import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap, addcyclic
from netCDF4 import Dataset
# ncep 1 monthly air temperature from ICDC
filename='/data/icdc/reanalyses/ncep_reanalysis1/DATA/2m_airtemp_monthly/air2m.mon.mean.nc'
fid=Dataset(filename,'r') # open file and create file identifier
# show all variables and their units
for i in fid.variables.keys():
    print i, fid.variables[i].units
lat=fid.variables['lat'][:]
lon=fid.variables['lon'][:]
air=fid.variables['air'][0,:,:] # first time step
# basemap instance with lat/lon corner values
m = Basemap(projection='cyl',llcrnrlat=-90,llcrnrlon=0,urcrnrlat=90,urcrnrlon=360,resolution='l')
# meshgrid returns coordinate matrices from 2 vectors
# basemap instance can take 2 arguments to convert lat,lon matrices to x,y
x, y = m(*np.meshgrid(lon,lat))
# min, max, step width for color bar (unit Kelvin)
ps=np.linspace(225,310,50)
m.contourf(x,y,air,ps)
m.drawcoastlines()
m.drawmeridians(np.arange(0, 360, 30), labels=[1,0,0,1])
m.drawparallels(np.arange(-90, 90, 30), labels=[0,1,1,0])
plt.title('NCEP')
plt.colorbar(shrink=0.5)
plt.show()