Running your first recipe

Overview

Teaching: 15 min
Exercises: 15 min
Compatibility: ESMValTool v2.14.0

Questions

How to run a recipe?

What happens when I run a recipe?

Objectives

Run an existing ESMValTool recipe

Examine the log information

Navigate the output created by ESMValTool

Make small adjustments to an existing recipe

This episode describes how ESMValTool recipes work, how to run a recipe and how to explore the recipe output. By the end of this episode, you should be able to run your first recipe, look at the recipe output, and make small modifications.

Running an existing recipe

The recipe format has briefly been introduced in the Introduction episode. To see all the recipes that are shipped with ESMValTool, type

esmvaltool recipes list

We will start by running examples/recipe_python.yml

esmvaltool run examples/recipe_python.yml

or if you have the user configuration file in your current directory then

esmvaltool run --config_dir . examples/recipe_python.yml

If everything is okay, you should see that ESMValTool is printing a lot of output to the command line. The final message should be “Run was successful”. The exact output varies depending on your machine, but it should look something like the example log output below.

Output


2026-04-02 12:02:54,972 UTC [3235444] INFO    
______________________________________________________________________
          _____ ____  __  ____     __    _ _____           _
         | ____/ ___||  \/  \ \   / /_ _| |_   _|__   ___ | |
         |  _| \___ \| |\/| |\ \ / / _` | | | |/ _ \ / _ \| |
         | |___ ___) | |  | | \ V / (_| | | | | (_) | (_) | |
         |_____|____/|_|  |_|  \_/ \__,_|_| |_|\___/ \___/|_|
______________________________________________________________________

Earth System Model Evaluation Tool

A community tool for the evaluation of Earth system models.

https://esmvaltool.org

The Earth System Model Evaluation Tool (ESMValTool) is a community
diagnostics and performance metrics tool for the evaluation of Earth
System Models (ESMs) that allows for routine comparison of single or
multiple models, either against predecessor versions or against
observations.

Tutorial: https://tutorial.esmvaltool.org
Documentation: https://docs.esmvaltool.org
Contact: esmvaltool-dev@listserv.dfn.de

If you find this software useful for your research, please cite it using
https://doi.org/10.5281/zenodo.3387139 for ESMValCore or
https://doi.org/10.5281/zenodo.3401363 for ESMValTool or
any of the reference papers listed at https://esmvaltool.org/references/.

Have fun!

