ls
ls ..
da0 = xr.open_dataarray('../TasJJA_AM4urban_wasteCool_0urban_amip_5ens_1870-2020.nc')
da0
da = xr.open_dataarray('../TasJJA_AM4urban_wasteCool_amip_5ens_1870-2020.nc')
da
daNA = xr.open_dataarray('../TasJJA_AM4urban_wasteCool_urbanNAonly_amip_5ens_1870-2020.nc')
daAS = xr.open_dataarray('../TasJJA_AM4urban_wasteCool_urbanASonly_amip_5ens_1870-2020.nc')
(da.mean('en') - da0.mean('en')).plot(label='urbanGlobal')
(da.mean('en') - da0.mean('en')).sel(years=slice(1901, None)).plot(label='urbanGlobal', marker='o', fillstyle='none')
(da.mean('en') - da0.mean('en')).sel(year=slice(1901, None)).plot(label='urbanGlobal', marker='o', fillstyle='none')
(daNA.mean('en') - da0.mean('en')).sel(year=slice(1901, None)).plot(label='urbanNA', marker='o', fillstyle='none')
(daAS.mean('en') - da0.mean('en')).sel(year=slice(1901, None)).plot(label='urbanAS', marker='o', fillstyle='none')
plt.legend()
import xfilter
figure(); (da.mean('en') - da0.mean('en')).filter(1/10, dim='year').sel(year=slice(1901, None)).plot(label='urbanGlobal')
figure(); (da.mean('en') - da0.mean('en')).filter.lowpass(1/10, dim='year').sel(year=slice(1901, None)).plot(label='urbanGlobal')
figure(); (da.mean('en') - da0.mean('en')).filter.lowpass(1/10, dim='year').sel(year=slice(1901, None)).plot(label='urbanGlobal', marker='o', fillstyle='none')
(daNA.mean('en') - da0.mean('en')).filter.lowpass(1/10, dim='year').sel(year=slice(1901, None)).plot(label='urbanNA', marker='o', fillstyle='none')
(daAS.mean('en') - da0.mean('en')).filter.lowpass(1/10, dim='year').sel(year=slice(1901, None)).plot(label='urbanAS', marker='o', fillstyle='none')
plt.legend()
plt.axhline(0, color='gray', ls='--')
plt.axvline(2014, color='gray', ls='--')
plt.axvline(1990, color='gray', ls='--')
plt.axvline(1976, color='gray', ls='--')
ls
%hist -f wytmep.txt