic
- pulse_width :
- 1
Apply offsets (VP)#
sweep_vp_1["DBZH"] -= zh_offset
sweep_vp_1["DBTH"] -= zh_offset
sweep_vp_1["ZDR"] -= zdr_offset
Calculate median (VP)#
with xr.set_options(keep_attrs=True):
vp_1 = sweep_vp_1.where(sweep_vp_1.RHOHV > 0.95).median("azimuth", skipna=True)
display(vp_1)
<xarray.Dataset> Size: 8MB
Dimensions: (time2: 66, range: 2000)
Coordinates:
* range (range) float32 8kB 12.5 37.5 ... 4.996e+04 4.999e+04
height (range) float64 16kB 112.0 137.0 ... 5.006e+04 5.009e+04
sweep_mode <U20 80B 'azimuth_surveillance'
longitude float64 8B 7.072
latitude float64 8B 50.73
altitude float64 8B 99.5
crs_wkt int64 8B 0
Dimensions without coordinates: time2
Data variables: (12/14)
KDP (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
PHIDP (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
DBZH (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
DBZV (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
RHOHV (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
DBTH (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
... ...
VRADV (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
WRADH (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
WRADV (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
ZDR (time2, range) float32 528kB dask.array<chunksize=(1, 2000), meta=np.ndarray>
sweep_number (time2, range) float64 1MB dask.array<chunksize=(1, 2000), meta=np.ndarray>
sweep_fixed_angle (time2, range) float64 1MB dask.array<chunksize=(1, 2000), meta=np.ndarray>
Attributes:
source: gamic
pulse_width: 1xarray.Dataset
- time2: 66
- range: 2000
- range(range)float3212.5 37.5 ... 4.996e+04 4.999e+04
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 25.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 12.5
array([1.25000e+01, 3.75000e+01, 6.25000e+01, ..., 4.99375e+04, 4.99625e+04, 4.99875e+04], shape=(2000,), dtype=float32) - height(range)float64112.0 137.0 ... 5.006e+04 5.009e+04
- standard_name :
- height_above_ground
- units :
- metre
array([ 111.99999977, 136.99999931, 161.99999885, ..., 50036.9990844 , 50061.99908605, 50086.99908946], shape=(2000,)) - sweep_mode()<U20'azimuth_surveillance'
array('azimuth_surveillance', dtype='<U20') - longitude()float647.072
- long_name :
- longitude
- units :
- degrees_east
- standard_name :
- longitude
array(7.071663)
- latitude()float6450.73
- long_name :
- latitude
- units :
- degrees_north
- positive :
- up
- standard_name :
- latitude
array(50.73052)
- altitude()float6499.5
- long_name :
- altitude
- units :
- meters
- standard_name :
- altitude
array(99.5)
- crs_wkt()int640
- crs_wkt :
- PROJCRS["AEQD centered at 50.73052N 7.071663E",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Azimuthal Equidistant",ID["EPSG",1125]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- AEQD centered at 50.73052N 7.071663E
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
array(0)
- KDP(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 401 graph layers Data type float32 numpy.ndarray - PHIDP(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 401 graph layers Data type float32 numpy.ndarray - DBZH(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 402 graph layers Data type float32 numpy.ndarray - DBZV(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 401 graph layers Data type float32 numpy.ndarray - RHOHV(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 202 graph layers Data type float32 numpy.ndarray - DBTH(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 402 graph layers Data type float32 numpy.ndarray - DBTV(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 401 graph layers Data type float32 numpy.ndarray - VRADH(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 401 graph layers Data type float32 numpy.ndarray - VRADV(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 401 graph layers Data type float32 numpy.ndarray - WRADH(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 401 graph layers Data type float32 numpy.ndarray - WRADV(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 401 graph layers Data type float32 numpy.ndarray - ZDR(time2, range)float32dask.array<chunksize=(1, 2000), meta=np.ndarray>
- format :
- UV8
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 402 graph layers Data type float32 numpy.ndarray - sweep_number(time2, range)float64dask.array<chunksize=(1, 2000), meta=np.ndarray>
Array Chunk Bytes 1.01 MiB 15.62 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 204 graph layers Data type float64 numpy.ndarray - sweep_fixed_angle(time2, range)float64dask.array<chunksize=(1, 2000), meta=np.ndarray>
Array Chunk Bytes 1.01 MiB 15.62 kiB Shape (66, 2000) (1, 2000) Dask graph 66 chunks in 204 graph layers Data type float64 numpy.ndarray
- source :
- gamic
- pulse_width :
- 1
Plot moments (VP)#
_kwargs = dict(x="time2", y="height", ylim=(0, 8000), cmap="HomeyerRainbow")
fig = plt.figure(figsize=(16, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
vp_1.DBZH.plot.contourf(**kwargs)
ax1.set_title(vp_1.DBZH.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
vp_1.ZDR.plot.contourf(**kwargs)
ax2.set_title(vp_1.ZDR.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
vp_1.RHOHV.plot.contourf(**kwargs)
ax3.set_title(vp_1.RHOHV.attrs["long_name"])
ax4 = fig.add_subplot(224)
philevels2 = np.arange(-10, 10, 1)
kwargs = _kwargs | levels(philevels2) | dict(ax=ax4)
vp_1.PHIDP.plot.contourf(**kwargs)
ax4.set_title(vp_1.PHIDP.attrs["long_name"])
# kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
# vp_1.KDP.plot.contourf(**kwargs)
# ax4.set_title(vp_1.KDP.attrs["long_name"])
Text(0.5, 1.0, 'Differential phase HV')
Quasi Vertical Profile - QVP#
22.06.2011 09:00 - 14:30 UTC
scan: ‘ppi_8p1deg’
# recent boxpol event
start_time = dt.datetime(2011, 6, 22, 9)
stop_time = dt.datetime(2011, 6, 22, 14, 30)
delta = stop_time - start_time
loc = "boxpol"
scan = "ppi_8p1deg"
Open dataset (QVP)#
reindex_angle = dict(start_angle=0, stop_angle=360, angle_res=1.0, direction=1)
sweep_1 = rp.load_timeseries_sweep(start_time, delta, scan, reindex_angle=reindex_angle)
sweep_1 = sweep_1.set_coords("sweep_mode")
sweep_1["sweep_mode"] = sweep_1["sweep_mode"][0]
sweep_1 = sweep_1.wrl.georef.georeference()
sweep_1 = sweep_1.assign_coords(height=sweep_1.z.mean("azimuth"))
loading 66 files
Apply offsets (QVP)#
sweep_1["DBTH"] -= zh_offset
sweep_1["DBZH"] -= zh_offset
sweep_1["ZDR"] -= zdr_offset
Preprocess data (QVP)#
##%%time
# sweep_1a = rp.workflow(sweep_1, scan, rp.data_path())
Open preprocessed dataset (QVP)#
workflow_file = f"/radar/rp-data/workflow/tmp_{start_time:%Y%m%dT%H%M}_{stop_time:%Y%m%dT%H%M}_workflow.nc"
with rp.rpol_data.open(workflow_file) as f:
workflow_file = f.name
sweep_1 = xr.open_dataset(
workflow_file,
chunks=dict(time2=1),
)
display(sweep_1)
<xarray.Dataset> Size: 6GB
Dimensions: (time2: 66, azimuth: 360, range: 1000)
Coordinates: (12/24)
* time2 (time2) datetime64[ns] 528B 2011-06-22T09:03:46 ... 20...
* azimuth (azimuth) float64 3kB 0.5 1.5 2.5 ... 357.5 358.5 359.5
elevation (azimuth) float64 3kB dask.array<chunksize=(360,), meta=np.ndarray>
time (time2, azimuth) datetime64[ns] 190kB dask.array<chunksize=(1, 360), meta=np.ndarray>
* range (range) float32 4kB 50.0 150.0 ... 9.985e+04 9.995e+04
x (azimuth, range) float64 3MB dask.array<chunksize=(360, 1000), meta=np.ndarray>
... ...
crs_wkt int64 8B ...
band int64 8B ...
spatial_ref int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/55)
KDP (time2, azimuth, range) float32 95MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
PHIDP (time2, azimuth, range) float32 95MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
DBZH (time2, azimuth, range) float32 95MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
DBZV (time2, azimuth, range) float32 95MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
RHOHV (time2, azimuth, range) float32 95MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
DBTH (time2, azimuth, range) float32 95MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
... ...
AH (time2, azimuth, range) float64 190MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
KDP_AH (time2, azimuth, range) float64 190MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
PHIDP_CORR5 (time2, azimuth, range) float64 190MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
DBTH_CORR5 (time2, azimuth, range) float64 190MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
DBZH_CORR5 (time2, azimuth, range) float64 190MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
ZDR_CORR5 (time2, azimuth, range) float64 190MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>xarray.Dataset
- time2: 66
- azimuth: 360
- range: 1000
- time2(time2)datetime64[ns]2011-06-22T09:03:46 ... 2011-06-...
array(['2011-06-22T09:03:46.000000000', '2011-06-22T09:08:46.000000000', '2011-06-22T09:13:46.000000000', '2011-06-22T09:18:46.000000000', '2011-06-22T09:23:46.000000000', '2011-06-22T09:28:46.000000000', '2011-06-22T09:33:47.000000000', '2011-06-22T09:38:46.000000000', '2011-06-22T09:43:46.000000000', '2011-06-22T09:48:46.000000000', '2011-06-22T09:53:46.000000000', '2011-06-22T09:58:47.000000000', '2011-06-22T10:03:46.000000000', '2011-06-22T10:08:47.000000000', '2011-06-22T10:13:46.000000000', '2011-06-22T10:18:46.000000000', '2011-06-22T10:23:46.000000000', '2011-06-22T10:28:46.000000000', '2011-06-22T10:33:46.000000000', '2011-06-22T10:38:46.000000000', '2011-06-22T10:43:46.000000000', '2011-06-22T10:48:46.000000000', '2011-06-22T10:53:46.000000000', '2011-06-22T10:58:46.000000000', '2011-06-22T11:03:46.000000000', '2011-06-22T11:08:47.000000000', '2011-06-22T11:13:46.000000000', '2011-06-22T11:18:46.000000000', '2011-06-22T11:23:46.000000000', '2011-06-22T11:28:46.000000000', '2011-06-22T11:33:46.000000000', '2011-06-22T11:38:47.000000000', '2011-06-22T11:43:46.000000000', '2011-06-22T11:48:47.000000000', '2011-06-22T11:53:46.000000000', '2011-06-22T11:58:46.000000000', '2011-06-22T12:03:46.000000000', '2011-06-22T12:08:46.000000000', '2011-06-22T12:13:46.000000000', '2011-06-22T12:18:46.000000000', '2011-06-22T12:23:46.000000000', '2011-06-22T12:28:47.000000000', '2011-06-22T12:33:46.000000000', '2011-06-22T12:38:46.000000000', '2011-06-22T12:43:46.000000000', '2011-06-22T12:48:47.000000000', '2011-06-22T12:53:47.000000000', '2011-06-22T12:58:46.000000000', '2011-06-22T13:03:46.000000000', '2011-06-22T13:08:46.000000000', '2011-06-22T13:13:47.000000000', '2011-06-22T13:18:46.000000000', '2011-06-22T13:23:46.000000000', '2011-06-22T13:28:45.000000000', '2011-06-22T13:33:47.000000000', '2011-06-22T13:38:47.000000000', '2011-06-22T13:43:46.000000000', '2011-06-22T13:48:46.000000000', '2011-06-22T13:53:47.000000000', '2011-06-22T13:58:46.000000000', '2011-06-22T14:03:46.000000000', '2011-06-22T14:08:47.000000000', '2011-06-22T14:13:47.000000000', '2011-06-22T14:18:47.000000000', '2011-06-22T14:23:47.000000000', '2011-06-22T14:28:46.000000000'], dtype='datetime64[ns]') - azimuth(azimuth)float640.5 1.5 2.5 ... 357.5 358.5 359.5
array([ 0.5, 1.5, 2.5, ..., 357.5, 358.5, 359.5], shape=(360,))
- elevation(azimuth)float64dask.array<chunksize=(360,), meta=np.ndarray>
Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - time(time2, azimuth)datetime64[ns]dask.array<chunksize=(1, 360), meta=np.ndarray>
Array Chunk Bytes 185.62 kiB 2.81 kiB Shape (66, 360) (1, 360) Dask graph 66 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - range(range)float3250.0 150.0 ... 9.985e+04 9.995e+04
array([5.000e+01, 1.500e+02, 2.500e+02, ..., 9.975e+04, 9.985e+04, 9.995e+04], shape=(1000,), dtype=float32) - x(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
- standard_name :
- east_west_distance_from_radar
- units :
- meters
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
- standard_name :
- north_south_distance_from_radar
- units :
- meters
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - z(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
- standard_name :
- height_above_ground
- units :
- meters
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - gr(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
- standard_name :
- distance_from_radar
- units :
- meters
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - rays(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - bins(azimuth, range)float32dask.array<chunksize=(360, 1000), meta=np.ndarray>
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 100.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 50.0
Array Chunk Bytes 1.37 MiB 1.37 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - height(range)float64dask.array<chunksize=(1000,), meta=np.ndarray>
Array Chunk Bytes 7.81 kiB 7.81 kiB Shape (1000,) (1000,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - xd(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - yd(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - sweep_mode()<U20...
[1 values with dtype=<U20]
- longitude()float64...
[1 values with dtype=float64]
- latitude()float64...
[1 values with dtype=float64]
- altitude()float64...
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- band()int64...
[1 values with dtype=int64]
- spatial_ref()int64...
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_specific_differential_phase_hv
- units :
- degrees per kilometer
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZH(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_v
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor V
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - RHOHV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- units :
- unitless
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTH(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_v
- units :
- dBZ
- long_name :
- Total power V (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - VRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- units :
- meters per seconds
- long_name :
- Radial velocity of scatterers away from instrument H
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - VRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- units :
- meters per second
- long_name :
- Radial velocity of scatterers away from instrument V
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - WRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_doppler_spectrum_width_h
- units :
- meters per seconds
- long_name :
- Doppler spectrum width H
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - WRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_doppler_spectrum_width_v
- units :
- meters per second
- long_name :
- Doppler spectrum width V
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - ZDR(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 351.56 kiB Shape (66, 360, 1000) (1, 180, 500) Dask graph 264 chunks in 2 graph layers Data type float32 numpy.ndarray - sweep_number(time2)int64dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 528 B 8 B Shape (66,) (1,) Dask graph 66 chunks in 2 graph layers Data type int64 numpy.ndarray - prt_mode(time2)<U7dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 1.80 kiB 28 B Shape (66,) (1,) Dask graph 66 chunks in 2 graph layers Data type - follow_mode(time2)<U7dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 1.80 kiB 28 B Shape (66,) (1,) Dask graph 66 chunks in 2 graph layers Data type - sweep_fixed_angle(time2)float64dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 528 B 8 B Shape (66,) (1,) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DEM(azimuth, range)float32dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 1.37 MiB 1.37 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - PBB(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - CBB(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - QBBF(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - SNRH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - RHOHV_NC(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- units :
- unitless
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - SYSPHI1(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 264 B 4 B Shape (66,) (1,) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC1(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 1.37 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI2(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 264 B 4 B Shape (66,) (1,) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 1.37 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI3(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 264 B 4 B Shape (66,) (1,) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC3(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 1.37 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI4(time2, azimuth)float64dask.array<chunksize=(1, 360), meta=np.ndarray>
Array Chunk Bytes 185.62 kiB 2.81 kiB Shape (66, 360) (1, 360) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_OC4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - RHOHV_SMOOTH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- units :
- unitless
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 1.37 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 1.37 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_LANC(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_VULP(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 1.37 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZH_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 1.37 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - ZDR_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 90.64 MiB 1.37 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTH_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - AH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_AH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_specific_differential_phase_hv
- units :
- degrees per kilometer
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 181.27 MiB 2.75 MiB Shape (66, 360, 1000) (1, 360, 1000) Dask graph 66 chunks in 2 graph layers Data type float64 numpy.ndarray
Calculate median (QVP)#
with xr.set_options(keep_attrs=True):
swp_median_1 = sweep_1.where(
(sweep_1.DBZH_CORR1 > 0) & (sweep_1.RHOHV_NC > 0.8)
).median("azimuth", skipna=True)
swp_median_1 = swp_median_1.where(swp_median_1.DBZH_CORR1 > 0)
display(swp_median_1)
<xarray.Dataset> Size: 22MB
Dimensions: (time2: 66, range: 1000)
Coordinates: (12/13)
* time2 (time2) datetime64[ns] 528B 2011-06-22T09:03:46 ... 20...
* range (range) float32 4kB 50.0 150.0 ... 9.985e+04 9.995e+04
height (range) float64 8kB dask.array<chunksize=(1000,), meta=np.ndarray>
sweep_mode <U20 80B ...
longitude float64 8B ...
latitude float64 8B ...
... ...
crs_wkt int64 8B ...
band int64 8B ...
spatial_ref int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/53)
KDP (time2, range) float32 264kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
PHIDP (time2, range) float32 264kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBZH (time2, range) float32 264kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBZV (time2, range) float32 264kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
RHOHV (time2, range) float32 264kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBTH (time2, range) float32 264kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
... ...
