dynamic_pme/plot_pme_check.py at main · dkhutch/dynamic_pme · GitHub

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import numpy as np
import netCDF4 as nc
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.util as cutl
import cmaps

plio_file = 'pme_eplio.nc'
glac_file = 'pme_glac.nc'
dyn_pme_file = 'pme_uvq_eplio.nc'

outfile_jja = 'pme_check_jja.pdf'
outfile_djf = 'pme_check_djf.pdf'

f = nc.Dataset(plio_file, 'r')
evap_plio = f.variables['evap'][:]
precip_plio = f.variables['precip'][:]
temp_plio = f.variables['t_ref'][:]
lat = f.variables['lat'][:]
lon = f.variables['lon'][:]
f.close()

f = nc.Dataset(glac_file, 'r')
evap_glac = f.variables['evap'][:]
precip_glac = f.variables['precip'][:]
temp_glac = f.variables['t_ref'][:]
f.close()

f = nc.Dataset(dyn_pme_file,'r')
pme_dyn = f.variables['pme_calc'][:]
f.close()

evap_plio = evap_plio
precip_plio = precip_plio
evap_glac = evap_glac
precip_glac = precip_glac

pme_plio = precip_plio - evap_plio
pme_glac = precip_glac - evap_glac

delta_pme = pme_glac - pme_plio
delta_T = temp_glac - temp_plio

delta_T_av = np.mean(delta_T)

alpha = 0.07

delta_held = alpha * delta_T * pme_plio

jja = [5,6,7]
djf = [0,1,11]

delta_held_jja = np.mean(delta_held[jja,:,:], axis=0) * 86400.
delta_held_djf = np.mean(delta_held[djf,:,:], axis=0) * 86400.
delta_pme_jja = np.mean(delta_pme[jja,:,:], axis=0) * 86400.
delta_pme_djf = np.mean(delta_pme[djf,:,:], axis=0) * 86400.
pme_plio_jja = np.mean(pme_plio[jja,:,:], axis=0) * 86400.
pme_plio_djf = np.mean(pme_plio[djf,:,:], axis=0) * 86400.
pme_dyn_jja = np.mean(pme_dyn[jja,:,:], axis=0) * 86400.
pme_dyn_djf = np.mean(pme_dyn[djf,:,:], axis=0) * 86400.

delta_held_jja_z = np.mean(delta_held_jja, axis=1)
delta_held_djf_z = np.mean(delta_held_djf, axis=1)
delta_pme_jja_z = np.mean(delta_pme_jja, axis=1)
delta_pme_djf_z = np.mean(delta_pme_djf, axis=1)
pme_plio_jja_z = np.mean(pme_plio_jja, axis=1)
pme_plio_djf_z = np.mean(pme_plio_djf, axis=1)

delta_held_jja, lon1 = cutl.add_cyclic_point(delta_held_jja, coord=lon)
delta_held_djf, _ = cutl.add_cyclic_point(delta_held_djf, coord=lon)
delta_pme_jja, _ = cutl.add_cyclic_point(delta_pme_jja, coord=lon)
delta_pme_djf, _ = cutl.add_cyclic_point(delta_pme_djf, coord=lon)
pme_plio_jja, _ = cutl.add_cyclic_point(pme_plio_jja, coord=lon)
pme_plio_djf, _ = cutl.add_cyclic_point(pme_plio_djf, coord=lon)
pme_dyn_jja, _ = cutl.add_cyclic_point(pme_dyn_jja, coord=lon)
pme_dyn_djf, _ = cutl.add_cyclic_point(pme_dyn_djf, coord=lon)

amin = -1.
amax = 1.
ivl = .1
levels = np.arange(amin, amax+ivl/2., ivl)

bmin = -10.
bmax = 10.
bivl = 1.
blevels = np.arange(bmin, bmax+bivl/2., bivl)

fig = plt.figure(num=1, figsize=(6,8))


ax1 = fig.add_subplot(2,1,1, projection=ccrs.PlateCarree())

# can also use cmap=cmaps.cmocean_balance
# h1 = ax1.contourf(lon1, lat, pme_plio_jja, blevels, extend="both", cmap=cmaps.BlueWhiteOrangeRed)
h1 = ax1.contourf(lon1, lat, pme_plio_jja, blevels, extend="both", cmap=cmaps.MPL_BrBG)
cbar = plt.colorbar(h1, fraction=0.025, pad=0.04)
ax1.set_title('Early Plio P-E JJA (mm/d)')
ax1.coastlines()
gl = ax1.gridlines(draw_labels=True, alpha=0.5, color='black', linewidth=0.5, linestyle='--')
gl.top_labels = False
gl.right_labels = False


ax1 = fig.add_subplot(2,1,2, projection=ccrs.PlateCarree())

# can also use cmap=cmaps.cmocean_balance
h1 = ax1.contourf(lon1, lat, pme_dyn_jja, blevels, extend="both", cmap=cmaps.MPL_BrBG)
cbar = plt.colorbar(h1, fraction=0.025, pad=0.04)
ax1.set_title('(P-E) from divergence JJA (mm/d)')
ax1.coastlines()
gl = ax1.gridlines(draw_labels=True, alpha=0.5, color='black', linewidth=0.5, linestyle='--')
gl.top_labels = False
gl.right_labels = False


plt.savefig(outfile_jja)


fig = plt.figure(num=2, figsize=(6,8))


ax1 = fig.add_subplot(2,1,1, projection=ccrs.PlateCarree())

h1 = ax1.contourf(lon1, lat, pme_plio_djf, blevels, extend="both", cmap=cmaps.MPL_BrBG)
cbar = plt.colorbar(h1, fraction=0.025, pad=0.04)
ax1.set_title('Early Plio P-E DJF (mm/d)')
ax1.coastlines()
gl = ax1.gridlines(draw_labels=True, alpha=0.5, color='black', linewidth=0.5, linestyle='--')
gl.top_labels = False
gl.right_labels = False


ax1 = fig.add_subplot(2,1,2, projection=ccrs.PlateCarree())

h1 = ax1.contourf(lon1, lat, pme_dyn_djf, blevels, extend="both", cmap=cmaps.MPL_BrBG)
cbar = plt.colorbar(h1, fraction=0.025, pad=0.04)
ax1.set_title('(P-E) from divergence JJA (mm/d)')
ax1.coastlines()
gl = ax1.gridlines(draw_labels=True, alpha=0.5, color='black', linewidth=0.5, linestyle='--')
gl.top_labels = False
gl.right_labels = False

plt.savefig(outfile_djf)