pyrad.proc.process_evp#

pyrad.proc.process_evp(procstatus, dscfg, radar_list=None)[source]#

Computes enhanced vertical profiles, by averaging over height levels PPI data.

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

  • dscfg (dictionary of dictionaries) –

    data set configuration. Accepted Configuration Keywords:

    datatype : string. Dataset keyword
        The data type where we want to extract the point measurement
    lat, lon : float
        latitude and longitude of the point of interest [deg]
    latlon_tol : float
        tolerance in latitude and longitude in deg. Default 0.0005
    delta_rng, delta_azi : float
        maximum range distance [m] and azimuth distance [degree] from the
        central point of the evp containing data to average. Default 5000.
        and 10.
    hmax : float
        The maximum height to plot [m]. Default 10000.
    hres : float
        The height resolution [m]. Default 250.
    avg_type : str
        The type of averaging to perform. Can be either "mean" or "median"
        Default "mean"
    nvalid_min : int
        Minimum number of valid points to consider the data valid when
        performing the averaging. Default 1
    interp_kind : str
        type of interpolation when projecting to vertical grid: 'none',
        or 'nearest', etc. Default 'none'.
        'none' will select from all data points within the regular grid
        height bin the closest to the center of the bin.
        'nearest' will select the closest data point to the center of the
        height bin regardless if it is within the height bin or not.
        Data points can be masked values
        If another type of interpolation is selected masked values will be
        eliminated from the data points before the interpolation
    
  • radar_list (list of Radar objects) – Optional. list of radar objects

Returns:

  • new_dataset (dict) – dictionary containing the EVP and a keyboard stating whether the processing has finished or not.

  • ind_rad (int) – radar index

  • Reference

  • ———

  • Kaltenboeck R., Ryzhkov A. 2016 (A freezing rain storm explored with a)

  • C-band polarimetric weather radar using the QVP methodology.

  • Meteorologische Zeitschrift vol. 26 pp 207-222