from __future__ import (absolute_import, division, print_function) from netCDF4 import Dataset from mpl_toolkits.basemap import Basemap import numpy as np import matplotlib.pyplot as plt nc = Dataset('wm201_Arctic_JJA_1990-2008_moyenneDesMoyennes.nc') lats = nc.variables['lat'][:] lons = nc.variables['lon'][:] rlats = nc.variables['rlat'][:] rlons = nc.variables['rlon'][:] rlons, rlats = np.meshgrid(rlons, rlats) data = nc.variables['air'][0,0,:,:].squeeze() data = np.ma.masked_values(data,-999.) rotpole = nc.variables['rotated_pole'] m = Basemap(projection='npstere',lon_0=10,boundinglat=30,resolution='c') x,y = m(lons,lats) m.drawcoastlines() m.contourf(x,y,data,20) m.drawmeridians(np.arange(-180,180,20)) m.drawparallels(np.arange(20,80,20)) m.colorbar() plt.title('rotated pole data in polar stere map') plt.figure() # o_lon_p, o_lat_p: true lat/lon of pole in rotated coordinate system # mapping to CF metadata convention: # grid_north_pole_longitude = normalize180(180 + lon_0), where normalize180 # is a function that maps to interval [-180,180). # grid_north_pole_latitude = o_lat_p # north_pole_grid_longitude = o_lon_p (optional, assumed zero if not present) def normalize180(lon): """Normalize lon to range [180, 180)""" lower = -180.; upper = 180. if lon > upper or lon == lower: lon = lower + abs(lon + upper) % (abs(lower) + abs(upper)) if lon < lower or lon == upper: lon = upper - abs(lon - lower) % (abs(lower) + abs(upper)) return lower if lon == upper else lon lon_0 = normalize180(rotpole.grid_north_pole_longitude-180.) o_lon_p = rotpole.north_pole_grid_longitude o_lat_p = rotpole.grid_north_pole_latitude print( rotpole ) print( 'lon_0,o_lon_p,o_lat_p=',lon_0,o_lon_p,o_lat_p) m= Basemap(projection='rotpole',lon_0=lon_0,o_lon_p=o_lon_p,o_lat_p=o_lat_p,\ llcrnrlat = lats[0,0], urcrnrlat = lats[-1,-1],\ llcrnrlon = lons[0,0], urcrnrlon = lons[-1,-1],resolution='c') x,y = m(lons,lats) m.drawcoastlines() m.contourf(x,y,data,20) m.drawmeridians(np.arange(-180,180,20)) m.drawparallels(np.arange(20,80,20)) m.colorbar() plt.title('rotated pole data in native map using real sphere corner lat/lons' ) plt.figure() m= Basemap(projection='rotpole',lon_0=lon_0,o_lon_p=o_lon_p,o_lat_p=o_lat_p,\ llcrnry = rlats[0,0], urcrnry = rlats[-1,-1],\ llcrnrx = rlons[0,0], urcrnrx = rlons[-1,-1],resolution='c') x,y = m(lons,lats) m.drawcoastlines() m.contourf(x,y,data,20) m.drawmeridians(np.arange(-180,180,20)) m.drawparallels(np.arange(20,80,20)) m.colorbar() plt.title('rotated pole data in native map using rotated sphere corner lat/lons' ) plt.show()