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I'm loading a NetCDF file (ERA5 surface temperatures), then I mask the data using country shapes, and finally generate a plot using geoviews. For the unmasked data everything works as intended. As soon as I clip using rioxarray, half the globe goes missing. In detail:

# Read all relevant data:
data0 = xr.open_dataset("./data/COPERNICUS/adaptor.mars.internal-1621870453.0792851-5880-10-bd60c7b4-8e84-4d2a-acfb-d2cc442d24e1.nc")
sf = geopandas.read_file("./data/NATURAL_EARTH/ne_50m_admin_0_countries.shp")

# Filter and set CRS:
dataslice = data0.load().where((data0.time.dt.strftime("%Y") == "2020") & (data0.expver == 1)
                                  , drop=True).sum("expver").resample({"time": "Y"}).mean()
dataslice.rio.set_spatial_dims(x_dim="longitude", y_dim="latitude", inplace=True)
dataslice.rio.write_crs("EPSG:4326", inplace=True)

Plotting this with geoviews looks ok:

dataset = gv.Dataset(dataslice, ['longitude', 'latitude', 'time'], 't2m')
images = dataset_clipped.to(gv.Image)
images.opts(cmap='viridis', colorbar=True, width=900, height=600, 
            projection=crs.PlateCarree())

enter image description here

Now I want to clip the data using the shapefile and plot the clipped data:

clipped = dataslice.rio.clip(sf.geometry, drop=False)
dataset_clipped = gv.Dataset(clipped, ['longitude', 'latitude', 'time'], 't2m')
images_clipped = dataset_clipped.to(gv.Image)
images_clipped.opts(cmap='viridis', colorbar=True, width=900, height=600, 
                    projection=crs.PlateCarree())

While the data is clipped by the landmass as intended, all of the Western hemisphere is gone as well.

enter image description here

Remarks:

  • This does not depend on the projection parameter of geoviews.
  • Both the gridded data and the shapefile have CRS EPSG:4326.
  • The Shapefile is complete:

enter image description here

Questions:

  • What is going wrong?
  • Why do we need to set the CRS anyway? Both the xarray and the geojsons are just tuples (lat,lon,value) and (lat,lon), respectively. Yet dataslice.rio.clip raises a MissingCRS exception if dataslice.rio.write_crs is skipped.
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  • Given that the clipping boundary appears to go through Greenwich, England (0 deg meridian), this looks like an issue with coordinates wrapping around at 0. You may be able to avoid it by adding 360 to the coordinates at some step, but if you can make a reproducible test case depending on open datasets then please file an issue on GeoViews so we can figure out where this is happening.
    – James A. Bednar
    Commented May 29, 2021 at 14:49
  • Many thanks for the comment but as it turns out it's not geoviews related.
    – mcsoini
    Commented May 29, 2021 at 19:29

1 Answer 1

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You likely need to adjust the longitude values to -180,180 range from 0-360. See: Clip global data by polygon using rioxarray fails (off by 180 longitude)

ds = ds.assign_coords(x=(((ds.x + 180) % 360) - 180)).sortby('x')
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  • Exactly what I was hoping for: Known problem, easy fix.
    – mcsoini
    Commented May 29, 2021 at 19:27

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