Mask Ocean or Land from data using Cartopy

Question

I would like to mask the Land area from Sea Surface Temperature Data over the globe. I am using Cartopy to plot the data.

import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from netCDF4 import Dataset

f = Dataset('sst.mnmean.nc')
sst = f.variables['sst'][0,:,:]
lats = f.variables['lat'][:]
lons = f.variables['lon'][:]

ax = plt.axes(projection=ccrs.PlateCarree())
ax.coastlines()
plot = ax.contourf(lons, lats, sst, 60, transform=ccrs.PlateCarree())
cb = plt.colorbar(plot)
plt.show()

The above code plots data like this:

I would like to mask out the Land from this.

Please clarify your question, I assume you mean how to remove the temperature data associated with land mass? — Maljam
No, the data is actually just ocean data. But in order to be interpolated effectively, the whole globe is used. As a result I have sea surface temperature over land as well (which is meaningless). Sea surface temperatures is a measure of temperature over just the water bodies — Kushal
@Maljam How did you edit my question to show the image in the question itself? — Kushal
@Kushal there's picture button above the textbox (next to the {} button) — Maljam

Kushal Kushal · Accepted Answer · 2016-04-10T07:49:43

I went through the cartopy documentation and came across the method called add_feature. The code is as follows:

import numpy as np
import matplotlib.pyplot as plt
import cartopy as cart
from mpl_toolkits.basemap import Basemap
from netCDF4 import Dataset

f = Dataset('sst.mnmean.nc')
sst = f.variables['sst'][0,:,:]
lats = f.variables['lat'][:]
lons = f.variables['lon'][:]

ax = plt.axes(projection=cart.crs.PlateCarree())
ax.coastlines()
ax.add_feature(cart.feature.LAND, zorder=100, edgecolor='k')
ax.set_global()
plot = ax.contourf(lons, lats, sst, 60, transform=cart.crs.PlateCarree())
cb = plt.colorbar(plot)
plt.show()

The plot now looks like this. To mask the oceans, change cart.feature.LAND to cart.feature.OCEAN

Mask Ocean or Land from data using Cartopy

2 Answers