def PM_ds_control3d(): ds = open_dataset('MPI-control-3D') ds = ds.isel(x=slice(0, 5), y=slice(145, 150)) t = list(np.arange(ds.time.size)) ds = ds.isel(time=t * 6) ds['time'] = np.arange(3000, 3000 + ds.time.size) return ds
def PM_da_control3d(): da = open_dataset('MPI-control-3D') da = da.isel(x=slice(0, 5), y=slice(145, 150)) # fix to span 300yr control t = list(np.arange(da.time.size)) da = da.isel(time=t * 6) da['time'] = np.arange(3000, 3000 + da.time.size) return da['tos']
def PM_ds_control1d(): ds = open_dataset('MPI-control-1D') return ds
def PM_ds_ds1d(): ds = open_dataset('MPI-PM-DP-1D') return ds
def PM_da_control1d(): da = open_dataset('MPI-control-1D') da = da['tos'] return da
def PM_da_ds1d(): da = open_dataset('MPI-PM-DP-1D') da = da['tos'] return da
def PM_ds_ds3d(): ds = open_dataset('MPI-PM-DP-3D') ds = ds.isel(x=slice(0, 5), y=slice(145, 150)) return ds
def PM_da_ds3d(): da = open_dataset('MPI-PM-DP-3D') # Box in South Atlantic with no NaNs. da = da.isel(x=slice(0, 5), y=slice(145, 150)) return da['tos']
def uninitialized(): da = open_dataset('CESM-LE')['SST'] # create fake ensemble data (i.e., multiple members) da = xr.concat([da] * 10, 'member') da['member'] = np.arange(10) return da
def reconstruction(): da = open_dataset('FOSI-SST') # same timeframe as DPLE da = da.sel(time=slice(1955, 2015)) da = da['SST'] return da
def observations(): da = open_dataset('ERSST') return da
def initialized(): da = open_dataset('CESM-DP-SST') da = da.sel(init=slice(1955, 2015)) return da