Ryan May
Actually, it looks like `compare_image_to_baseline` duplicates the entire 3-line block of setting up the result image, which doesn't seem necessary at all?
I like option 1 above. I haven't reviewed the implementation in detail, but I like the concept in general.
Seems fine to me.
I would suggest then, that some labels for those sliders would go a long way towards making that clearer--I had no idea whatsoever that's what the different sliders were for....
I can confirm this workflow worked without any problems for the most recent MetPy release.
You can see the `dataset.xml` document that includes all of the variables by changing the URL from `dataset.html` to `dataset.xml`, as in: https://thredds.ucar.edu/thredds/ncss/grid/grib/NCEP/GFS/Global_0p25deg_ana/GFS_Global_0p25deg_ana_20220815_1800.grib2/dataset.xml This is also accessible off the NCSS...
So while I think the original query will always have problems due to a mix of surface and profile variables, changing to request `'v-component_of_wind_height_above_ground', 'Liquid_Volumetric_Soil_Moisture_non_Frozen_depth_below_surface_layer'`, which have dimensions of `time=373,...
Right, try doing the request for `Low_cloud_cover_low_cloud_Mixed_intervals_Average` separately. The problem is that the surface fields result in a timeseries return, while the other ends up with a profile timeseries return....
Looks like a bug to me. Tracking this down could really use a simplified case or direct access to the data to understand what's going on.
It's tricky because Natural Earth doesn't really [document](https://www.naturalearthdata.com/downloads/10m-cultural-vectors/) those names either. You have to go to the download page and look at the URLs to pull out the name. A...