This lesson is being piloted (Beta version)

Running your first recipe

Overview

Teaching: 15 min
Exercises: 15 min
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_file ./config-user.yml 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 output below.

Example output

2022-01-24 17:31:48,745 UTC [190720] INFO    
______________________________________________________________________
         _____ ____  __  ____     __    _ _____           _
        | ____/ ___||  \/  \ \   / /_ _| |_   _|__   ___ | |
        |  _| \___ \| |\/| |\ \ / / _` | | | |/ _ \ / _ \| |
        | |___ ___) | |  | | \ V / (_| | | | | (_) | (_) | |
        |_____|____/|_|  |_|  \_/ \__,_|_| |_|\___/ \___/|_|
______________________________________________________________________

ESMValTool - Earth System Model Evaluation Tool.

http://www.esmvaltool.org

 CORE DEVELOPMENT TEAM AND CONTACTS:
 Birgit Hassler (Co-PI; DLR, Germany - birgit.hassler@dlr.de)
 Alistair Sellar (Co-PI; Met Office, UK - alistair.sellar@metoffice.gov.uk)
 Bouwe Andela (Netherlands eScience Center, The Netherlands - b.andela@esciencecenter.nl)
 Lee de Mora (PML, UK - ledm@pml.ac.uk)
 Niels Drost (Netherlands eScience Center, The Netherlands - n.drost@esciencecenter.nl)
 Veronika Eyring (DLR, Germany - veronika.eyring@dlr.de)
 Bettina Gier (UBremen, Germany - gier@uni-bremen.de)
 Remi Kazeroni (DLR, Germany - remi.kazeroni@dlr.de)
 Nikolay Koldunov (AWI, Germany - nikolay.koldunov@awi.de)
 Axel Lauer (DLR, Germany - axel.lauer@dlr.de)
 Saskia Loosveldt-Tomas (BSC, Spain - saskia.loosveldt@bsc.es)
 Ruth Lorenz (ETH Zurich, Switzerland - ruth.lorenz@env.ethz.ch)
 Benjamin Mueller (LMU, Germany - b.mueller@iggf.geo.uni-muenchen.de)
 Valeriu Predoi (URead, UK - valeriu.predoi@ncas.ac.uk)
 Mattia Righi (DLR, Germany - mattia.righi@dlr.de)
 Manuel Schlund (DLR, Germany - manuel.schlund@dlr.de)
 Breixo Solino Fernandez (DLR, Germany - breixo.solinofernandez@dlr.de)
 Javier Vegas-Regidor (BSC, Spain - javier.vegas@bsc.es)
 Klaus Zimmermann (SMHI, Sweden - klaus.zimmermann@smhi.se)

For further help, please read the documentation at
http://docs.esmvaltool.org. Have fun!