AH (time2, range) float64 528kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
KDP_AH (time2, range) float64 528kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
PHIDP_CORR5 (time2, range) float64 528kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBTH_CORR5 (time2, range) float64 528kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBZH_CORR5 (time2, range) float64 528kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
ZDR_CORR5 (time2, range) float64 528kB dask.array<chunksize=(1, 1000), meta=np.ndarray>xarray.Dataset
- time2: 66
- range: 1000
- time2(time2)datetime64[ns]2011-06-22T09:03:46 ... 2011-06-...
array(['2011-06-22T09:03:46.000000000', '2011-06-22T09:08:46.000000000', '2011-06-22T09:13:46.000000000', '2011-06-22T09:18:46.000000000', '2011-06-22T09:23:46.000000000', '2011-06-22T09:28:46.000000000', '2011-06-22T09:33:47.000000000', '2011-06-22T09:38:46.000000000', '2011-06-22T09:43:46.000000000', '2011-06-22T09:48:46.000000000', '2011-06-22T09:53:46.000000000', '2011-06-22T09:58:47.000000000', '2011-06-22T10:03:46.000000000', '2011-06-22T10:08:47.000000000', '2011-06-22T10:13:46.000000000', '2011-06-22T10:18:46.000000000', '2011-06-22T10:23:46.000000000', '2011-06-22T10:28:46.000000000', '2011-06-22T10:33:46.000000000', '2011-06-22T10:38:46.000000000', '2011-06-22T10:43:46.000000000', '2011-06-22T10:48:46.000000000', '2011-06-22T10:53:46.000000000', '2011-06-22T10:58:46.000000000', '2011-06-22T11:03:46.000000000', '2011-06-22T11:08:47.000000000', '2011-06-22T11:13:46.000000000', '2011-06-22T11:18:46.000000000', '2011-06-22T11:23:46.000000000', '2011-06-22T11:28:46.000000000', '2011-06-22T11:33:46.000000000', '2011-06-22T11:38:47.000000000', '2011-06-22T11:43:46.000000000', '2011-06-22T11:48:47.000000000', '2011-06-22T11:53:46.000000000', '2011-06-22T11:58:46.000000000', '2011-06-22T12:03:46.000000000', '2011-06-22T12:08:46.000000000', '2011-06-22T12:13:46.000000000', '2011-06-22T12:18:46.000000000', '2011-06-22T12:23:46.000000000', '2011-06-22T12:28:47.000000000', '2011-06-22T12:33:46.000000000', '2011-06-22T12:38:46.000000000', '2011-06-22T12:43:46.000000000', '2011-06-22T12:48:47.000000000', '2011-06-22T12:53:47.000000000', '2011-06-22T12:58:46.000000000', '2011-06-22T13:03:46.000000000', '2011-06-22T13:08:46.000000000', '2011-06-22T13:13:47.000000000', '2011-06-22T13:18:46.000000000', '2011-06-22T13:23:46.000000000', '2011-06-22T13:28:45.000000000', '2011-06-22T13:33:47.000000000', '2011-06-22T13:38:47.000000000', '2011-06-22T13:43:46.000000000', '2011-06-22T13:48:46.000000000', '2011-06-22T13:53:47.000000000', '2011-06-22T13:58:46.000000000', '2011-06-22T14:03:46.000000000', '2011-06-22T14:08:47.000000000', '2011-06-22T14:13:47.000000000', '2011-06-22T14:18:47.000000000', '2011-06-22T14:23:47.000000000', '2011-06-22T14:28:46.000000000'], dtype='datetime64[ns]') - range(range)float3250.0 150.0 ... 9.985e+04 9.995e+04
array([5.000e+01, 1.500e+02, 2.500e+02, ..., 9.975e+04, 9.985e+04, 9.995e+04], shape=(1000,), dtype=float32) - height(range)float64dask.array<chunksize=(1000,), meta=np.ndarray>
Array Chunk Bytes 7.81 kiB 7.81 kiB Shape (1000,) (1000,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - sweep_mode()<U20...
[1 values with dtype=<U20]
- longitude()float64...
[1 values with dtype=float64]
- latitude()float64...
[1 values with dtype=float64]
- altitude()float64...
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- band()int64...
[1 values with dtype=int64]
- spatial_ref()int64...
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_specific_differential_phase_hv
- units :
- degrees per kilometer
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - PHIDP(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - DBZH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - DBZV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_v
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor V
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - RHOHV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- units :
- unitless
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - DBTH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - DBTV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
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- standard_name :
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- units :
- dBZ
- long_name :
- Total power V (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - VRADH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- units :
- meters per seconds
- long_name :
- Radial velocity of scatterers away from instrument H
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - VRADV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- units :
- meters per second
- long_name :
- Radial velocity of scatterers away from instrument V
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - WRADH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_doppler_spectrum_width_h
- units :
- meters per seconds
- long_name :
- Doppler spectrum width H
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - WRADV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_doppler_spectrum_width_v
- units :
- meters per second
- long_name :
- Doppler spectrum width V
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - ZDR(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - sweep_number(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 17 graph layers Data type float64 numpy.ndarray - sweep_fixed_angle(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 16 graph layers Data type float64 numpy.ndarray - DEM(range, time2)float32dask.array<chunksize=(1000, 1), meta=np.ndarray>
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (1000, 66) (1000, 1) Dask graph 66 chunks in 18 graph layers Data type float32 numpy.ndarray - PBB(range, time2)float64dask.array<chunksize=(1000, 1), meta=np.ndarray>
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (1000, 66) (1000, 1) Dask graph 66 chunks in 18 graph layers Data type float64 numpy.ndarray - CBB(range, time2)float64dask.array<chunksize=(1000, 1), meta=np.ndarray>
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (1000, 66) (1000, 1) Dask graph 66 chunks in 18 graph layers Data type float64 numpy.ndarray - QBBF(range, time2)float64dask.array<chunksize=(1000, 1), meta=np.ndarray>
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (1000, 66) (1000, 1) Dask graph 66 chunks in 18 graph layers Data type float64 numpy.ndarray - SNRH(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - RHOHV_NC(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- units :
- unitless
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 13 graph layers Data type float64 numpy.ndarray - SYSPHI1(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC1(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI3(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC3(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
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Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 16 graph layers Data type float64 numpy.ndarray - PHIDP_OC4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
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- standard_name :
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- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - RHOHV_SMOOTH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- units :
- unitless
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float32 numpy.ndarray - PHIDP_CORR1(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
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Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float32 numpy.ndarray - PHIDP_CORR3(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- units :
- degrees
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_LANC(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_VULP(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR1(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR1(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 11 graph layers Data type float64 numpy.ndarray - ZDR_CORR1(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
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- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
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Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float32 numpy.ndarray - DBZH_CORR2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float32 numpy.ndarray - ZDR_CORR2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
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- standard_name :
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- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
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Array Chunk Bytes 257.81 kiB 3.91 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float32 numpy.ndarray - DBTH_CORR3(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
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- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR3(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
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- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR3(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
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- standard_name :
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- units :
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- long_name :
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- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
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- standard_name :
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- units :
- dB
- long_name :
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- _Undetect :
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Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - AH(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_AH(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
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- units :
- degrees per kilometer
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR5(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
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- standard_name :
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- units :
- degrees
- long_name :
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- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR5(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR5(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- units :
- dBZ
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR5(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- units :
- dB
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 515.62 kiB 7.81 kiB Shape (66, 1000) (1, 1000) Dask graph 66 chunks in 15 graph layers Data type float64 numpy.ndarray
Plot moments (QVP)#
_kwargs = dict(x="time2", y="height", ylim=(0, 10000), cmap="HomeyerRainbow")
fig = plt.figure(figsize=(14, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
swp_median_1.DBZH_CORR1.plot.contourf(**kwargs)
ax1.set_title(swp_median_1.DBZH_CORR1.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
swp_median_1.ZDR_CORR1.plot.contourf(**kwargs)
ax2.set_title(swp_median_1.ZDR_CORR1.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
swp_median_1.RHOHV_NC.plot.contourf(**kwargs)
ax3.set_title(swp_median_1.RHOHV_NC.attrs["long_name"])
ax4 = fig.add_subplot(224)
# kwargs = _kwargs | levels(philevels) | dict(ax=ax4)
# swp_median_1.PHIDP_CORR1.plot.contourf(**kwargs)
# ax4.set_title(swp_median_1.PHIDP_CORR1.attrs["long_name"])
kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
swp_median_1.KDP_VULP.plot.contourf(**kwargs)
ax4.set_title(swp_median_1.KDP_VULP.attrs["long_name"])
fig.tight_layout()
Range Height Indicator - RHI#
22.06.2011 12 UTC
scan: ‘rhi309’
# recent boxpol event
start_time = dt.datetime(2011, 6, 22, 12)
stop_time = dt.datetime(2011, 6, 22, 12, 5)
delta = stop_time - start_time
loc = "boxpol"
scan = "rhi309"
Open dataset (QVP)#
reindex_angle = dict(start_angle=0, stop_angle=90, angle_res=0.2, direction=1)
sweep_rhi_1 = rp.load_single_sweep(start_time, scan, reindex_angle=reindex_angle)
Apply offsets (QVP)#
sweep_rhi_1["DBZH"] -= zh_offset
sweep_rhi_1["DBTH"] -= zh_offset
sweep_rhi_1["ZDR"] -= zdr_offset
Preprocess data (QVP)#
##%%time
# sweep_rhi_1 = rp.workflow(sweep_rhi_1, scan, rp.data_path())
Open preprocessed dataset (QVP)#
workflow_file = f"/radar/rp-data/workflow/tmp_{start_time:%Y%m%dT%H%M}_{stop_time:%Y%m%dT%H%M}_workflow.nc"
with rp.rpol_data.open(workflow_file) as f:
workflow_file = f.name
sweep_rhi_1 = xr.open_dataset(workflow_file)
display(sweep_rhi_1)
<xarray.Dataset> Size: 151MB
Dimensions: (elevation: 450, range: 1000)
Coordinates: (12/18)
* elevation (elevation) float64 4kB 0.1 0.3 0.5 ... 89.5 89.7 89.9
azimuth (elevation) float64 4kB ...
time (elevation) datetime64[ns] 4kB ...
* range (range) float32 4kB 25.0 75.0 ... 4.992e+04 4.998e+04
x (elevation, range) float64 4MB ...
y (elevation, range) float64 4MB ...
... ...
latitude float64 8B ...
altitude float64 8B ...
crs_wkt int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/51)
KDP (elevation, range) float32 2MB ...
PHIDP (elevation, range) float32 2MB ...
DBZH (elevation, range) float32 2MB ...
DBZV (elevation, range) float32 2MB ...
RHOHV (elevation, range) float32 2MB ...
DBTH (elevation, range) float32 2MB ...
... ...
AH (elevation, range) float64 4MB ...
KDP_AH (elevation, range) float64 4MB ...
PHIDP_CORR5 (elevation, range) float64 4MB ...
DBTH_CORR5 (elevation, range) float64 4MB ...
DBZH_CORR5 (elevation, range) float64 4MB ...
ZDR_CORR5 (elevation, range) float64 4MB ...xarray.Dataset
- elevation: 450
- range: 1000
- elevation(elevation)float640.1 0.3 0.5 0.7 ... 89.5 89.7 89.9
- standard_name :
- ray_elevation_angle
- long_name :
- elevation_angle_from_horizontal_plane
- units :
- degrees
- axis :
- radial_elevation_coordinate
array([ 0.1, 0.3, 0.5, ..., 89.5, 89.7, 89.9], shape=(450,))
- azimuth(elevation)float64...
- standard_name :
- ray_azimuth_angle
- long_name :
- azimuth_angle_from_true_north
- units :
- degrees
- axis :
- radial_azimuth_coordinate
[450 values with dtype=float64]
- time(elevation)datetime64[ns]...
- standard_name :
- time
[450 values with dtype=datetime64[ns]]
- range(range)float3225.0 75.0 ... 4.992e+04 4.998e+04
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 50.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 25.0
array([2.5000e+01, 7.5000e+01, 1.2500e+02, ..., 4.9875e+04, 4.9925e+04, 4.9975e+04], shape=(1000,), dtype=float32) - x(elevation, range)float64...
- standard_name :
- east_west_distance_from_radar
- units :
- meters
[450000 values with dtype=float64]
- y(elevation, range)float64...
- standard_name :
- north_south_distance_from_radar
- units :
- meters
[450000 values with dtype=float64]
- z(elevation, range)float64...
- standard_name :
- height_above_ground
- units :
- meters
[450000 values with dtype=float64]
- gr(elevation, range)float64...
- standard_name :
- distance_from_radar
- units :
- meters
[450000 values with dtype=float64]
- rays(elevation, range)float64...
- standard_name :
- ray_elevation_angle
- long_name :
- elevation_angle_from_horizontal_plane
- units :
- degrees
- axis :
- radial_elevation_coordinate
[450000 values with dtype=float64]
- bins(elevation, range)float32...
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 50.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 25.0
[450000 values with dtype=float32]
- sweep_mode()<U3...
[1 values with dtype=<U3]
- longitude()float64...
- long_name :
- longitude
- units :
- degrees_east
- standard_name :
- longitude
[1 values with dtype=float64]
- latitude()float64...
- long_name :
- latitude
- units :
- degrees_north
- positive :
- up
- standard_name :
- latitude
[1 values with dtype=float64]
- altitude()float64...
- long_name :
- altitude
- units :
- meters
- standard_name :
- altitude
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- PHIDP(elevation, range)float32...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- DBZH(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- DBZV(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_v
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- RHOHV(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- units :
- unitless
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- DBTH(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- DBTV(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_v
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- VRADH(elevation, range)float32...
- format :
- UV8
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- VRADV(elevation, range)float32...
- format :
- UV8
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- WRADH(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_doppler_spectrum_width_h
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- WRADV(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_doppler_spectrum_width_v
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- ZDR(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- sweep_number()int64...
[1 values with dtype=int64]
- prt_mode()<U7...
[1 values with dtype=<U7]
- follow_mode()<U7...
[1 values with dtype=<U7]
- sweep_fixed_angle()float64...
[1 values with dtype=float64]
- SNRH(elevation, range)float64...
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
[450000 values with dtype=float64]
- RHOHV_NC(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- units :
- unitless
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- SYSPHI1()float64...
[1 values with dtype=float64]
- PHIDP_OC1(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- SYSPHI2()float64...
[1 values with dtype=float64]
- PHIDP_OC2(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- SYSPHI3()float64...
[1 values with dtype=float64]
- PHIDP_OC3(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- SYSPHI4(elevation)float64...
[450 values with dtype=float64]
- PHIDP_OC4(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- RHOHV_SMOOTH(elevation, range)float32...
- format :
- UV8
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- units :
- unitless
- _Undetect :
- 0.0
[450000 values with dtype=float32]
- PHIDP_CORR1(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- PHIDP_CORR2(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- PHIDP_CORR3(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- PHIDP_CORR4(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- KDP_LANC(elevation, range)float64...
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
[450000 values with dtype=float64]
- KDP_VULP(elevation, range)float64...
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
[450000 values with dtype=float64]
- DBTH_CORR1(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBZH_CORR1(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- ZDR_CORR1(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBTH_CORR2(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBZH_CORR2(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- ZDR_CORR2(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBTH_CORR3(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBZH_CORR3(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- ZDR_CORR3(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBTH_CORR4(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBZH_CORR4(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- ZDR_CORR4(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- AH(elevation, range)float64...
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
[450000 values with dtype=float64]
- KDP_AH(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- PHIDP_CORR5(elevation, range)float64...
- format :
- UV16
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- units :
- degrees
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBTH_CORR5(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- DBZH_CORR5(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- _Undetect :
- 0.0
[450000 values with dtype=float64]
- ZDR_CORR5(elevation, range)float64...
- format :
- UV8
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- _Undetect :
- 0.0
[450000 values with dtype=float64]
Plot moments (QVP)#
_kwargs = dict(x="gr", y="z", ylim=(0, 8000), cmap="HomeyerRainbow")
fig = plt.figure(figsize=(16, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
sweep_rhi_1.DBZH_CORR2.plot.contourf(**kwargs)
ax1.set_title(sweep_rhi_1.DBZH_CORR2.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
sweep_rhi_1.ZDR_CORR2.plot.contourf(**kwargs)
ax2.set_title(sweep_rhi_1.ZDR_CORR2.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
sweep_rhi_1.RHOHV_NC.plot.contourf(**kwargs)
ax3.set_title(sweep_rhi_1.RHOHV_NC.attrs["long_name"])
ax4 = fig.add_subplot(224)
# philevels2 = np.arange(0, 15, 1)
# kwargs = _kwargs | levels(philevels2) | dict(ax=ax4)
# sweep_rhi_1.PHIDP_CORR2.plot.contourf(**kwargs)
# ax4.set_title(sweep_rhi_1.PHIDP_CORR2.attrs["long_name"])
kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
sweep_rhi_1.KDP_VULP.plot(**kwargs)
ax4.set_title(sweep_rhi_1.KDP_VULP.attrs["long_name"])
fig.tight_layout()
Event 2 - QVP#
22.02.2016 16:00 - 19:30 UTC
scan: ‘n_ppi_280deg’
zh_offset: -1.0
zdr_offset: -0.4
zh_offset = -1
zdr_offset = -0.4
# recent boxpol event
start_time = dt.datetime(2016, 2, 22, 16)
stop_time = dt.datetime(2016, 2, 22, 19, 35)
delta = stop_time - start_time
loc = "boxpol"
scan = "n_ppi_280deg"
Open dataset - 2#
reindex_angle = dict(start_angle=0, stop_angle=360, angle_res=1.0, direction=1)
sweep_2 = rp.load_timeseries_sweep(start_time, delta, scan, reindex_angle=reindex_angle)
sweep_2 = sweep_2.set_coords("sweep_mode")
sweep_2["sweep_mode"] = sweep_2["sweep_mode"][0]
sweep_2 = sweep_2.wrl.georef.georeference()
sweep_2 = sweep_2.assign_coords(height=sweep_2.z.mean("azimuth"))
loading 43 files
Apply offsets - 2#
sweep_2["DBTH"] -= zh_offset
sweep_2["DBZH"] -= zh_offset
sweep_2["ZDR"] -= zdr_offset
Preprocess data - 2#
##%%time
# sweep_2a = rp.workflow(sweep_2, scan, rp.data_path())
Open preprocessed dataset - 2#
workflow_file = f"/radar/rp-data/workflow/tmp_{start_time:%Y%m%dT%H%M}_{stop_time:%Y%m%dT%H%M}_workflow.nc"
with rp.rpol_data.open(workflow_file) as f:
workflow_file = f.name
sweep_2 = xr.open_dataset(
workflow_file,
chunks=dict(time2=1),
)
display(sweep_2)
<xarray.Dataset> Size: 1GB
Dimensions: (time2: 43, azimuth: 360, range: 350)
Coordinates: (12/24)
* time2 (time2) datetime64[ns] 344B 2016-02-22T16:00:50 ... 20...
