Geometry module

The module of the package is used to generate the output files after the processing of the raw data is completed. With this module it is possible to convert the weather radar data into a cartesian coordinate system and save it as a netcdf file.

import wrainfo as wrf

import xarray as xr
import warnings
warnings.filterwarnings('ignore')

Note

This is only an example how the geometry module works. If you want to save all processed variables in the dataset after clutter and attenuation correction as well as precipitation estimation, please check the json file.

We load an scnx-file as follows.

file_path="/tests/data/raw/2022/04/05/2006_20220405_123000_000.scnx.gz"
path_to_config_file="/tests/data/test_settings_wrainfo.json"

file_scnx=wrf.reader.read_single_file(file_path,
                                      path=path_to_config_file,
                                      grp="sweep_0")
display(file_scnx)

<xarray.Dataset>
Dimensions:     (azimuth: 720, range: 936)
Coordinates:
  * azimuth     (azimuth) float32 0.25 0.75 1.25 1.75 ... 358.8 359.2 359.8
    elevation   (azimuth) float32 0.5 0.5 0.5 0.5 0.5 ... 0.5 0.5 0.5 0.5 0.5
  * range       (range) float32 37.5 112.5 187.5 ... 7.009e+04 7.016e+04
    time        datetime64[ns] 2022-04-05T12:30:01
    rtime       (azimuth) datetime64[ns] 2022-04-05T12:30:09.601952500 ... 20...
    longitude   float64 13.24
    latitude    float64 53.55
    altitude    float64 38.0
    sweep_mode  <U20 'azimuth_surveillance'
Data variables:
    RATE        (azimuth, range) float32 ...
    DBZH        (azimuth, range) float32 ...
    VRADH       (azimuth, range) float32 ...
    ZDR         (azimuth, range) float32 ...
    KDP         (azimuth, range) float32 ...
    PHIDP       (azimuth, range) float32 ...
    RHOHV       (azimuth, range) float32 ...
    WRADH       (azimuth, range) float32 ...
    QUAL        (azimuth, range) uint16 ...
Attributes:
    fixed_angle:  0.5

xarray.Dataset

• Dimensions:
  • azimuth: 720
  • range: 936
• Coordinates: (9)
  • azimuth
    (azimuth)
    float32
    0.25 0.75 1.25 ... 359.2 359.8

    standard_name :

    ray_azimuth_angle

    long_name :

    azimuth_angle_from_true_north

    units :

    degrees

    axis :

    radial_azimuth_coordinate

    a1gate :

    499

    angle_res :

    0.5

    array([2.5000e-01, 7.5000e-01, 1.2500e+00, ..., 3.5875e+02, 3.5925e+02,
           3.5975e+02], dtype=float32)

  • elevation
    (azimuth)
    float32
    ...

    standard_name :

    ray_elevation_angle

    long_name :

    elevation_angle_from_horizontal_plane

    units :

    degrees

    axis :

    radial_elevation_coordinate

    array([0.5, 0.5, 0.5, ..., 0.5, 0.5, 0.5], dtype=float32)

  • range
    (range)
    float32
    37.5 112.5 ... 7.009e+04 7.016e+04

    units :

    meters

    standard_name :

    projection_range_coordinate

    long_name :

    range_to_measurement_volume

    spacing_is_constant :

    true

    axis :

    radial_range_coordinate

    meters_to_center_of_first_gate :

    37.5

    meters_between_gates :

    75

    array([3.75000e+01, 1.12500e+02, 1.87500e+02, ..., 7.00125e+04, 7.00875e+04,
           7.01625e+04], dtype=float32)

  • time
    ()
    datetime64[ns]
    ...

    standard_name :

    time

    array('2022-04-05T12:30:01.000000000', dtype='datetime64[ns]')

  • rtime
    (azimuth)
    datetime64[ns]
    ...

    standard_name :

    time

    array(['2022-04-05T12:30:09.601952500', '2022-04-05T12:30:09.640787500',
           '2022-04-05T12:30:09.679622500', ..., '2022-04-05T12:30:09.485447499',
           '2022-04-05T12:30:09.524282500', '2022-04-05T12:30:09.563117500'],
          dtype='datetime64[ns]')

  • longitude
    ()
    float64
    ...

    long_name :

    longitude

    units :

    degrees_east

    standard_name :

    longitude

    array(13.24397)

  • latitude
    ()
    float64
    ...

    long_name :

    latitude

    units :

    degrees_north

    positive :

    up

    standard_name :

    latitude

    array(53.55478)

  • altitude
    ()
    float64
    ...

    long_name :

    altitude

    units :

    meters

    standard_name :

    altitude

    array(38.)

