eofs.ipynb

Kernel: Python 2 (SageMath)

North Atlantic Oscillation

Source : http://ajdawson.github.io/eofs/examples/nao_iris.html

import warnings

import iris
import iris.plot as iplt
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import numpy as np

from eofs.iris import Eof
from eofs.examples import example_data_path

filename = example_data_path('hgt_djf.nc')
z_djf = iris.load_cube(filename)

with warnings.catch_warnings():
    # Iris emits a warning due to the non-contiguous time dimension.
    warnings.simplefilter('ignore', UserWarning)
    z_djf_mean = z_djf.collapsed('time', iris.analysis.MEAN)
z_djf = z_djf - z_djf_mean

solver = Eof(z_djf, weights='coslat')

eof1 = solver.eofsAsCovariance(neofs=1)

clevs = np.linspace(-75, 75, 11)
proj = ccrs.Orthographic(central_longitude=-20, central_latitude=60)
ax = plt.axes(projection=proj)
# ax.coastlines()
ax.set_global()
iplt.contourf(eof1[0, 0], levels=clevs, cmap=plt.cm.RdBu_r)
ax.set_title('EOF1 expressed as covariance', fontsize=16)
plt.show()

El Niño

Source : http://ajdawson.github.io/eofs/examples/elnino_iris.html

import cartopy.crs as ccrs
import cartopy.feature as cfeature
import iris
import iris.plot as iplt
import matplotlib.pyplot as plt
import numpy as np

from eofs.iris import Eof
from eofs.examples import example_data_path

iris.FUTURE.netcdf_promote = True

filename = example_data_path('sst_ndjfm_anom.nc')
sst = iris.load_cube(filename)

solver = Eof(sst, weights='coslat')

eof1 = solver.eofsAsCorrelation(neofs=1)
pc1 = solver.pcs(npcs=1, pcscaling=1)

clevs = np.linspace(-1, 1, 11)
ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=190))
fill = iplt.contourf(eof1[0], clevs, cmap=plt.cm.RdBu_r)
# ax.add_feature(cfeature.LAND, facecolor='w', edgecolor='k')
cb = plt.colorbar(fill, orientation='horizontal')
cb.set_label('coefficient de correlation', fontsize=12)
ax.set_title('EOF1 exprime comme correlation', fontsize=16)

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plt.figure()
iplt.plot(pc1[:, 0], color='b', linewidth=2)
ax = plt.gca()
ax.axhline(0, color='k')
ax.set_ylim(-3, 3)
ax.set_xlabel('Year')
ax.set_ylabel('Normalized Units')
ax.set_title('PC1 Time Series', fontsize=16)
plt.show()