* azimuth (azimuth) float64 3kB 0.5 1.5 2.5 ... 357.5 358.5 359.5
elevation (azimuth) float64 3kB dask.array<chunksize=(360,), meta=np.ndarray>
time (time2, azimuth) datetime64[ns] 124kB dask.array<chunksize=(1, 360), meta=np.ndarray>
* range (range) float32 1kB 50.0 150.0 ... 3.485e+04 3.495e+04
x (azimuth, range) float64 1MB dask.array<chunksize=(360, 350), meta=np.ndarray>
... ...
crs_wkt int64 8B ...
band int64 8B ...
spatial_ref int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/55)
KDP (time2, azimuth, range) float32 22MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
PHIDP (time2, azimuth, range) float32 22MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
DBZH (time2, azimuth, range) float32 22MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
DBZV (time2, azimuth, range) float32 22MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
RHOHV (time2, azimuth, range) float32 22MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
DBTH (time2, azimuth, range) float32 22MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
... ...
AH (time2, azimuth, range) float64 43MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
KDP_AH (time2, azimuth, range) float64 43MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
PHIDP_CORR5 (time2, azimuth, range) float64 43MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
DBTH_CORR5 (time2, azimuth, range) float64 43MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
DBZH_CORR5 (time2, azimuth, range) float64 43MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
ZDR_CORR5 (time2, azimuth, range) float64 43MB dask.array<chunksize=(1, 360, 350), meta=np.ndarray>xarray.Dataset
- time2: 43
- azimuth: 360
- range: 350
- time2(time2)datetime64[ns]2016-02-22T16:00:50 ... 2016-02-...
array(['2016-02-22T16:00:50.000000000', '2016-02-22T16:05:50.000000000', '2016-02-22T16:10:50.000000000', '2016-02-22T16:15:51.000000000', '2016-02-22T16:20:50.000000000', '2016-02-22T16:25:50.000000000', '2016-02-22T16:30:50.000000000', '2016-02-22T16:35:50.000000000', '2016-02-22T16:40:50.000000000', '2016-02-22T16:45:51.000000000', '2016-02-22T16:50:50.000000000', '2016-02-22T16:55:50.000000000', '2016-02-22T17:00:50.000000000', '2016-02-22T17:05:50.000000000', '2016-02-22T17:10:50.000000000', '2016-02-22T17:15:50.000000000', '2016-02-22T17:20:50.000000000', '2016-02-22T17:25:50.000000000', '2016-02-22T17:30:50.000000000', '2016-02-22T17:35:50.000000000', '2016-02-22T17:40:50.000000000', '2016-02-22T17:45:50.000000000', '2016-02-22T17:50:50.000000000', '2016-02-22T17:55:50.000000000', '2016-02-22T18:00:50.000000000', '2016-02-22T18:05:50.000000000', '2016-02-22T18:10:50.000000000', '2016-02-22T18:15:50.000000000', '2016-02-22T18:20:50.000000000', '2016-02-22T18:25:50.000000000', '2016-02-22T18:30:50.000000000', '2016-02-22T18:35:50.000000000', '2016-02-22T18:40:50.000000000', '2016-02-22T18:45:50.000000000', '2016-02-22T18:50:50.000000000', '2016-02-22T18:55:50.000000000', '2016-02-22T19:00:50.000000000', '2016-02-22T19:05:50.000000000', '2016-02-22T19:10:50.000000000', '2016-02-22T19:15:50.000000000', '2016-02-22T19:20:50.000000000', '2016-02-22T19:25:50.000000000', '2016-02-22T19:30:50.000000000'], dtype='datetime64[ns]') - azimuth(azimuth)float640.5 1.5 2.5 ... 357.5 358.5 359.5
array([ 0.5, 1.5, 2.5, ..., 357.5, 358.5, 359.5], shape=(360,))
- elevation(azimuth)float64dask.array<chunksize=(360,), meta=np.ndarray>
Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - time(time2, azimuth)datetime64[ns]dask.array<chunksize=(1, 360), meta=np.ndarray>
Array Chunk Bytes 120.94 kiB 2.81 kiB Shape (43, 360) (1, 360) Dask graph 43 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - range(range)float3250.0 150.0 ... 3.485e+04 3.495e+04
array([ 50., 150., 250., ..., 34750., 34850., 34950.], shape=(350,), dtype=float32) - x(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
- standard_name :
- east_west_distance_from_radar
- units :
- meters
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
- standard_name :
- north_south_distance_from_radar
- units :
- meters
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - z(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
- standard_name :
- height_above_ground
- units :
- meters
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - gr(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
- standard_name :
- distance_from_radar
- units :
- meters
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - rays(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - bins(azimuth, range)float32dask.array<chunksize=(360, 350), meta=np.ndarray>
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 100.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 50.0
Array Chunk Bytes 492.19 kiB 492.19 kiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - height(range)float64dask.array<chunksize=(350,), meta=np.ndarray>
Array Chunk Bytes 2.73 kiB 2.73 kiB Shape (350,) (350,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - xd(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - yd(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - sweep_mode()<U20...
[1 values with dtype=<U20]
- longitude()float64...
[1 values with dtype=float64]
- latitude()float64...
[1 values with dtype=float64]
- altitude()float64...
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- band()int64...
[1 values with dtype=int64]
- spatial_ref()int64...
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- long_name :
- Equivalent reflectivity factor V
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - RHOHV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- long_name :
- Total power V (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - VRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- long_name :
- Radial velocity of scatterers away from instrument H
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - VRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- long_name :
- Radial velocity of scatterers away from instrument V
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - WRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- long_name :
- Doppler spectrum width H
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - WRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- long_name :
- Doppler spectrum width V
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - ZDR(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - sweep_number(time2)int64dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 344 B 8 B Shape (43,) (1,) Dask graph 43 chunks in 2 graph layers Data type int64 numpy.ndarray - prt_mode(time2)<U7dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 1.18 kiB 28 B Shape (43,) (1,) Dask graph 43 chunks in 2 graph layers Data type - follow_mode(time2)<U7dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 1.18 kiB 28 B Shape (43,) (1,) Dask graph 43 chunks in 2 graph layers Data type - sweep_fixed_angle(time2)float64dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 344 B 8 B Shape (43,) (1,) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DEM(azimuth, range)float32dask.array<chunksize=(360, 350), meta=np.ndarray>
Array Chunk Bytes 492.19 kiB 492.19 kiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - PBB(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - CBB(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - QBBF(azimuth, range)float64dask.array<chunksize=(360, 350), meta=np.ndarray>
Array Chunk Bytes 0.96 MiB 0.96 MiB Shape (360, 350) (360, 350) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - SNRH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - RHOHV_NC(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - SYSPHI1(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 172 B 4 B Shape (43,) (1,) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC1(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI2(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 172 B 4 B Shape (43,) (1,) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI3(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 172 B 4 B Shape (43,) (1,) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC3(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI4(time2, azimuth)float64dask.array<chunksize=(1, 360), meta=np.ndarray>
Array Chunk Bytes 120.94 kiB 2.81 kiB Shape (43, 360) (1, 360) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_OC4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - RHOHV_SMOOTH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_LANC(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_VULP(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZH_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - ZDR_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 20.67 MiB 492.19 kiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTH_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - AH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_AH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 41.34 MiB 0.96 MiB Shape (43, 360, 350) (1, 360, 350) Dask graph 43 chunks in 2 graph layers Data type float64 numpy.ndarray
Calculate median - 2#
with xr.set_options(keep_attrs=True):
qvp_2 = sweep_2.where((sweep_2.DBZH_CORR2 > 0) & (sweep_2.RHOHV_NC > 0.8)).median(
"azimuth", skipna=True
)
qvp_2 = qvp_2.where(qvp_2.DBZH_CORR2 > 0)
display(qvp_2)
<xarray.Dataset> Size: 5MB
Dimensions: (time2: 43, range: 350)
Coordinates: (12/13)
* time2 (time2) datetime64[ns] 344B 2016-02-22T16:00:50 ... 20...
* range (range) float32 1kB 50.0 150.0 ... 3.485e+04 3.495e+04
height (range) float64 3kB dask.array<chunksize=(350,), meta=np.ndarray>
sweep_mode <U20 80B ...
longitude float64 8B ...
latitude float64 8B ...
... ...
crs_wkt int64 8B ...
band int64 8B ...
spatial_ref int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/53)
KDP (time2, range) float32 60kB dask.array<chunksize=(1, 350), meta=np.ndarray>
PHIDP (time2, range) float32 60kB dask.array<chunksize=(1, 350), meta=np.ndarray>
DBZH (time2, range) float32 60kB dask.array<chunksize=(1, 350), meta=np.ndarray>
DBZV (time2, range) float32 60kB dask.array<chunksize=(1, 350), meta=np.ndarray>
RHOHV (time2, range) float32 60kB dask.array<chunksize=(1, 350), meta=np.ndarray>
DBTH (time2, range) float32 60kB dask.array<chunksize=(1, 350), meta=np.ndarray>
... ...
AH (time2, range) float64 120kB dask.array<chunksize=(1, 350), meta=np.ndarray>
KDP_AH (time2, range) float64 120kB dask.array<chunksize=(1, 350), meta=np.ndarray>
PHIDP_CORR5 (time2, range) float64 120kB dask.array<chunksize=(1, 350), meta=np.ndarray>
DBTH_CORR5 (time2, range) float64 120kB dask.array<chunksize=(1, 350), meta=np.ndarray>
DBZH_CORR5 (time2, range) float64 120kB dask.array<chunksize=(1, 350), meta=np.ndarray>
ZDR_CORR5 (time2, range) float64 120kB dask.array<chunksize=(1, 350), meta=np.ndarray>xarray.Dataset
- time2: 43
- range: 350
- time2(time2)datetime64[ns]2016-02-22T16:00:50 ... 2016-02-...
array(['2016-02-22T16:00:50.000000000', '2016-02-22T16:05:50.000000000', '2016-02-22T16:10:50.000000000', '2016-02-22T16:15:51.000000000', '2016-02-22T16:20:50.000000000', '2016-02-22T16:25:50.000000000', '2016-02-22T16:30:50.000000000', '2016-02-22T16:35:50.000000000', '2016-02-22T16:40:50.000000000', '2016-02-22T16:45:51.000000000', '2016-02-22T16:50:50.000000000', '2016-02-22T16:55:50.000000000', '2016-02-22T17:00:50.000000000', '2016-02-22T17:05:50.000000000', '2016-02-22T17:10:50.000000000', '2016-02-22T17:15:50.000000000', '2016-02-22T17:20:50.000000000', '2016-02-22T17:25:50.000000000', '2016-02-22T17:30:50.000000000', '2016-02-22T17:35:50.000000000', '2016-02-22T17:40:50.000000000', '2016-02-22T17:45:50.000000000', '2016-02-22T17:50:50.000000000', '2016-02-22T17:55:50.000000000', '2016-02-22T18:00:50.000000000', '2016-02-22T18:05:50.000000000', '2016-02-22T18:10:50.000000000', '2016-02-22T18:15:50.000000000', '2016-02-22T18:20:50.000000000', '2016-02-22T18:25:50.000000000', '2016-02-22T18:30:50.000000000', '2016-02-22T18:35:50.000000000', '2016-02-22T18:40:50.000000000', '2016-02-22T18:45:50.000000000', '2016-02-22T18:50:50.000000000', '2016-02-22T18:55:50.000000000', '2016-02-22T19:00:50.000000000', '2016-02-22T19:05:50.000000000', '2016-02-22T19:10:50.000000000', '2016-02-22T19:15:50.000000000', '2016-02-22T19:20:50.000000000', '2016-02-22T19:25:50.000000000', '2016-02-22T19:30:50.000000000'], dtype='datetime64[ns]') - range(range)float3250.0 150.0 ... 3.485e+04 3.495e+04
array([ 50., 150., 250., ..., 34750., 34850., 34950.], shape=(350,), dtype=float32) - height(range)float64dask.array<chunksize=(350,), meta=np.ndarray>
Array Chunk Bytes 2.73 kiB 2.73 kiB Shape (350,) (350,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - sweep_mode()<U20...
[1 values with dtype=<U20]
- longitude()float64...
[1 values with dtype=float64]
- latitude()float64...
[1 values with dtype=float64]
- altitude()float64...
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- band()int64...
[1 values with dtype=int64]
- spatial_ref()int64...
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - PHIDP(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - DBZH(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - DBZV(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- long_name :
- Equivalent reflectivity factor V
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - RHOHV(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - DBTH(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - DBTV(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- long_name :
- Total power V (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - VRADH(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- long_name :
- Radial velocity of scatterers away from instrument H
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - VRADV(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- long_name :
- Radial velocity of scatterers away from instrument V
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - WRADH(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- long_name :
- Doppler spectrum width H
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - WRADV(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- long_name :
- Doppler spectrum width V
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - ZDR(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - sweep_number(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 17 graph layers Data type float64 numpy.ndarray - sweep_fixed_angle(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 16 graph layers Data type float64 numpy.ndarray - DEM(range, time2)float32dask.array<chunksize=(350, 1), meta=np.ndarray>
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (350, 43) (350, 1) Dask graph 43 chunks in 18 graph layers Data type float32 numpy.ndarray - PBB(range, time2)float64dask.array<chunksize=(350, 1), meta=np.ndarray>
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (350, 43) (350, 1) Dask graph 43 chunks in 18 graph layers Data type float64 numpy.ndarray - CBB(range, time2)float64dask.array<chunksize=(350, 1), meta=np.ndarray>
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (350, 43) (350, 1) Dask graph 43 chunks in 18 graph layers Data type float64 numpy.ndarray - QBBF(range, time2)float64dask.array<chunksize=(350, 1), meta=np.ndarray>
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (350, 43) (350, 1) Dask graph 43 chunks in 18 graph layers Data type float64 numpy.ndarray - SNRH(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - RHOHV_NC(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 13 graph layers Data type float64 numpy.ndarray - SYSPHI1(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC1(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI2(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC2(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI3(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC3(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI4(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 16 graph layers Data type float64 numpy.ndarray - PHIDP_OC4(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - RHOHV_SMOOTH(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - PHIDP_CORR1(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR2(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - PHIDP_CORR3(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR4(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_LANC(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_VULP(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR1(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR1(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR1(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR2(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - DBZH_CORR2(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 11 graph layers Data type float32 numpy.ndarray - ZDR_CORR2(time2, range)float32dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 58.79 kiB 1.37 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float32 numpy.ndarray - DBTH_CORR3(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR3(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR3(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR4(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR4(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR4(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - AH(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_AH(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR5(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR5(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR5(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR5(time2, range)float64dask.array<chunksize=(1, 350), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 117.58 kiB 2.73 kiB Shape (43, 350) (1, 350) Dask graph 43 chunks in 15 graph layers Data type float64 numpy.ndarray
Plot moments - 2#
_kwargs = dict(x="time2", y="height", ylim=(0, 5000), cmap="HomeyerRainbow")
fig = plt.figure(figsize=(14, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
qvp_2.DBZH_CORR2.plot.contourf(**kwargs)
ax1.set_title(qvp_2.DBZH_CORR2.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
qvp_2.ZDR_CORR2.plot.contourf(**kwargs)
ax2.set_title(qvp_2.ZDR_CORR2.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
qvp_2.RHOHV_NC.plot.contourf(**kwargs)
ax3.set_title(qvp_2.RHOHV_NC.attrs["long_name"])
ax4 = fig.add_subplot(224)
philevels2 = np.arange(0, 5, 0.2)
kwargs = _kwargs | levels(philevels2) | dict(ax=ax4)
qvp_2.PHIDP_CORR2.plot(**kwargs)
ax4.set_title(qvp_2.PHIDP_CORR2.attrs["long_name"])
# kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
# qvp_2.KDP_VULP.plot.contourf(**kwargs)
# ax4.set_title(qvp_2.KDP_VULP.attrs["long_name"])
fig.tight_layout()
Event 3 - RHI#
01.07.2013 15:30, 15:40, 15:50 UTC
n_rhi_lacros
n_rhi_joyce
korrigiert/unkorrigiert
zh_offset = -4
zdr_offset = -2
# recent boxpol event
start_time = dt.datetime(2013, 7, 1, 15, 30)
stop_time = dt.datetime(2013, 7, 1, 16, 00)
delta = stop_time - start_time
loc = "boxpol"
scan1 = "n_rhi_joyce"
scan2 = "n_rhi_lacros"
Open dataset - 3#
reindex_angle = dict(start_angle=0, stop_angle=90, angle_res=0.2, direction=1)
sweep_rhi_3_1 = rp.load_timeseries_sweep(
start_time, delta, scan1, reindex_angle=reindex_angle
)
sweep_rhi_3_1 = sweep_rhi_3_1.assign_coords(time2=sweep_rhi_3_1.time.min("elevation"))
sweep_rhi_3_2 = rp.load_timeseries_sweep(
start_time, delta, scan2, reindex_angle=reindex_angle
)
sweep_rhi_3_2 = sweep_rhi_3_2.assign_coords(time2=sweep_rhi_3_2.time.min("elevation"))
sweep_rhi_3 = xr.merge([sweep_rhi_3_1, sweep_rhi_3_2])
display(sweep_rhi_3)
loading 3 files
loading 3 files
<xarray.Dataset> Size: 86MB
Dimensions: (elevation: 450, range: 667, time2: 6)
Coordinates:
* elevation (elevation) float64 4kB 0.1 0.3 0.5 ... 89.5 89.7 89.9
azimuth (elevation) float64 4kB dask.array<chunksize=(450,), meta=np.ndarray>
time (time2, elevation) datetime64[ns] 22kB dask.array<chunksize=(1, 450), meta=np.ndarray>
* range (range) float32 3kB 37.5 112.5 ... 4.991e+04 4.999e+04
* time2 (time2) datetime64[ns] 48B 2013-07-01T15:30:01 ... 201...
longitude float64 8B 7.072
latitude float64 8B 50.73
altitude float64 8B 99.5
Data variables: (12/18)
KDP (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
PHIDP (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
DBZH (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
DBZV (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
RHOHV (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
DBTH (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
... ...
sweep_mode (time2) object 48B 'rhi' 'rhi' 'rhi' 'rhi' 'rhi' 'rhi'
sweep_number (time2) float64 48B 0.0 0.0 0.0 0.0 0.0 0.0
prt_mode (time2) object 48B 'not_set' 'not_set' ... 'not_set'
follow_mode (time2) object 48B 'not_set' 'not_set' ... 'not_set'
sweep_fixed_angle (time2) float64 48B 175.0 175.0 175.0 175.0 175.0 175.0
nyquist_velocity (time2) object 48B None nan None nan None nan
Attributes:
source: gamic
pulse_width: 1xarray.Dataset
- elevation: 450
- range: 667
- time2: 6
- elevation(elevation)float640.1 0.3 0.5 0.7 ... 89.5 89.7 89.9
- standard_name :
- ray_elevation_angle
- long_name :
- elevation_angle_from_horizontal_plane
- units :
- degrees
- axis :
- radial_elevation_coordinate
array([ 0.1, 0.3, 0.5, ..., 89.5, 89.7, 89.9], shape=(450,))
- azimuth(elevation)float64dask.array<chunksize=(450,), meta=np.ndarray>
- standard_name :
- ray_azimuth_angle
- long_name :
- azimuth_angle_from_true_north
- units :
- degrees
- axis :
- radial_azimuth_coordinate
Array Chunk Bytes 3.52 kiB 3.52 kiB Shape (450,) (450,) Dask graph 1 chunks in 12 graph layers Data type float64 numpy.ndarray - time(time2, elevation)datetime64[ns]dask.array<chunksize=(1, 450), meta=np.ndarray>
- standard_name :
- time
Array Chunk Bytes 21.09 kiB 3.52 kiB Shape (6, 450) (1, 450) Dask graph 6 chunks in 19 graph layers Data type datetime64[ns] numpy.ndarray - range(range)float3237.5 112.5 ... 4.991e+04 4.999e+04
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 75.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 37.5
array([3.75000e+01, 1.12500e+02, 1.87500e+02, ..., 4.98375e+04, 4.99125e+04, 4.99875e+04], shape=(667,), dtype=float32) - time2(time2)datetime64[ns]2013-07-01T15:30:01 ... 2013-07-...
