SMAP Python Notebooks

Summary

In this set of three tutorials we demonstrate how to search for, download and plot SMAP data. Tutorial 1 demonstrates how to search for and download SMAP data using the earthaccess library. The second tutorial demonstrates how to read in and plot the data downloaded in Tutorial 1. And Tutorial 3 provides information on the surface quality and retrieval quality flags.

We use the SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 8 data set as an example.

NOTE these notebooks are an updated version of the notebooks orginially published in this repo. The notebooks are based on notebooks originally provided to NSIDC by Adam Purdy. Jennifer Roebuck of NSIDC applied the following updates:

Used earthaccess instead of requests for authentication, searching for and downloading the data. This reduced the code to just a few lines.
Used a more recent version of SPL3SMP (version 8).
Replaced the use of Basemap with cartopy.
Updated the surface quality flag names to reflect the ones used in the latest version.
Minor text edits to provide additional information where necessary.
Moved the tutorials to the standard NSIDC tutorials template.

Set up

To run the notebook provided in this folder, please see the NSIDC-Data-Tutorials repository readme for instructions on several ways (using Binder, Docker, or Conda) to do this.

Key Learning Objectives

Use the earthaccess library to search for and download SMAP data.
Use the h5py library to read in the HDF5 files and plot the variables on a map using cartopy and matplotlib.
Understand the surface quality and retrieval quality flag options.