Regrid SWOT data to regular grid

[nilsleh]

Dear SWOT-community,

I downloaded SWOT L3 data from Aviso for a research project. I am new to SWOT data and these sort of data sources in general, so apologies in advance.

swot = xr.open_dataset("SWOT_L3_LR_SSH_Basic_001_584_20230811T012726_20230811T021852_v1.0.nc")

However, I would like to match the SWOT data with other data products that come in a regular grid like (time, lat, lon) format, like so:

I have done some searching with respect to possible tools like:

• xESMF
• pygeo-pyinterp
• HarmonyPy
• and likely others

But was wondering if you have a recommended workflow or possibly even a suggestion on how to do this? The SWOT data wouldn't need to be in the same resolution as the other data sources, but should be regridded to be in lat/lon format. Thank you for any hints, suggestions, and possible solutions. Cheers.

[iuryt]

This is an old post so you probably have found a workaround for that. An easy way to do that is to interpolate your gridded data to SWOT, since you have the coordinate longitude, latitude defined as dimensions.

gridded.interp(longitude=swot.longitude, latitude=swot.latitude)

I hope that helps.