2026-04-02 12:02:54,973 UTC [3235444] INFO    Package versions
2026-04-02 12:02:54,973 UTC [3235444] INFO    ----------------
2026-04-02 12:02:54,973 UTC [3235444] INFO    ESMValCore: 2.15.0.dev9+g412767341
2026-04-02 12:02:54,973 UTC [3235444] INFO    ESMValTool: 2.15.0.dev4+g74d7837f0
2026-04-02 12:02:54,973 UTC [3235444] INFO    ----------------
2026-04-02 12:02:54,974 UTC [3235444] INFO    Reading configuration files from:
/home/b/username/ESMValTool/ESMValCore/esmvalcore/config/configurations/defaults (defaults)
/home/b/username/.config/esmvaltool (default user configuration directory)
2026-04-02 12:02:54,974 UTC [3235444] INFO    Writing program log files to:
/scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/main_log.txt
/scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/main_log_debug.txt
/scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/cmor_log.txt
2026-04-02 12:02:56,104 UTC [3235444] INFO    Starting the Earth System Model Evaluation Tool at time: 2026-04-02 12:02:56 UTC
2026-04-02 12:02:56,104 UTC [3235444] INFO    ----------------------------------------------------------------------
2026-04-02 12:02:56,105 UTC [3235444] INFO    RECIPE   = /home/b/username/ESMValTool/ESMValTool/esmvaltool/recipes/examples/recipe_python.yml
2026-04-02 12:02:56,105 UTC [3235444] INFO    RUNDIR     = /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run
2026-04-02 12:02:56,105 UTC [3235444] INFO    WORKDIR    = /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/work
2026-04-02 12:02:56,105 UTC [3235444] INFO    PREPROCDIR = /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/preproc
2026-04-02 12:02:56,105 UTC [3235444] INFO    PLOTDIR    = /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/plots
2026-04-02 12:02:56,105 UTC [3235444] INFO    ----------------------------------------------------------------------
2026-04-02 12:02:56,163 UTC [3235444] INFO    Running tasks using at most 256 processes
2026-04-02 12:02:56,163 UTC [3235444] INFO    If your system hangs during execution, it may not have enough memory for keeping this number of tasks in memory.
2026-04-02 12:02:56,163 UTC [3235444] INFO    If you experience memory problems, try reducing 'max_parallel_tasks' in your configuration.
2026-04-02 12:02:56,808 UTC [3235444] INFO    Creating tasks from recipe
2026-04-02 12:02:56,808 UTC [3235444] INFO    Creating tasks for diagnostic map
2026-04-02 12:02:56,808 UTC [3235444] INFO    Creating diagnostic task map/script1
2026-04-02 12:02:56,810 UTC [3235444] INFO    Creating preprocessor task map/tas
2026-04-02 12:02:56,810 UTC [3235444] INFO    Creating preprocessor 'to_degrees_c' task for variable 'tas'
2026-04-02 12:02:56,821 UTC [3235444] INFO    Found input files for Dataset: tas, Amon, CMIP6, BCC-ESM1, historical, r1i1p1f1, mon, gn, v20181214
2026-04-02 12:02:56,826 UTC [3235444] INFO    Found input files for Dataset: tas, Amon, CMIP5, bcc-csm1-1, historical, r1i1p1, mon, v1
2026-04-02 12:02:56,827 UTC [3235444] INFO    PreprocessingTask map/tas created.
2026-04-02 12:02:56,827 UTC [3235444] INFO    Creating tasks for diagnostic timeseries
2026-04-02 12:02:56,827 UTC [3235444] INFO    Creating diagnostic task timeseries/script1
2026-04-02 12:02:56,828 UTC [3235444] INFO    Creating preprocessor task timeseries/tas_amsterdam
2026-04-02 12:02:56,828 UTC [3235444] INFO    Creating preprocessor 'annual_mean_amsterdam' task for variable 'tas_amsterdam'
2026-04-02 12:02:56,833 UTC [3235444] INFO    Found input files for Dataset: tas, Amon, CMIP6, BCC-ESM1, historical, r1i1p1f1, mon, gn, v20181214
2026-04-02 12:02:56,837 UTC [3235444] INFO    Found input files for Dataset: tas, Amon, CMIP5, bcc-csm1-1, historical, r1i1p1, mon, v1
2026-04-02 12:02:56,838 UTC [3235444] INFO    PreprocessingTask timeseries/tas_amsterdam created.
2026-04-02 12:02:56,838 UTC [3235444] INFO    Creating preprocessor task timeseries/tas_global
2026-04-02 12:02:56,838 UTC [3235444] INFO    Creating preprocessor 'annual_mean_global' task for variable 'tas_global'
2026-04-02 12:02:56,845 UTC [3235444] INFO    Found input files for Dataset: tas, Amon, CMIP6, BCC-ESM1, historical, r1i1p1f1, mon, gn, v20181214, 
supplementaries: areacella, fx, 1pctCO2, fx, v20190613
2026-04-02 12:02:56,849 UTC [3235444] INFO    Found input files for Dataset: tas, Amon, CMIP5, bcc-csm1-1, historical, r1i1p1, mon, v1, supplementaries: 
