Tutorials

We provide some tutorials that cover the main features of the PySPOD library. These are organized in the form of jupyter-notebooks, along with their plain python implementation.

In particular, we divided the tutorials in such a way that they cover different functionalities of the library and practical application areas.

Basic

Tutorial 1: 2D pressure fluctuations in a turbulent jet

This tutorial shows a simple 2D application to a turbulent jet. The variable studied is pressure.

Tutorial 2: 2D total precipitation from the ERA Interim dataset

This tutorial shows a 2D application to climate reanalysis data from the ERA Interim dataset. The variable studied is total precipitation, and the aim to capture the Madden-Julian Oscillation (MJO).

Climate

Tutorial: 2D Multivariate ENSO Index

This tutorial shows how to download data from an ECMWF reanalysis dataset (ERA20C), and use PySPOD to identify spatio-temporal coherent structured in multivariate 2D data. In particular, we seek to identify the multivariate ENSO index (MEI). The data is composed by the following monthly-averaged variables: mean sea level pressure (MSL), zonal component of the surface wind (U10), meridional component of the surface wind (V10), sea surface temperature (SST), 2-meter temperature (T2M), and total cloud cover (TCC), on a 2D longitude-latitude grid.

Tutorial: 3D Quasi-Bienniel Oscillation

This tutorial shows how to download data from an ECMWF reanalysis dataset (ERA20C), and use PySPOD to identify spatio-temporal coherent structured in univariate 3D data. In particular, we seek to identify the Quasi-Bienniel Oscillation (QBO). The data is composed by the monthly-averages of the zonal-mean zonal winds on a 3D longitude, latitude, pressure-levels grid.