  • sweep_mode
    ()
    <U20
    ...

    array('azimuth_surveillance', dtype='<U20')

• Data variables: (9)
  • RATE
    (azimuth, range)
    float32
    ...

    units :

    mm h-1

    standard_name :

    rainfall_rate

    long_name :

    rainfall_rate

    [673920 values with dtype=float32]

  • DBZH
    (azimuth, range)
    float32
    ...

    units :

    dBZ

    standard_name :

    radar_equivalent_reflectivity_factor_h

    long_name :

    Equivalent reflectivity factor H

    [673920 values with dtype=float32]

  • VRADH
    (azimuth, range)
    float32
    ...

    units :

    meters per seconds

    standard_name :

    radial_velocity_of_scatterers_away_from_instrument_h

    long_name :

    Radial velocity of scatterers away from instrument H

    [673920 values with dtype=float32]

  • ZDR
    (azimuth, range)
    float32
    ...

    units :

    dB

    standard_name :

    radar_differential_reflectivity_hv

    long_name :

    Log differential reflectivity H/V

    [673920 values with dtype=float32]

  • KDP
    (azimuth, range)
    float32
    ...

    units :

    degrees per kilometer

    standard_name :

    radar_specific_differential_phase_hv

    long_name :

    Specific differential phase HV

    [673920 values with dtype=float32]

  • PHIDP
    (azimuth, range)
    float32
    ...

    units :

    degrees

    standard_name :

    radar_differential_phase_hv

    long_name :

    Differential phase HV

    [673920 values with dtype=float32]

  • RHOHV
    (azimuth, range)
    float32
    ...

    units :

    unitless

    standard_name :

    radar_correlation_coefficient_hv

    long_name :

    Correlation coefficient HV

    [673920 values with dtype=float32]

  • WRADH
    (azimuth, range)
    float32
    ...

    units :

    meters per seconds

    standard_name :

    radar_doppler_spectrum_width_h

    long_name :

    Doppler spectrum width H

    [673920 values with dtype=float32]

  • QUAL
    (azimuth, range)
    uint16
    ...

    [673920 values with dtype=uint16]

• Attributes: (1)

  fixed_angle :

  0.5

Georeferencing

In the function furuno_georeferencing the configuration file is loaded by defining the target coordinate system using the EPSG code and the pixel resolution of the projected data. In addition, the variables to be included in the georeferenced dataset are defined in the configuration file. Afterwards the source and target coordinates are determined in the function. For each variable a new data array with the cartesian coordinates is created and then the single data arrays are merged to a xarray dataset.

Note

The function works only for a dataset of one time step!

ds_georef = wrf.geometry.furuno_georeferencing(ds=file_scnx,
                                               path=path_to_config_file)
display(ds_georef)

<xarray.Dataset>
Dimensions:              (y: 1400, x: 1400, time: 1)
Coordinates:
  * time                 (time) datetime64[ns] 2022-04-05T12:30:01
  * x                    (x) float32 3.135e+05 3.136e+05 ... 4.537e+05 4.538e+05
  * y                    (y) float32 5.865e+06 5.865e+06 ... 6.005e+06 6.006e+06
    transverse_mercator  int64 0
Data variables:
    RATE                 (time, y, x) float32 0.31 0.31 0.31 0.0 ... 0.0 0.0 0.0
    DBZH                 (time, y, x) float32 -78.54 -78.54 ... -79.02 -79.02
    ZDR                  (time, y, x) float32 0.39 0.39 0.39 ... 1.31 0.65 0.65
    KDP                  (time, y, x) float32 nan nan nan nan ... nan nan nan
    PHIDP                (time, y, x) float32 48.9 48.9 48.9 ... -132.9 -132.9
    RHOHV                (time, y, x) float32 0.107 0.107 ... 0.3583 0.3583
Attributes:
    Conventions:      CF-1.5
    elevation_angle:  0.5

xarray.Dataset

• Dimensions:
  • y: 1400
  • x: 1400
  • time: 1
• Coordinates: (4)
  • time
    (time)
    datetime64[ns]
    2022-04-05T12:30:01

    standard_name :

    time

    array(['2022-04-05T12:30:01.000000000'], dtype='datetime64[ns]')

