def get_radar_variables_Exponential_fwScattering(N0=None,
Lambda=None,
D_max=None):
scatterer.psd = psd.ExponentialPSD(N0=N0, Lambda=Lambda, D_max=D_max)
return [
radar.Ai(scatterer, h_pol=True),
radar.Ai(scatterer, h_pol=False),
radar.Kdp(scatterer)
]
def test_integrated_x_sca(self):
"""Test Rayleigh scattering cross section integrated over sizes.
"""
m = complex(3.0, 0.5)
K = (m**2 - 1) / (m**2 + 2)
N0 = 10
Lambda = 1e4
sca = Scatterer(wavelength=1, m=m)
sca.psd_integrator = psd.PSDIntegrator()
sca.psd = psd.ExponentialPSD(N0=N0, Lambda=Lambda)
sca.psd.D_max = 0.002
sca.psd_integrator.D_max = sca.psd.D_max
# 256 is quite low, but we want to run the test reasonably fast
sca.psd_integrator.num_points = 256
sca.psd_integrator.init_scatter_table(sca, angular_integration=True)
# This size-integrated scattering cross section has an analytical value.
# Check that we can reproduce it.
sca_xsect_ref = 480 * N0 * np.pi**5 * abs(K)**2 / Lambda**7
sca_xsect = scatter.sca_xsect(sca)
test_less(self, abs(1 - sca_xsect / sca_xsect_ref), 1e-3)
def get_radar_variables_Exponential(N0=None, Lambda=None, D_max=None):
scatterer.psd = psd.ExponentialPSD(N0=N0, Lambda=Lambda, D_max=D_max)
return [
10. * np.log10(radar.refl(scatterer)),
10. * np.log10(radar.Zdr(scatterer))
]
fig, (ax1,ax2,ax3) = plt.subplots(3,1)#,sharex=True)
Zdr_array = []
Z_array = []
for wl in wavelengths:
ref_func = m_rho_func(wl)
for lamb in lambdas:
scatterer = tmatrix.Scatterer(wavelength=wl,
axis_ratio=1.0/ar,
Kw_sqr=tmatrix_aux.K_w_sqr[wl])
scatterer.psd_integrator = psd.PSDIntegrator()
scatterer.psd_integrator.m_func = ref_func
scatterer.psd_integrator.geometries=[tmatrix_aux.geom_horiz_back,tmatrix_aux.geom_horiz_forw,]
scatterer.set_geometry(tmatrix_aux.geom_horiz_back)
scatterer.psd = psd.ExponentialPSD(N0=1.0,Lambda=lamb,D_max=20.0)
scatterer.psd_integrator.D_max = 20.0
scatterer.psd_integrator.init_scatter_table(scatterer)
Zdr = 10.0*np.log10(radar.Zdr(scatterer))
scatterer.set_geometry(tmatrix_aux.geom_horiz_forw)
W = np.pi*1e3*(1.0/lamb)**4
Kdp = 1.0e6*radar.Kdp(scatterer)/W
Zdr_array.append(Zdr)
Z_array.append(Kdp)
ax1.plot(D0s,Zdr_array,label=wl)
ax2.plot(D0s,Z_array,label=wl)
Zdr_array = []
Z_array = []
ax1.legend()
ax1.grid()
ax2.grid()
def get_radar_variables_Exponential(N0=None,Lambda=None,D_max=None):
scatterer.psd = psd.ExponentialPSD(N0=N0, Lambda=Lambda, D_max=D_max)
return [radar.refl(scatterer), radar.Zdr(scatterer), radar.ldr(scatterer)]