pyrad.proc.process_selfconsistency_bias

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

Estimates the reflectivity bias by means of the selfconsistency algorithm by Gourley

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
  parametrization : str
      The type of parametrization for the self-consistency curves. Can
      be 'None', 'Gourley', 'Wolfensberger', 'Louf', 'Gorgucci' or
      'Vaccarono'
      'None' will use tables from config files. Default 'None'.
  fzl : float. Dataset keyword
      Default freezing level height. Default 2000.
  sounding : str. Dataset keyword
      The nearest radiosounding WMO code (5 int digits). It will be used to
      compute the freezing level, if no temperature field name is specified,
      if the temperature field isin the radar object or if no freezing_level
      is explicitely defined.
  rsmooth : float. Dataset keyword
      length of the smoothing window [m]. Default 2000.
  min_rhohv : float. Dataset keyword
      minimum valid RhoHV. Default 0.92
  filter_rain : Bool. Dataset keyword
      If True the hydrometeor classification is used to filter out gates
      that are not rain. Default True
  max_phidp : float. Dataset keyword
      maximum valid PhiDP [deg]. Default 20.
  ml_thickness : float. Dataset keyword
      Melting layer thickness [m]. Default 700.
  rcell : float. Dataset keyword
      length of continuous precipitation to consider the precipitation
      cell a valid phidp segment [m]. Default 15000.
  dphidp_min : float. Dataset keyword
      minimum phase shift [deg]. Default 2.
  dphidp_max : float. Dataset keyword
      maximum phase shift [deg]. Default 16.
  frequency : float. Dataset keyword
      the radar frequency [Hz]. If None that of the key
      frequency in attribute instrument_parameters of the radar
      object will be used. If the key or the attribute are not present
      the selfconsistency will not be computed
  check_wet_radome : Bool. Dataset keyword
      if True the average reflectivity of the closest gates to the radar
      is going to be check to find out whether there is rain over the
      radome. If there is rain no bias will be computed. Default True.
  wet_radome_refl : Float. Dataset keyword
      Average reflectivity [dBZ] of the gates close to the radar to
      consider the radome as wet. Default 25.
  wet_radome_rng_min, wet_radome_rng_max : Float. Dataset keyword
      Min and max range [m] of the disk around the radar used to compute
      the average reflectivity to determine whether the radome is wet.
      Default 2000 and 4000.
  wet_radome_ngates_min : int
      Minimum number of valid gates to consider that the radome is wet.
      Default 180
  valid_gates_only : Bool
      If True the reflectivity bias obtained for each valid ray is going
      to be assigned only to gates of the segment used. That will give
      more weight to longer segments when computing the total bias.
      Default False
  keep_points : Bool
      If True the ZDR, ZH and KDP of the gates used in the self-
      consistency algorithm are going to be stored for further analysis.
      Default False
  rkdp : float
      The length of the window used to compute KDP with the single
      window least square method [m]. Default 6000.
  

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

Returns:

• new_dataset (dict) – dictionary containing the output

• ind_rad (int) – radar index