def hgt_500mb(self):
u = self.dataSet.readNCVariable('U')
v = self.dataSet.readNCVariable('V')
u_corr = wrf.unstaggerX(u)
v_corr = wrf.unstaggerY(v)
height = wrf.unstaggerZ(self.height)
ref_val = 50000.
#Switched to Cython
#self.u10 = wrf.loglinear_interpolate(u_corr, self.press, ref_val)
#self.v10 = wrf.loglinear_interpolate(v_corr, self.press, ref_val)
self.u10 = np.array(wrf_cython.loglinear_interpolate(u_corr, self.press, ref_val))
self.v10 = np.array(wrf_cython.loglinear_interpolate(v_corr, self.press, ref_val))
#self.var = wrf.hypsometric(height,self.press, ref_val, self.temp)
self.var = np.array(wrf_cython.hypsometric(height, self.press, ref_val, self.temp))
self.var2 = self.var
self.varTitle = "500-mb Geopotential Height (m)\n" + self.dataSet.getTime()
#Set short variable title for time series
self.sTitle = "500-mb Geopotential Height (m)"
def winds_300mb(self):
u = self.dataSet.readNCVariable('U')
v = self.dataSet.readNCVariable('V')
u_corr = wrf.unstaggerX(u)
v_corr = wrf.unstaggerY(v)
height = wrf.unstaggerZ(self.height)
ref_val = 30000.
#Switched to Cython
#self.u10 = wrf.loglinear_interpolate(u_corr, self.press, ref_val)
#self.v10 = wrf.loglinear_interpolate(v_corr, self.press, ref_val)
self.u10 = np.array(wrf_cython.loglinear_interpolate(u_corr, self.press, ref_val))
self.v10 = np.array(wrf_cython.loglinear_interpolate(v_corr, self.press, ref_val))
var1 = wrf.get_bulk_wind(self.u10,self.v10)
self.var = wrf.convertWind_MStoKT(var1)
#self.var2 = wrf.hypsometric(height, self.press, ref_val, self.temp)
self.var2 = np.array(wrf_cython.hypsometric(height, self.press, ref_val, self.temp))
self.varTitle = "300-mb Wind\n" + self.dataSet.getTime()
#Set short variable title for time series
self.sTitle = "300-mb Wind"
def temp_500mb(self):
u = self.dataSet.readNCVariable('U')
v = self.dataSet.readNCVariable('V')
u_corr = wrf.unstaggerX(u)
v_corr = wrf.unstaggerY(v)
height = wrf.unstaggerZ(self.height)
ref_val = 50000.
#Switched to Cython
#var1 = wrf.loglinear_interpolate(self.temp, self.press, ref_val)
#self.u10 = wrf.loglinear_interpolate(u_corr, self.press, ref_val)
#self.v10 = wrf.loglinear_interpolate(v_corr, self.press, ref_val)
var1 = np.array(wrf_cython.loglinear_interpolate(self.temp, self.press, ref_val))
self.u10 = np.array(wrf_cython.loglinear_interpolate(u_corr, self.press, ref_val))
self.v10 = np.array(wrf_cython.loglinear_interpolate(v_corr, self.press, ref_val))
self.var = wrf.convertT_KtoC(var1)
#self.var2 = wrf.hypsometric(height, self.press, ref_val, self.temp)
self.var2 = np.array(wrf_cython.hypsometric(height, self.press, ref_val, self.temp))
self.varTitle = "500-mb Temperature ($^{\circ}$C)\n" + self.dataSet.getTime()
#Set short variable title for time series
self.sTitle = "500-mb Temperature ($^{\circ}$C)"
def vort_500mb(self):
u = self.dataSet.readNCVariable('U')
v = self.dataSet.readNCVariable('V')
u_corr = wrf.unstaggerX(u)
v_corr = wrf.unstaggerY(v)
height = wrf.unstaggerZ(self.height)
ref_val = 50000.
#Switched to Cython
#self.u10 = wrf.loglinear_interpolate(u_corr, self.press, ref_val)
#self.v10 = wrf.loglinear_interpolate(v_corr, self.press, ref_val)
self.u10 = np.array(wrf_cython.loglinear_interpolate(u_corr, self.press, ref_val))
self.v10 = np.array(wrf_cython.loglinear_interpolate(v_corr, self.press, ref_val))
self.var = wrf.rel_vort(self.u10, self.v10,
self.dataSet.dx[self.dataSet.currentGrid-1],
self.dataSet.dy[self.dataSet.currentGrid-1])
#self.var2 = wrf.hypsometric(height, self.press, ref_val, self.temp)
self.var2 = np.array(wrf_cython.hypsometric(height, self.press, ref_val, self.temp))
self.varTitle = "500-mb Relative Vorticity ($10^{-5}$ $s^{-1}$)\n" +\
self.dataSet.getTime()
#Set short variable title for time series
self.sTitle = "500-mb Relative Vorticity ($10^{-5}$ $s^{-1}$)"