pyart.retrieve.hydroclass_semisupervised#

pyart.retrieve.hydroclass_semisupervised(radar, hydro_names=('AG', 'CR', 'LR', 'RP', 'RN', 'VI', 'WS', 'MH', 'IH/HDG'), var_names=('dBZ', 'ZDR', 'KDP', 'RhoHV', 'H_ISO0'), mass_centers=None, weights=array([1., 1., 1., 0.75, 0.5]), value=50.0, lapse_rate=-6.5, refl_field=None, zdr_field=None, rhv_field=None, kdp_field=None, temp_field=None, iso0_field=None, hydro_field=None, entropy_field=None, temp_ref='temperature', compute_entropy=False, output_distances=False, vectorize=False)[source]#

Classifies precipitation echoes following the approach by Besic et al (2016).

Parameters:

radar (radar) – Radar object.
hydro_names (array of str) – name of the types of hydrometeors
var_names (array of str) – name of the variables
mass_centers (ndarray 2D, optional) – The centroids for each variable and hydrometeor class in (nclasses, nvariables).
weights (ndarray 1D, optional) – The weight given to each variable. Ordered by [dBZ, ZDR, KDP, RhoHV, H_ISO0]
value (float) – The value controlling the rate of decay in the distance transformation
lapse_rate (float) – The decrease in temperature for each vertical km [deg/km]
refl_field, zdr_field, rhv_field, kdp_field, temp_field, iso0_field (str) – Inputs. Field names within the radar object which represent the horizonal reflectivity, the differential reflectivity, the copolar correlation coefficient, the specific differential phase, the temperature (in deg celsius) and the height respect to the iso0 fields. A value of None for any of these parameters will use the default field name as defined in the Py-ART configuration file.
hydro_field (str) – Output. Field name which represents the hydrometeor class field. 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 or height_over_iso0
compute_entropy (bool) – If true, the entropy is computed
output_distances (bool) – If true, the normalized distances to the centroids for each hydrometeor are provided as output
vectorize (bool) – If true, a vectorized version of the class assignation is going to be used

Returns:

fields_dict (dict) – Dictionary containing the retrieved fields

References

Besic, N., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmos. Meas. Tech., 9, 4425-4445, doi:10.5194/amt-9-4425-2016, 2016