pyrad.proc.process_turbulence#

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

Computes turbulence from the Doppler spectrum width and reflectivity using the PyTDA package

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 input data type, must contain,
    "dBuZ" or "dBZ" or "dBZc" or "dBuZv" or "dBZv" or "dBZvc" or "CNRc", and,
    "W" or "Wv" or "Wu" or "Wvu" or "WD" or "WDc"
radius : float. Dataset keyword
    Search radius for calculating Eddy Dissipation Rate (EDR).
    Default 2
split_cut : Bool. Dataset keyword
    Set to True for split-cut volumes. Default False
max_split_cut : Int. Dataset keyword
    Total number of tilts that are affected by split cuts. Only
    relevant if split_cut=True. Default 2
xran, yran : float array. Dataset keyword
    Spatial range in X,Y to consider. Default [-100, 100] for both
    X and Y
use_ntda : Bool. Dataset keyword
    Wether to use NCAR Turbulence Detection Algorithm (NTDA). Default
    True
beamwidth : Float. Dataset keyword
    Radar beamwidth. Default None. If None it will be obtained from
    the radar object metadata. If cannot be obtained defaults to 1
    deg.
compute_gate_pos : Bool. Dataset keyword
    If True the gate position is going to be computed in PyTDA.
    Otherwise the position from the radar object is used. Default
    False
verbose : Bool. Dataset keyword
    True for verbose output. Default False

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

Returns:

new_dataset (dict) – dictionary containing the output field “EDR”
ind_rad (int) – radar index