2022-04-24 17:31:48,745 UTC [190720] INFO    Package versions
2022-04-24 17:31:48,746 UTC [190720] INFO    ----------------
2022-04-24 17:31:48,746 UTC [190720] INFO    ESMValCore: 2.5.0
2022-04-24 17:31:48,746 UTC [190720] INFO    ESMValTool: 2.5.0
2022-04-24 17:31:48,746 UTC [190720] INFO    ----------------
2022-04-24 17:31:48,746 UTC [190720] INFO    Using config file /home/users/username/esmvaltool-tutorial/config-user.yml
2022-04-24 17:31:48,746 UTC [190720] INFO    Writing program log files to:
/home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/main_log.txt
/home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/main_log_debug.txt
2022-04-24 17:31:48,747 UTC [190720] INFO    Starting the Earth System Model Evaluation Tool at time: 2022-04-24 17:31:48 UTC
2022-04-24 17:31:48,747 UTC [190720] INFO    ----------------------------------------------------------------------
2022-04-24 17:31:48,747 UTC [190720] INFO    RECIPE   = /apps/jasmin/community/esmvaltool/ESMValTool_2.5.0/esmvaltool/recipes/examples/recipe_python.yml
2022-04-24 17:31:48,747 UTC [190720] INFO    RUNDIR     = /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run
2022-04-24 17:31:48,747 UTC [190720] INFO    WORKDIR    = /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/work
2022-04-24 17:31:48,747 UTC [190720] INFO    PREPROCDIR = /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/preproc
2022-04-24 17:31:48,747 UTC [190720] INFO    PLOTDIR    = /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/plots
2022-04-24 17:31:48,747 UTC [190720] INFO    ----------------------------------------------------------------------
2022-04-24 17:31:48,747 UTC [190720] INFO    Running tasks using at most 24 processes
2022-04-24 17:31:48,747 UTC [190720] INFO    If your system hangs during execution, it may not have enough memory for keeping this number of tasks in memory.
2022-04-24 17:31:48,747 UTC [190720] INFO    If you experience memory problems, try reducing 'max_parallel_tasks' in your user configuration file.
2022-04-24 17:31:48,805 UTC [190720] INFO    Creating tasks from recipe
2022-04-24 17:31:48,805 UTC [190720] INFO    Creating tasks for diagnostic map
2022-04-24 17:31:48,805 UTC [190720] INFO    Creating preprocessor task map/tas
2022-04-24 17:31:48,805 UTC [190720] INFO    Creating preprocessor 'select_january' task for variable 'tas'
2022-04-24 17:31:48,835 UTC [190720] INFO    Found input files for CMIP6
2022-04-24 17:31:48,900 UTC [190720] INFO    Found input files for CMIP5
2022-04-24 17:31:48,961 UTC [190720] INFO    PreprocessingTask map/tas created.
2022-04-24 17:31:48,961 UTC [190720] INFO    Creating diagnostic task map/script1
2022-04-24 17:31:48,962 UTC [190720] INFO    Creating tasks for diagnostic timeseries
2022-04-24 17:31:48,962 UTC [190720] INFO    Creating preprocessor task timeseries/tas_amsterdam
2022-04-24 17:31:48,963 UTC [190720] INFO    Creating preprocessor 'annual_mean_amsterdam' task for variable 'tas'
2022-04-24 17:31:48,969 UTC [190720] INFO    Found input files for CMIP6
2022-04-24 17:31:49,019 UTC [190720] INFO    Found input files for CMIP5
2022-04-24 17:31:49,063 UTC [190720] INFO    PreprocessingTask timeseries/tas_amsterdam created.
2022-04-24 17:31:49,064 UTC [190720] INFO    Creating preprocessor task timeseries/tas_global
2022-04-24 17:31:49,064 UTC [190720] INFO    Creating preprocessor 'annual_mean_global' task for variable 'tas'
2022-04-24 17:31:49,065 UTC [190720] WARNING Missing data for fx variable 'areacella' of dataset CMIP6
2022-04-24 17:31:49,071 UTC [190720] INFO    Found input files for CMIP6
2022-04-24 17:31:49,138 UTC [190720] INFO    Found input files for CMIP5
2022-04-24 17:31:49,183 UTC [190720] INFO    PreprocessingTask timeseries/tas_global created.
2022-04-24 17:31:49,183 UTC [190720] INFO    Creating diagnostic task timeseries/script1
2022-04-24 17:31:49,184 UTC [190720] INFO    These tasks will be executed: map/script1, map/tas, timeseries/tas_amsterdam, timeseries/script1, timeseries/tas_global
2022-04-24 17:31:49,195 UTC [190720] INFO    Running 5 tasks using 5 processes
2022-04-24 17:31:49,239 UTC [190776] INFO    Starting task map/tas in process [190776]
2022-04-24 17:31:49,240 UTC [190777] INFO    Starting task timeseries/tas_amsterdam in process [190777]
2022-04-24 17:31:49,240 UTC [190778] INFO    Starting task timeseries/tas_global in process [190778]
2022-04-24 17:31:49,335 UTC [190720] INFO    Progress: 3 tasks running, 2 tasks waiting for ancestors, 0/5 done
2022-04-24 17:31:55,735 UTC [190776] INFO    Successfully completed task map/tas (priority 0) in 0:00:06.494906
2022-04-24 17:31:55,847 UTC [190720] INFO    Progress: 2 tasks running, 2 tasks waiting for ancestors, 1/5 done
2022-04-24 17:31:55,852 UTC [190779] INFO    Starting task map/script1 in process [190779]