- standard_name :
- time
array(['2013-07-01T15:30:01.000000000', '2013-07-01T15:35:01.000000000', '2013-07-01T15:40:01.000000000', '2013-07-01T15:45:01.000000000', '2013-07-01T15:50:01.000000000', '2013-07-01T15:55:01.000000000'], dtype='datetime64[ns]') - longitude()float647.072
- long_name :
- longitude
- units :
- degrees_east
- standard_name :
- longitude
array(7.071663)
- latitude()float6450.73
- long_name :
- latitude
- units :
- degrees_north
- positive :
- up
- standard_name :
- latitude
array(50.73052)
- altitude()float6499.5
- long_name :
- altitude
- units :
- meters
- standard_name :
- altitude
array(99.5)
- KDP(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - PHIDP(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - DBZH(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - DBZV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - RHOHV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - DBTH(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - DBTV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - VRADH(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - VRADV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - WRADH(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - WRADV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - ZDR(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 26 graph layers Data type float32 numpy.ndarray - sweep_mode(time2)object'rhi' 'rhi' 'rhi' 'rhi' 'rhi' 'rhi'
array(['rhi', 'rhi', 'rhi', 'rhi', 'rhi', 'rhi'], dtype=object)
- sweep_number(time2)float640.0 0.0 0.0 0.0 0.0 0.0
array([0., 0., 0., 0., 0., 0.])
- prt_mode(time2)object'not_set' 'not_set' ... 'not_set'
array(['not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set'], dtype=object) - follow_mode(time2)object'not_set' 'not_set' ... 'not_set'
array(['not_set', 'not_set', 'not_set', 'not_set', 'not_set', 'not_set'], dtype=object) - sweep_fixed_angle(time2)float64175.0 175.0 175.0 175.0 175.0 175.0
array([175., 175., 175., 175., 175., 175.])
- nyquist_velocity(time2)objectNone nan None nan None nan
- standard_name :
- nyquist_velocity
- units :
- m s-1
array([None, nan, None, nan, None, nan], dtype=object)
- source :
- gamic
- pulse_width :
- 1
Apply offsets - 3#
sweep_rhi_3["DBZH"] -= zh_offset
sweep_rhi_3["DBTH"] -= zh_offset
sweep_rhi_3["ZDR"] -= zdr_offset
Preprocess data - 3#
##%%time
# sweep_rhi_3a = rp.workflow(sweep_rhi_3, scan, rp.data_path())
Open preprocessed dataset - 3#
workflow_file = f"/radar/rp-data/workflow/tmp_{start_time:%Y%m%dT%H%M}_{stop_time:%Y%m%dT%H%M}_workflow.nc"
with rp.rpol_data.open(workflow_file) as f:
workflow_file = f.name
sweep_rhi_3 = xr.open_dataset(
workflow_file,
chunks=dict(time2=1),
)
display(sweep_rhi_3)
<xarray.Dataset> Size: 496MB
Dimensions: (time2: 6, elevation: 450, range: 667)
Coordinates: (12/19)
* time2 (time2) datetime64[ns] 48B 2013-07-01T15:30:01 ... 201...
* elevation (elevation) float64 4kB 0.1 0.3 0.5 ... 89.5 89.7 89.9
azimuth (elevation) float64 4kB dask.array<chunksize=(450,), meta=np.ndarray>
time (time2, elevation) datetime64[ns] 22kB dask.array<chunksize=(1, 450), meta=np.ndarray>
* range (range) float32 3kB 37.5 112.5 ... 4.991e+04 4.999e+04
x (elevation, range) float64 2MB dask.array<chunksize=(450, 667), meta=np.ndarray>
... ...
latitude float64 8B ...
altitude float64 8B ...
crs_wkt int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/51)
KDP (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
PHIDP (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
DBZH (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
DBZV (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
RHOHV (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
DBTH (time2, elevation, range) float32 7MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
... ...
AH (time2, elevation, range) float64 14MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
KDP_AH (time2, elevation, range) float64 14MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
PHIDP_CORR5 (time2, elevation, range) float64 14MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
DBTH_CORR5 (time2, elevation, range) float64 14MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
DBZH_CORR5 (time2, elevation, range) float64 14MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
ZDR_CORR5 (time2, elevation, range) float64 14MB dask.array<chunksize=(1, 450, 667), meta=np.ndarray>xarray.Dataset
- time2: 6
- elevation: 450
- range: 667
- time2(time2)datetime64[ns]2013-07-01T15:30:01 ... 2013-07-...
array(['2013-07-01T15:30:01.000000000', '2013-07-01T15:35:01.000000000', '2013-07-01T15:40:01.000000000', '2013-07-01T15:45:01.000000000', '2013-07-01T15:50:01.000000000', '2013-07-01T15:55:01.000000000'], dtype='datetime64[ns]') - elevation(elevation)float640.1 0.3 0.5 0.7 ... 89.5 89.7 89.9
array([ 0.1, 0.3, 0.5, ..., 89.5, 89.7, 89.9], shape=(450,))
- azimuth(elevation)float64dask.array<chunksize=(450,), meta=np.ndarray>
Array Chunk Bytes 3.52 kiB 3.52 kiB Shape (450,) (450,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - time(time2, elevation)datetime64[ns]dask.array<chunksize=(1, 450), meta=np.ndarray>
Array Chunk Bytes 21.09 kiB 3.52 kiB Shape (6, 450) (1, 450) Dask graph 6 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - range(range)float3237.5 112.5 ... 4.991e+04 4.999e+04
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 75.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 37.5
array([3.75000e+01, 1.12500e+02, 1.87500e+02, ..., 4.98375e+04, 4.99125e+04, 4.99875e+04], shape=(667,), dtype=float32) - x(elevation, range)float64dask.array<chunksize=(450, 667), meta=np.ndarray>
- standard_name :
- east_west_distance_from_radar
- units :
- meters
Array Chunk Bytes 2.29 MiB 2.29 MiB Shape (450, 667) (450, 667) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - y(elevation, range)float64dask.array<chunksize=(450, 667), meta=np.ndarray>
- standard_name :
- north_south_distance_from_radar
- units :
- meters
Array Chunk Bytes 2.29 MiB 2.29 MiB Shape (450, 667) (450, 667) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - z(elevation, range)float64dask.array<chunksize=(450, 667), meta=np.ndarray>
- standard_name :
- height_above_ground
- units :
- meters
Array Chunk Bytes 2.29 MiB 2.29 MiB Shape (450, 667) (450, 667) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - gr(elevation, range)float64dask.array<chunksize=(450, 667), meta=np.ndarray>
- standard_name :
- distance_from_radar
- units :
- meters
Array Chunk Bytes 2.29 MiB 2.29 MiB Shape (450, 667) (450, 667) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - rays(elevation, range)float64dask.array<chunksize=(450, 667), meta=np.ndarray>
Array Chunk Bytes 2.29 MiB 2.29 MiB Shape (450, 667) (450, 667) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - bins(elevation, range)float32dask.array<chunksize=(450, 667), meta=np.ndarray>
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 75.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 37.5
Array Chunk Bytes 1.14 MiB 1.14 MiB Shape (450, 667) (450, 667) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - sweep_mode()<U3...
[1 values with dtype=<U3]
- longitude()float64...
[1 values with dtype=float64]
- latitude()float64...
[1 values with dtype=float64]
- altitude()float64...
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZH(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- long_name :
- Equivalent reflectivity factor V
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - RHOHV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTH(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- long_name :
- Total power V (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - VRADH(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- long_name :
- Radial velocity of scatterers away from instrument H
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - VRADV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- long_name :
- Radial velocity of scatterers away from instrument V
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - WRADH(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- long_name :
- Doppler spectrum width H
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - WRADV(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- long_name :
- Doppler spectrum width V
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - ZDR(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - sweep_number(time2)float64dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 48 B 8 B Shape (6,) (1,) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - prt_mode(time2)<U7dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 168 B 28 B Shape (6,) (1,) Dask graph 6 chunks in 2 graph layers Data type - follow_mode(time2)<U7dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 168 B 28 B Shape (6,) (1,) Dask graph 6 chunks in 2 graph layers Data type - sweep_fixed_angle(time2)float64dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 48 B 8 B Shape (6,) (1,) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - SNRH(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - RHOHV_NC(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - SYSPHI1(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 24 B 4 B Shape (6,) (1,) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC1(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI2(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 24 B 4 B Shape (6,) (1,) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC2(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI3(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 24 B 4 B Shape (6,) (1,) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC3(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI4(time2, elevation)float64dask.array<chunksize=(1, 450), meta=np.ndarray>
Array Chunk Bytes 21.09 kiB 3.52 kiB Shape (6, 450) (1, 450) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_OC4(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - RHOHV_SMOOTH(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- long_name :
- Correlation coefficient HV
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR1(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR2(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_CORR3(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR4(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_LANC(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_VULP(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR1(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR1(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR1(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR2(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZH_CORR2(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - ZDR_CORR2(time2, elevation, range)float32dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 6.87 MiB 1.14 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTH_CORR3(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR3(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR3(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR4(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR4(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR4(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - AH(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_AH(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR5(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- long_name :
- Differential phase HV
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR5(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Total power H (uncorrected reflectivity)
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR5(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- long_name :
- Equivalent reflectivity factor H
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR5(time2, elevation, range)float64dask.array<chunksize=(1, 450, 667), meta=np.ndarray>
- format :
- UV16
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- long_name :
- Log differential reflectivity H/V
- _Undetect :
- 0.0
Array Chunk Bytes 13.74 MiB 2.29 MiB Shape (6, 450, 667) (1, 450, 667) Dask graph 6 chunks in 2 graph layers Data type float64 numpy.ndarray
Plot moments - 3#
seletc different timesteps below
_kwargs = dict(x="gr", y="z", xlim=(0, 20000), ylim=(0, 10000), cmap="HomeyerRainbow")
rhi_3 = sweep_rhi_3.isel(time2=1)
uncorrected - 3#
fig = plt.figure(figsize=(16, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
rhi_3.DBZH.plot.contourf(**kwargs)
ax1.set_title(rhi_3.DBZH.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
rhi_3.ZDR.plot.contourf(**kwargs)
ax2.set_title(rhi_3.ZDR.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
rhi_3.RHOHV.plot.contourf(**kwargs)
ax3.set_title(rhi_3.RHOHV.attrs["long_name"])
ax4 = fig.add_subplot(224)
philevels2 = np.arange(0, 15, 1)
philevels2 = np.arange(-100, -80, 1)
kwargs = _kwargs | levels(philevels2) | dict(ax=ax4)
rhi_3.PHIDP.plot.contourf(**kwargs)
ax4.set_title(rhi_3.PHIDP.attrs["long_name"])
# kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
# rhi_3.KDP_VULP.plot(**kwargs)
# ax4.set_title(rhi_3.KDP_VULP.attrs["long_name"])
fig.tight_layout()
corrected - 3#
fig = plt.figure(figsize=(16, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
rhi_3.DBZH_CORR2.plot.contourf(**kwargs)
ax1.set_title(rhi_3.DBZH_CORR2.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
rhi_3.ZDR_CORR2.plot.contourf(**kwargs)
ax2.set_title(rhi_3.ZDR_CORR1.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
rhi_3.RHOHV_NC.plot.contourf(**kwargs)
ax3.set_title(rhi_3.RHOHV_NC.attrs["long_name"])
ax4 = fig.add_subplot(224)
philevels2 = np.arange(0, 40, 2)
kwargs = _kwargs | levels(philevels2) | dict(ax=ax4)
rhi_3.PHIDP_CORR2.plot.contourf(**kwargs)
ax4.set_title(rhi_3.PHIDP_CORR2.attrs["long_name"])
# kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
# rhi_3.KDP_VULP.plot(**kwargs)
# ax4.set_title(rhi_3.KDP_VULP.attrs["long_name"])
fig.tight_layout()
Event 4 - QVP#
01.06.2016 04:00 - 10:00 UTC
scan: ‘n_ppi_280deg
zh_offset: -1.0
zdr_offset: -0.8
zh_offset = -1.0
zdr_offset = -0.8
# recent boxpol event
start_time = dt.datetime(2016, 6, 1, 4)
stop_time = dt.datetime(2016, 6, 1, 10)
delta = stop_time - start_time
loc = "boxpol"
scan = "n_ppi_280deg"
Open dataset - 4#
reindex_angle = dict(start_angle=0, stop_angle=360, angle_res=1.0, direction=1)
sweep_4 = rp.load_timeseries_sweep(start_time, delta, scan, reindex_angle=reindex_angle)
sweep_4 = sweep_4.set_coords("sweep_mode")
sweep_4["sweep_mode"] = sweep_4["sweep_mode"][0]
sweep_4 = sweep_4.wrl.georef.georeference()
sweep_4 = sweep_4.assign_coords(height=sweep_4.z.mean("azimuth"))
loading 72 files
Apply offsets - 4#
sweep_4["DBTH"] -= zh_offset
sweep_4["DBZH"] -= zh_offset
sweep_4["ZDR"] -= zdr_offset
Preprocess data - 4#
##%%time
# sweep_4a = rp.workflow(sweep_4, scan, rp.data_path())
Open preprocessed dataset - 4#
workflow_file = f"/radar/rp-data/workflow/tmp_{start_time:%Y%m%dT%H%M}_{stop_time:%Y%m%dT%H%M}_workflow.nc"
with rp.rpol_data.open(workflow_file) as f:
workflow_file = f.name
sweep_4 = xr.open_dataset(workflow_file)
display(sweep_4)
<xarray.Dataset> Size: 2GB
Dimensions: (time2: 72, azimuth: 360, range: 350)
Coordinates: (12/24)
* time2 (time2) datetime64[ns] 576B 2016-06-01T04:00:50 ... 20...
* azimuth (azimuth) float64 3kB 0.5 1.5 2.5 ... 357.5 358.5 359.5
elevation (azimuth) float64 3kB ...
time (time2, azimuth) datetime64[ns] 207kB ...
* range (range) float32 1kB 50.0 150.0 ... 3.485e+04 3.495e+04
x (azimuth, range) float64 1MB ...
... ...
crs_wkt int64 8B ...
band int64 8B ...
spatial_ref int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/55)
KDP (time2, azimuth, range) float32 36MB ...
PHIDP (time2, azimuth, range) float32 36MB ...
DBZH (time2, azimuth, range) float32 36MB ...
DBZV (time2, azimuth, range) float32 36MB ...
RHOHV (time2, azimuth, range) float32 36MB ...
DBTH (time2, azimuth, range) float32 36MB ...
... ...
AH (time2, azimuth, range) float64 73MB ...
KDP_AH (time2, azimuth, range) float64 73MB ...
PHIDP_CORR5 (time2, azimuth, range) float64 73MB ...
DBTH_CORR5 (time2, azimuth, range) float64 73MB ...
DBZH_CORR5 (time2, azimuth, range) float64 73MB ...
