Question about Area-Averaging over Irregular Regions in CESM2 lonlat Grid

[Kitty]

I'm a bit confused about area averaging over irregular regions in CESM2's lonlat grid output. Since the grid is regular in longitude and latitude, do I still need to apply area weights (e.g., cos(lat)) when computing spatial means, or is this already accounted for? Could anyone clarify this for me?
Thank you for any useful information.

 

[islas]

You still need to apply a cos(lat) weighting when computing spatial means because the grid is not equal area - the regular longitude grid means that each grid box represents a smaller area the closer you get to the pole.

 

[Kitty]

You still need to apply a cos(lat) weighting when computing spatial means because the grid is not equal area - the regular longitude grid means that each grid box represents a smaller area the closer you get to the pole.

Thank you very much for your reply!
I understand that the `cos(lat)` approach is actually an estimated form of area weighting. If the latitudinal variation within the region is not very large, the difference between using `cos(lat)` weighting and simply averaging over grid points is generally small. I first want to ask: is it acceptable to directly compute the regional average by simply taking the mean over the number of grid points? Second, if area weighting is considered, is using only this estimated method (i.e., `cos(lat)`) sufficiently rigorous?
Could you please clarify this for me?

 

[islas]

I think using the cos(lat) weighting is sufficiently rigorous. Certainly the errors introduced by not applying the weighting when averaging over a small latitude range are smaller than when averaging over a large latitude range, but I'm not sure why you would want to make that approximation when you can just as well do it more accurately and apply the weighting. I see no reason to not apply the weighting even if you're averaging only over a small latitude range.

 

[Kitty]

I think using the cos(lat) weighting is sufficiently rigorous. Certainly the errors introduced by not applying the weighting when averaging over a small latitude range are smaller than when averaging over a large latitude range, but I'm not sure why you would want to make that approximation when you can just as well do it more accurately and apply the weighting. I see no reason to not apply the weighting even if you're averaging only over a small latitude range.

The point that I'm currently in doubt about is that the data I downloaded is planar data rather than spherical data. So I'm wondering if the values assigned to each grid point have already been processed? Secondly, in the literature I have already read, I did not find any explanation that the data undergoes weighting processing when used. Thank you very much for answering my questions.

 

[islas]

It has not been processed. It is the values on the model grid which is not an equal area grid. Each value represents the value at a given grid box and those grid boxes have different size.

 

[Kitty]

In fact, the GPP data of CESM2 that I downloaded was read using the cdo command, and it showed a total of 55296 grid points (288×192). There was a description stating "lon: 0 to 358.75 by 1.25 degrees east (circular); lat: -90 to 90 by 0.9424084 degrees north". Therefore, the grid point size here is consistent. Later, I obtained 0.5°×0.5° latitude-longitude grid data using the bilinear interpolation method. From this perspective, is the optimal solution for calculating the regional average not dependent on the number of regional grid points?

 

[islas]

It doesn't matter if you've regridded. You would still want to apply an area (cosine(lat)) weighting. If you're wanting to calculate the area sum then of course you would need to account for the different size of your grid box after regridding. But if you're wanting to calculate the area average, you would just do the same thing - average with a cos(lat) weighting applied.