"""Precipitation estimation module."""
# WRaINfo, Is a software to process FURUNO weather radar data.
#
# Copyright (c) 2022, FernLab (GFZ Potsdam, fernlab@gfz-potsdam.de)
#
# This software was developed within the context of the RaINfo ("Potential use of
# high resolution weather data in agriculture") project of FernLab funded by
# the Impulse and Networking Fund of the Helmholtz Association.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
#
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# imports
# -------
import wradlib as wrl
import xarray as xr
from wrainfo.reader import read_config_file
# quantitative precipitation estimation (QPE): R(Z)
# -------------------------------------------------
[docs]def qpe_zr(ds,
moment,
path,
a=200,
b=1.6):
"""Qualitative precipitation estimation with z-R conversion.
Parameters
----------
ds : xarray.Dataset
moment : str
name of the clutter and attenuation corrected data array in the dataset.
path : str
path to configuration file
a : integer
parameter for the z-R-conversion
(Marschall Palmer default value: a = 200, German Weather Service = 256)
b : float
parameter for the z-R-conversion
(Marschall Palmer default value: b = 1.6, German Weather Service = 1.42)
Returns
-------
: xarray.Dataset
xarray.Dataset with a data array of derived precipitation amounts.
"""
# read setting from configuration file
dims = read_config_file(path=path, selection="dimensions")
interval = read_config_file(path=path, selection="scan_interval")
# precipitation attributes
prec_attrs = {"standard_name": "precipitation_amount_z_r_relationship",
"long_name": "precipitation_amount_z_r_relationship",
"unit": "mm", }
# QPE Z(R)
rr = ds[moment].pipe(wrl.trafo.idecibel).pipe(wrl.zr.z_to_r, a=a, b=b)
depth = wrl.trafo.r_to_depth(rr, interval)
# add to dataset
ds["PREC_ZR"] = xr.DataArray(depth, dims=dims, attrs=prec_attrs)
# fix encoding
chunk = read_config_file(path=path, selection="chunksize")
comp = dict(zlib=True, complevel=7, chunksizes=(chunk[0], chunk[1], chunk[2]))
ds.PREC_ZR.encoding = comp
return ds