areacella, fx, r0i0p0, fx
2026-04-02 12:02:56,850 UTC [3235444] INFO    PreprocessingTask timeseries/tas_global created.
2026-04-02 12:02:56,850 UTC [3235444] INFO    These tasks will be executed: timeseries/tas_amsterdam, map/tas, map/script1, timeseries/script1, timeseries/tas_global
2026-04-02 12:02:56,880 UTC [3235444] INFO    Wrote recipe with version numbers and wildcards to:
file:///scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/recipe_python_filled.yml
2026-04-02 12:03:15,435 UTC [3235444] INFO    Using Dask distributed scheduler (address: tcp://127.0.0.1:46079, dashboard link: http://127.0.0.1:8787/status)
2026-04-02 12:03:15,436 UTC [3235444] INFO    Running 5 tasks using 5 processes
2026-04-02 12:03:15,519 UTC [3236556] INFO    Starting task map/tas in process [3236556]
2026-04-02 12:03:15,519 UTC [3236558] INFO    Starting task timeseries/tas_amsterdam in process [3236558]
2026-04-02 12:03:15,520 UTC [3236560] INFO    Starting task timeseries/tas_global in process [3236560]
2026-04-02 12:03:15,606 UTC [3235444] INFO    Progress: 3 tasks running, 2 tasks waiting for ancestors, 0/5 done
2026-04-02 12:03:15,805 UTC [3236558] INFO    Extracting data for Amsterdam, Noord-Holland, Nederland (52.3730796 °N, 4.8924534 °E)
2026-04-02 12:03:16,177 UTC [3236558] INFO    Extracting data for Amsterdam, Noord-Holland, Nederland (52.3730796 °N, 4.8924534 °E)
2026-04-02 12:03:16,239 UTC [3236556] INFO    Computing and saving data for preprocessing task map/tas
2026-04-02 12:03:16,384 UTC [3236558] INFO    Generated PreprocessorFile: /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/preproc/
timeseries/tas_amsterdam/MultiModelMean_historical_Amon_tas_1850-2000.nc
2026-04-02 12:03:17,250 UTC [3236556] INFO    map/tas                       [########################################] | 100% Completed | 1.01 s
2026-04-02 12:03:17,252 UTC [3236560] INFO    Computing and saving data for preprocessing task timeseries/tas_global
2026-04-02 12:03:17,256 UTC [3236556] INFO    Successfully completed task map/tas (priority 1) in 0:00:01.736625
2026-04-02 12:03:17,414 UTC [3235444] INFO    Progress: 2 tasks running, 2 tasks waiting for ancestors, 1/5 done
2026-04-02 12:03:17,442 UTC [3236562] INFO    Starting task map/script1 in process [3236562]
2026-04-02 12:03:17,447 UTC [3236562] INFO    Running command ['/work/bd0854/username/utils/mambaforge/envs/esmvaltool/bin/python3.12', 
'/home/b/username/ESMValTool/ESMValTool/esmvaltool/diag_scripts/examples/diagnostic.py', 
'/scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/map/script1/settings.yml']
2026-04-02 12:03:17,447 UTC [3236562] INFO    Writing output to /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/work/map/script1
2026-04-02 12:03:17,447 UTC [3236562] INFO    Writing plots to /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/plots/map/script1
2026-04-02 12:03:17,447 UTC [3236562] INFO    Writing log to /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/map/script1/log.txt
2026-04-02 12:03:17,447 UTC [3236562] INFO    To re-run this diagnostic script, run:
cd /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/map/script1; MPLBACKEND="Agg" /work/bd0854/username/utils/mambaforge/envs/
esmvaltool/bin/python3.12 /home/b/username/ESMValTool/ESMValTool/esmvaltool/diag_scripts/examples/diagnostic.py 
/scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/map/script1/settings.yml
2026-04-02 12:03:17,514 UTC [3235444] INFO    Progress: 3 tasks running, 1 tasks waiting for ancestors, 1/5 done
2026-04-02 12:03:18,367 UTC [3236560] INFO    timeseries/tas_global         [########################################] | 100% Completed | 1.10 s
2026-04-02 12:03:18,370 UTC [3236558] INFO    Computing and saving data for preprocessing task timeseries/tas_amsterdam
2026-04-02 12:03:18,394 UTC [3236560] INFO    Successfully completed task timeseries/tas_global (priority 4) in 0:00:02.873452
2026-04-02 12:03:18,675 UTC [3235444] INFO    Progress: 2 tasks running, 1 tasks waiting for ancestors, 2/5 done
2026-04-02 12:03:20,566 UTC [3236558] INFO    timeseries/tas_amsterdam      [########################################] | 100% Completed | 2.18 s
2026-04-02 12:03:20,591 UTC [3236558] INFO    Successfully completed task timeseries/tas_amsterdam (priority 3) in 0:00:05.071412
2026-04-02 12:03:20,712 UTC [3235444] INFO    Progress: 1 tasks running, 1 tasks waiting for ancestors, 3/5 done
2026-04-02 12:03:20,730 UTC [3236564] INFO    Starting task timeseries/script1 in process [3236564]
2026-04-02 12:03:20,757 UTC [3236564] INFO    Running command ['/work/bd0854/username/utils/mambaforge/envs/esmvaltool/bin/python3.12', 
'/home/b/username/ESMValTool/ESMValTool/esmvaltool/diag_scripts/examples/diagnostic.py', 
'/scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/timeseries/script1/settings.yml']
2026-04-02 12:03:20,757 UTC [3236564] INFO    Writing output to /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/work/timeseries/script1
2026-04-02 12:03:20,757 UTC [3236564] INFO    Writing plots to /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/plots/timeseries/script1
2026-04-02 12:03:20,757 UTC [3236564] INFO    Writing log to /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/timeseries/script1/log.txt
2026-04-02 12:03:20,758 UTC [3236564] INFO    To re-run this diagnostic script, run:
cd /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/timeseries/script1; MPLBACKEND="Agg" 
/work/bd0854/username/utils/mambaforge/envs/esmvaltool/bin/python3.12 /home/b/username/ESMValTool/ESMValTool/esmvaltool/diag_scripts/examples/diagnostic.py 
/scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/timeseries/script1/settings.yml
2026-04-02 12:03:20,812 UTC [3235444] INFO    Progress: 2 tasks running, 0 tasks waiting for ancestors, 3/5 done
2026-04-02 12:03:28,198 UTC [3236562] INFO    Maximum memory used (estimate): 0.3 GB
2026-04-02 12:03:28,199 UTC [3236562] INFO    Sampled every second. It may be inaccurate if short but high spikes in memory consumption occur.
2026-04-02 12:03:28,274 UTC [3236564] INFO    Maximum memory used (estimate): 0.3 GB
2026-04-02 12:03:28,275 UTC [3236564] INFO    Sampled every second. It may be inaccurate if short but high spikes in memory consumption occur.
2026-04-02 12:03:28,618 UTC [3236562] INFO    Successfully completed task map/script1 (priority 0) in 0:00:11.175930
2026-04-02 12:03:28,820 UTC [3235444] INFO    Progress: 1 tasks running, 0 tasks waiting for ancestors, 4/5 done
2026-04-02 12:03:29,008 UTC [3236564] INFO    Successfully completed task timeseries/script1 (priority 2) in 0:00:08.278011
2026-04-02 12:03:29,020 UTC [3235444] INFO    Progress: 0 tasks running, 0 tasks waiting for ancestors, 5/5 done
2026-04-02 12:03:29,020 UTC [3235444] INFO    Successfully completed all tasks.
2026-04-02 12:03:29,716 UTC [3235444] INFO    Wrote recipe with version numbers and wildcards to:
file:///scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/run/recipe_python_filled.yml
2026-04-02 12:03:30,651 UTC [3235444] INFO    Wrote recipe output to:
file:///scratch/b/username/esmvaltool_output/recipe_python_20260402_120254/index.html
2026-04-02 12:03:30,651 UTC [3235444] INFO    It looks like you are connected to a remote machine via SSH. To show the output html file, you can try the 
following command on your local machine:
server=136.172.124.6 && port=31415 && ssh -t -L ${port}:localhost:${port} username@${server} /work/bd0854/username/utils/mambaforge/envs/esmvaltool/bin/
python3.12 -m http.server ${port} -d /scratch/b/username/esmvaltool_output/recipe_python_20260402_120254
Then visit http://localhost:31415 in your browser
2026-04-02 12:03:30,651 UTC [3235444] INFO    If the port 31415 is already in use, you can replace it with any other free one (e.g., 12789). If you are 
connected through a jump host, replace the server IP address 136.172.124.6 with your SSH server name
2026-04-02 12:03:30,652 UTC [3235444] INFO    Ending the Earth System Model Evaluation Tool at time: 2026-04-02 12:03:30 UTC
2026-04-02 12:03:30,652 UTC [3235444] INFO    Time for running the recipe was: 0:00:34.547424
2026-04-02 12:03:31,701 UTC [3235444] INFO    Maximum memory used (estimate): 8.3 GB
2026-04-02 12:03:31,708 UTC [3235444] INFO    Sampled every second. It may be inaccurate if short but high spikes in memory consumption occur.
2026-04-02 12:03:31,733 UTC [3235444] WARNING Input data is not (fully) CMOR-compliant, see /scratch/b/username/esmvaltool_output/
recipe_python_20260402_120254/run/cmor_log.txt for details
2026-04-02 12:03:31,733 UTC [3235444] INFO    Run was successful

Pro tip: ESMValTool search paths

You might wonder how ESMValTool was able find the recipe file, even though it’s not in your working directory. All the recipe paths printed from esmvaltool recipes list are relative to ESMValTool’s installation location. This is where ESMValTool will look if it cannot find the file by following the path from your working directory.

Investigating the log messages

Let’s dissect what’s happening here.

Output files and directories

After the banner and general information, the output starts with some important locations.

Did ESMValTool use the right config files?

What is the path to the example recipe?

What is the main output folder generated by ESMValTool?

Can you guess what the different output directories are for?

ESMValTool creates two log files. What is the difference?

Answers

The list of directories involves the directory with all default config files (e.g., ../ESMValCore/esmvalcore/config/configurations/defaults) and should list the (default) user configuration directory with our edited files from the previous episode (default: ~/.config/esmvaltool).

ESMValTool found the recipe in its installation directory, something like /home/users/username/mambaforge/envs/esmvaltool/bin/esmvaltool/recipes/examples/ or if you are using a pre-installed module on a server, something like /apps/jasmin/community/esmvaltool/ESMValTool_<version> /esmvaltool/recipes/examples/recipe_python.yml, where <version> is the latest release.

ESMValTool creates a time-stamped output directory for every run. In this case, it should be something like recipe_python_YYYYMMDD_HHMMSS. This folder is made inside the output directory specified in the previous episode: ~/esmvaltool_tutorial/esmvaltool_output.

There should be four output folders:

run/: this is where esmvaltool stores general information about the run, such as log messages and a copy of the recipe file.

work/: this is where output files (not figures) are stored.

preproc/: this is where pre-processed data are stored.

plots/: this is where output figures are stored.

The log files are:

main_log.txt is a copy of the command-line output

main_log_debug.txt contains more detailed information that may be useful for debugging.

Debugging: No ‘preproc’ directory?

If you’re missing the preproc directory, then your config-user.yml file has the value remove_preproc_dir set to true (this is used to save disk space). Please set this value to false and run the recipe again.

After the output locations, there are two main sections that can be distinguished in the log messages:

Creating tasks
Executing tasks

Analyse the tasks

List all the tasks that ESMValTool is executing for this recipe. Can you guess what this recipe does?
Answer

Just after all the ‘creating tasks’ and before ‘executing tasks’, we find the following line in the output:
[3098040] INFO    These tasks will be executed: timeseries/tas_global, 
map/tas, map/script1, timeseries/tas_amsterdam, timeseries/script1
So there are three tasks related to timeseries: global temperature, Amsterdam temperature, and a script (tas: near-surface air temperature). And then there are two tasks related to a map: something with temperature, and again a script.

Examining the recipe file

To get more insight into what is happening, we will have a look at the recipe file itself. Use the following command to copy the recipe to your working directory

esmvaltool recipes get examples/recipe_python.yml

Now you should see the recipe file in your working directory (type ls to verify). Use the nano editor to open this file:

nano recipe_python.yml

For reference, you can also view the recipe by unfolding the box below.

recipe_python.yml

# ESMValTool
# recipe_python.yml
#
# See https://docs.esmvaltool.org/en/latest/recipes/recipe_examples.html
# for a description of this recipe.
#
# See https://docs.esmvaltool.org/projects/esmvalcore/en/latest/recipe/overview.html
# for a description of the recipe format.
---
documentation:
 description: |
   Example recipe that plots a map and timeseries of temperature.

 title: Recipe that runs an example diagnostic written in Python.

 authors:
   - andela_bouwe
   - righi_mattia

 maintainer:
   - schlund_manuel

 references:
   - acknow_project

 projects:
   - esmval
   - c3s-magic

datasets:
 - {dataset: BCC-ESM1, project: CMIP6, exp: historical, ensemble: r1i1p1f1, grid: gn}
 - {dataset: bcc-csm1-1, project: CMIP5, exp: historical, ensemble: r1i1p1}

preprocessors:
 # See https://docs.esmvaltool.org/projects/esmvalcore/en/latest/recipe/preprocessor.html
 # for a description of the preprocessor functions.

 to_degrees_c:
   convert_units:
     units: degrees_C

 annual_mean_amsterdam:
   extract_location:
     location: Amsterdam
     scheme: linear
   annual_statistics:
     operator: mean
   multi_model_statistics:
     statistics:
       - mean
     span: overlap
   convert_units:
     units: degrees_C

 annual_mean_global:
   area_statistics:
     operator: mean
   annual_statistics:
     operator: mean
   convert_units:
     units: degrees_C

diagnostics:

 map:
   description: Global map of temperature in January 2000.
   themes:
     - phys
   realms:
     - atmos
   variables:
     tas:
       mip: Amon
       preprocessor: to_degrees_c
       timerange: 2000/P1M
       caption: |
         Global map of {long_name} in January 2000 according to {dataset}.
   scripts:
     script1:
       script: examples/diagnostic.py
       quickplot:
         plot_type: pcolormesh
         cmap: Reds

 timeseries:
   description: Annual mean temperature in Amsterdam and global mean since 1850.
   themes:
     - phys
   realms:
     - atmos
   variables:
     tas_amsterdam:
       short_name: tas
       mip: Amon
       preprocessor: annual_mean_amsterdam
       timerange: 1850/2000
       caption: Annual mean {long_name} in Amsterdam according to {dataset}.
     tas_global:
       short_name: tas
       mip: Amon
       preprocessor: annual_mean_global
       timerange: 1850/2000
       caption: Annual global mean {long_name} according to {dataset}.
   scripts:
     script1:
       script: examples/diagnostic.py
       quickplot:
         plot_type: plot

Do you recognize the basic recipe structure that was introduced in episode 1?

Documentation with relevant (citation) information
Datasets that should be analysed
Preprocessors groups of common preprocessing steps
Diagnostics scripts performing more specific evaluation steps

Analyse the recipe

Try to answer the following questions:

Who wrote this recipe?

Who should be approached if there is a problem with this recipe?

How many datasets are analyzed?

What does the preprocessor called annual_mean_global do?

Which script is applied for the diagnostic called map?

Can you link specific lines in the recipe to the tasks that we saw before?

How is the location of the city specified?

How is the temporal range of the data specified?

Answers

The example recipe is written by Bouwe Andela and Mattia Righi.

Manuel Schlund is listed as the maintainer of this recipe.

Two datasets are analysed:

CMIP6 data from the model BCC-ESM1

CMIP5 data from the model bcc-csm1-1

The preprocessor annual_mean_global computes an area mean as well as annual means

The diagnostic called map executes a script referred to as script1. This is a python script named examples/diagnostic.py

There are two diagnostics: map and timeseries. Under the diagnostic map we find two tasks:

a preprocessor task called tas, applying the preprocessor called to_degrees_c to the variable tas.

a diagnostic task called script1, applying the script examples/diagnostic.py to the preprocessed data (map/tas).

Under the diagnostic timeseries we find three tasks:

a preprocessor task called tas_amsterdam, applying the preprocessor called annual_mean_amsterdam to the variable tas.

a preprocessor task called tas_global, applying the preprocessor called annual_mean_global to the variable tas.

a diagnostic task called script1, applying the script examples/diagnostic.py to the preprocessed data (timeseries/tas_global and timeseries/tas_amsterdam).

The extract_location preprocessor is used to get data for a specific location here. ESMValTool interpolates to the location based on the chosen scheme. Can you tell the scheme used here? For more ways to extract areas, see the Area operations page.

The timerange tag is used to extract data from a specific time period here. The start time is 01/01/2000 and the span of time to calculate means is 1 Month given by P1M. For more options on how to specify time ranges, see the timerange documentation.

