pyrad.proc.process_gecsx

pyrad.proc.process_gecsx(procstatus, dscfg, radar_list=None)

Computes ground clutter RCS, radar visibility and many others using the GECSX algorithmn translated from IDL into python

Parameters:

• procstatus (int) – Processing status: 0 initializing, 1 processing volume, 2 post-processing

• dscfg (dictionary of dictionaries) –

  data set configuration. Accepted Configuration Keywords:

  datatype : list of string. Dataset keyword
      The input data types
  range_discretization : float. Dataset keyword
      Range discretization used when computing the Cartesian visibility field
      the larger the better but the slower the processing will be
  az_discretization : float. Dataset keyword
      Azimuth discretization used when computing the Cartesian visibility
      field, the larger the better but the slower the processing will be
  ke : float. Dataset keyword
      Equivalent earth-radius factor used in the computation of the radar
      beam refraction
  atm_att : float. Dataset keyword
      One-way atmospheric refraction in db / km
  mosotti_kw : float. Dataset keyword
      Clausius-Mosotti factor K, depends on material (water) and wavelength
      for water = sqrt(0.93)
  raster_oversampling : int. Dataset keyword
      The raster resolution of the DEM should be smaller than
      the range resolution of the radar (defined by the pulse length).
      If this is not the case, this keyword can be set to increase the
      raster resolution. The values for the elevation, sigma naught,
      visibility are repeated. The other values are recalculated.
      Values for raster_oversampling:
      0 or undefined: No oversampling is done
      1: Oversampling is done. The factor N is automatically calculated
      such that 2*dx/N < pulse length
      2 or larger: Oversampling is done with this value as N
  sigma0_method : string. Dataset keyword
      Which estimation method to use, either 'Gabella' or 'Delrieu'
  clip : int. Dataset keyword
      If set to true, the provided DEM will be clipped to the extent
      of the polar radar domain. Increases computation speed a lot but
      Cartesian output fields will be available only over radar domain
  

• radar_list (list of Radar objects) – Optional. list of radar objects

Returns:

• new_dataset (list of dict) – list of dictionaries containing the polar data output and the Cartesian data output in this order

• ind_rad (int) – radar index