
%matplotlib inline
import xarray as xr
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import os, datetime, warnings, cmocean
from cesm_utils import fixtime, spd
print('Last updated on {}'.format(datetime.datetime.now().ctime()))

Last updated on Wed May 26 16:22:19 2021


sns.set_theme(context='paper', palette='tab10', rc={'figure.dpi':100})
warnings.filterwarnings('ignore')


datadir = '/home/ivan/Data/Postproc/1DPOP_CESM2/'
infile = datadir + 'cesm2.B1850.f09_g17.1dpop.003.natl.nc'
ds_tseries = xr.open_dataset(infile, decode_times=False)
ds_tseries = fixtime(ds_tseries, 1851)
ds_tseries = ds_tseries.squeeze(drop=True)

ds_tseries['FRAZIL'] = - ds_tseries.QFLUX/ds_tseries.latent_heat_fusion_mks
ds_tseries['FRAZIL'].attrs = {'long_name':'frazil ice formation', 'units':'kg/m^2/s'}


zz = 25
fig, ax = plt.subplots(1,2,figsize=(12,6))
pm = ax[0].pcolormesh(ds_tseries.time.values, -ds_tseries.z_t[:zz].values/100, ds_tseries.SALT[:,:zz].transpose().values,cmap=cmocean.cm.haline)
_ = ax[0].set(title='salinity profile at Hudson Bay', ylabel='depth (m)')
cb = fig.colorbar(pm, ax=ax[0], orientation='horizontal', pad=0.075)
cb.set_label('g/kg')

_ = sns.lineplot(ds_tseries.time.to_index().to_datetimeindex(), ds_tseries.SALT[:,0].values, ax=ax[1])
_ = ax[1].set(xlabel='time', ylabel=ds_tseries['SALT'].units, title='surface salinity')


varlist = ['SFWF','EVAP_F','PREC_F','ROFF_F','MELT_F','IOFF_F','SALT_F','FRAZIL','IFRAC']
data_dict = {vname: ds_tseries[vname].values for vname in varlist}
for vname in ['S_INTERIOR']:
    data_dict[vname] = ds_tseries[vname][:,0].values
df_fluxes = pd.DataFrame(data_dict, index=ds_tseries.time.to_index().to_datetimeindex())
df_fluxes.index.name = 'time'


df = df_fluxes.stack().reset_index().rename(columns={'level_1':'source', 0:'flux'})
g = sns.relplot(x='time', y='flux', data=df, kind='line', col='source', col_wrap=4,
                height=4, facet_kws={'sharey': False, 'sharex': True})
_ = g.set_xticklabels(rotation=-45, ha='left')
_ = g.set_titles(col_template='{col_name}')
for ax, vname in zip(g.axes.flat, varlist + ['S_INTERIOR','SALT']):
    ax.set_ylabel('{}'.format(ds_tseries[vname].units))
    ax.autoscale(axis='x', tight=True)


df_fluxes['sum'] = df_fluxes.EVAP_F + df_fluxes.PREC_F + df_fluxes.ROFF_F + df_fluxes.MELT_F + df_fluxes.IOFF_F + df_fluxes.SALT_F + df_fluxes.FRAZIL
df = df_fluxes[['SFWF','sum']].stack().reset_index().rename(columns={'level_1':'source', 0:'flux'})
g = sns.relplot(x='time', y='flux', data=df, kind='line', hue='source', alpha=0.7, aspect=1.1)
_ = g.set_xticklabels(rotation=-45, ha='left')
g.ax.set_ylabel('{}'.format(ds_tseries['SFWF'].units))
g.ax.autoscale(axis='x', tight=True)


df_fluxes_monthly = df_fluxes.resample('M').mean()
df_fluxes_monthly['sum'] = (df_fluxes_monthly.EVAP_F + df_fluxes_monthly.PREC_F + df_fluxes_monthly.ROFF_F + df_fluxes_monthly.MELT_F + 
                            df_fluxes_monthly.IOFF_F + df_fluxes_monthly.SALT_F + df_fluxes_monthly.FRAZIL)
df = df_fluxes_monthly[['SFWF','sum']].stack().reset_index().rename(columns={'level_1':'source', 0:'flux'})
g = sns.relplot(x='time', y='flux', data=df, kind='line', hue='source', alpha=0.75, aspect=1.1)
_ = g.set_xticklabels(rotation=-45, ha='left')
g.ax.set_ylabel('{}'.format(ds_tseries['SFWF'].units))
g.ax.autoscale(axis='x', tight=True)

df_fluxes_monthly

Salinity diagnostics¶

Time series of salinity at grid point (somewhere in the middle of the North Atlantic)¶

Time series of fluxes at grid point¶

Time series of SFWF and sum of fluxes at grid point¶

Converted to monthly averages¶

	SFWF	EVAP_F	PREC_F	ROFF_F	MELT_F	IOFF_F	SALT_F	FRAZIL	IFRAC	S_INTERIOR	sum
time
1851-01-31	-6.533538e-06	-0.000063	0.000056	0.0	0.0	0.0	0.0	0.0	0.0	-3.554562e-11	-7.369134e-06
1851-02-28	1.075058e-05	-0.000075	0.000085	0.0	0.0	0.0	0.0	0.0	0.0	-2.783932e-11	9.808529e-06
1851-03-31	-3.773256e-05	-0.000075	0.000036	0.0	0.0	0.0	0.0	0.0	0.0	-2.070065e-11	-3.893238e-05
1851-04-30	1.612895e-05	-0.000034	0.000048	0.0	0.0	0.0	0.0	0.0	0.0	-1.505104e-11	1.475011e-05
1851-05-31	-1.580216e-05	-0.000038	0.000020	0.0	0.0	0.0	0.0	0.0	0.0	-2.159142e-11	-1.741568e-05
1851-06-30	4.520905e-06	-0.000020	0.000022	0.0	0.0	0.0	0.0	0.0	0.0	-2.058928e-11	2.520106e-06
1851-07-31	2.675369e-05	-0.000025	0.000050	0.0	0.0	0.0	0.0	0.0	0.0	6.836893e-12	2.527385e-05
1851-08-31	-2.081891e-05	-0.000038	0.000016	0.0	0.0	0.0	0.0	0.0	0.0	4.419851e-12	-2.202718e-05
1851-09-30	-7.867239e-06	-0.000046	0.000037	0.0	0.0	0.0	0.0	0.0	0.0	-1.437811e-11	-9.025152e-06
1851-10-31	3.248177e-07	-0.000064	0.000063	0.0	0.0	0.0	0.0	0.0	0.0	-1.696747e-11	-7.687340e-07
1851-11-30	2.078587e-05	-0.000050	0.000070	0.0	0.0	0.0	0.0	0.0	0.0	-9.618006e-12	1.999790e-05
1851-12-31	1.026176e-05	-0.000070	0.000080	0.0	0.0	0.0	0.0	0.0	0.0	-9.240487e-12	9.439122e-06