<jupyter_start><jupyter_text>Notebook to loop through the available datasets and check they open and load OK<jupyter_code>import sys
import os
sys.path.append('/home/jovyan/intake-aodn')
import intake_aodn
import intake
from intake_aodn.utils import get_local_cluster
client = get_local_cluster()
client<jupyter_output><empty_output><jupyter_text>SSTARS Climatology<jupyter_code>intake_aodn.cat.aodn_s3.SSTAARS_Daily_Climatology.to_dask()
intake_aodn.cat.aodn_s3.SSTAARS_Monthly_Climatology.to_dask()<jupyter_output><empty_output><jupyter_text>Fuse SST and ocean colour<jupyter_code>dsets = []
for entry in intake_aodn.cat.aodn_s3:
    if isinstance(intake_aodn.cat.aodn_s3[entry],intake_aodn.drivers.RefZarrStackSource):
        print(entry)
        ds=intake_aodn.cat.aodn_s3[entry](startdt='2021-01-01',
                                          enddt='2021-03-01',
                                          cropto=dict(latitude=-32.,longitude=115.,method='nearest')).read()
        dsets.append(ds)
    
import xarray as xr
ds = xr.merge(dsets,compat='override')
ds
import matplotlib.pyplot as plt
variables = ['sea_surface_temperature','chl_oc3','chl_gsm','K_490']
fig, axs = plt.subplots(len(variables),1,sharex=True,figsize=(8,10))
for i,v in enumerate(variables):
    ds[v].plot(ax=axs[i],marker='.')
fig.tight_layout()<jupyter_output><empty_output>
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