  • x
    (x)
    float32
    3.135e+05 3.136e+05 ... 4.538e+05

    standard_name :

    projection_x_coordinate

    long_name :

    x coordinate of projection

    units :

    m

    array([313529.06, 313629.34, 313729.6 , ..., 453603.7 , 453703.94, 453804.22],
          dtype=float32)

  • y
    (y)
    float32
    5.865e+06 5.865e+06 ... 6.006e+06

    standard_name :

    projection_y_coordinate

    long_name :

    y coordinate of projection

    units :

    m

    array([5865286. , 5865386.5, 5865486.5, ..., 6005358. , 6005458. , 6005558.5],
          dtype=float32)

  • transverse_mercator
    ()
    int64
    0

    crs_wkt :

    PROJCS["WGS 84 / UTM zone 33N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",15],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32633"]]

    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 :

    WGS 84

    horizontal_datum_name :

    World Geodetic System 1984

    projected_crs_name :

    WGS 84 / UTM zone 33N

    grid_mapping_name :

    transverse_mercator

    latitude_of_projection_origin :

    0.0

    longitude_of_central_meridian :

    15.0

    false_easting :

    500000.0

    false_northing :

    0.0

    scale_factor_at_central_meridian :

    0.9996

    spatial_ref :

    PROJCS["WGS 84 / UTM zone 33N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",15],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32633"]]

    array(0)

• Data variables: (6)
  • RATE
    (time, y, x)
    float32
    0.31 0.31 0.31 0.0 ... 0.0 0.0 0.0

    units :

    mm h-1

    standard_name :

    rainfall_rate

    long_name :

    rainfall_rate

    array([[[0.30999756, 0.30999756, 0.30999756, ..., 0.        ,
             0.        , 0.        ],
            [0.30999756, 0.30999756, 0.30999756, ..., 0.        ,
             0.        , 0.        ],
            [0.30999756, 0.30999756, 0.30999756, ..., 0.        ,
             0.        , 0.        ],
            ...,
            [0.        , 0.        , 0.        , ..., 0.        ,
             0.        , 0.        ],
            [0.        , 0.        , 0.        , ..., 0.        ,
             0.        , 0.        ],
            [0.        , 0.        , 0.        , ..., 0.        ,
             0.        , 0.        ]]], dtype=float32)

  • DBZH
    (time, y, x)
    float32
    -78.54 -78.54 ... -79.02 -79.02

    units :

    dBZ

    standard_name :

    radar_equivalent_reflectivity_factor_h

    long_name :

    Equivalent reflectivity factor H

    array([[[-78.53999 , -78.53999 , -78.53999 , ..., -79.479996,
             -79.479996, -79.479996],
            [-78.53999 , -78.53999 , -78.53999 , ..., -79.479996,
             -79.479996, -79.479996],
            [-78.53999 , -78.53999 , -78.53999 , ..., -79.479996,
             -79.479996, -79.479996],
            ...,
            [-79.09    , -79.42999 , -79.42999 , ..., -79.020004,
             -79.020004, -79.020004],
            [-79.42999 , -79.42999 , -79.42999 , ..., -79.020004,
             -79.020004, -79.020004],
            [-79.42999 , -79.42999 , -79.42999 , ..., -78.740005,
             -79.020004, -79.020004]]], dtype=float32)

  • ZDR
    (time, y, x)
    float32
    0.39 0.39 0.39 ... 1.31 0.65 0.65

    units :

    dB

    standard_name :

    radar_differential_reflectivity_hv

    long_name :

