Regridding reanalysis to n48 results in too cold climatology


I’m trying to regrid an ERA-Interim reanalysis climatology (lat: 241 x lon: 480) to a N48 grid (latitude: 73 x longitude: 96). My problem is that the the climatology comes out ~0.5° too cold on the N48 grid.

The climatology is multi-year 6-hourly means for T,U,V from ERA-Interim (lat: 241 x lon: 480). I have uploaded a notebook here which produces this figure:


The notebook shows the two regridding methods (bilinear, conservative) of the xesmf python package. I’ve also tried using iris and cdo functions for regridding, all with the same result.
The background for this is that I’m using this N48 data as forcing files for the UM. I’ve also calculated the climatology on a N96 grid (latitude: 144 x longitude: 192) which didn’t show this shift in temperature.

Anyone know what I’m missing here? Thanks for any comments / suggestions!

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Hi @pia welcome to the Forum. Thanks for sharing your notebook, and making it easy to read.

I think the problem is you’re not weighting by the grid cell area when taking your global (spatial) mean for the final plot and comparison.

See here for an example of how to do this easily using xarray.weighted

Thanks @Aidan , I was trying to help @pia out with this, but I figured there was a piece of the puzzle I was missing. Weighting by grid cell area makes perfect sense. Given Pia is using standard global grids (N96 and N48), are there a standard set of weights that can be used to avoid any potential errors in attempting to construct them manually?

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Hi @pia I’ve had a chance to revisit this a bit today based on @Aidan’s comment. I’ve come up with this notebook which seems to have had the desired effect on the means. The hires and lowres means now match, and they’ve increased to a more reasonable 13-17 degrees C now that the polar grid cells are weighted lower.

I acknowledge I’ve probably done this in the least practical way possible, but I’m hoping Cunningham’s Law prevails here and someone else has a better answer.


Thank you both for your effort! I also tested it in my notebook and I get a climatology that agrees for the different grids! Thanks

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Given there doesn’t seem to be any grid cell area information available what you’ve done seems a very practical and straightforward solution. That Iris capability to guess grid bounds is very useful! I’d not seen that before.