This lesson is being piloted (Beta version)

Introduction

Overview

Teaching: 5 min
Exercises: 10 min
Questions
  • What is ESMValTool?

  • Who are the people behind ESMValTool?

Objectives
  • Familiarize with ESMValTool

  • Synchronize expectations

What is ESMValTool?

This tutorial is a first introduction to ESMValTool. Before diving into the technical steps, let’s talk about what ESMValTool is all about.

What is ESMValTool?

What do you already know about, or expect from ESMValTool?

ESMValTool is…

EMSValTool is many things, but in this tutorial we will focus on the following traits:

A tool to analyse climate data

A collection of diagnostics for reproducible climate science

A community effort

A tool to analyse climate data

ESMValTool takes care of finding, opening, checking, fixing, concatenating, and preprocessing CMIP data and several other supported datasets.

The central component of ESMValTool that we will see in this tutorial is the recipe. Any ESMValTool recipe is basically a set of instructions to reproduce a certain result. The basic structure of a recipe is as follows:

An example recipe could look like this:

documentation:
  description: Example recipe
  authors:
    - lastname_firstname

datasets:
  - {dataset: HadGEM2-ES, project: CMIP5, exp: historical, mip: Amon, ensemble: r1i1p1, start_year: 1960, end_year: 2005}

preprocessors:
  global_mean:
    area_statistics:
      operator: mean

diagnostics:
  hockeystick_plot:
    description: plot of global mean temperature change
    variables:
      temperature:
        short_name: tas
        preprocessor: global_mean
    scripts: hockeystick.py

Understanding the different section of the recipe

Try to figure out the meaning of the different dataset keys. Hint: they can be found in the documentation of ESMValTool.

Solution

The keys are explained in the ESMValTool documentation, in the section The recipe format, under datasets

A collection of diagnostics for reproducible climate science

More than a tool, ESMValTool is a collection of publicly available recipes and diagnostic scripts. This makes it possible to easily reproduce important results.

Explore the available recipes

Go to the documentation of esmvaltool and explore the available recipes section. Which recipe(s) would you like to try?

A community effort

ESMValTool is built and maintained by an active community of scientists and software engineers. It is an open source project to which anyone can contribute. Many of the interactions take place on GitHub. Here, we briefly introduce you to some of the most important pages.

Meet ESMValGroup

Browse to github.com/ESMValGroup. This is our ‘organization’ GitHub page. Have a look around. How many collaborators are there? Do you know any of them?

Near the top of the page there are 2 pinned repositories: ESMValTool and ESMValCore. Visit each of the repositories. How many people have contributed to each of them? Can you also find out how many people have contributed to this tutorial?

Issues and pull requests

Go back to the repository pages of ESMValTool or ESMValCore. There are tabs for ‘issues’ and ‘pull requests’. You can use the labels to navigate them a bit more. How many open issues are about enhancements of ESMValTool? And how many bugs have been fixed in ESMValCore? There is also an ‘insights’ tab, where you can see a summary of recent activity. How many issues have been opened and closed in the past month?

Conclusion

This concludes the introduction of the tutorial. You now have a basic knowledge of ESMValTool and its community. The following episodes will walk you through the installation, configuration and running your first recipes.

Key Points

  • ESMValTool provides a reliable interface to analyse and evaluate climate data

  • A large collection of recipes and diagnostic scripts is already available

  • ESMValTool is built and maintained by an active community of scientists and developers