ESMValTool Tutorial: Glossary

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

The purpose of the quickstart guide is to enable a user of ESMValTool to run ESMValTool as quickly as possible without having to go through the whole tutorial

Use the module load command to load the ESMValTool environment, see the [Installation][lesson-installation] episode for more details and use esmvaltool --help to check the ESMValTool environment

Use esmvaltool config get_config_user to create the ESMValTool user configuration file

Use esmvaltool run <recipe>.yml to run a recipe

All the required packages can be installed using mamba.

You can find more information about installation in the documentation.

The config-user.yml tells ESMValTool where to find input data.

output_dir defines the destination directory.

rootpath defines the root path of the data.

drs defines the directory structure of the data.

ESMValTool recipes work ‘out of the box’ (if input data is available)

There are strong links between the recipe, log file, and output folders

Recipes can easily be modified to re-use existing code for your own use case

Individual mini-tutorials help work through a specific issue (not developed yet).

We are constantly improving this tutorial.

A recipe can work with different preprocessors at the same time.

The setting additional_datasets can be used to add a different dataset.

Variable groups are useful for defining different settings for different variables.

Multiple ensemble members and experiments can be analysed in a single recipe through concatenation.

A development installation is needed if you want to incorporate your code into ESMValTool.

Contributions include adding a new or improved script or helping with a review process.

There are several tools to help improve the quality of your code.

It is possible to run tests on your machine.

You can preview documentation pages locally.

ESMValTool provides helper functions to interface a Python diagnostic script with preprocessor output.

Existing diagnostics can be used as templates and modified to write new diagnostics.

Helper functions can be imported from esmvaltool.diag_scripts.shared and used in your own diagnostic script.

CMORizers are dataset-specific scripts that can be run once to generate CMOR-compliant data.

ESMValTool comes with a set of CMORizers readily available, but you can also add your own.

There are three different kinds of log files: main_log.txt, and main_log_debug.txt and log.txt.