root = Dataset('wrf_2011_07_01','r')
cen_lat = getattr(root,'CEN_LAT')
cen_lon = getattr(root,'CEN_LON')
true_lat1 = getattr(root,'TRUELAT1')
true_lat2 = getattr(root,'TRUELAT2')
ref_lat = getattr(root,'MOAD_CEN_LAT')
ref_lon = getattr(root,'STAND_LON')
vars = root.variables
u = vars['U'][:,height_level,:,:]
v = vars['V'][:,height_level,:,:]
lat_vel = vars['XLAT'][0,:,:]
lon_vel = vars['XLONG'][0,:,:]
root.close()
checklon, checklat = mf.lonlat2km(ref_lon,ref_lat,lon_vel,lat_vel,true_lat1,true_lat2)
root = Dataset('wrf_2011_07_02','r')
vars = root.variables
u = np.concatenate((u,vars['U'][:,height_level,:,:]))
v = np.concatenate((v,vars['V'][:,height_level,:,:]))
root.close()
u = mf.unstagger(u[:tdim,:,:],2)
v = mf.unstagger(v[:tdim,:,:],1)
dx = grid_spacing
dy = grid_spacing
time_in = np.linspace(0,24,25)
time_want = np.linspace(0,24,145)
u_out = np.empty([145,82,102])
v_out = np.empty([145,82,102])
root = Dataset('wrf_species_2011_07_01', 'r')
vars = root.variables
print(u.max())
#u = vars['U'+species][:,1:-1,1:-1]
#v = vars['V'+species][:,1:-1,1:-1]
cen_lat = getattr(root, 'CEN_LAT')
cen_lon = getattr(root, 'CEN_LON')
true_lat1 = getattr(root, 'TRUELAT1')
true_lat2 = getattr(root, 'TRUELAT2')
ref_lat = getattr(root, 'MOAD_CEN_LAT')
ref_lon = getattr(root, 'STAND_LON')
lat_in = vars['XLAT'][0, 1:-1, 1:-1]
lon_in = vars['XLONG'][0, 1:-1, 1:-1]
root.close()
xin, yin = mf.lonlat2km(ref_lon, ref_lat, lon_in, lat_in, true_lat1,
true_lat2)
lat2file = np.linspace(np.min(lat_in), np.max(lat_in), (ydim - 1) * 4 + 1)
lon2file = np.linspace(np.min(lon_in), np.max(lon_in), (xdim - 1) * 4 + 1)
xodim = lon2file.shape[0]
yodim = lat2file.shape[0]
lonout, latout = np.meshgrid(lon2file, lat2file)
xout, yout = mf.lonlat2km(ref_lon, ref_lat, lonout, latout, true_lat1,
true_lat2)
uout = np.empty([tdim, yodim * xodim])
vout = np.empty([tdim, yodim * xodim])
spout = np.empty([tdim, yodim * xodim])
for t in range(tdim):
from scipy.interpolate import griddata
import matplotlib.pyplot as plt
plt.close('all')
#25N
#-90E
root = Dataset('data/07_25_2019/rtofs_glo_2ds_f000_1hrly_prog.nc', 'r')
vars = root.variables #dictionary, all variables in dataset\
lon = vars['Longitude'][:-1, :] - 360
lat = vars['Latitude'][:-1, :]
u = vars['u_velocity'][:, :, :-1, :].squeeze()
v = vars['v_velocity'][:, :, :-1, :].squeeze()
del vars
root.close()
x, y = mf.lonlat2km(-90, 25, lon, lat, std_lat1=20, std_lat2=30)
del lon, lat
plt.figure()
plt.pcolormesh(x, y, np.sqrt(u**2 + v**2), vmin=0,
vmax=3) #np.sqrt(u**2+v**2))
plt.xlim([-900, 1100])
plt.ylim([-800, 800])
plt.colorbar()
u = u[x >= -1000]
v = v[x >= -1000]
y = y[x >= -1000]
x = x[x >= -1000]
u = u[x <= 1200]
