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A recent use case: when writing the ERA5 data component, @gantian127 found that the dataset uses 5 dimensions: three spatial + time + an ensemble number.
Building on this. we could swap the dim parameter for a name parameter, which might be more readable (e.g., name = "x" or name = "x1" for the first coordinate dimension).
Currently, to obtain the nodes of rectilinear, structured quadrilateral, and unstructured grids, the BMI has functions
representing grids of up to three dimensions.
The BMI should also support grids of these types with rank greater than three.
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