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,
    can be any datatype supported by pyrad and available in the data
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 keyword 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