user308827 - 4 months ago 39

Python Question

I would like to extract a spatial subset of a rather large netcdf file. From Loop through netcdf files and run calculations - Python or R

`from pylab import *`

import netCDF4

f = netCDF4.MFDataset('/usgs/data2/rsignell/models/ncep/narr/air.2m.1989.nc')

# print variables

f.variables.keys()

atemp = f.variables['air'] # TODO: extract spatial subset

How do I extract just the subset of netcdf file corresponding to a state (say Iowa). Iowa has following boundary lat lon:

Longitude: 89° 5' W to 96° 31' W

Latitude: 40° 36' N to 43° 30' N

Answer

Well this is pretty easy, you have to find the index for the upper and lower bound in latitude and longitude. You can do it by finding the value that is closest to the ones you're looking for.

```
latbounds = [ 40 , 43 ]
lonbounds = [ -96 , -89 ] # degrees east ?
lats = f.variables['latitude'][:]
lons = f.variables['longitude'][:]
# latitude lower and upper index
latli = np.argmin( np.abs( lats - latbounds[0] ) )
latui = np.argmin( np.abs( lats - latbounds[1] ) )
# longitude lower and upper index
lonli = np.argmin( np.abs( lons - lonbounds[0] ) )
lonui = np.argmin( np.abs( lons - lonbounds[1] ) )
```

Then just subset the variable array.

```
# Air (time, latitude, longitude)
airSubset = f.variables['air'][ : , latli:latui , lonli:lonui ]
```

- Note, i'm assuming the longitude dimension variable is in degrees east, and the air variable has time, latitude, longitude dimensions.