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| import xarray as xr | |
| import matplotlib.pyplot as plt | |
| ds=xr.open_mfdataset('/discover/nobackup/sakella/m6_test/holding/geosgcm_surf/*/m6_test.geosgcm_surf.*_1200z.nc4') | |
| frice = ds['FRSEAICE'] | |
| frocn = ds['FROCEAN'] | |
| ts = ds['TS'] | |
| t2m = ds['T2M'] | |
| ts.load() # force load into memory | |
| #ts.compute() # creates a new array without changing ts itself. | |
| #ds.resample(...) # to get monthly means | |
| #ds_monthly=ds.resample(time='1M').mean('time') # resample to monthly means to make it faster | |
| ts.sel(lon=-178.0,lat=78.0).plot() # this will be slow unless loaded into memory | |
| plt.show() | |
| ts.sel( lon=slice(-170,178), lat=slice(78,80)).mean().plot() # makes a histogram | |
| plt.show() | |
| ts.sel( lon=slice(-170,178), lat=slice(78,80)).mean( ('lon', 'lat')).plot() # geometric box averaged time series | |
| plt.show | |
| # | |
| frocn.load() | |
| frice.load() | |
| t2m.load() | |
| plt.figure( figsize=(12,8)) | |
| plt.subplot(211), ts.sel( lon=slice(-170,178), lat=slice(78,80)).mean( ('lon', 'lat')).plot(ls=':', color='r', label='TS') | |
| plt.subplot(211), t2m.sel( lon=slice(-170,178), lat=slice(78,80)).mean( ('lon', 'lat')).plot(ls='-', color='b', label='T2M') | |
| plt.legend() | |
| plt.title('box av lon: [-170, 178], lat: [78, 80N]') | |
| plt.xlabel(' ') | |
| plt.ylabel('[K]') | |
| plt.subplot(212), frocn.sel( lon=slice(-170,178), lat=slice(78,80)).mean( ('lon', 'lat')).plot(ls=':', color='k', label='fr Ocn') | |
| plt.subplot(212), frice.sel( lon=slice(-170,178), lat=slice(78,80)).mean( ('lon', 'lat')).plot(ls='-', color='b', label='fr Ice') | |
| plt.legend() | |
| #plt.ylabel('[1]') | |
| plt.savefig('test1.png', dpi=100) | |
| # |
Author
sanAkel
commented
Jul 31, 2020
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