Radar Precipitation Estimates (Radolan RW product) interpolated onto LfULG Stations Saxony

Radar Precipitation Estimates interpolated onto LfULG Air Quality Measurement / Monitoring Stations

Processing Steps

• Radolan RW data were retrieved from DWD Climate Data Center: https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/historical/bin/
• Radolan RW data were interpolated onto a subset of LfULG Stations using the Nearest Neighbor method
• statistics (average, maximum & standard deviation) are provided for a 5 x 5 km**2 cutout

Data Description

• data are packed into TAR Archives for each station
• individual data are stored as ASCII tables for each month and station (CSV with space as separator)
• variable meaning is described in the header section of each file

Example for Data Input with Python

import numpy as np
import xarray as xr
import datetime

def read_rado_dat( filename ):
    
    '''
    Reads Radolan RW time series from ASCII files and returns `xarray` Dataset.
    
    
    Parameters
    ----------
    filename : str
        input filename
        
        
    Returns
    -------
    rr : xr.Dataset
        time series data (rain rates in mm/h)
    '''
    
    print(f'.. open {filename}')
    dat = np.genfromtxt( filename )
    ndat = len(dat)
    print(ndat)
    time = []
    for i in range( ndat ):
        d = dat[i]
        t = datetime.datetime(int( d[0] ), 
                              int( d[1] ), 
                              int( d[2] ), 
                              int( d[3] ),
                              int( d[4] ))
        time += [t,]
        
    rr = xr.Dataset()
    rr['time'] = time
    rr['rr'] = xr.DataArray( data = dat[:, 7], dims = 'time', coords = {'time':time})
    rr['rr_mean'] = xr.DataArray( data = dat[:, 8], dims = 'time', coords = {'time':time})
    rr['rr_max'] = xr.DataArray( data = dat[:, 9], dims = 'time', coords = {'time':time})
    rr['rr_std'] = xr.DataArray( data = dat[:, 10], dims = 'time', coords = {'time':time})

    m = (rr != -999)
    
    return rr.where( m )