It can be easily installed with the following command. Rioxarray is available from Anaconda’s conda-forge channel. For this tutorial, I created a fresh conda environment ( conda create -name myenv python=3.9) then installed the required packages. This is especially true if you are newer to Python. I recommend using Anaconda (or miniconda) for your Python environment and package management.

Once downloaded, make note of the file location so you can read it into your Python environment later. You can download the same data I’m using at the following link. Download NetCDF Dataįor this example, I’ll be using 2020 daily precipitation data from the GRIDMET dataset. You’ll learn more about this as we go through some examples. With NetCDF, the spatial structure of the data can be defined once, and then new data layers are added to the existing spatial definition. Datasets of climatic data, like precipitation and temperature, usually have repeat values at each recorded location at equally spaced time intervals. The NetCDF file format lends itself to climate data especially well. This type of format is very powerful because it provides detailed documentation for the data and can store large volumes of data in an easily accessible way. NetCDF is based on the HDF5 file format, which allows for the segregation of metadata and different data types in the same file. Those just getting started with NetCDF may find it a slightly confusing data format. While the netCDF4 package is a complete, powerful package for interesting with NetCDF data, rioxarray provides more simple and concise data access that will be preferred by most users. 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).

Recently, I’ve started using rioxarray to read NetCDF data into xarray format. In the initial article, I used the netCDF4 Python package to access data from NetCDF files. However, since then, I’ve found an even better way to read NetCDF data with Python. This article still receives many views on my website and on Medium.

A few months ago I wrote an article about reading NetCDF data with Python.

Read cdf files python