RADOLAN Quick Start

All RADOLAN composite products can be read by the following function:

data, metadata = wradlib.io.read_radolan_composite("mydrive:/path/to/my/file/filename")

Here, data is a two dimensional integer or float array of shape (number of rows, number of columns). metadata is a dictionary which provides metadata from the files header section, e.g. using the keys producttype, datetime, intervalseconds, nodataflag.

The RADOLAN Grid coordinates can be calculated with wradlib.georef.get_radolan_grid().

With the following code snippet the RW-product is shown in the Polar Stereographic Projection.

Import modules, filter warnings to avoid cluttering output with DeprecationWarnings and use matplotlib inline or interactive mode if running in ipython or python respectively.

In [1]:
import wradlib as wrl
import matplotlib.pyplot as pl
import warnings
warnings.filterwarnings('ignore')
try:
    get_ipython().magic("matplotlib inline")
except:
    pl.ion()
import numpy as np
/home/travis/miniconda/envs/wradlib/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
In [2]:
# load radolan files
rw_filename = wrl.util.get_wradlib_data_file('radolan/misc/raa01-rw_10000-1408102050-dwd---bin.gz')
rwdata, rwattrs = wrl.io.read_radolan_composite(rw_filename)
# print the available attributes
print("RW Attributes:", rwattrs)
RW Attributes: {'producttype': 'RW', 'datetime': datetime.datetime(2014, 8, 10, 20, 50), 'radarid': '10000', 'datasize': 1620000, 'maxrange': '150 km', 'radolanversion': '2.13.1', 'precision': 0.1, 'intervalseconds': 3600, 'nrow': 900, 'ncol': 900, 'radarlocations': ['boo', 'ros', 'emd', 'hnr', 'umd', 'pro', 'ess', 'asd', 'neu', 'nhb', 'oft', 'tur', 'isn', 'fbg', 'mem'], 'nodataflag': -9999, 'secondary': array([   799,    800,    801, ..., 806263, 806264, 807163]), 'cluttermask': array([], dtype=int64)}
In [3]:
# do some masking
sec = rwattrs['secondary']
rwdata.flat[sec] = -9999
rwdata = np.ma.masked_equal(rwdata, -9999)
In [4]:
# Get coordinates
radolan_grid_xy = wrl.georef.get_radolan_grid(900,900)
x = radolan_grid_xy[:,:,0]
y = radolan_grid_xy[:,:,1]
In [5]:
# plot function
pl.pcolormesh(x, y, rwdata, cmap="viridis")
cb = pl.colorbar(shrink=0.75)
cb.set_label("mm/h")
pl.title('RADOLAN RW Product Polar Stereo \n' + rwattrs['datetime'].isoformat())
pl.grid(color='r')
../../_images/notebooks_radolan_radolan_quickstart_8_0.png

A much more comprehensive section using several RADOLAN composites is shown in chapter RADOLAN Product Showcase.