Extrapolation of results beyond the heating source about xinvert HOT 9 CLOSED

Hi thanks for your interests in this. So you don't use xarray? You can install it and load your netcdf file by dset = xarray.open_dataset('data.nc') and then quickly peek the dataset by dset.u.plot(). Also, the results returned by xinvert are also xarray object and can be plotted simply as u_gill.plot()

That is not the key point. Could you please show that if your heating source is a 2D global field? If yes, the returned data will be a 2D global field. Note that do not fill the region where heat source = 0 with nan, because nan is used as land-sea mask by default.

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Hi, many thanks for your answer. It seems that the problem has to do with the definition of longitudes and latitudes of the heating source and the region for which h1, v1 and u1 are estimated. Can you please clarify what are your:

lat, lon = xr.broadcast(ds.lat, ds.lon) for the heating source, and
lat, lon = xr.broadcast(u1.lat, u1.lon) for the impacted region

Many thanks in advance.

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Hi, I guess you read my notebook about Gill model at here. Now I've change a little of the notebook so that the heat source Q is a global field, and so are the h1, u1 and v1. You can follow this example because this idealized test does not need any data files.

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Sorry, I cannot see your figure. Could you post it as a link?

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This is the figure:

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Well, I see... The original Gill model does not take into account topographic effects. But I guess one can modify it to parameterize their effect into the model. As xinvert support topographic (see oceanic case), maybe you can prescribe the Andes as a patch of NaN and set kwarg undef=np.nan. Then you can get the flow stopped at Andes.

Also, the effects of the cooling over the cold tongue is not clear. You can invert the flow separately for the cooling source only. Generally, the flow pattern is NOT totally unrealistic to me. It still fits Gill's classical pattern in the tropics.

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Many thanks for your insights.

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