era5_consistency.py

import xarray as xr
import numpy as np
import matplotlib.pyplot as plt

print("Jan")
ds = xr.open_dataset("era5_prec_2018H1.nc")
prec = ds.tp.sel(dict(time=slice('2018-01-01', '2018-01-31'))).data * 1000
ds.close()
print(prec.shape)

mean = np.mean(prec[:,:,:], axis=(1,2))[:-1]
plt.plot(mean)
plt.savefig("prec_mean.png")
plt.clf()
plt.plot(mean[:24])
plt.savefig("prec_mean_24.png")
plt.clf()
plt.plot(mean[:48])
plt.savefig("prec_mean_48.png")
plt.clf()
plt.plot(mean[:96])
plt.savefig("prec_mean_96.png")
plt.clf()

diff = np.mean(np.abs(prec[:-1,:,:] - prec[1:,:,:]), axis=(1,2))
prec = None
plt.plot(diff)
plt.savefig("prec_diff.png")
plt.clf()
plt.plot(diff[:24])
plt.savefig("prec_diff_24.png")
plt.clf()
plt.plot(diff[:48])
plt.savefig("prec_diff_48.png")
plt.clf()
plt.plot(diff[:96])
plt.savefig("prec_diff_96.png")
plt.clf()


ds = xr.open_dataset("era5_geop_201801.nc")
z500 = ds.z[:,0,:,:].data
ds.close()

mean = np.mean(z500[:,:,:], axis=(1,2))[:-1]
plt.plot(mean)
plt.savefig("geop_mean.png")
plt.clf()
plt.plot(mean[:24])
plt.savefig("geop_mean_24.png")
plt.clf()
plt.plot(mean[:48])
plt.savefig("geop_mean_48.png")
plt.clf()
plt.plot(mean[:96])
plt.savefig("geop_mean_96.png")
plt.clf()

diff = np.mean(np.abs(z500[:-1,:,:] - z500[1:,:,:]), axis=(1,2))
z500 = None
plt.plot(diff)
plt.savefig("geop_diff.png")
plt.clf()
plt.plot(diff[:24])
plt.savefig("geop_diff_24.png")
plt.clf()
plt.plot(diff[:48])
plt.savefig("geop_diff_48.png")
plt.clf()
plt.plot(diff[:96])
plt.savefig("geop_diff_96.png")
plt.clf()