def correctRadomeAttenuationEmpirical(gateset,
frequency=5.64,
hydrophobicity=0.165,
n_r=2,
stat=np.mean):
"""Estimate two-way wet radome losses as an empirical
function of frequency and rainfall rate for both standard and
hydrophobic radomes based on the approach of :cite:`Merceret2000`.
Parameters
----------
gateset : array
Multidimensional array, where the range gates (over which
iteration has to be performed) are supposed to vary along the
last array-dimension and the azimuths are supposed to vary
along the next to last array-dimension. Data has to be provided
in decibel representation of reflectivity [dBZ].
frequency : float
Radar-frequency [GHz]:
Standard frequencies in X-band range between 8.0 and 12.0 GHz,
Standard frequencies in C-band range between 4.0 and 8.0 GHz,
Standard frequencies in S-band range between 2.0 and 4.0 GHz.
Be aware that the empirical fit of the formula was just
done for C- and S-band. The use for X-band 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 : integer
The radius of rangebins within the rain-intensity is
statistically evaluated as the representative rain-intensity
over radome.
stat : class
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 : array
Array with the same shape as ``gateset`` containing the
calculated two-way 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.
"""
# Select rangebins inside the defined center-range n_r.
center = gateset[..., :n_r].reshape(-1, n_r * gateset.shape[-2])
center_m = np.ma.masked_array(center, np.isnan(center))
# Calculate rainrate in the center-range based on statistical method stat
# and with standard ZR-relation.
rain_over_radome = z2r(idecibel(stat(center_m, axis=-1)))
# Estimate the empirical two-way transmission loss due to
# radome-attenuation.
k = 2 * hydrophobicity * rain_over_radome * np.tanh(frequency / 10.)**2
# Reshape the result to gateset-shape.
k = np.repeat(k,
gateset.shape[-1] * gateset.shape[-2]).reshape(gateset.shape)
return k
def test_z2r(self):
self.assertEqual(zr.z2r(trafo.idecibel(10.)), 0.1537645610180688)
def correctRadomeAttenuationEmpirical(gateset, frequency=5.64,
hydrophobicity=0.165, n_r=2,
stat=np.mean):
"""Estimate two-way wet radome losses as an empirical
function of frequency and rainfall rate for both standard and
hydrophobic radomes based on the approach of Francis J. Merceret
and Jennifer G. Ward :cite:`Merceret2000`.
Parameters
----------
gateset : array
Multidimensional array, where the range gates (over which
iteration has to be performed) are supposed to vary along the
last array-dimension and the azimuths are supposed to vary
along the next to last array-dimension. Data has to be provided
in decibel representation of reflectivity [dBZ].
frequency : float
Radar-frequency [GHz]:
Standard frequencies in X-band range between 8.0 and 12.0 GHz,
Standard frequencies in C-band range between 4.0 and 8.0 GHz,
Standard frequencies in S-band range between 2.0 and 4.0 GHz.
Be aware that the empirical fit of the formula was just
done for C- and S-band. The use for X-band 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 : integer
The radius of rangebins within the rain-intensity is
statistically evaluated as the representative rain-intensity
over radome.
stat : class
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 : array
Array with the same shape as ``gateset`` containing the
calculated two-way 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.
"""
# Select rangebins inside the defined center-range n_r.
center = gateset[...,:n_r].reshape(-1, n_r * gateset.shape[-2])
center_m = np.ma.masked_array(center, np.isnan(center))
# Calculate rainrate in the center-range based on statistical method stat
# and with standard ZR-relation.
rain_over_radome = z2r(idecibel(stat(center_m, axis = -1)))
# Estimate the empirical two-way transmission loss due to
# radome-attenuation.
k = 2 * hydrophobicity * rain_over_radome * np.tanh(frequency / 10.)**2
# Reshape the result to gateset-shape.
k = np.repeat(k, gateset.shape[-1] *
gateset.shape[-2]).reshape(gateset.shape)
return k
def test_z2r(self):
self.assertEqual(zr.z2r(trafo.idecibel(10.)), 0.1537645610180688)