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Recently, I’ve started using rioxarray to read NetCDF data into xarray format. If you’re not familiar with the xarray python package it’s basically a wrapper (for lack of a better term) around numpy arrays that allows metadata to be included with the arrays (more on this later with an example).
Gridded, spatial data are commonly stored in NetCDF files. This is especially true for climate data. NetCDF files offer more flexibility and transparency than some traditional raster formats by supporting multiple variables and detailed metadata. Because of the metadata and file structure NetCDF files can be more difficult to access than traditional raster formats. This…
Important information describing the data contained in netCDF files is embedded directly in the netCDF file. Accessing and reading of this information (i.e. metadata) can help you automate tasks, debug code, and validate results easily. This tutorial covers how to access information describing the metadata, dimensions, and variables contained in a netCDF file. For the…
Many geographic data are store in netCDF format. This is especially true for climate data. Interacting with netCDF data files is an important skill for any geographer, physical scientist or data scientist to have. This tutorial will get you started using the netCDF4 Python package to read netCDF data. First, you’ll need to install netCDF4….
