# ## Plot $\Delta$ T and ERF whole period +/- 1 standard deviation over the models
# %%
scenarios_fl=['ssp119',
'ssp126',
'ssp245',
'ssp370',
'ssp370-lowNTCF-aerchemmip',
'ssp585']
# %%
from ar6_ch6_rcmipfigs.utils.plot import get_scenario_ls_dic, get_scenario_c_dic
lsdic = get_scenario_ls_dic()#get_ls_dic(ds_DT[climatemodel].values)
s_y = '2021'
e_y = '2100'
cdic = get_scenario_c_dic()
alpha = 0.3
for var in variables_erf_comp:
fig, axs = plt.subplots(1, 2, figsize=[20, 6])
for scn in scenarios_fl:#) - {'historical'}):
first = True
_da1 = ds_DT[new_varname(var, name_deltaT)].sel(scenario=scn)
_da2 = ds_DT[var].sel(scenario=scn)
for _da, ax in zip([_da1, _da2], axs):
_pl_da = _da.mean(climatemodel)
_pl_da.plot(ax=ax, c=cdic[scn], label=scn, linestyle = lsdic[scn])
_std = _da.std(climatemodel)
ax.fill_between(_pl_da['time'].values, _pl_da - _std, _pl_da + _std, alpha=alpha,
color=cdic[scn], label='_nolegen_')
#for cm in _da[climatemodel].values:
# _da.sel(climatemodel=cm).plot(ax=ax, color=cdic[scn], label='_nolabel_')
def fix_ax(_ax):
_ax.spines['right'].set_visible(False)
_ax.spines['top'].set_visible(False)
return
def fign_dt(_var, _s_y, _e_y):
return '%s_refy%s_fy%s.png' % (_var.replace(' ', '_').replace(
'|', '-'), _s_y, _e_y)
# %% [markdown]
# ### Functions to plot uncertainty
# %%
cdic = get_scenario_c_dic()
cdic: dict
lsdic = get_scenario_ls_dic() # get_ls_dic(ds_DT[climatemodel].values)
def add_uncertainty_bar(
ax,
var,
end_y=last_y,
s_y=ref_year,
to='p95-p50',
frm='p05-p50',
linewidth=4,
i_plus=1.5,
alpha=1,
):