    Log differential reflectivity H/V

    array([[[ 0.39001465,  0.39001465,  0.39001465, ...,  0.51000977,
              0.51000977,  0.51000977],
            [ 0.39001465,  0.39001465,  0.39001465, ...,  0.51000977,
              0.51000977,  0.51000977],
            [ 0.39001465,  0.39001465,  0.39001465, ...,  0.51000977,
              0.51000977,  0.51000977],
            ...,
            [ 0.45999146, -0.19000244, -0.19000244, ...,  0.6499939 ,
              0.6499939 ,  0.6499939 ],
            [-0.19000244, -0.19000244, -0.19000244, ...,  0.6499939 ,
              0.6499939 ,  0.6499939 ],
            [-0.19000244, -0.19000244, -0.19000244, ...,  1.3099976 ,
              0.6499939 ,  0.6499939 ]]], dtype=float32)

  • KDP
    (time, y, x)
    float32
    nan nan nan nan ... nan nan nan nan

    units :

    degrees per kilometer

    standard_name :

    radar_specific_differential_phase_hv

    long_name :

    Specific differential phase HV

    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]]], dtype=float32)

  • PHIDP
    (time, y, x)
    float32
    48.9 48.9 48.9 ... -132.9 -132.9

    units :

    degrees

    standard_name :

    radar_differential_phase_hv

    long_name :

    Differential phase HV

    array([[[  48.900894,   48.900894,   48.900894, ...,   93.47861 ,
               93.47861 ,   93.47861 ],
            [  48.900894,   48.900894,   48.900894, ...,   93.47861 ,
               93.47861 ,   93.47861 ],
            [  48.900894,   48.900894,   48.900894, ...,   93.47861 ,
               93.47861 ,   93.47861 ],
            ...,
            [  12.909134,   35.9588  ,   35.9588  , ..., -132.87617 ,
             -132.87617 , -132.87617 ],
            [  35.9588  ,   35.9588  ,   35.9588  , ..., -132.87617 ,
             -132.87617 , -132.87617 ],
            [  35.9588  ,   35.9588  ,   35.9588  , ..., -116.8304  ,
             -132.87617 , -132.87617 ]]], dtype=float32)

  • RHOHV
    (time, y, x)
    float32
    0.107 0.107 0.107 ... 0.3583 0.3583

    units :

    unitless

    standard_name :

    radar_correlation_coefficient_hv

    long_name :

    Correlation coefficient HV

    array([[[0.10702841, 0.10702841, 0.10702841, ..., 0.08334605,
             0.08334605, 0.08334605],
            [0.10702841, 0.10702841, 0.10702841, ..., 0.08334605,
             0.08334605, 0.08334605],
            [0.10702841, 0.10702841, 0.10702841, ..., 0.08334605,
             0.08334605, 0.08334605],
            ...,
            [0.14636678, 0.2451857 , 0.2451857 , ..., 0.35834834,
             0.35834834, 0.35834834],
            [0.2451857 , 0.2451857 , 0.2451857 , ..., 0.35834834,
             0.35834834, 0.35834834],
            [0.2451857 , 0.2451857 , 0.2451857 , ..., 0.22943816,
             0.35834834, 0.35834834]]], dtype=float32)

• Attributes: (2)

  Conventions :

  CF-1.5

  elevation_angle :

  0.5

Now we can plot the georeferenced dataset.

ds_georef.DBZH.plot()

<matplotlib.collections.QuadMesh at 0x14d6eb3265b0>

Output as NetCDF

The processed data can be saved as NetCDF file. For this, we use the function furuno_sweep_to_netcdf. The configuration file is loaded by defining the output path and the variable, which are saved in the output files. The time dimension is used for create the name of the output file and also the output path. If the file was save in the output directory, you get an information where the file was saved.

Note

The function works only for a georeferenced xarray dataset of one time tep!

wrf.geometry.furuno_cartesian_sweep_to_netcdf(ds=ds_georef,
                                              path=path_to_config_file,
                                              data_type="Level1")

-- output to tests/data/output/2022/04/05/elev_0.5/NB_WR2120_20220405_123001UTC_elev_0.5_Level1.nc

Library Reference

Seealso

Get more information about the geometry module in the library reference section.