issue_comments: 197601132

Hi @jhamman , this is close to how I would've done it, but I am maybe not the most qualified (probably the gis specialists from rasterio would be more helpful). But still, a couple of remarks from my side: - I wouldn't necessarily do the try_to_get_latlon_coords systematically. When the raster coords are lat-lon, the new coords are redundant. And when the coords are x-y, the lat-lon info are only partly useful (since the grid will be unstructured in lat-lon). Furthermore, I am not sure if +init=EPSG:4326 is the only lat-lon proj available (there are surely more - at least if you leave the wgs-84 area) - as mentioned by perrygeo in your rasterio post, the data model of geotiffs is not always clear. The pixel coordinates are very likely to be at the top-left corner of the pixel (as I assume in my small salem library). Most netcdf datasets we are using in the meteo/climate community are pixel-centered. I don't know if this is something that xarray wants to consider, but this becomes important if you want to make accurate projections. (in practice, the two concepts are equivalent for most applications, but you have to know what is what: in my small library I called those representations center_grid and corner_grid: https://github.com/fmaussion/salem/blob/master/salem/gis.py#L101 )

To your questions: 1. I agree that returning a dataset is a good idea. I don't know if raster is a good name, but I have no other idea right now 2. I don't know. The projection was always enough for me :flushed: