Introduction

  • 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

Quickstart guide

  • 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

Installation

  • All the required packages can be installed using mamba.
  • You can find more information about installation in the documentation.

Configuration

  • 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.

Running your first recipe

  • 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

Conclusion of the basic tutorial

  • Individual mini-tutorials help work through a specific issue (not developed yet).
  • We are constantly improving this tutorial.

Writing your own recipe

  • 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.

Development and contribution

  • 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.

Writing your own diagnostic script

  • 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.

CMORization: adding new datasets to ESMValTool

  • 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.

Debugging

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