2022-04-24 17:31:55,861 UTC [190779] INFO    Running command ['/apps/jasmin/community/esmvaltool/miniconda3/envs/esmvaltool/bin/python', '/apps/jasmin/community/esmvaltool/ESMValTool_2.5.0/esmvaltool/diag_scripts/examples/diagnostic.py', '/home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/map/script1/settings.yml']
2022-04-24 17:31:55,862 UTC [190779] INFO    Writing output to /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/work/map/script1
2022-04-24 17:31:55,862 UTC [190779] INFO    Writing plots to /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/plots/map/script1
2022-04-24 17:31:55,862 UTC [190779] INFO    Writing log to /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/map/script1/log.txt
2022-04-24 17:31:55,862 UTC [190779] INFO    To re-run this diagnostic script, run:
cd /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/map/script1; MPLBACKEND="Agg" /apps/jasmin/community/esmvaltool/miniconda3/envs/esmvaltool/bin/python /apps/jasmin/community/esmvaltool/ESMValTool_2.5.0/esmvaltool/diag_scripts/examples/diagnostic.py /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/map/script1/settings.yml
2022-04-24 17:31:55,947 UTC [190720] INFO    Progress: 3 tasks running, 1 tasks waiting for ancestors, 1/5 done
2022-04-24 17:31:58,538 UTC [190777] INFO    Generated PreprocessorFile: /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/preproc/timeseries/tas_amsterdam/MultiModelMean_Amon_tas_1850-2000.nc
2022-04-24 17:31:58,762 UTC [190777] INFO    Successfully completed task timeseries/tas_amsterdam (priority 2) in 0:00:09.521837
2022-04-24 17:31:58,953 UTC [190720] INFO    Progress: 2 tasks running, 1 tasks waiting for ancestors, 2/5 done
2022-04-24 17:31:59,700 UTC [190778] INFO    Successfully completed task timeseries/tas_global (priority 3) in 0:00:10.459256
2022-04-24 17:31:59,855 UTC [190720] INFO    Progress: 1 tasks running, 1 tasks waiting for ancestors, 3/5 done
2022-04-24 17:31:59,863 UTC [190780] INFO    Starting task timeseries/script1 in process [190780]
2022-04-24 17:31:59,871 UTC [190780] INFO    Running command ['/apps/jasmin/community/esmvaltool/miniconda3/envs/esmvaltool/bin/python', '/apps/jasmin/community/esmvaltool/ESMValTool_2.5.0/esmvaltool/diag_scripts/examples/diagnostic.py', '/home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/timeseries/script1/settings.yml']
2022-04-24 17:31:59,872 UTC [190780] INFO    Writing output to /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/work/timeseries/script1
2022-04-24 17:31:59,872 UTC [190780] INFO    Writing plots to /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/plots/timeseries/script1
2022-04-24 17:31:59,872 UTC [190780] INFO    Writing log to /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/timeseries/script1/log.txt
2022-04-24 17:31:59,872 UTC [190780] INFO    To re-run this diagnostic script, run:
cd /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/timeseries/script1; MPLBACKEND="Agg" /apps/jasmin/community/esmvaltool/miniconda3/envs/esmvaltool/bin/python /apps/jasmin/community/esmvaltool/ESMValTool_2.5.0/esmvaltool/diag_scripts/examples/diagnostic.py /home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/run/timeseries/script1/settings.yml
2022-04-24 17:31:59,956 UTC [190720] INFO    Progress: 2 tasks running, 0 tasks waiting for ancestors, 3/5 done
2022-04-24 17:32:01,586 UTC [190779] INFO    Successfully completed task map/script1 (priority 1) in 0:00:05.733018
2022-04-24 17:32:01,760 UTC [190720] INFO    Progress: 1 tasks running, 0 tasks waiting for ancestors, 4/5 done
2022-04-24 17:32:06,079 UTC [190780] INFO    Maximum memory used (estimate): 0.2 GB
2022-04-24 17:32:06,081 UTC [190780] INFO    Sampled every second. It may be inaccurate if short but high spikes in memory consumption occur.
2022-04-24 17:32:06,760 UTC [190780] INFO    Successfully completed task timeseries/script1 (priority 4) in 0:00:06.896972
2022-04-24 17:32:06,771 UTC [190720] INFO    Progress: 0 tasks running, 0 tasks waiting for ancestors, 5/5 done
2022-04-24 17:32:06,771 UTC [190720] INFO    Successfully completed all tasks.
2022-04-24 17:32:07,764 UTC [190720] INFO    Wrote recipe output to:
file:///home/users/username/esmvaltool-tutorial/esmvaltool_output/recipe_python_20220424_173145/index.html
2022-04-24 17:32:07,764 UTC [190720] INFO    Ending the Earth System Model Evaluation Tool at time: 2022-04-24 17:32:07 UTC
2022-04-24 17:32:07,764 UTC [190720] INFO    Time for running the recipe was: 0:00:19.017514
2022-04-24 17:32:08,702 UTC [190720] INFO    Maximum memory used (estimate): 1.3 GB
2022-04-24 17:32:08,703 UTC [190720] INFO    Sampled every second. It may be inaccurate if short but high spikes in memory consumption occur.
2022-04-24 17:32:08,704 UTC [190720] 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.