ZDR_CORR5 (time2, azimuth, range) float64 73MB ...xarray.Dataset
- time2: 72
- azimuth: 360
- range: 350
- time2(time2)datetime64[ns]2016-06-01T04:00:50 ... 2016-06-...
array(['2016-06-01T04:00:50.000000000', '2016-06-01T04:05:50.000000000', '2016-06-01T04:10:50.000000000', '2016-06-01T04:15:50.000000000', '2016-06-01T04:20:50.000000000', '2016-06-01T04:25:50.000000000', '2016-06-01T04:30:50.000000000', '2016-06-01T04:35:50.000000000', '2016-06-01T04:40:50.000000000', '2016-06-01T04:45:50.000000000', '2016-06-01T04:50:50.000000000', '2016-06-01T04:55:50.000000000', '2016-06-01T05:00:50.000000000', '2016-06-01T05:05:50.000000000', '2016-06-01T05:10:50.000000000', '2016-06-01T05:15:50.000000000', '2016-06-01T05:20:50.000000000', '2016-06-01T05:25:50.000000000', '2016-06-01T05:30:50.000000000', '2016-06-01T05:35:50.000000000', '2016-06-01T05:40:50.000000000', '2016-06-01T05:45:50.000000000', '2016-06-01T05:50:50.000000000', '2016-06-01T05:55:50.000000000', '2016-06-01T06:00:50.000000000', '2016-06-01T06:05:50.000000000', '2016-06-01T06:10:50.000000000', '2016-06-01T06:15:50.000000000', '2016-06-01T06:20:50.000000000', '2016-06-01T06:25:50.000000000', '2016-06-01T06:30:50.000000000', '2016-06-01T06:35:50.000000000', '2016-06-01T06:40:50.000000000', '2016-06-01T06:45:50.000000000', '2016-06-01T06:50:50.000000000', '2016-06-01T06:55:50.000000000', '2016-06-01T07:00:50.000000000', '2016-06-01T07:05:50.000000000', '2016-06-01T07:10:50.000000000', '2016-06-01T07:15:50.000000000', '2016-06-01T07:20:50.000000000', '2016-06-01T07:25:50.000000000', '2016-06-01T07:30:50.000000000', '2016-06-01T07:35:50.000000000', '2016-06-01T07:40:50.000000000', '2016-06-01T07:45:50.000000000', '2016-06-01T07:50:50.000000000', '2016-06-01T07:55:50.000000000', '2016-06-01T08:00:50.000000000', '2016-06-01T08:05:50.000000000', '2016-06-01T08:10:50.000000000', '2016-06-01T08:15:50.000000000', '2016-06-01T08:20:50.000000000', '2016-06-01T08:25:50.000000000', '2016-06-01T08:30:50.000000000', '2016-06-01T08:35:50.000000000', '2016-06-01T08:40:50.000000000', '2016-06-01T08:45:50.000000000', '2016-06-01T08:50:50.000000000', '2016-06-01T08:55:50.000000000', '2016-06-01T09:00:50.000000000', '2016-06-01T09:05:50.000000000', '2016-06-01T09:10:50.000000000', '2016-06-01T09:15:50.000000000', '2016-06-01T09:20:50.000000000', '2016-06-01T09:25:50.000000000', '2016-06-01T09:30:50.000000000', '2016-06-01T09:35:50.000000000', '2016-06-01T09:40:50.000000000', '2016-06-01T09:45:50.000000000', '2016-06-01T09:50:50.000000000', '2016-06-01T09:55:50.000000000'], dtype='datetime64[ns]') - azimuth(azimuth)float640.5 1.5 2.5 ... 357.5 358.5 359.5
array([ 0.5, 1.5, 2.5, ..., 357.5, 358.5, 359.5], shape=(360,))
- elevation(azimuth)float64...
[360 values with dtype=float64]
- time(time2, azimuth)datetime64[ns]...
[25920 values with dtype=datetime64[ns]]
- range(range)float3250.0 150.0 ... 3.485e+04 3.495e+04
array([ 50., 150., 250., ..., 34750., 34850., 34950.], shape=(350,), dtype=float32) - x(azimuth, range)float64...
- standard_name :
- east_west_distance_from_radar
- units :
- meters
[126000 values with dtype=float64]
- y(azimuth, range)float64...
- standard_name :
- north_south_distance_from_radar
- units :
- meters
[126000 values with dtype=float64]
- z(azimuth, range)float64...
- standard_name :
- height_above_ground
- units :
- meters
[126000 values with dtype=float64]
- gr(azimuth, range)float64...
- standard_name :
- distance_from_radar
- units :
- meters
[126000 values with dtype=float64]
- rays(azimuth, range)float64...
[126000 values with dtype=float64]
- bins(azimuth, range)float32...
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 100.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 50.0
[126000 values with dtype=float32]
- height(range)float64...
[350 values with dtype=float64]
- xd(azimuth, range)float64...
[126000 values with dtype=float64]
- yd(azimuth, range)float64...
[126000 values with dtype=float64]
- sweep_mode()<U20...
[1 values with dtype=<U20]
- longitude()float64...
[1 values with dtype=float64]
- latitude()float64...
[1 values with dtype=float64]
- altitude()float64...
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- band()int64...
[1 values with dtype=int64]
- spatial_ref()int64...
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- PHIDP(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- DBZH(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- DBZV(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- RHOHV(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- DBTH(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- DBTV(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- VRADH(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- VRADV(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- WRADH(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- WRADV(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- ZDR(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- sweep_number(time2)int64...
[72 values with dtype=int64]
- prt_mode(time2)<U7...
[72 values with dtype=<U7]
- follow_mode(time2)<U7...
[72 values with dtype=<U7]
- sweep_fixed_angle(time2)float64...
[72 values with dtype=float64]
- DEM(azimuth, range)float32...
[126000 values with dtype=float32]
- PBB(azimuth, range)float64...
[126000 values with dtype=float64]
- CBB(azimuth, range)float64...
[126000 values with dtype=float64]
- QBBF(azimuth, range)float64...
[126000 values with dtype=float64]
- SNRH(time2, azimuth, range)float64...
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
[9072000 values with dtype=float64]
- RHOHV_NC(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- SYSPHI1(time2)float32...
[72 values with dtype=float32]
- PHIDP_OC1(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- SYSPHI2(time2)float32...
[72 values with dtype=float32]
- PHIDP_OC2(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- SYSPHI3(time2)float32...
[72 values with dtype=float32]
- PHIDP_OC3(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- SYSPHI4(time2, azimuth)float64...
[25920 values with dtype=float64]
- PHIDP_OC4(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- RHOHV_SMOOTH(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- PHIDP_CORR1(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- PHIDP_CORR2(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- PHIDP_CORR3(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- PHIDP_CORR4(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- KDP_LANC(time2, azimuth, range)float64...
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
[9072000 values with dtype=float64]
- KDP_VULP(time2, azimuth, range)float64...
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
[9072000 values with dtype=float64]
- DBTH_CORR1(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- DBZH_CORR1(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- ZDR_CORR1(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- DBTH_CORR2(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- DBZH_CORR2(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- ZDR_CORR2(time2, azimuth, range)float32...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float32]
- DBTH_CORR3(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- DBZH_CORR3(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- ZDR_CORR3(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- DBTH_CORR4(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- DBZH_CORR4(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- ZDR_CORR4(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- AH(time2, azimuth, range)float64...
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
[9072000 values with dtype=float64]
- KDP_AH(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- PHIDP_CORR5(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- DBTH_CORR5(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- DBZH_CORR5(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
- ZDR_CORR5(time2, azimuth, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[9072000 values with dtype=float64]
Calculate median - 4#
with xr.set_options(keep_attrs=True):
qvp_4 = sweep_4.where((sweep_4.DBZH_CORR2 > 0) & (sweep_4.RHOHV_NC > 0.8)).median(
"azimuth", skipna=True
)
qvp_4 = qvp_4.where(qvp_4.DBZH_CORR2 > 0)
display(qvp_4)
<xarray.Dataset> Size: 8MB
Dimensions: (time2: 72, range: 350)
Coordinates: (12/13)
* time2 (time2) datetime64[ns] 576B 2016-06-01T04:00:50 ... 20...
* range (range) float32 1kB 50.0 150.0 ... 3.485e+04 3.495e+04
height (range) float64 3kB 123.0 170.0 ... 1.652e+04 1.657e+04
sweep_mode <U20 80B 'azimuth_surveillance'
longitude float64 8B 7.072
latitude float64 8B 50.73
... ...
crs_wkt int64 8B 0
band int64 8B 1
spatial_ref int64 8B 0
stdev float64 8B 0.00128
NOISE_LEVEL float64 8B -24.0
alpha float64 8B 0.28
Data variables: (12/53)
KDP (time2, range) float32 101kB nan nan 0.7706 ... nan nan
PHIDP (time2, range) float32 101kB nan nan -84.83 ... nan nan
DBZH (time2, range) float32 101kB nan nan 4.573 ... nan nan
DBZV (time2, range) float32 101kB nan nan 4.306 ... nan nan
RHOHV (time2, range) float32 101kB nan nan 0.9388 ... nan nan
DBTH (time2, range) float32 101kB nan nan 5.171 ... nan nan
... ...
AH (time2, range) float64 202kB nan nan ... nan nan
KDP_AH (time2, range) float64 202kB nan nan 3.33e-06 ... nan nan
PHIDP_CORR5 (time2, range) float64 202kB nan nan ... nan nan
DBTH_CORR5 (time2, range) float64 202kB nan nan 5.172 ... nan nan
DBZH_CORR5 (time2, range) float64 202kB nan nan 4.574 ... nan nan
ZDR_CORR5 (time2, range) float64 202kB nan nan 0.0783 ... nan nanxarray.Dataset
- time2: 72
- range: 350
- time2(time2)datetime64[ns]2016-06-01T04:00:50 ... 2016-06-...
array(['2016-06-01T04:00:50.000000000', '2016-06-01T04:05:50.000000000', '2016-06-01T04:10:50.000000000', '2016-06-01T04:15:50.000000000', '2016-06-01T04:20:50.000000000', '2016-06-01T04:25:50.000000000', '2016-06-01T04:30:50.000000000', '2016-06-01T04:35:50.000000000', '2016-06-01T04:40:50.000000000', '2016-06-01T04:45:50.000000000', '2016-06-01T04:50:50.000000000', '2016-06-01T04:55:50.000000000', '2016-06-01T05:00:50.000000000', '2016-06-01T05:05:50.000000000', '2016-06-01T05:10:50.000000000', '2016-06-01T05:15:50.000000000', '2016-06-01T05:20:50.000000000', '2016-06-01T05:25:50.000000000', '2016-06-01T05:30:50.000000000', '2016-06-01T05:35:50.000000000', '2016-06-01T05:40:50.000000000', '2016-06-01T05:45:50.000000000', '2016-06-01T05:50:50.000000000', '2016-06-01T05:55:50.000000000', '2016-06-01T06:00:50.000000000', '2016-06-01T06:05:50.000000000', '2016-06-01T06:10:50.000000000', '2016-06-01T06:15:50.000000000', '2016-06-01T06:20:50.000000000', '2016-06-01T06:25:50.000000000', '2016-06-01T06:30:50.000000000', '2016-06-01T06:35:50.000000000', '2016-06-01T06:40:50.000000000', '2016-06-01T06:45:50.000000000', '2016-06-01T06:50:50.000000000', '2016-06-01T06:55:50.000000000', '2016-06-01T07:00:50.000000000', '2016-06-01T07:05:50.000000000', '2016-06-01T07:10:50.000000000', '2016-06-01T07:15:50.000000000', '2016-06-01T07:20:50.000000000', '2016-06-01T07:25:50.000000000', '2016-06-01T07:30:50.000000000', '2016-06-01T07:35:50.000000000', '2016-06-01T07:40:50.000000000', '2016-06-01T07:45:50.000000000', '2016-06-01T07:50:50.000000000', '2016-06-01T07:55:50.000000000', '2016-06-01T08:00:50.000000000', '2016-06-01T08:05:50.000000000', '2016-06-01T08:10:50.000000000', '2016-06-01T08:15:50.000000000', '2016-06-01T08:20:50.000000000', '2016-06-01T08:25:50.000000000', '2016-06-01T08:30:50.000000000', '2016-06-01T08:35:50.000000000', '2016-06-01T08:40:50.000000000', '2016-06-01T08:45:50.000000000', '2016-06-01T08:50:50.000000000', '2016-06-01T08:55:50.000000000', '2016-06-01T09:00:50.000000000', '2016-06-01T09:05:50.000000000', '2016-06-01T09:10:50.000000000', '2016-06-01T09:15:50.000000000', '2016-06-01T09:20:50.000000000', '2016-06-01T09:25:50.000000000', '2016-06-01T09:30:50.000000000', '2016-06-01T09:35:50.000000000', '2016-06-01T09:40:50.000000000', '2016-06-01T09:45:50.000000000', '2016-06-01T09:50:50.000000000', '2016-06-01T09:55:50.000000000'], dtype='datetime64[ns]') - range(range)float3250.0 150.0 ... 3.485e+04 3.495e+04
array([ 50., 150., 250., ..., 34750., 34850., 34950.], shape=(350,), dtype=float32) - height(range)float64123.0 170.0 ... 1.652e+04 1.657e+04
array([ 123.03764921, 169.99093815, 216.94396734, 263.89673678, 310.84924648, 357.80149643, 404.75348666, 451.70521715, 498.65668792, 545.60789896, 592.55887861, 639.50957023, 686.46000213, 733.41017433, 780.36008683, 827.30973963, 874.25913275, 921.20826617, 968.15713991, 1015.10575397, 1062.54818445, 1109.49633308, 1156.44410875, 1203.39173806, 1250.33899441, 1297.2861044 , 1344.23284146, 1391.17943216, 1438.12564993, 1485.07172135, 1532.01741986, 1578.96297202, 1625.90815128, 1672.8531842 , 1719.79784422, 1767.23644963, 1814.18058771, 1861.12457946, 1908.06819834, 1955.01167091, 2001.95477061, 2048.89761073, 2095.84041781, 2142.78273878, 2189.72480017, 2236.666602 , 2284.10243243, 2331.04371241, 2377.98473283, 2424.9254937 , 2471.86622156, 2518.80646335, 2565.7464456 , 2612.68616832, 2660.11989779, 2707.05909873, 2753.99804015, 2800.93672205, 2847.87537097, 2894.81353385, 2941.75143724, 2989.18310172, 3036.12070991, 3083.05783208, 3129.99469477, 3176.9315245 , 3223.86786823, 3270.80395249, 3318.23377874, 3365.16956786, 3412.104871 , 3459.03991468, 3505.97469892, 3552.90945022, 3600.33770061, 3647.2717038 , 3694.20544755, 3741.13915837, 3788.07238327, 3835.49932011, ... 12928.68959554, 12975.57209162, 13022.94776657, 13069.82974277, 13117.20489238, 13164.57977795, 13211.46187802, 13258.83623827, 13306.2103345 , 13353.09074845, 13400.4643194 , 13447.83762633, 13494.71725922, 13542.09004089, 13589.46255856, 13636.83481224, 13683.71340287, 13731.08513132, 13778.4565958 , 13825.33440545, 13872.70534473, 13920.07602004, 13966.95395368, 14014.32410381, 14061.69398999, 14109.06361221, 14155.93959884, 14203.30869593, 14250.67752908, 14297.55273486, 14344.9210429 , 14392.28908702, 14439.65686722, 14486.53103103, 14533.89828615, 14581.26527737, 14628.13866043, 14675.5051266 , 14722.87223371, 14770.2381721 , 14817.1105133 , 14864.47592667, 14911.84107616, 14959.20596178, 15006.07726121, 15053.44162185, 15100.80571864, 15148.16955157, 15195.03980929, 15242.40311727, 15289.76616142, 15337.12894173, 15384.49236298, 15431.36131798, 15478.72330955, 15526.0850373 , 15573.44650125, 15620.31441469, 15667.67535377, 15715.03602904, 15762.39644052, 15809.75658821, 15856.62319913, 15903.982822 , 15951.34218108, 15998.70127639, 16046.06010794, 16092.92541645, 16140.28372321, 16187.64176622, 16234.99954548, 16282.35706099, 16329.22106719, 16376.57805796, 16423.934785 , 16471.29124831, 16518.6474479 , 16566.00519306]) - sweep_mode()<U20'azimuth_surveillance'
array('azimuth_surveillance', dtype='<U20') - longitude()float647.072
array(7.071663)
- latitude()float6450.73
array(50.73052)
- altitude()float6499.5
array(99.5)
- crs_wkt()int640
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
array(0)
- band()int641
array(1)
- spatial_ref()int640
array(0)
- stdev()float640.00128
array(0.00128011)
- NOISE_LEVEL()float64-24.0
array(-24.)
