wradlib.atten.correct_radome_attenuation_empirical¶

wradlib.atten.
correct_radome_attenuation_empirical
(gateset, frequency=5.64, hydrophobicity=0.165, n_r=2, stat=<function mean>)¶ Estimate twoway wet radome losses.
Empirical function of frequency and rainfall rate for both standard and hydrophobic radomes based on the approach of [Merceret et al., 2000].
Parameters:  gateset (
numpy.ndarray
) – Multidimensional array, where the range gates (over which iteration has to be performed) are supposed to vary along the last arraydimension and the azimuths are supposed to vary along the next to last arraydimension. Data has to be provided in decibel representation of reflectivity [dBZ].  frequency (float) –
Radarfrequency [GHz]:
Standard frequencies in Xband range between 8.0 and 12.0 GHz,Standard frequencies in Cband range between 4.0 and 8.0 GHz,
Standard frequencies in Sband range between 2.0 and 4.0 GHz.
Be aware that the empirical fit of the formula was just done for C and Sband. The use for Xband is probably an undue extrapolation.
Per default set to 5.64 as used by the German Weather Service radars.
 hydrophobicity (float) –
Empirical parameter based on the hydrophobicity of the radome material.
 0.165 for standard radomes,
 0.0575 for hydrophobic radomes.
Per default set to 0.165.
 n_r (int) – The radius of rangebins within the rainintensity is statistically evaluated as the representative rainintensity over radome.
 stat (object) –
A name of a numpy function for statistical aggregation of the central rangebins defined by n_r.
Potential options: np.mean, np.median, np.max, np.min.
Returns: k (
numpy.ndarray
) – Array with the same shape asgateset
containing the calculated twoway transmission loss [dB] for each range gate. In case the input array (gateset) contains NaNs the corresponding beams of the output array (k) will be set as NaN, too. gateset (