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pyart.correct.selfconsistency_bias2#

pyart.correct.selfconsistency_bias2(radar, zdr_kdpzh_dict, min_rhohv=0.92, min_zdr=0.2, filter_rain=True, max_phidp=20.0, smooth_wind_len=5, doc=None, fzl=None, thickness=700.0, min_rcons=20, parametrization='None', refl_field=None, phidp_field=None, zdr_field=None, temp_field=None, iso0_field=None, hydro_field=None, rhohv_field=None, kdp_field=None, temp_ref='temperature', check_wet_radome=True, wet_radome_refl=25.0, wet_radome_len_min=4, wet_radome_len_max=8, wet_radome_ngates_min=180, keep_points=False, bias_per_gate=False)[source]#

Estimates reflectivity bias at each ray using the self-consistency algorithm by Gourley

Parameters:

  • radar (Radar) – radar object

  • zdr_kdpzh_dict (dict) – dictionary containing a look up table relating ZDR with KDP/Zh for different elevations

  • min_rhohv (float) – minimum RhoHV value to consider the data valid

  • min_zdr (float) – minimum ZDR value to consider the data valid

  • filter_rain (bool) – If True the hydrometeor classification is going to be used to filter out all gates that are not rain

  • max_phidp (float) – maximum PhiDP value to consider the data valid

  • smooth_wind_len (int) – length of the smoothing window

  • doc (float) – Number of gates at the end of each ray to to remove from the calculation.

  • fzl (float) – Freezing layer, gates above this point are not included in the correction.

  • thickness (float) – assumed melting layer thickness [m]

  • min_rcons (int) – minimum number of consecutive gates to consider a valid segment of PhiDP

  • parametrization (str) – The type of parametrization for the self-consistency curves. Can be ‘None’, ‘Gourley’, ‘Wolfensberger’, ‘Louf’, ‘Gorgucci’ or ‘Vaccarono’. ‘None’ will use tables contained in zdr_kdpzh_dict.

  • refl_field, kdp_field, zdr_field (str) – Field names within the radar object which represent the reflectivity, differential phase and differential reflectivity fields. A value of None will use the default field name as defined in the Py-ART configuration file.

  • temp_field, iso0_field, hydro_field, rhohv_field, phidp_field (str) – Field names within the radar object which represent the temperature, the height relative to the iso0, the hydrometeor classification and the co-polar correlation fields. A value of None will use the default field name as defined in the Py-ART configuration file. They are going to be used only if available.

  • kdpsim_field, phidpsim_field (str) – Field names which represent the estimated specific differential phase and differential phase. A value of None will use the default field name as defined in the Py-ART configuration file.

  • temp_ref (str) – the field use as reference for temperature. Can be either temperature, height_over_iso0 or fixed_fzl

  • check_wet_radome (Bool) – 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

  • wet_radome_refl (Float) – Average reflectivity of the gates close to the radar to consider the radome as wet

  • wet_radome_len_min, wet_radome_len_max (int) – Mim and max gate indices of the disk around the radome used to decide whether the radome is wet

  • wet_radome_ngates_min (int) – Minimum number of valid gates to consider that the radome is wet

  • 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

  • bias_per_gate (Bool) – If True the bias per gate will be computed

Returns:

  • kdp_data_dict (dict) – A dictionary containing valid observed and estimated using self- consistency values of KDP

  • refl_bias_dict (dict) – If bias_per_gate is set, the bias at each gate field and metadata. None otherwise

  • selfconsistency_dict (dict) – If keep_poinst set, a dictionary containing the measured valid values of ZDR, Zh and KDP. None otherwise

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