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# %% | |
import xarray as xr | |
import pandas as pd | |
# %% | |
df = ( | |
xr.open_mfdataset("C:/Users/matte/data/CPC/preci*") | |
.resample(time = "MS").sum() | |
.load() | |
) | |
# %% | |
soi = ( | |
pd.read_table("soi.txt", skiprows=3, | |
sep = " ", | |
nrows = 73) | |
.melt(id_vars = 'YEAR') | |
) | |
soi.index = pd.to_datetime([f'{y}-{m}-01' for y, m in zip(soi.YEAR, soi.variable)]) | |
soi = ( | |
soi | |
.sort_index() | |
.drop(columns = ['YEAR', 'variable']) | |
.squeeze() | |
) | |
soi.head() | |
# %% | |
# df = df.assign_coords(month = df.time.dt.month) | |
clim = df.groupby("time.month").mean("time") | |
anom = df.groupby("time.month") - clim | |
# %% | |
pd.infer_freq(soi.index) == pd.infer_freq(anom.time) | |
# %% | |
if len(soi) > len(anom.time): | |
soi = soi.loc[soi.index.isin(anom.time.values)] | |
# df = df.sel(time = df.time.isin(soi.index)) | |
anom = anom.sel(time = soi.index) | |
else: | |
anom = anom.sel(time = soi.index) | |
# %% | |
high = ( | |
anom | |
.sel(time = anom.time.isin(soi.loc[soi < -1.4].index)) | |
.mean(dim = 'time') | |
) | |
# %% | |
# %% | |
import matplotlib.pyplot as plt | |
import cartopy.crs as ccrs | |
fig, ax = plt.subplots(figsize=(10, 10), subplot_kw={'projection': ccrs.Robinson()}) | |
(high.precip | |
.where(high.lat > -60, drop = True) | |
.where(high.lat < 70, drop = True) | |
.plot(ax=ax, transform=ccrs.PlateCarree(), | |
vmin = -30, | |
vmax = 30, cmap = 'RdBu') | |
) | |
ax.coastlines(resolution='10m', color='black', linewidth=1) | |
# %% |
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