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