- alpha()float640.28
array(0.28)
- KDP(time2, range)float32nan nan 0.7706 ... nan nan nan
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.7705927 , ..., nan, nan, nan], [ nan, -1.5030375 , 5.5201874 , ..., nan, nan, nan], [ nan, 0.8359022 , nan, ..., nan, nan, nan], ..., [ nan, nan, 0.4870758 , ..., nan, nan, nan], [ nan, 0.26978302, 0.5011139 , ..., nan, nan, nan], [ 0.34608078, 0.28076935, 0.515152 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - PHIDP(time2, range)float32nan nan -84.83 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, -84.828026, ..., nan, nan, nan], [ nan, -77.87073 , -77.928406, ..., nan, nan, nan], [ nan, -71.25675 , nan, ..., nan, nan, nan], ..., [ nan, nan, -86.06677 , ..., nan, nan, nan], [ nan, -85.98712 , -85.98712 , ..., nan, nan, nan], [-86.65731 , -85.94867 , -85.98987 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - DBZH(time2, range)float32nan nan 4.573 6.417 ... nan nan nan
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 4.572891 , ..., nan, nan, nan], [ nan, 12.190315 , 0.8154526, ..., nan, nan, nan], [ nan, 11.928101 , nan, ..., nan, nan, nan], ..., [ nan, nan, 13.757744 , ..., nan, nan, nan], [ nan, 20.361458 , 24.079346 , ..., nan, nan, nan], [ 0.9531555, 17.87555 , 20.900543 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - DBZV(time2, range)float32nan nan 4.306 6.171 ... nan nan nan
- format :
- UV16
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
array([[ nan, nan, 4.306282 , ..., nan, nan, nan], [ nan, -2.1831722, -1.7334518, ..., nan, nan, nan], [ nan, -2.471756 , nan, ..., nan, nan, nan], ..., [ nan, nan, 13.281654 , ..., nan, nan, nan], [ nan, 19.076752 , 23.695549 , ..., nan, nan, nan], [ 0.3818512, 15.915527 , 20.427383 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - RHOHV(time2, range)float32nan nan 0.9388 ... nan nan nan
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.93879515, ..., nan, nan, nan], [ nan, 0.8271737 , 0.8704184 , ..., nan, nan, nan], [ nan, 0.84213537, nan, ..., nan, nan, nan], ..., [ nan, nan, 0.9906308 , ..., nan, nan, nan], [ nan, 0.8907132 , 0.99794 , ..., nan, nan, nan], [0.8651082 , 0.8637501 , 0.9972076 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - DBTH(time2, range)float32nan nan 5.171 6.613 ... nan nan nan
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 5.1705704, ..., nan, nan, nan], [ nan, 12.4203 , 1.2812881, ..., nan, nan, nan], [ nan, 12.241585 , nan, ..., nan, nan, nan], ..., [ nan, nan, 13.905701 , ..., nan, nan, nan], [ nan, 20.551895 , 24.088135 , ..., nan, nan, nan], [ 8.265877 , 19.68029 , 21.990417 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - DBTV(time2, range)float32nan nan 4.926 6.468 ... nan nan nan
- format :
- UV16
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
array([[ nan, nan, 4.9259338e+00, ..., nan, nan, nan], [ nan, -1.5312958e+00, 3.9062500e-03, ..., nan, nan, nan], [ nan, -1.4331493e+00, nan, ..., nan, nan, nan], ..., [ nan, nan, 1.3653740e+01, ..., nan, nan, nan], [ nan, 1.9240822e+01, 2.3746819e+01, ..., nan, nan, nan], [ 8.4563141e+00, 1.8019104e+01, 2.1534836e+01, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - VRADH(time2, range)float32nan nan -2.912 ... nan nan nan
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
array([[ nan, nan, -2.91214 , ..., nan, nan, nan], [ nan, 3.9196892 , 0.64839554, ..., nan, nan, nan], [ nan, 4.365673 , nan, ..., nan, nan, nan], ..., [ nan, nan, -2.1222248 , ..., nan, nan, nan], [ nan, -3.2464867 , -2.9217243 , ..., nan, nan, nan], [-26.736433 , -1.1919212 , -2.5129547 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - VRADV(time2, range)float32nan nan -2.927 ... nan nan nan
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
array([[ nan, nan, -2.9267979 , ..., nan, nan, nan], [ nan, 3.308506 , 0.66080093, ..., nan, nan, nan], [ nan, -3.0598602 , nan, ..., nan, nan, nan], ..., [ nan, nan, -2.0805035 , ..., nan, nan, nan], [ nan, -2.9211597 , -2.8794384 , ..., nan, nan, nan], [-0.86828613, -0.8750534 , -2.4796886 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - WRADH(time2, range)float32nan nan 2.961 2.419 ... nan nan nan
- format :
- UV16
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
array([[ nan, nan, 2.9606285, ..., nan, nan, nan], [ nan, 2.8952253, 4.6718283, ..., nan, nan, nan], [ nan, 2.5560865, nan, ..., nan, nan, nan], ..., [ nan, nan, 2.956118 , ..., nan, nan, nan], [ nan, 3.2704487, 3.2405663, ..., nan, nan, nan], [0. , 3.9828377, 3.9191258, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - WRADV(time2, range)float32nan nan 2.889 2.448 ... nan nan nan
- format :
- UV16
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
array([[ nan, nan, 2.8890233 , ..., nan, nan, nan], [ nan, 0.64529413, 4.5331283 , ..., nan, nan, nan], [ nan, 2.1391401 , nan, ..., nan, nan, nan], ..., [ nan, nan, 2.969086 , ..., nan, nan, nan], [ nan, 3.380394 , 3.2673478 , ..., nan, nan, nan], [0. , 4.2906847 , 3.950136 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - ZDR(time2, range)float32nan nan 0.07813 ... nan nan nan
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.07812881, ..., nan, nan, nan], [ nan, 14.254341 , 1.9863892 , ..., nan, nan, nan], [ nan, 14.23481 , nan, ..., nan, nan, nan], ..., [ nan, nan, 0.104496 , ..., nan, nan, nan], [ nan, 1.1098976 , 0.22852325, ..., nan, nan, nan], [ 0.37208176, 1.8291588 , 0.29883575, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - sweep_number(time2, range)float64nan nan 0.0 0.0 ... nan nan nan nan
array([[nan, nan, 0., ..., nan, nan, nan], [nan, 0., 0., ..., nan, nan, nan], [nan, 0., nan, ..., nan, nan, nan], ..., [nan, nan, 0., ..., nan, nan, nan], [nan, 0., 0., ..., nan, nan, nan], [ 0., 0., 0., ..., nan, nan, nan]], shape=(72, 350)) - sweep_fixed_angle(time2, range)float64nan nan 28.0 28.0 ... nan nan nan
array([[nan, nan, 28., ..., nan, nan, nan], [nan, 28., 28., ..., nan, nan, nan], [nan, 28., nan, ..., nan, nan, nan], ..., [nan, nan, 28., ..., nan, nan, nan], [nan, 28., 28., ..., nan, nan, nan], [28., 28., 28., ..., nan, nan, nan]], shape=(72, 350)) - DEM(range, time2)float32nan nan nan nan ... nan nan nan nan
array([[ nan, nan, nan, ..., nan, nan, 72.677864], [ nan, 71.43132 , 70.39011 , ..., nan, 72.184326, 71.07218 ], [71.16739 , 72.65429 , nan, ..., 71.157074, 71.19573 , 71.294914], ..., [ nan, nan, nan, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan]], shape=(350, 72), dtype=float32) - PBB(range, time2)float64nan nan nan nan ... nan nan nan nan
array([[nan, nan, nan, ..., nan, nan, 0.], [nan, 0., 0., ..., nan, 0., 0.], [ 0., 0., nan, ..., 0., 0., 0.], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], shape=(350, 72)) - CBB(range, time2)float64nan nan nan nan ... nan nan nan nan
array([[nan, nan, nan, ..., nan, nan, 0.], [nan, 0., 0., ..., nan, 0., 0.], [ 0., 0., nan, ..., 0., 0., 0.], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], shape=(350, 72)) - QBBF(range, time2)float64nan nan nan nan ... nan nan nan nan
array([[nan, nan, nan, ..., nan, nan, 1.], [nan, 1., 1., ..., nan, 1., 1.], [ 1., 1., nan, ..., 1., 1., 1.], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], shape=(350, 72)) - SNRH(time2, range)float64nan nan 40.61 39.53 ... nan nan nan
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
array([[ nan, nan, 40.60678792, ..., nan, nan, nan], [ nan, 52.6644855 , 36.84935307, ..., nan, nan, nan], [ nan, 52.40227084, nan, ..., nan, nan, nan], ..., [ nan, nan, 49.79164052, ..., nan, nan, nan], [ nan, 60.83562617, 60.11324048, ..., nan, nan, nan], [50.97305284, 58.34971766, 56.93443799, ..., nan, nan, nan]], shape=(72, 350)) - RHOHV_NC(time2, range)float64nan nan 0.9388 ... nan nan nan
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.93884742, ..., nan, nan, nan], [ nan, 0.82717596, 0.87052103, ..., nan, nan, nan], [ nan, 0.84213821, nan, ..., nan, nan, nan], ..., [ nan, nan, 0.9906383 , ..., nan, nan, nan], [ nan, 0.89071399, 0.99794071, ..., nan, nan, nan], [0.86511165, 0.86375097, 0.99720894, ..., nan, nan, nan]], shape=(72, 350)) - SYSPHI1(time2, range)float32nan nan -84.71 ... nan nan nan
array([[ nan, nan, -84.71267, ..., nan, nan, nan], [ nan, -84.69619, -84.69619, ..., nan, nan, nan], [ nan, -84.43251, nan, ..., nan, nan, nan], ..., [ nan, nan, -85.1439 , ..., nan, nan, nan], [ nan, -84.78683, -84.78683, ..., nan, nan, nan], [-84.88022, -84.88022, -84.88022, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - PHIDP_OC1(time2, range)float32nan nan -0.1154 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, -0.11535645, ..., nan, nan, nan], [ nan, 6.825466 , 6.767784 , ..., nan, nan, nan], [ nan, 13.175758 , nan, ..., nan, nan, nan], ..., [ nan, nan, -0.92287445, ..., nan, nan, nan], [ nan, -1.2002945 , -1.2002945 , ..., nan, nan, nan], [-1.777092 , -1.0684509 , -1.1096497 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - SYSPHI2(time2, range)float32nan nan -84.81 ... nan nan nan
array([[ nan, nan, -84.8088 , ..., nan, nan, nan], [ nan, -84.764854, -84.764854, ..., nan, nan, nan], [ nan, -84.49843 , nan, ..., nan, nan, nan], ..., [ nan, nan, -85.19745 , ..., nan, nan, nan], [ nan, -84.79781 , -84.79781 , ..., nan, nan, nan], [-85.1535 , -85.1535 , -85.1535 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - PHIDP_OC2(time2, range)float32nan nan -0.01923 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, -0.01922607, ..., nan, nan, nan], [ nan, 6.8941307 , 6.8364487 , ..., nan, nan, nan], [ nan, 13.241676 , nan, ..., nan, nan, nan], ..., [ nan, nan, -0.86932373, ..., nan, nan, nan], [ nan, -1.1893082 , -1.1893082 , ..., nan, nan, nan], [-1.5038071 , -0.795166 , -0.83636475, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - SYSPHI3(time2, range)float32nan nan -84.77 ... nan nan nan
array([[ nan, nan, -84.768974, ..., nan, nan, nan], [ nan, -84.71953 , -84.71953 , ..., nan, nan, nan], [ nan, -84.405045, nan, ..., nan, nan, nan], ..., [ nan, nan, -85.21942 , ..., nan, nan, nan], [ nan, -84.83627 , -84.83627 , ..., nan, nan, nan], [-85.079346, -85.079346, -85.079346, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - PHIDP_OC3(time2, range)float32nan nan -0.05905 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, -0.05905151, ..., nan, nan, nan], [ nan, 6.8488045 , 6.7911224 , ..., nan, nan, nan], [ nan, 13.148293 , nan, ..., nan, nan, nan], ..., [ nan, nan, -0.8473511 , ..., nan, nan, nan], [ nan, -1.1508484 , -1.1508484 , ..., nan, nan, nan], [-1.5779648 , -0.86932373, -0.91052246, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - SYSPHI4(time2, range)float64nan nan -85.05 ... nan nan nan
array([[ nan, nan, -85.05, ..., nan, nan, nan], [ nan, -84.75, -84.95, ..., nan, nan, nan], [ nan, -84.85, nan, ..., nan, nan, nan], ..., [ nan, nan, -85.1 , ..., nan, nan, nan], [ nan, -84.65, -84.65, ..., nan, nan, nan], [-82.65, -84.65, -84.8 , ..., nan, nan, nan]], shape=(72, 350)) - PHIDP_OC4(time2, range)float64nan nan 0.5068 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.50677032, ..., nan, nan, nan], [ nan, 7.56407623, 7.02159424, ..., nan, nan, nan], [ nan, 13.6805275 , nan, ..., nan, nan, nan], ..., [ nan, nan, -0.93824081, ..., nan, nan, nan], [ nan, -1.27669678, -1.29536133, ..., nan, nan, nan], [-4.00731049, -1.20303955, -1.13162842, ..., nan, nan, nan]], shape=(72, 350)) - RHOHV_SMOOTH(time2, range)float32nan nan 0.9771 ... nan nan nan
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.97712636, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], ..., [ nan, nan, 0.99285865, ..., nan, nan, nan], [ nan, 0.998352 , 0.99839395, ..., nan, nan, nan], [0.99849695, 0.9982299 , 0.9980468 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - PHIDP_CORR1(time2, range)float64nan nan nan nan ... nan nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], shape=(72, 350)) - PHIDP_CORR2(time2, range)float32nan nan 0.3708 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.37080383, ..., nan, nan, nan], [ nan, 0.86520195, 0.75258636, ..., nan, nan, nan], [ nan, 0.3296051 , nan, ..., nan, nan, nan], ..., [ nan, nan, 0.29389763, ..., nan, nan, nan], [ nan, 0.35980988, 0.37903595, ..., nan, nan, nan], [0.91464233, 0.6592026 , 0.28016663, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - PHIDP_CORR3(time2, range)float64nan nan 0.2142 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.21424103, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], ..., [ nan, nan, 0.77456665, ..., nan, nan, nan], [ nan, 0.35157013, 0.61799622, ..., nan, nan, nan], [ nan, 0.87893677, 0.51912689, ..., nan, nan, nan]], shape=(72, 350)) - PHIDP_CORR4(time2, range)float64nan nan 0.4169 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.41685577, ..., nan, nan, nan], [ nan, 0.81465045, 0.72352518, ..., nan, nan, nan], [ nan, 0.31515443, nan, ..., nan, nan, nan], ..., [ nan, nan, 0.39553805, ..., nan, nan, nan], [ nan, 0.41155699, 0.44067541, ..., nan, nan, nan], [1.12581455, 0.67634479, 0.33429543, ..., nan, nan, nan]], shape=(72, 350)) - KDP_LANC(time2, range)float64nan nan nan nan ... nan nan nan nan
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
array([[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], shape=(72, 350)) - KDP_VULP(time2, range)float64nan nan 0.0 0.0 ... nan nan nan nan
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
array([[nan, nan, 0., ..., nan, nan, nan], [nan, 0., 0., ..., nan, nan, nan], [nan, 0., nan, ..., nan, nan, nan], ..., [nan, nan, 0., ..., nan, nan, nan], [nan, 0., 0., ..., nan, nan, nan], [ 0., 0., 0., ..., nan, nan, nan]], shape=(72, 350)) - DBTH_CORR1(time2, range)float64nan nan nan nan ... nan nan nan nan
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], shape=(72, 350)) - DBZH_CORR1(time2, range)float64nan nan nan nan ... nan nan nan nan
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], shape=(72, 350)) - ZDR_CORR1(time2, range)float64nan nan nan nan ... nan nan nan nan
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
array([[nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], ..., [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan], [nan, nan, nan, ..., nan, nan, nan]], shape=(72, 350)) - DBTH_CORR2(time2, range)float32nan nan 5.273 6.752 ... nan nan nan
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 5.272956 , ..., nan, nan, nan], [ nan, 12.569988 , 1.4929584, ..., nan, nan, nan], [ nan, 12.384533 , nan, ..., nan, nan, nan], ..., [ nan, nan, 13.973665 , ..., nan, nan, nan], [ nan, 20.645405 , 24.196423 , ..., nan, nan, nan], [ 8.5229225, 19.836329 , 22.049814 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - DBZH_CORR2(time2, range)float32nan nan 4.719 6.517 ... nan nan nan
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 4.718609 , ..., nan, nan, nan], [ nan, 12.375414 , 1.0071315, ..., nan, nan, nan], [ nan, 12.145849 , nan, ..., nan, nan, nan], ..., [ nan, nan, 13.799395 , ..., nan, nan, nan], [ nan, 20.472198 , 24.197174 , ..., nan, nan, nan], [ 1.2102014, 18.018917 , 21.059364 , ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - ZDR_CORR2(time2, range)float32nan nan 0.09794 ... nan nan nan
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.09793703, ..., nan, nan, nan], [ nan, 14.276005 , 2.024187 , ..., nan, nan, nan], [ nan, 14.277395 , nan, ..., nan, nan, nan], ..., [ nan, nan, 0.11923124, ..., nan, nan, nan], [ nan, 1.118566 , 0.24116804, ..., nan, nan, nan], [ 0.4179844 , 1.8364077 , 0.31115496, ..., nan, nan, nan]], shape=(72, 350), dtype=float32) - DBTH_CORR3(time2, range)float64nan nan 5.716 6.998 ... nan nan nan
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 5.71615891, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], ..., [ nan, nan, 14.30088364, ..., nan, nan, nan], [ nan, 23.76068909, 24.20909454, ..., nan, nan, nan], [ nan, 24.07399765, 22.32034088, ..., nan, nan, nan]], shape=(72, 350)) - DBZH_CORR3(time2, range)float64nan nan 5.615 6.59 ... nan nan nan
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 5.6154837 , ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], ..., [ nan, nan, 14.12553574, ..., nan, nan, nan], [ nan, 24.44036331, 24.26168457, ..., nan, nan, nan], [ nan, 15.61441315, 21.50198486, ..., nan, nan, nan]], shape=(72, 350)) - ZDR_CORR3(time2, range)float64nan nan 0.1576 ... nan nan nan
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.15763131, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], [ nan, nan, nan, ..., nan, nan, nan], ..., [ nan, nan, 0.13681813, ..., nan, nan, nan], [ nan, 0.8514084 , 0.25480272, ..., nan, nan, nan], [ nan, 6.24889622, 0.31919633, ..., nan, nan, nan]], shape=(72, 350)) - DBTH_CORR4(time2, range)float64nan nan 5.295 6.777 ... nan nan nan
