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BenMGeo
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adds explanations and further reading
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_episodes/first_example_recipe.md

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@@ -16,7 +16,7 @@ objectives:
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keypoints:
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- "A recipe does not break by fiddling with it"
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- "Log information is useful when interpreting the first warnings/errors"
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- "The dataset section in the recipe relates to Understanding the directory structure of CMIP data on your server/disk and knowing how to use data from different experiments such as CMIP/ScenarioMIP."
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- "The dataset section resembles the filename or directory structure (e.g. CMIP subdirectories)."
2020

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---
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- datasets: what datasets you want to use, including
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- the time range and time resolution,
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- the MIP, ensemble member,
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- the experiment (i.e. historical, ssp125 etc...),
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- the experiment (i.e. historical, ssp125, etc.),
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- and the grid type (CMIP6 only).
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- preprocessors: general operations applied to a dataset before handling it in a diagnostic, listing
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- the desired diagnostic script to use,
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- and additional diagnostic script options or arguments, if needed.
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Also Include additional datasets beyond those included in the datasets section mentioned above, for instance variable specific observational data.
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Also include additional datasets beyond those included in the datasets section mentioned above, for instance variable specific observational data.
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- description: a brief description of the recipe, including
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- who wrote the recipe and who maintains it,
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Note that the authors, publications and references are to be named in the config-references.yml
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This information ...
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The information you provide in the recipe is not only affecting the processes you are starting, but also the directory names your output will be structured in.
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For additional reeds, please have a look at the recipe format description in the [ESMValTool manual](https://docs.esmvaltool.org/projects/esmvalcore/en/latest/recipe/overview.html#recipe-section-diagnostics).
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## How to run ESMValTool
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## Introduction to the example recipe
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Threcipe presented here is a simple, basic recipe that takes a single dataset and produces a time series plot.
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The recipe presented here is a simple, basic recipe that takes a single dataset and produces a time series plot.
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Please copy and paste the following recipe into your ESMValTool working area with the name: recipe_example.yml
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Please download the following recipe into your ESMValTool working area with the name: recipe_example.yml LINK
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>## recipe_example.yml
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>~~~YAML
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- plots
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> ## Inspect the output:
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> Now that you have ran the esmvaltool command for the first time, please locate your output directory.
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> Now that you have run the esmvaltool command for the first time, please locate your output directory.
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> 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.
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>
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{: .challenge}
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> - the dataset:
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> - mip, start_year, end_year
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> - the preprocessor:
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> - These fields are all 2D fields, but thetaga was a 0D field. This means that we need to take the average over the latitude and longitude dimensions. To do this, add the area_statistics to the preprocessor.
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> - These fields are all 2D fields, but thetaoga was a 0D field. This means that we need to take the average over the latitude and longitude dimensions. To do this, add the area_statistics to the preprocessor.
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> - the diagnostic
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> - change the short_name value (thetaoga) for another:
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> - Land surface average temperature (tsland)
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> - Atmospheric surface average temperature (tas)
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> - Ocean surface average temperature (tos)
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> ### Advanced:
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{: .challenge}
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> ## Advanced:
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> If you want to add a different field, please have a look here:
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> http://clipc-services.ceda.ac.uk/dreq/index/CMORvar.html
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{: .challenge}
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{: .callout}
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## Common issues & tips
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> Can you run the command “esmvaltool -h”. If no, then it’s possible that the conda environment isn’t activated. Please return to the installation section, episode #2 LINK.
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{: .solution}
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> ## ESMValTool can’t locate the data. The error message is esmvalcore._recipe_checks.RecipeError: Missing data
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> ## ESMValTool can’t locate the data. The error message is `esmvalcore._recipe_checks.RecipeError: Missing data`
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> Which computing machine are you using? Does your user-config.yml file reflect your machine's settings? Is the dataset’s name in the correct order?
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{: .solution}
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> ## Diagnostic path problems
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> The directory path to your diagnostics code is set relative to the esmvaltool/diag_scripts subdirectory. Is the code placed in this subdirectory? Is it spelled correctly?
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{: .solution}
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> ## FX files not found
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>
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> There is no FX file for your corresponding dataset. Are your datasets’ names spelled correctly? Is there a FX file for this dataset?
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{: .solution}
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> ## The preprocessor works but the diagnostic fails
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> If your preprocessor works fine but your diagnostic script fails, congratulations! A failed diagnostic means that you won’t need to re-run the preprocessor. In your “run/main_log.txt” run output, you should see a line that reads: “To re-run this diagnostic script, run:”, followed by a line with a command that will allow you to re-run your diagnostic script only. Append this line with the “-i” option after the python script you call to re-run your diagnostic.
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{: .solution}
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> ## Your recipe’s name/project/reference isn’t recognised by ESMValTool. Error message is “ValueError: Tag 'NAME' does not exist in section 'authors' of path/esmvaltool/config-references.yml”
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> ## Your recipe’s name/project/reference isn’t recognised by ESMValTool. Error message is `ValueError: Tag 'NAME' does not exist in section 'authors' of path/esmvaltool/config-references.yml`
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> Most likely, you added your own name to the recipe in the description section, but didn’t add it to the esmvaltool/config-references.yml file, where the names are linked to an email address, institute, and ORCID Identity.
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{: .solution}

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