pyrad.proc.process_qvp#

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

Computes quasi 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
    angle : int or float
        If the radar object contains a PPI volume, the sweep number to
        use, if it contains an RHI volume the elevation angle.
        Default 0.
    ang_tol : float
        If the radar object contains an RHI volume, the tolerance in the
        elevation angle for the conversion into PPI
    hmax : float
        The maximum height to plot [m]. Default 10000.
    hres : float
        The height resolution [m]. Default 50
    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 accept average. Default 30.
    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 QVP and a keyboard stating whether the processing has finished or not.

  • ind_rad (int) – radar index

  • Reference

  • ———

  • Ryzhkov A., Zhang P., Reeves H., Kumjian M., Tschallener T., Trömel S.,

  • Simmer C. 2016 (Quasi-Vertical Profiles: A New Way to Look at Polarimetric)

  • Radar Data. JTECH vol. 33 pp 551-562