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 5.29485996, ..., nan, nan, nan], [ nan, 12.63809178, 1.49285418, ..., nan, nan, nan], [ nan, 12.39254792, nan, ..., nan, nan, nan], ..., [ nan, nan, 13.99643137, ..., nan, nan, nan], [ nan, 20.64994459, 24.21173383, ..., nan, nan, nan], [ 8.58205089, 19.8416686 , 22.06871792, ..., nan, nan, nan]], shape=(72, 350)) - DBZH_CORR4(time2, range)float64nan nan 4.739 6.526 ... nan nan nan
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 4.73904481, ..., nan, nan, nan], [ nan, 12.39906002, 1.01898948, ..., nan, nan, nan], [ nan, 12.1438726 , nan, ..., nan, nan, nan], ..., [ nan, nan, 13.81324221, ..., nan, nan, nan], [ nan, 20.4879113 , 24.23982788, ..., nan, nan, nan], [ 1.26932964, 18.05099484, 21.10896047, ..., nan, nan, nan]], shape=(72, 350)) - ZDR_CORR4(time2, range)float64nan nan 0.09912 ... nan nan nan
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.09911685, ..., nan, nan, nan], [ nan, 14.2903924 , 2.02416843, ..., nan, nan, nan], [ nan, 14.2672085 , nan, ..., nan, nan, nan], ..., [ nan, nan, 0.12669754, ..., nan, nan, nan], [ nan, 1.1216456 , 0.24610298, ..., nan, nan, nan], [ 0.42854301, 1.82967703, 0.31464734, ..., nan, nan, nan]], shape=(72, 350)) - AH(time2, range)float64nan nan 9.324e-07 ... nan nan nan
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
array([[ nan, nan, 9.32385615e-07, ..., nan, nan, nan], [ nan, 7.34900116e-07, 8.00128817e-08, ..., nan, nan, nan], [ nan, 2.15179877e-07, nan, ..., nan, nan, nan], ..., [ nan, nan, 8.49750149e-08, ..., nan, nan, nan], [ nan, 3.62816958e-08, 1.10027329e-07, ..., nan, nan, nan], [1.20495107e-07, 9.17598157e-08, 1.16768547e-07, ..., nan, nan, nan]], shape=(72, 350)) - KDP_AH(time2, range)float64nan nan 3.33e-06 ... nan nan nan
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, 3.32994863e-06, ..., nan, nan, nan], [ nan, 2.62464327e-06, 2.85760292e-07, ..., nan, nan, nan], [ nan, 7.68499560e-07, nan, ..., nan, nan, nan], ..., [ nan, nan, 3.03482196e-07, ..., nan, nan, nan], [ nan, 1.29577485e-07, 3.92954746e-07, ..., nan, nan, nan], [4.30339667e-07, 3.27713627e-07, 4.17030525e-07, ..., nan, nan, nan]], shape=(72, 350)) - PHIDP_CORR5(time2, range)float64nan nan 1.332e-06 ... nan nan nan
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
array([[ nan, nan, 1.33197941e-06, ..., nan, nan, nan], [ nan, 5.24928646e-07, 1.14304116e-07, ..., nan, nan, nan], [ nan, 1.53699911e-07, nan, ..., nan, nan, nan], ..., [ nan, nan, 1.21392878e-07, ..., nan, nan, nan], [ nan, 2.59154970e-08, 1.56812979e-07, ..., nan, nan, nan], [0.00000000e+00, 6.55427254e-08, 1.66812209e-07, ..., nan, nan, nan]], shape=(72, 350)) - DBTH_CORR5(time2, range)float64nan nan 5.172 6.616 ... nan nan nan
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 5.17151647, ..., nan, nan, nan], [ nan, 12.42147151, 1.28223419, ..., nan, nan, nan], [ nan, 12.24425836, nan, ..., nan, nan, nan], ..., [ nan, nan, 13.90664678, ..., nan, nan, nan], [ nan, 20.55284143, 24.09077727, ..., nan, nan, nan], [ 8.26682281, 19.6812363 , 21.99136361, ..., nan, nan, nan]], shape=(72, 350)) - DBZH_CORR5(time2, range)float64nan nan 4.574 6.42 ... nan nan nan
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
array([[ nan, nan, 4.57384157, ..., nan, nan, nan], [ nan, 12.19170261, 0.81640286, ..., nan, nan, nan], [ nan, 11.92905135, nan, ..., nan, nan, nan], ..., [ nan, nan, 13.75869128, ..., nan, nan, nan], [ nan, 20.36240388, 24.08029175, ..., nan, nan, nan], [ 0.95410156, 17.87649536, 20.90149055, ..., nan, nan, nan]], shape=(72, 350)) - ZDR_CORR5(time2, range)float64nan nan 0.0783 ... nan nan nan
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
array([[ nan, nan, 0.07829757, ..., nan, nan, nan], [ nan, 14.25455149, 1.98655772, ..., nan, nan, nan], [ nan, 14.23498059, nan, ..., nan, nan, nan], ..., [ nan, nan, 0.10466653, ..., nan, nan, nan], [ nan, 1.11006618, 0.2286941 , ..., nan, nan, nan], [ 0.37225229, 1.82932735, 0.29919069, ..., nan, nan, nan]], shape=(72, 350))
Plot moments - 4#
_kwargs = dict(x="time2", y="height", ylim=(0, 8000), cmap="HomeyerRainbow")
fig = plt.figure(figsize=(14, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
qvp_4.DBZH_CORR2.plot.contourf(**kwargs)
ax1.set_title(qvp_4.DBZH_CORR2.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
qvp_4.ZDR_CORR2.plot.contourf(**kwargs)
ax2.set_title(qvp_4.ZDR_CORR2.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
qvp_4.RHOHV_NC.plot.contourf(**kwargs)
ax3.set_title(qvp_4.RHOHV_NC.attrs["long_name"])
ax4 = fig.add_subplot(224)
philevels2 = np.arange(0, 15, 1)
kwargs = _kwargs | levels(philevels2) | dict(ax=ax4)
qvp_4.PHIDP_CORR2.plot(**kwargs)
ax4.set_title(qvp_4.PHIDP_CORR2.attrs["long_name"])
# kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
# qvp_4.KDP_VULP.plot.contourf(**kwargs)
# ax4.set_title(qvp_4.KDP_VULP.attrs["long_name"])
fig.tight_layout()
Event 5 - RHI#
07.10.2014 01:20 UTC
scan: ‘n_rhi_lacros’
zh_offset = -0.2
zdr_offset = -0.4
# recent boxpol event
start_time = dt.datetime(2014, 10, 7, 1, 20)
stop_time = dt.datetime(2014, 10, 7, 1, 25)
loc = "boxpol"
scan = "n_rhi_lacros"
Open dataset - 5#
reindex_angle = dict(start_angle=0, stop_angle=90, angle_res=0.2, direction=1)
sweep_rhi_5 = rp.load_single_sweep(start_time, scan, reindex_angle=reindex_angle)
Apply offsets - 5#
sweep_rhi_5["DBZH"] -= zh_offset
sweep_rhi_5["DBTH"] -= zh_offset
sweep_rhi_5["ZDR"] -= zdr_offset
Preprocess data - 5#
##%%time
# sweep_rhi_5 = rp.workflow(sweep_rhi_5, scan, rp.data_path())
Open preprocessed dataset - 5#
workflow_file = f"/radar/rp-data/workflow/tmp_{start_time:%Y%m%dT%H%M}_{stop_time:%Y%m%dT%H%M}_workflow.nc"
with rp.rpol_data.open(workflow_file) as f:
workflow_file = f.name
sweep_rhi_5 = xr.open_dataset(workflow_file)
display(sweep_rhi_5)
<xarray.Dataset> Size: 101MB
Dimensions: (elevation: 450, range: 667)
Coordinates: (12/18)
* elevation (elevation) float64 4kB 0.1 0.3 0.5 ... 89.5 89.7 89.9
azimuth (elevation) float64 4kB ...
time (elevation) datetime64[ns] 4kB ...
* range (range) float32 3kB 37.5 112.5 ... 4.991e+04 4.999e+04
x (elevation, range) float64 2MB ...
y (elevation, range) float64 2MB ...
... ...
latitude float64 8B ...
altitude float64 8B ...
crs_wkt int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/51)
KDP (elevation, range) float32 1MB ...
PHIDP (elevation, range) float32 1MB ...
DBZH (elevation, range) float32 1MB ...
DBZV (elevation, range) float32 1MB ...
RHOHV (elevation, range) float32 1MB ...
DBTH (elevation, range) float32 1MB ...
... ...
AH (elevation, range) float64 2MB ...
KDP_AH (elevation, range) float64 2MB ...
PHIDP_CORR5 (elevation, range) float64 2MB ...
DBTH_CORR5 (elevation, range) float64 2MB ...
DBZH_CORR5 (elevation, range) float64 2MB ...
ZDR_CORR5 (elevation, range) float64 2MB ...xarray.Dataset
- elevation: 450
- range: 667
- elevation(elevation)float640.1 0.3 0.5 0.7 ... 89.5 89.7 89.9
- standard_name :
- ray_elevation_angle
- long_name :
- elevation_angle_from_horizontal_plane
- units :
- degrees
- axis :
- radial_elevation_coordinate
array([ 0.1, 0.3, 0.5, ..., 89.5, 89.7, 89.9], shape=(450,))
- azimuth(elevation)float64...
- standard_name :
- ray_azimuth_angle
- long_name :
- azimuth_angle_from_true_north
- units :
- degrees
- axis :
- radial_azimuth_coordinate
[450 values with dtype=float64]
- time(elevation)datetime64[ns]...
- standard_name :
- time
[450 values with dtype=datetime64[ns]]
- range(range)float3237.5 112.5 ... 4.991e+04 4.999e+04
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 75.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 37.5
array([3.75000e+01, 1.12500e+02, 1.87500e+02, ..., 4.98375e+04, 4.99125e+04, 4.99875e+04], shape=(667,), dtype=float32) - x(elevation, range)float64...
- standard_name :
- east_west_distance_from_radar
- units :
- meters
[300150 values with dtype=float64]
- y(elevation, range)float64...
- standard_name :
- north_south_distance_from_radar
- units :
- meters
[300150 values with dtype=float64]
- z(elevation, range)float64...
- standard_name :
- height_above_ground
- units :
- meters
[300150 values with dtype=float64]
- gr(elevation, range)float64...
- standard_name :
- distance_from_radar
- units :
- meters
[300150 values with dtype=float64]
- rays(elevation, range)float64...
- standard_name :
- ray_elevation_angle
- long_name :
- elevation_angle_from_horizontal_plane
- units :
- degrees
- axis :
- radial_elevation_coordinate
[300150 values with dtype=float64]
- bins(elevation, range)float32...
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 75.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 37.5
[300150 values with dtype=float32]
- sweep_mode()<U3...
[1 values with dtype=<U3]
- longitude()float64...
- long_name :
- longitude
- units :
- degrees_east
- standard_name :
- longitude
[1 values with dtype=float64]
- latitude()float64...
- long_name :
- latitude
- units :
- degrees_north
- positive :
- up
- standard_name :
- latitude
[1 values with dtype=float64]
- altitude()float64...
- long_name :
- altitude
- units :
- meters
- standard_name :
- altitude
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(elevation, range)float32...
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- PHIDP(elevation, range)float32...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- DBZH(elevation, range)float32...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- DBZV(elevation, range)float32...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- RHOHV(elevation, range)float32...
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- DBTH(elevation, range)float32...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- DBTV(elevation, range)float32...
- format :
- UV16
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- VRADH(elevation, range)float32...
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- VRADV(elevation, range)float32...
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- WRADH(elevation, range)float32...
- format :
- UV16
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- WRADV(elevation, range)float32...
- format :
- UV16
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- ZDR(elevation, range)float32...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- sweep_number()int64...
[1 values with dtype=int64]
- prt_mode()<U7...
[1 values with dtype=<U7]
- follow_mode()<U7...
[1 values with dtype=<U7]
- sweep_fixed_angle()float64...
[1 values with dtype=float64]
- SNRH(elevation, range)float64...
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
[300150 values with dtype=float64]
- RHOHV_NC(elevation, range)float64...
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- SYSPHI1()float64...
[1 values with dtype=float64]
- PHIDP_OC1(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- SYSPHI2()float64...
[1 values with dtype=float64]
- PHIDP_OC2(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- SYSPHI3()float64...
[1 values with dtype=float64]
- PHIDP_OC3(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- SYSPHI4(elevation)float64...
[450 values with dtype=float64]
- PHIDP_OC4(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- RHOHV_SMOOTH(elevation, range)float32...
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
[300150 values with dtype=float32]
- PHIDP_CORR1(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- PHIDP_CORR2(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- PHIDP_CORR3(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- PHIDP_CORR4(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- KDP_LANC(elevation, range)float64...
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
[300150 values with dtype=float64]
- KDP_VULP(elevation, range)float64...
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
[300150 values with dtype=float64]
- DBTH_CORR1(elevation, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBZH_CORR1(elevation, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- ZDR_CORR1(elevation, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBTH_CORR2(elevation, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBZH_CORR2(elevation, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- ZDR_CORR2(elevation, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBTH_CORR3(elevation, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBZH_CORR3(elevation, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- ZDR_CORR3(elevation, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBTH_CORR4(elevation, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBZH_CORR4(elevation, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- ZDR_CORR4(elevation, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- AH(elevation, range)float64...
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
[300150 values with dtype=float64]
- KDP_AH(elevation, range)float64...
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- PHIDP_CORR5(elevation, range)float64...
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBTH_CORR5(elevation, range)float64...
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- DBZH_CORR5(elevation, range)float64...
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
[300150 values with dtype=float64]
- ZDR_CORR5(elevation, range)float64...
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
[300150 values with dtype=float64]
Plot moments - 5#
_kwargs = dict(x="gr", y="z", xlim=(0, 25000), ylim=(0, 8000), cmap="HomeyerRainbow")
fig = plt.figure(figsize=(16, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
sweep_rhi_5.DBZH_CORR2.plot.contourf(**kwargs)
ax1.set_title(sweep_rhi_5.DBZH_CORR2.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
sweep_rhi_5.ZDR_CORR2.plot.contourf(**kwargs)
ax2.set_title(sweep_rhi_5.ZDR_CORR1.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
sweep_rhi_5.RHOHV_NC.plot.contourf(**kwargs)
ax3.set_title(sweep_rhi_5.RHOHV_NC.attrs["long_name"])
ax4 = fig.add_subplot(224)
# philevels2 = np.arange(0, 40, 2)
# kwargs = _kwargs | levels(philevels2) | dict(ax=ax4)
# sweep_rhi_5.PHIDP_CORR2.plot.contourf(**kwargs)
# ax4.set_title(sweep_rhi_5.PHIDP_CORR2.attrs["long_name"])
kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
sweep_rhi_5.KDP_VULP.plot(**kwargs)
ax4.set_title(sweep_rhi_5.KDP_VULP.attrs["long_name"])
fig.tight_layout()
Event 6 - QVP#
26.7.2015 von 15:30 bis 18:30 UTC
scan: ‘n_ppi_280deg’
zh_offset = 2.5 ??
zdr_offset = 0.8 ??
zh_offset = -1.0
zdr_offset = -0.9
# recent boxpol event
start_time = dt.datetime(2015, 7, 26, 15, 30)
stop_time = dt.datetime(2015, 7, 26, 18, 30)
delta = stop_time - start_time
loc = "boxpol"
scan = "n_ppi_110deg"
Open dataset - 6#
reindex_angle = dict(start_angle=0, stop_angle=360, angle_res=1.0, direction=1)
sweep_6 = rp.load_timeseries_sweep(start_time, delta, scan, reindex_angle=reindex_angle)
sweep_6 = sweep_6.set_coords("sweep_mode")
sweep_6["sweep_mode"] = sweep_6["sweep_mode"][0]
sweep_6 = sweep_6.wrl.georef.georeference()
sweep_6 = sweep_6.assign_coords(height=sweep_6.z.mean("azimuth"))
loading 36 files
Apply offsets - 6#
sweep_6["DBTH"] -= zh_offset
sweep_6["DBZH"] -= zh_offset
sweep_6["ZDR"] -= zdr_offset
Preprocess data - 6#
##%%time
# sweep_6a = rp.workflow(sweep_6, scan, rp.data_path())
Open preprocessed dataset - 6#
workflow_file = f"/radar/rp-data/workflow/tmp_{start_time:%Y%m%dT%H%M}_{stop_time:%Y%m%dT%H%M}_workflow.nc"
with rp.rpol_data.open(workflow_file) as f:
workflow_file = f.name
sweep_6 = xr.open_dataset(workflow_file, chunks=dict(time2=1))
display(sweep_6)
<xarray.Dataset> Size: 3GB
Dimensions: (time2: 36, azimuth: 360, range: 1000)
Coordinates: (12/24)
* time2 (time2) datetime64[ns] 288B 2015-07-26T15:31:42 ... 20...
* azimuth (azimuth) float64 3kB 0.5 1.5 2.5 ... 357.5 358.5 359.5
elevation (azimuth) float64 3kB dask.array<chunksize=(360,), meta=np.ndarray>
time (time2, azimuth) datetime64[ns] 104kB dask.array<chunksize=(1, 360), meta=np.ndarray>
* range (range) float32 4kB 50.0 150.0 ... 9.985e+04 9.995e+04
x (azimuth, range) float64 3MB dask.array<chunksize=(360, 1000), meta=np.ndarray>
... ...
crs_wkt int64 8B ...
band int64 8B ...
spatial_ref int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/55)
KDP (time2, azimuth, range) float32 52MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
PHIDP (time2, azimuth, range) float32 52MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
DBZH (time2, azimuth, range) float32 52MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
DBZV (time2, azimuth, range) float32 52MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
RHOHV (time2, azimuth, range) float32 52MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
DBTH (time2, azimuth, range) float32 52MB dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
... ...