  1. Did ESMValTool use the right config file?
  2. What is the path to the example recipe?
  3. What is the main output folder generated by ESMValTool?
  4. Can you guess what the different output directories are for?
  5. ESMValTool creates two log files. What is the difference?

Answers

  1. The config file should be the one we edited in the previous episode, something like /home/<username>/.esmvaltool/config-user.yml or ~/esmvaltool_tutorial/config-user.yml.
  2. ESMValTool found the recipe in its installation directory, something like /home/users/username/miniconda3/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_2.5.0/esmvaltool/recipes/examples/recipe_python.yml
  3. 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.
  4. There should be four output folders:
    • plots/: this is where output figures are stored.
    • preproc/: this is where pre-processed data are stored.
    • 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.
  5. 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:

Analyse the tasks

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

Answer

Just after ‘creating tasks’ and before ‘executing tasks’, we find the following line in the output:

[190720] INFO    These tasks will be executed: map/script1, map/tas, timeseries/tas_amsterdam, timeseries/script1, timeseries/tas_global

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
---
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: CanESM2, project: CMIP5, exp: historical, ensemble: r1i1p1}

preprocessors:

  select_january:
    extract_month:
      month: 1

  annual_mean_amsterdam:
    extract_point:
      latitude: 52.379189
      longitude: 4.899431
      scheme: linear
    annual_statistics:
      operator: mean
    multi_model_statistics:
      statistics:
        - mean
      span: overlap

  annual_mean_global:
    area_statistics:
      operator: mean
      fx_variables:
        areacella:
    annual_statistics:
      operator: mean

diagnostics:

  map:
    description: Global map of temperature in January 2000.
    themes:
      - phys
    realms:
      - atmos
    variables:
      tas:
        mip: Amon
        preprocessor: select_january
        start_year: 2000
        end_year: 2000
    scripts:
      script1:
        script: examples/diagnostic.py
        write_netcdf: true
        output_file_type: pdf
        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
        start_year: 1850
        end_year: 2000
      tas_global:
        short_name: tas
        mip: Amon
        preprocessor: annual_mean_global
        start_year: 1850
        end_year: 2000
    scripts:
      script1:
        script: examples/diagnostic.py
        quickplot:
          plot_type: plot

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

Analyse the recipe

Try to answer the following questions:

  1. Who wrote this recipe?
  2. Who should be approached if there is a problem with this recipe?
  3. How many datasets are analyzed?
  4. What does the preprocessor called annual_mean_global do?
  5. Which script is applied for the diagnostic called map?
  6. Can you link specific lines in the recipe to the tasks that we saw before?

Answers

  1. The example recipe is written by Bouwe Andela and Mattia Righi.
  2. Manual Schlund is listed as the maintainer of this recipe.
  3. Two datasets are analysed:
    • CMIP6 data from the model BCC-ESM1
    • CMIP5 data from the model CANESM2
  4. The preprocessor annual_mean_global computes an area mean as well as annual means
  5. The diagnostic called map executes a script referred to as script1. This is a python script named examples/diagnostic.py
  6. There are two diagnostics: map and timeseries. Under the diagnostic map we find two tasks:
    • a preprocessor task called tas, applying the preprocessor called select_january 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).

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, and a file called metadata.yml describing the contents of these datasets.
  • timeseries/tas_global: creates /preproc/timeseries/tas_global, which contains preprocessed data for each of the input datasets, and metadata.yml.
  • timeseries/tas_amsterdam: creates /preproc/timeseries/tas_amsterdam, which contains preprocessed data for each of the input datasets, plus a combined MultiModelMean, and metadata.yml.
  • 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_example.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 latitude and longitude coordinates 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 @@ -31,10 +31,10 @@ 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
@@ -31,10 +31,10 @@
     extract_month:
       month: 1

-  annual_mean_amsterdam:
+  annual_mean_london:
     extract_point:
-      latitude: 52.379189
-      longitude: 4.899431
+      latitude: 51.5074
+      longitude: 0.1278
       scheme: linear
     annual_statistics:
       operator: mean
@@ -73,16 +73,16 @@
           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:
       - atmos
     variables:
-      tas_amsterdam:
+      tas_london:
         short_name: tas
         mip: Amon
-        preprocessor: annual_mean_amsterdam
+        preprocessor: annual_mean_london
         start_year: 1850
         end_year: 2000
       tas_global:

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