def plot_comp_reflect():
print(" COMP REFLECTIVITY")
# Set Figure Size (1000 x 800)
pylab.figure(figsize=(width,height),frameon=False)
QR = nc.variables['QRAIN']
QS = nc.variables['QSNOW']
# Define 'constant' densities (kg m-3)
rhor = 1000
rhos = 100
rhog = 400
rhoi = 917
# Define "fixed intercepts" (m-4)
Norain = 8.0E6
#Nosnow = 2.0E7
Nosnow = 2.0E6*np.exp(-0.12 * (temps[time]-273))
Nograu = 4.0E6
# First, find the density at the first sigma level
# above the surface
density = np.divide(psfc[time],(287.0 * temps[time]))
#print "Rho: ", np.mean(density)
Qra_all = QR[time]
Qsn_all = QS[time]
for j in range(len(Qra_all[1,:,1])):
curcol_r = []
curcol_s = []
for i in range(len(Qra_all[1,1,:])):
maxrval = np.max(Qra_all[:,j,i])
maxsval = np.max(Qsn_all[:,j,i])
curcol_r.append(maxrval)
curcol_s.append(maxsval)
np_curcol_r = np.array(curcol_r)
np_curcol_s = np.array(curcol_s)
if j == 0:
Qra = np_curcol_r
Qsn = np_curcol_s
else:
Qra = np.row_stack((Qra, np_curcol_r))
Qsn = np.row_stack((Qsn, np_curcol_s))
#print "Qra shp: ", np.shape(Qra)
#print "Den shp: ", np.shape(density)
# Calculate slope factor lambda
lambr = np.divide((3.14159 * Norain * rhor), np.multiply(density, Qra))
lambr = lambr ** 0.25
#lambs = np.divide((3.14159 * Nosnow * rhoi), np.multiply(density, Qsn))
#lambs = lambs ** 0.25
lambs = np.exp(-0.0536 * (temps[time] - 273))
# Calculate equivalent reflectivity factor
Zer = (720.0 * Norain * (lambr ** -7.0)) * 1E18
Zes = (0.224 * 720.0 * Nosnow * (lambr ** -7.0) * (rhos/rhoi) ** 2) * 1E18
Zes_int = np.divide((lambs * Qsn * density), Nosnow)
Zes = ((0.224 * 720 * 1E18) / (3.14159 * rhor) ** 2) * Zes_int ** 2
Ze = np.add(Zer, Zes)
#Ze = Zer
# Convert to dBZ
dBZ = 10 * np.log10(Ze)
dBZ = np.nan_to_num(dBZ)
units = 'dBZe'
print " MAX: ", np.max(dBZ)
# Now plot
REF_LEVELS = range(5,90,5)
CREFLECT=pylab.contourf(x,y,dBZ,REF_LEVELS,cmap=coltbls.reflect())
#SREFLECT=pylab.contourf(x,y,dBZ)
title = 'Simulated Composite Reflectivity'
prodid = 'cref'
drawmap(CREFLECT, title, prodid, units)
def plot_sim_reflect():
print(" SIM REFLECTIVITY")
# Set Figure Size (1000 x 800)
pylab.figure(figsize=(width,height),frameon=False)
QR = nc.variables['QRAIN']
QS = nc.variables['QSNOW']
# Define 'constant' densities (kg m-3)
rhor = 1000
rhos = 100
rhog = 400
rhoi = 917
# Define "fixed intercepts" (m-4)
Norain = 8.0E6
#Nosnow = 2.0E7
Nosnow = 2.0E6*np.exp(-0.12 * (temps[time]-273))
Nograu = 4.0E6
# First, find the density at the first sigma level
# above the surface
density = np.divide(psfc[time],(287.0 * temps[time]))
#print "Rho: ", np.mean(density)
Qra = QR[time,1]
Qsn = QS[time,1]
Qra = np.nan_to_num(Qra)
Qsn = np.nan_to_num(Qsn)
# Calculate slope factor lambda
lambr = np.divide((3.14159 * Norain * rhor), np.multiply(density, Qra))
lambr = lambr ** 0.25
#lambs = np.divide((3.14159 * Nosnow * rhoi), np.multiply(density, Qsn))
#lambs = lambs ** 0.25
lambs = np.exp(-0.0536 * (temps[time] - 273))
# Calculate equivalent reflectivity factor
Zer = (720.0 * Norain * (lambr ** -7.0)) * 1E18
Zes = (0.224 * 720.0 * Nosnow * (lambr ** -7.0) * (rhos/rhoi) ** 2) * 1E18
Zes_int = np.divide((lambs * Qsn * density), Nosnow)
Zes = ((0.224 * 720 * 1E18) / (3.14159 * rhor) ** 2) * Zes_int ** 2
Ze = np.add(Zer, Zes)
#Ze = Zer
# Convert to dBZ
dBZ = 10 * np.log10(Ze)
dBZ = np.nan_to_num(dBZ)
units = 'dBZe'
print " MAX: ", np.max(dBZ)
# Now plot
REF_LEVELS = range(5,90,5)
SREFLECT=pylab.contourf(x,y,dBZ,REF_LEVELS,cmap=coltbls.reflect())
#SREFLECT=pylab.contourf(x,y,dBZ)
title = 'Simulated Surface Reflectivity'
prodid = 'sref'
drawmap(SREFLECT, title, prodid, units)
