Combine ERA5 and ERA5T data

Requesting cutout data spanning recent (ERA5T)
and data older than ~3 months (ERA5) results in an
additional dimension in `cutout.data`, called `expver`,
which `atlite` currently cannot handle gracefully.

This change collapses the two dimensions into a single dimension.

See discussion in PyPSA#190

atlite/data.py

@@ -108,7 +108,7 @@ def wrapper(*args, **kwargs):
 
 
 @maybe_remove_tmpdir
-def cutout_prepare(cutout, features=None, tmpdir=None, overwrite=False):
+def cutout_prepare(cutout, features=None, tmpdir=None, overwrite=False, flatten_expver=True):
     """
     Prepare all or a selection of features in a cutout.
 
@@ -133,6 +133,11 @@ def cutout_prepare(cutout, features=None, tmpdir=None, overwrite=False):
     overwrite : bool, optional
         Whether to overwrite variables which are already included in the
         cutout. The default is False.
+    flatten_expver: bool, default True
+        If true, data for time periods spanning both ERA5 and ERA5T data
+        will be combined into a single dimension.
+        See https://confluence.ecmwf.int/pages/viewpage.action?pageId=173385064
+        for details.
 
     Returns
     -------
@@ -169,6 +174,11 @@ def cutout_prepare(cutout, features=None, tmpdir=None, overwrite=False):
         attrs.update(ds.attrs)
         ds = cutout.data.merge(ds[missing_vars.values]).assign_attrs(**attrs)
 
+        # Combine ERA5 and ERA5T data into a single dimension.
+        # See https://github.com/PyPSA/atlite/issues/190
+        if flatten_expver and 'expver' in ds.dims.mapping.keys():
+            ds = ds.sel(expver=1).combine_first(ds.sel(expver=5))
+
         # write data to tmp file, copy it to original data, this is much safer
         # than appending variables
         directory, filename = os.path.split(str(cutout.path))