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gregrmundayJon-Lillisehogan
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CMIP6 climate patterns (#2785)
Co-authored-by: Jon Lillis <jonathan.lillis@hotmail.com> Co-authored-by: Emma Hogan <ehogan@users.noreply.github.com>
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.zenodo.json

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"affiliation": "DLR, Germany",
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"name": "Bonnet, Pauline",
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"orcid": "0000-0003-3780-0784"
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},
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{
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"affiliation": "MetOffice, UK",
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"name": "Munday, Gregory",
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"orcid": "0000-0003-4750-9923"
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}
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],
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"description": "ESMValTool: A community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP.",

CITATION.cff

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family-names: Bonnet
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given-names: Pauline
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orcid: "https://orcid.org/0000-0003-3780-0784"
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-
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affiliation: "MetOffice, UK"
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family-names: Munday
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given-names: Gregory
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orcid: "https://orcid.org/0000-0003-4750-9923"
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cff-version: 1.2.0
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date-released: 2023-12-20
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doc/sphinx/source/recipes/index.rst

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:maxdepth: 1
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recipe_miles
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recipe_climate_patterns
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recipe_clouds
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recipe_cmug_h2o
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recipe_crem
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.. _recipes_climate_patterns:
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Generating Climate Patterns from CMIP6 Models
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=============================================
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Overview
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--------
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The recipe recipe_climate_patterns generates climate patterns from CMIP6 model
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datasets.
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.. note::
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The regrid setting in the recipe is set to a 2.5x3.75 grid. This is done to
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match the current resolution in the IMOGEN-JULES model, but can be
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adjusted with no issues for a finer/coarser patterns grid.
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Available recipes and diagnostics
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---------------------------------
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Recipes are stored in esmvaltool/recipes/
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* recipe_climate_patterns.yml
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Diagnostics are stored in esmvaltool/diag_scripts/climate_patterns/
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* climate_patterns.py: generates climate patterns from input datasets
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* sub_functions.py: set of sub functions to assist with driving scripts
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* plotting.py: contains all plotting functions for driving scripts
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User settings in recipe
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-----------------------
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#. Script climate_patterns.py
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*Required settings for script*
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None
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*Optional settings for script*
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* jules_mode: output jules-specific var names + .nc files
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* parallelise: parallelise over models or not
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* area: calculate the patterns globally, or over land only
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*Required settings for variables*
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* short_name
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* additional_datasets
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*Optional settings for variables*
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None
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*Required settings for preprocessor*
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* monthly_statistics: converts data to mean monthly data
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*Optional settings for preprocessor*
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* regrid: regrids data
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Variables
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---------
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#. Script climate_patterns.py
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* tasmax (atmos, monthly, longitude latitude time)
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* tasmin (atmos, monthly, longitude latitude time)
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* tas (atmos, monthly, longitude latitude time)
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* huss (atmos, monthly, longitude latitude time)
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* pr (atmos, monthly, longitude latitude time)
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* sfcWind (atmos, monthly, longitude latitude time)
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* ps (atmos, monthly, longitude latitude time)
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* rsds (atmos, monthly, longitude latitude time)
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* rlds (atmos, monthly, longitude latitude time)
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Observations and reformat scripts
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---------------------------------
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None
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References
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----------
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* Huntingford, C., Cox, P. An analogue model to derive additional climate
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change scenarios from existing GCM simulations.
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Climate Dynamics 16, 575–586 (2000). https://doi.org/10.1007/s003820000067
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* Mathison, C. T. et al. A rapid application emissions-to-impacts tool
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for scenario assessment: Probabilistic Regional Impacts from Model patterns
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and Emissions (PRIME).
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EGUsphere [preprint], (2024). https://doi.org/10.5194/egusphere-2023-2932
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Example plots
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-------------
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.. _fig_climate_patterns_2:
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.. figure:: /recipes/figures/climate_patterns/patterns.png
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:align: center
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:width: 80%
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Patterns generated for CMIP6 models, gridded view. Patterns are shown per
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variable, for the month of January.

esmvaltool/config-references.yml

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institute: BSC, Spain
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orcid:
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github: emchamarro
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munday_gregory:
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name: Munday, Gregory
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institute: MetOffice, UK
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orcid: https://orcid.org/0000-0003-4750-9923
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github: mo-gregmunday
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nikulin_grigory:
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name: Nikulin, Grigory
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institute: SMHI, Sweden

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