[python #LLO-424423]: problem with metpy importing modules

Greetings!

Apologies for the delayed response.

Since you're working with a DataArray, you don't even need to manually 
calculate the deltas, but instead you can do this with a single call to 
gradient:

  dlon, dlat = mpcalc.gradient(temps, axes=['longitude', 'latitude'])

The fact that the coordinates are attached to temps lets the function handle 
all the coordinate manipulation for you.

Hope this helps!

Ryan

> I have another issue. I am trying to use the gradient function on a 3D xarray 
> DataSet (lat,lon,time)
> 
> <xarray.Dataset>
> Dimensions:    (latitude: 141, longitude: 401, time: 16)
> Coordinates:
> * latitude   (latitude) float32 20.0 20.25 20.5 20.75 ... 54.5 54.75 55.0
> * longitude  (longitude) float32 140.0 140.2 140.5 140.8 ... 239.5 239.8 240.0
> * time       (time) datetime64[ns] 2013-01-13 ... 2013-01-16T18:00:00
> Data variables:
> t          (time, latitude, longitude) float32 289.4 289.5 ... 275.1 275.5
> Attributes:
> Conventions:  CF-1.6
> history:      2022-06-06 12:05:32 GMT by grib_to_netcdf-2.24.3: /opt/ecmw…
> 
> 
> I have calculated the delays for longitude and latitude:
> 
> deltas=mpcalc.lat_lon_grid_deltas(DS.longitude,DS.latitude)
> 
> I now wish to calculate the gradients along latitude and longitude for each 
> tilmestep.
> 
> I can do this for a single tilmestep using:
> 
> temps=DS.t[9,:,:]
> gradients=mpcalc.gradient(temps,deltas=(deltas[1],deltas[0]))
> 
> however I cannot get it to work on the dataset with multiple time steps. I 
> could use a loop but assume it is something to do with using axes in the 
> gradient function. I have tried both on the original dataset and on the 
> extracted DataArray but cannot achieve any success. What should I add to the 
> gradient command to match the deltas with the longitude and latitude axes 
> only?
> 


Ticket Details
===================
Ticket ID: LLO-424423
Department: Support Python
Priority: Low
Status: Closed
===================
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