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[python #SWP-244115]: metpy cross-section issue


So what you'll need is to create a fully CF-compliant set of projection 
information (http://cfconventions.org). In this case, since you're working in 
latitude/longitude space, you should:

1. Add a variable (can be called anything, like "LatLonProjection") to the 
Dataset. At a minimum this variable needs to have an attribute 
"grid_mapping_name" with a "latitude_longitude".
2. Add an attribute to all of your data fields (e.g. "potential temperature", 
"u wind") called "grid_mapping" with a value equal to the name of the variable 
you created in (1) (e.g. "LatLonProjection").

Then you should be able to do e.g. dataset.metpy.parse_cf() or 
dataset.metpy.parse_cf('u wind').

Unfortunately, this won't work right now:

arr = dataset['potential temperature']
arr.metpy.crs = ccrs.LambertConformal()

because the `crs` attribute is read-only. Improvements to the cross-section 
functionality to make it easier to work with other data sets is being tracked 
in: https://github.com/Unidata/MetPy/issues/1004


> I have some WRF output in sigma coordinates, with the lat-lon grid in 2 
> dimensional arrays. After converting the output into isobaric coordinates, I 
> want to create a new xarray with the output so I can use metpy to plot a 
> cross-section. However, I am getting 2 errors:
> AttributeError: 'Dataset' object has no attribute 'crs'
> AttributeError: cannot set attribute 'crs' on a 'Dataset' object. Use 
> __setitem__ style assignment (e.g., `ds['name'] = ...`) instead to assign 
> variables.
> How do I set up my data to be compatible with the metpy cross-section 
> feature? I looked into Issue 949 and Issue 1004, but I haven't been able to 
> find a solution.
> Attached is my code. The WRF output is too large to send, but it is a 
> standard output file in netCDF format.

Ticket Details
Ticket ID: SWP-244115
Department: Support Python
Priority: Low
Status: Closed
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