Pro tip: short names and variable groups

The preprocessor tasks in ESMValTool are called ‘variable groups’. For the diagnostic timeseries, we have two variable groups: tas_amsterdam and tas_global. Both of them operate on the variable tas (as indicated by the short_name), but they apply different preprocessors. For the diagnostic map the variable group itself is named tas, and you’ll notice that we do not explicitly provide the short_name. This is a shorthand built into ESMValTool.

Output files

Have another look at the output directory created by the ESMValTool run.

Which files/folders are created by each task?

Answer

map/tas: creates /preproc/map/tas, which contains preprocessed data for each of the input datasets, a file called metadata.yml describing the contents of these datasets and provenance information in the form of .xml files.

timeseries/tas_global: creates /preproc/timeseries/tas_global, which contains preprocessed data for each of the input datasets, a metadata.yml file and provenance information in the form of .xml files.

timeseries/tas_amsterdam: creates /preproc/timeseries/tas_amsterdam, which contains preprocessed data for each of the input datasets, plus a combined MultiModelMean, a metadata.yml file and provenance files.

map/script1: creates /run/map/script1 with general information and a log of the diagnostic script run. It also creates /plots/map/script1/ and /work/map/script1, which contain output figures and output datasets, respectively. For each output file, there is also corresponding provenance information in the form of .xml, .bibtex and .txt files.

timeseries/script1: creates /run/timeseries/script1 with general information and a log of the diagnostic script run. It also creates /plots/timeseries/script1 and /work/timeseries/script1, which contain output figures and output datasets, respectively. For each output file, there is also corresponding provenance information in the form of .xml, .bibtex and .txt files.

Pro tip: diagnostic logs

When you run ESMValTool, any log messages from the diagnostic script are not printed on the terminal. But they are written to the log.txt files in the folder /run/<diag_name>/log.txt.

ESMValTool does print a command that can be used to re-run a diagnostic script. When you use this the output will be printed to the command line.

Modifying the example recipe

Let’s make a small modification to the example recipe. Notice that now that you have copied and edited the recipe, you can use

esmvaltool run recipe_python.yml

to refer to your local file rather than the default version shipped with ESMValTool.

Change your location

Modify and run the recipe to analyse the temperature for your own location.
Solution

In principle, you only have to modify the location in the preprocessor called annual_mean_amsterdam. However, it is good practice to also replace all instances of amsterdam with the correct name of your location. Otherwise the log messages and output will be confusing. You are free to modify the names of preprocessors or diagnostics.

In the diff file below you will see the changes we have made to the file. The top 2 lines are the filenames and the lines like @@ -39,9 +39,9 @@ represent the line numbers in the original and modified file, respectively. For more info on this format, see here.
--- recipe_python.yml	
+++ recipe_python_london.yml	
@@ -39,9 +39,9 @@
    convert_units:
      units: degrees_C

-  annual_mean_amsterdam:
+  annual_mean_london:
    extract_location:
-      location: Amsterdam
+      location: London
      scheme: linear
    annual_statistics:
      operator: mean
@@ -83,7 +83,7 @@
          cmap: Reds

  timeseries:
-    description: Annual mean temperature in Amsterdam and global mean since 1850.
+    description: Annual mean temperature in London and global mean since 1850.
    themes:
      - phys
    realms:
@@ -92,9 +92,9 @@
      tas_amsterdam:
        short_name: tas
        mip: Amon
-        preprocessor: annual_mean_amsterdam
+        preprocessor: annual_mean_london
        timerange: 1850/2000
-        caption: Annual mean {long_name} in Amsterdam according to {dataset}.
+        caption: Annual mean {long_name} in London according to {dataset}.
      tas_global:
        short_name: tas
        mip: Amon

Key Points

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

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ESMValTool Tutorial

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Running your first recipe

Overview

Running an existing recipe

Output

Pro tip: ESMValTool search paths

Investigating the log messages

Output files and directories

Answers

Debugging: No ‘preproc’ directory?

Analyse the tasks

Answer

Examining the recipe file

recipe_python.yml

Analyse the recipe

Answers

Pro tip: short names and variable groups

Output files

Answer

Pro tip: diagnostic logs

Modifying the example recipe

Change your location

Solution

Key Points

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