Match spaceborn SR (GPM/TRMM) with ground radars GR#

The idea is to match ground radar (GR) and space-born radar (SR) measurements in order to create spatially and temporally coicident samples without interpolation. The procedure had been suggested by Schwaller and Morris (2011) and is based on the adaption by Warren, et. al. (2017).

The basic principle is illustrated in Fig. 2 of the original paper of Schwaller and Morris (2011):

Quote Warren, et.al: “[…] In this approach, intersections between indi vidual SR beams and GR elevation sweeps are identified and the reflectivity values from both instruments are averaged within a spatial neighborhood around the intersection. Specifically, SR data are averaged in range over the width of the GR beam at the GR range of the intersection, while GR data are averaged in the range–azimuth plane within the footprint of the SR beam. The result is a pair of reflectivity measurements corresponding to approximately the same volume of atmosphere. […]”.

This becomes clearer in Fig. 3:

Schwaller, MR, and Morris, KR. 2011. A ground validation network for the Global Precipitation Measurement mission. J. Atmos. Oceanic Technol., 28, 301-319.

Warren, R.A., A. Protat, S.T. Siems, H.A. Ramsay, V. Louf, M.J. Manton, and T.A. Kane, 0: Calibrating ground-based radars against TRMM and GPM. J. Atmos. Oceanic Technol., 0,

Conventions#

This code is based on the following conventions:

gr indicates ground radar
sr indicates space-born precipitation radar (TRMM or GPM)

The base routines are designed to process one GR sweep at a time. If a full GR volume with nelev of sweeps is available, you can iterate over each sweep. In this code, ee is an index that points to one of the nelev sweeps/elevation angles. Accordingly, a GR data set will be organised as an array of shape (nelev_gr, nray_gr, ngate_gr).

A SR data set is typically organised as arrays with dimensions (nscan_sr, nray_sr, ngate_sr).

import warnings

import cmweather  # noqa: F401
import matplotlib.pyplot as plt
import numpy as np
import wradlib as wrl
import wradlib_data
import xarray as xr
import xradar as xd
from IPython.display import display

warnings.filterwarnings("ignore")

Acquire datafiles#

# define GPM data set
gpm_file = wradlib_data.DATASETS.fetch(
    "gpm/2A-CS-151E24S154E30S.GPM.Ku.V7-20170308.20141206-S095002-E095137.004383.V05A.HDF5"
)
# define matching ground radar file
gr2gpm_file = wradlib_data.DATASETS.fetch("hdf5/IDR66_20141206_094829.vol.h5")

# define TRMM data sets
trmm_2a23_file = wradlib_data.DATASETS.fetch(
    "trmm/2A-CS-151E24S154E30S.TRMM.PR.2A23.20100206-S111425-E111526.069662.7.HDF"
)
trmm_2a25_file = wradlib_data.DATASETS.fetch(
    "trmm/2A-CS-151E24S154E30S.TRMM.PR.2A25.20100206-S111425-E111526.069662.7.HDF"
)

# define matching ground radar file
gr2trmm_file = wradlib_data.DATASETS.fetch("hdf5/IDR66_20100206_111233.vol.h5")

Downloading file 'gpm/2A-CS-151E24S154E30S.GPM.Ku.V7-20170308.20141206-S095002-E095137.004383.V05A.HDF5' from 'https://github.com/wradlib/wradlib-data/raw/main/data/gpm/2A-CS-151E24S154E30S.GPM.Ku.V7-20170308.20141206-S095002-E095137.004383.V05A.HDF5' to '/home/docs/.cache/wradlib-data'.

Downloading file 'hdf5/IDR66_20141206_094829.vol.h5' from 'https://github.com/wradlib/wradlib-data/raw/main/data/hdf5/IDR66_20141206_094829.vol.h5' to '/home/docs/.cache/wradlib-data'.

Downloading file 'trmm/2A-CS-151E24S154E30S.TRMM.PR.2A23.20100206-S111425-E111526.069662.7.HDF' from 'https://github.com/wradlib/wradlib-data/raw/main/data/trmm/2A-CS-151E24S154E30S.TRMM.PR.2A23.20100206-S111425-E111526.069662.7.HDF' to '/home/docs/.cache/wradlib-data'.

Downloading file 'trmm/2A-CS-151E24S154E30S.TRMM.PR.2A25.20100206-S111425-E111526.069662.7.HDF' from 'https://github.com/wradlib/wradlib-data/raw/main/data/trmm/2A-CS-151E24S154E30S.TRMM.PR.2A25.20100206-S111425-E111526.069662.7.HDF' to '/home/docs/.cache/wradlib-data'.

Downloading file 'hdf5/IDR66_20100206_111233.vol.h5' from 'https://github.com/wradlib/wradlib-data/raw/main/data/hdf5/IDR66_20100206_111233.vol.h5' to '/home/docs/.cache/wradlib-data'.

Set SR and GR parameters#

# Space-born precipitation radar parameters
sr_pars = {
    "trmm": {
        "zt": 402500.0,  # orbital height of TRMM (post boost)   APPROXIMATION!
        "dr": 250.0,  # gate spacing of TRMM
        "gr_file": gr2trmm_file,
    },
    "gpm": {
        "zt": 407000.0,  # orbital height of GPM                 APPROXIMATION!
        "dr": 125.0,  # gate spacing of GPM
        "gr_file": gr2gpm_file,
    },
}

# Set parameters for this procedure
bw_sr = 0.71  # SR beam width
platf = "gpm"  # SR platform/product: one out of ["gpm", "trmm"]
zt = sr_pars[platf]["zt"]  # SR orbit height (meters)
dr_sr = sr_pars[platf]["dr"]  # SR gate length (meters)
gr_file = sr_pars[platf]["gr_file"]
ee = 2  # Index that points to the GR elevation angle to be used