AH (time2, azimuth, range) float64 104MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
KDP_AH (time2, azimuth, range) float64 104MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
PHIDP_CORR5 (time2, azimuth, range) float64 104MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
DBTH_CORR5 (time2, azimuth, range) float64 104MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
DBZH_CORR5 (time2, azimuth, range) float64 104MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
ZDR_CORR5 (time2, azimuth, range) float64 104MB dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>xarray.Dataset
- time2: 36
- azimuth: 360
- range: 1000
- time2(time2)datetime64[ns]2015-07-26T15:31:42 ... 2015-07-...
array(['2015-07-26T15:31:42.000000000', '2015-07-26T15:36:42.000000000', '2015-07-26T15:41:42.000000000', '2015-07-26T15:46:42.000000000', '2015-07-26T15:51:42.000000000', '2015-07-26T15:56:42.000000000', '2015-07-26T16:01:42.000000000', '2015-07-26T16:06:42.000000000', '2015-07-26T16:11:42.000000000', '2015-07-26T16:16:42.000000000', '2015-07-26T16:21:42.000000000', '2015-07-26T16:26:43.000000000', '2015-07-26T16:31:42.000000000', '2015-07-26T16:36:42.000000000', '2015-07-26T16:41:42.000000000', '2015-07-26T16:46:42.000000000', '2015-07-26T16:51:42.000000000', '2015-07-26T16:56:42.000000000', '2015-07-26T17:01:42.000000000', '2015-07-26T17:06:42.000000000', '2015-07-26T17:11:42.000000000', '2015-07-26T17:16:42.000000000', '2015-07-26T17:21:42.000000000', '2015-07-26T17:26:42.000000000', '2015-07-26T17:31:42.000000000', '2015-07-26T17:36:42.000000000', '2015-07-26T17:41:42.000000000', '2015-07-26T17:46:42.000000000', '2015-07-26T17:51:42.000000000', '2015-07-26T17:56:42.000000000', '2015-07-26T18:01:42.000000000', '2015-07-26T18:06:42.000000000', '2015-07-26T18:11:42.000000000', '2015-07-26T18:16:42.000000000', '2015-07-26T18:21:42.000000000', '2015-07-26T18:26:42.000000000'], dtype='datetime64[ns]') - azimuth(azimuth)float640.5 1.5 2.5 ... 357.5 358.5 359.5
array([ 0.5, 1.5, 2.5, ..., 357.5, 358.5, 359.5], shape=(360,))
- elevation(azimuth)float64dask.array<chunksize=(360,), meta=np.ndarray>
Array Chunk Bytes 2.81 kiB 2.81 kiB Shape (360,) (360,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - time(time2, azimuth)datetime64[ns]dask.array<chunksize=(1, 360), meta=np.ndarray>
Array Chunk Bytes 101.25 kiB 2.81 kiB Shape (36, 360) (1, 360) Dask graph 36 chunks in 2 graph layers Data type datetime64[ns] numpy.ndarray - range(range)float3250.0 150.0 ... 9.985e+04 9.995e+04
array([5.000e+01, 1.500e+02, 2.500e+02, ..., 9.975e+04, 9.985e+04, 9.995e+04], shape=(1000,), dtype=float32) - x(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
- standard_name :
- east_west_distance_from_radar
- units :
- meters
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
- standard_name :
- north_south_distance_from_radar
- units :
- meters
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - z(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
- standard_name :
- height_above_ground
- units :
- meters
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - gr(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
- standard_name :
- distance_from_radar
- units :
- meters
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - rays(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - bins(azimuth, range)float32dask.array<chunksize=(360, 1000), meta=np.ndarray>
- units :
- meters
- standard_name :
- projection_range_coordinate
- long_name :
- range_to_measurement_volume
- axis :
- radial_range_coordinate
- meters_between_gates :
- 100.0
- spacing_is_constant :
- true
- meters_to_center_of_first_gate :
- 50.0
Array Chunk Bytes 1.37 MiB 1.37 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - height(range)float64dask.array<chunksize=(1000,), meta=np.ndarray>
Array Chunk Bytes 7.81 kiB 7.81 kiB Shape (1000,) (1000,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - xd(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - yd(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - sweep_mode()<U20...
[1 values with dtype=<U20]
- longitude()float64...
[1 values with dtype=float64]
- latitude()float64...
[1 values with dtype=float64]
- altitude()float64...
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- band()int64...
[1 values with dtype=int64]
- spatial_ref()int64...
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZH(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - RHOHV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTH(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - VRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - VRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - WRADH(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - WRADV(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - ZDR(time2, azimuth, range)float32dask.array<chunksize=(1, 180, 500), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 351.56 kiB Shape (36, 360, 1000) (1, 180, 500) Dask graph 144 chunks in 2 graph layers Data type float32 numpy.ndarray - sweep_number(time2)int64dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 288 B 8 B Shape (36,) (1,) Dask graph 36 chunks in 2 graph layers Data type int64 numpy.ndarray - prt_mode(time2)<U7dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 0.98 kiB 28 B Shape (36,) (1,) Dask graph 36 chunks in 2 graph layers Data type - follow_mode(time2)<U7dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 0.98 kiB 28 B Shape (36,) (1,) Dask graph 36 chunks in 2 graph layers Data type - sweep_fixed_angle(time2)float64dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 288 B 8 B Shape (36,) (1,) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DEM(azimuth, range)float32dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 1.37 MiB 1.37 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float32 numpy.ndarray - PBB(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - CBB(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - QBBF(azimuth, range)float64dask.array<chunksize=(360, 1000), meta=np.ndarray>
Array Chunk Bytes 2.75 MiB 2.75 MiB Shape (360, 1000) (360, 1000) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - SNRH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - RHOHV_NC(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - SYSPHI1(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 144 B 4 B Shape (36,) (1,) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC1(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 1.37 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI2(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 144 B 4 B Shape (36,) (1,) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 1.37 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI3(time2)float32dask.array<chunksize=(1,), meta=np.ndarray>
Array Chunk Bytes 144 B 4 B Shape (36,) (1,) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_OC3(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 1.37 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - SYSPHI4(time2, azimuth)float64dask.array<chunksize=(1, 360), meta=np.ndarray>
Array Chunk Bytes 101.25 kiB 2.81 kiB Shape (36, 360) (1, 360) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_OC4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - RHOHV_SMOOTH(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 1.37 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 1.37 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - PHIDP_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_LANC(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_VULP(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR1(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 1.37 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - DBZH_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 1.37 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - ZDR_CORR2(time2, azimuth, range)float32dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 49.44 MiB 1.37 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float32 numpy.ndarray - DBTH_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR3(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR4(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - AH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - KDP_AH(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - PHIDP_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DBTH_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - DBZH_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray - ZDR_CORR5(time2, azimuth, range)float64dask.array<chunksize=(1, 360, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 98.88 MiB 2.75 MiB Shape (36, 360, 1000) (1, 360, 1000) Dask graph 36 chunks in 2 graph layers Data type float64 numpy.ndarray
Calculate median - 6#
with xr.set_options(keep_attrs=True):
qvp_6 = sweep_6.where((sweep_6.DBZH_CORR2 > 0) & (sweep_6.RHOHV_NC > 0.8)).median(
"azimuth", skipna=True
)
qvp_6 = qvp_6.where(qvp_6.DBZH_CORR2 > 0)
display(qvp_6)
<xarray.Dataset> Size: 12MB
Dimensions: (time2: 36, range: 1000)
Coordinates: (12/13)
* time2 (time2) datetime64[ns] 288B 2015-07-26T15:31:42 ... 20...
* range (range) float32 4kB 50.0 150.0 ... 9.985e+04 9.995e+04
height (range) float64 8kB dask.array<chunksize=(1000,), meta=np.ndarray>
sweep_mode <U20 80B ...
longitude float64 8B ...
latitude float64 8B ...
... ...
crs_wkt int64 8B ...
band int64 8B ...
spatial_ref int64 8B ...
stdev float64 8B ...
NOISE_LEVEL float64 8B ...
alpha float64 8B ...
Data variables: (12/53)
KDP (time2, range) float32 144kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
PHIDP (time2, range) float32 144kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBZH (time2, range) float32 144kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBZV (time2, range) float32 144kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
RHOHV (time2, range) float32 144kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBTH (time2, range) float32 144kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
... ...
AH (time2, range) float64 288kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
KDP_AH (time2, range) float64 288kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
PHIDP_CORR5 (time2, range) float64 288kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBTH_CORR5 (time2, range) float64 288kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
DBZH_CORR5 (time2, range) float64 288kB dask.array<chunksize=(1, 1000), meta=np.ndarray>
ZDR_CORR5 (time2, range) float64 288kB dask.array<chunksize=(1, 1000), meta=np.ndarray>xarray.Dataset
- time2: 36
- range: 1000
- time2(time2)datetime64[ns]2015-07-26T15:31:42 ... 2015-07-...
array(['2015-07-26T15:31:42.000000000', '2015-07-26T15:36:42.000000000', '2015-07-26T15:41:42.000000000', '2015-07-26T15:46:42.000000000', '2015-07-26T15:51:42.000000000', '2015-07-26T15:56:42.000000000', '2015-07-26T16:01:42.000000000', '2015-07-26T16:06:42.000000000', '2015-07-26T16:11:42.000000000', '2015-07-26T16:16:42.000000000', '2015-07-26T16:21:42.000000000', '2015-07-26T16:26:43.000000000', '2015-07-26T16:31:42.000000000', '2015-07-26T16:36:42.000000000', '2015-07-26T16:41:42.000000000', '2015-07-26T16:46:42.000000000', '2015-07-26T16:51:42.000000000', '2015-07-26T16:56:42.000000000', '2015-07-26T17:01:42.000000000', '2015-07-26T17:06:42.000000000', '2015-07-26T17:11:42.000000000', '2015-07-26T17:16:42.000000000', '2015-07-26T17:21:42.000000000', '2015-07-26T17:26:42.000000000', '2015-07-26T17:31:42.000000000', '2015-07-26T17:36:42.000000000', '2015-07-26T17:41:42.000000000', '2015-07-26T17:46:42.000000000', '2015-07-26T17:51:42.000000000', '2015-07-26T17:56:42.000000000', '2015-07-26T18:01:42.000000000', '2015-07-26T18:06:42.000000000', '2015-07-26T18:11:42.000000000', '2015-07-26T18:16:42.000000000', '2015-07-26T18:21:42.000000000', '2015-07-26T18:26:42.000000000'], dtype='datetime64[ns]') - range(range)float3250.0 150.0 ... 9.985e+04 9.995e+04
array([5.000e+01, 1.500e+02, 2.500e+02, ..., 9.975e+04, 9.985e+04, 9.995e+04], shape=(1000,), dtype=float32) - height(range)float64dask.array<chunksize=(1000,), meta=np.ndarray>
Array Chunk Bytes 7.81 kiB 7.81 kiB Shape (1000,) (1000,) Dask graph 1 chunks in 2 graph layers Data type float64 numpy.ndarray - sweep_mode()<U20...
[1 values with dtype=<U20]
- longitude()float64...
[1 values with dtype=float64]
- latitude()float64...
[1 values with dtype=float64]
- altitude()float64...
[1 values with dtype=float64]
- crs_wkt()int64...
- crs_wkt :
- PROJCRS["unknown",BASEGEOGCRS["unknown",DATUM["World Geodetic System 1984",ELLIPSOID["WGS 84",6378137,298.257223563,LENGTHUNIT["metre",1]],ID["EPSG",6326]],PRIMEM["Greenwich",0,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8901]]],CONVERSION["unknown",METHOD["Modified Azimuthal Equidistant",ID["EPSG",9832]],PARAMETER["Latitude of natural origin",50.73052,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8801]],PARAMETER["Longitude of natural origin",7.071663,ANGLEUNIT["degree",0.0174532925199433],ID["EPSG",8802]],PARAMETER["False easting",0,LENGTHUNIT["metre",1],ID["EPSG",8806]],PARAMETER["False northing",0,LENGTHUNIT["metre",1],ID["EPSG",8807]]],CS[Cartesian,2],AXIS["(E)",east,ORDER[1],LENGTHUNIT["metre",1,ID["EPSG",9001]]],AXIS["(N)",north,ORDER[2],LENGTHUNIT["metre",1,ID["EPSG",9001]]]]
- semi_major_axis :
- 6378137.0
- semi_minor_axis :
- 6356752.314245179
- inverse_flattening :
- 298.257223563
- reference_ellipsoid_name :
- WGS 84
- longitude_of_prime_meridian :
- 0.0
- prime_meridian_name :
- Greenwich
- geographic_crs_name :
- unknown
- horizontal_datum_name :
- World Geodetic System 1984
- projected_crs_name :
- unknown
- grid_mapping_name :
- azimuthal_equidistant
- latitude_of_projection_origin :
- 50.73052
- longitude_of_projection_origin :
- 7.071663
- false_easting :
- 0.0
- false_northing :
- 0.0
[1 values with dtype=int64]
- band()int64...
[1 values with dtype=int64]
- spatial_ref()int64...
[1 values with dtype=int64]
- stdev()float64...
[1 values with dtype=float64]
- NOISE_LEVEL()float64...
[1 values with dtype=float64]
- alpha()float64...
[1 values with dtype=float64]
- KDP(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - PHIDP(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - DBZH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - DBZV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor V
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - RHOHV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - DBTH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - DBTV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power V (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_v
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - VRADH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument H
- units :
- meters per seconds
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_h
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - VRADV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Radial velocity of scatterers away from instrument V
- units :
- meters per second
- standard_name :
- radial_velocity_of_scatterers_away_from_instrument_v
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - WRADH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Doppler spectrum width H
- units :
- meters per seconds
- standard_name :
- radar_doppler_spectrum_width_h
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - WRADV(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Doppler spectrum width V
- units :
- meters per second
- standard_name :
- radar_doppler_spectrum_width_v
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - ZDR(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - sweep_number(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 17 graph layers Data type float64 numpy.ndarray - sweep_fixed_angle(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 16 graph layers Data type float64 numpy.ndarray - DEM(range, time2)float32dask.array<chunksize=(1000, 1), meta=np.ndarray>
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (1000, 36) (1000, 1) Dask graph 36 chunks in 18 graph layers Data type float32 numpy.ndarray - PBB(range, time2)float64dask.array<chunksize=(1000, 1), meta=np.ndarray>
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (1000, 36) (1000, 1) Dask graph 36 chunks in 18 graph layers Data type float64 numpy.ndarray - CBB(range, time2)float64dask.array<chunksize=(1000, 1), meta=np.ndarray>
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (1000, 36) (1000, 1) Dask graph 36 chunks in 18 graph layers Data type float64 numpy.ndarray - QBBF(range, time2)float64dask.array<chunksize=(1000, 1), meta=np.ndarray>
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (1000, 36) (1000, 1) Dask graph 36 chunks in 18 graph layers Data type float64 numpy.ndarray - SNRH(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- standard_name :
- signal_noise_ratio_h
- long_name :
- Signal Noise Ratio H
- short_name :
- SNRH
- units :
- unitless
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - RHOHV_NC(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 13 graph layers Data type float64 numpy.ndarray - SYSPHI1(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC1(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI3(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 16 graph layers Data type float32 numpy.ndarray - PHIDP_OC3(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float32 numpy.ndarray - SYSPHI4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 16 graph layers Data type float64 numpy.ndarray - PHIDP_OC4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - RHOHV_SMOOTH(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Correlation coefficient HV
- units :
- unitless
- standard_name :
- radar_correlation_coefficient_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float32 numpy.ndarray - PHIDP_CORR1(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float32 numpy.ndarray - PHIDP_CORR3(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_LANC(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_VULP(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- standard_name :
- radar_specific_differential_phase_hv
- long_name :
- Specific differential phase HV
- short_name :
- KDP
- units :
- degrees per kilometer
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR1(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR1(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR1(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float32 numpy.ndarray - DBZH_CORR2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 11 graph layers Data type float32 numpy.ndarray - ZDR_CORR2(time2, range)float32dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 140.62 kiB 3.91 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float32 numpy.ndarray - DBTH_CORR3(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR3(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR3(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR4(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - AH(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- units :
- dB/km
- standard_name :
- specific_attenuation_h
- long_name :
- Specific attenuation H
- short_name :
- AH
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - KDP_AH(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Specific differential phase HV
- units :
- degrees per kilometer
- standard_name :
- radar_specific_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - PHIDP_CORR5(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Differential phase HV
- units :
- degrees
- standard_name :
- radar_differential_phase_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - DBTH_CORR5(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Total power H (uncorrected reflectivity)
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - DBZH_CORR5(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Equivalent reflectivity factor H
- units :
- dBZ
- standard_name :
- radar_equivalent_reflectivity_factor_h
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray - ZDR_CORR5(time2, range)float64dask.array<chunksize=(1, 1000), meta=np.ndarray>
- format :
- UV16
- long_name :
- Log differential reflectivity H/V
- units :
- dB
- standard_name :
- radar_differential_reflectivity_hv
- _Undetect :
- 0.0
Array Chunk Bytes 281.25 kiB 7.81 kiB Shape (36, 1000) (1, 1000) Dask graph 36 chunks in 15 graph layers Data type float64 numpy.ndarray
Plot moments - 6#
_kwargs = dict(x="time2", y="height", ylim=(0, 8000), cmap="HomeyerRainbow")
fig = plt.figure(figsize=(14, 8))
ax1 = fig.add_subplot(221)
kwargs = _kwargs | levels(zlevels) | dict(ax=ax1)
qvp_6.DBZH_CORR2.plot.contourf(**kwargs)
ax1.set_title(qvp_6.DBZH_CORR2.attrs["long_name"])
ax2 = fig.add_subplot(222)
kwargs = _kwargs | levels(zdrlevels) | dict(ax=ax2)
qvp_6.ZDR_CORR2.plot.contourf(**kwargs)
ax2.set_title(qvp_6.ZDR_CORR2.attrs["long_name"])
ax3 = fig.add_subplot(223)
kwargs = _kwargs | levels(rholevels) | dict(ax=ax3)
qvp_6.RHOHV_NC.plot.contourf(**kwargs)
ax3.set_title(qvp_6.RHOHV_NC.attrs["long_name"])
ax4 = fig.add_subplot(224)
philevels2 = np.arange(0, 25, 1)
kwargs = _kwargs | levels(philevels2) | dict(ax=ax4)
qvp_6.PHIDP_CORR2.plot(**kwargs)
ax4.set_title(qvp_6.PHIDP_CORR2.attrs["long_name"])
# kwargs = _kwargs | levels(kdplevels) | dict(ax=ax4)
# qvp_6.KDP_VULP.plot.contourf(**kwargs)
# ax4.set_title(qvp_6.KDP_VULP.attrs["long_name"])
fig.tight_layout()
