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When making the interpolation, ClimaAnalysis uses something along the lines of Intp.interpolate(dims_tuple, data, Intp.Gridded(Intp.Linear())). This causes issues with resampling along the longitude dimension as the boundary condition is Intp.Periodic() as oppose to Intp.Periodic(OnCell()). This means that anything beyond the last point in longitude dimension is effectively ignored and the value of the first point in the longitude dimension is used.
The solution is not as simple as using Intp.Periodic(OnCell()) instead of Intp.Periodic() in that part of the code because the grid is not necessarily uniform if there are more than 2 dimensions. For example, you might want to resample with longitude, latitude, and time as dimensions. It is unclear to me how to approach this issue.
The text was updated successfully, but these errors were encountered:
When making the interpolation, ClimaAnalysis uses something along the lines of
Intp.interpolate(dims_tuple, data, Intp.Gridded(Intp.Linear()))
. This causes issues with resampling along the longitude dimension as the boundary condition isIntp.Periodic()
as oppose toIntp.Periodic(OnCell())
. This means that anything beyond the last point in longitude dimension is effectively ignored and the value of the first point in the longitude dimension is used.The solution is not as simple as using
Intp.Periodic(OnCell())
instead ofIntp.Periodic()
in that part of the code because the grid is not necessarily uniform if there are more than 2 dimensions. For example, you might want to resample with longitude, latitude, and time as dimensions. It is unclear to me how to approach this issue.The text was updated successfully, but these errors were encountered: