rasterio - load multi-dimensional data
rasterio is really not the tool of choice for multi-dimensional netCDF data. It excels at handling 3D (band, y, x) data where band is some relatively short, unlabeled axis.
Look into xarray instead, which is built around the netCDF model and supports labeled axes and many dimensions, plus lazy loading, out-of-memory computation, plotting, indexing, ...
I just discovered rasterio for easy raster handling in Python. I am working with multi-dimensional climate data (4D and 5D). I was successful to open and read my 4D-NetCDF file with rasterio (lat: 180, lon: 361, time: 6, number: 51). However, the rasterio dataset object shows me three dimensions (180, 361, 306), whereby dimension 3 and 4 were combined. Can rasterio dataset objects only store 3 dimensions?
If yes, how does rasterio combine dimensions 3 and 4, to know what layer of the 306 resembles the original?
Thanks.