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| 1 | +.. _recipes_climate_patterns: |
| 2 | + |
| 3 | +Generating Climate Patterns from CMIP6 Models |
| 4 | +============================================= |
| 5 | + |
| 6 | +Overview |
| 7 | +-------- |
| 8 | + |
| 9 | +The recipe recipe_climate_patterns generates climate patterns from CMIP6 model |
| 10 | +datasets. |
| 11 | + |
| 12 | +.. note:: |
| 13 | + The regrid setting in the recipe is set to a 2.5x3.75 grid. This is done to |
| 14 | + match the current resolution in the IMOGEN-JULES model, but can be |
| 15 | + adjusted with no issues for a finer/coarser patterns grid. |
| 16 | + |
| 17 | + |
| 18 | +Available recipes and diagnostics |
| 19 | +--------------------------------- |
| 20 | + |
| 21 | +Recipes are stored in esmvaltool/recipes/ |
| 22 | + |
| 23 | +* recipe_climate_patterns.yml |
| 24 | + |
| 25 | +Diagnostics are stored in esmvaltool/diag_scripts/climate_patterns/ |
| 26 | + |
| 27 | +* climate_patterns.py: generates climate patterns from input datasets |
| 28 | +* sub_functions.py: set of sub functions to assist with driving scripts |
| 29 | +* plotting.py: contains all plotting functions for driving scripts |
| 30 | + |
| 31 | + |
| 32 | +User settings in recipe |
| 33 | +----------------------- |
| 34 | + |
| 35 | +#. Script climate_patterns.py |
| 36 | + |
| 37 | + *Required settings for script* |
| 38 | + |
| 39 | + None |
| 40 | + |
| 41 | + *Optional settings for script* |
| 42 | + |
| 43 | + * jules_mode: output jules-specific var names + .nc files |
| 44 | + * parallelise: parallelise over models or not |
| 45 | + * area: calculate the patterns globally, or over land only |
| 46 | + |
| 47 | + *Required settings for variables* |
| 48 | + |
| 49 | + * short_name |
| 50 | + * additional_datasets |
| 51 | + |
| 52 | + *Optional settings for variables* |
| 53 | + |
| 54 | + None |
| 55 | + |
| 56 | + *Required settings for preprocessor* |
| 57 | + |
| 58 | + * monthly_statistics: converts data to mean monthly data |
| 59 | + |
| 60 | + *Optional settings for preprocessor* |
| 61 | + |
| 62 | + * regrid: regrids data |
| 63 | + |
| 64 | + |
| 65 | +Variables |
| 66 | +--------- |
| 67 | + |
| 68 | +#. Script climate_patterns.py |
| 69 | + |
| 70 | +* tasmax (atmos, monthly, longitude latitude time) |
| 71 | +* tasmin (atmos, monthly, longitude latitude time) |
| 72 | +* tas (atmos, monthly, longitude latitude time) |
| 73 | +* huss (atmos, monthly, longitude latitude time) |
| 74 | +* pr (atmos, monthly, longitude latitude time) |
| 75 | +* sfcWind (atmos, monthly, longitude latitude time) |
| 76 | +* ps (atmos, monthly, longitude latitude time) |
| 77 | +* rsds (atmos, monthly, longitude latitude time) |
| 78 | +* rlds (atmos, monthly, longitude latitude time) |
| 79 | + |
| 80 | + |
| 81 | +Observations and reformat scripts |
| 82 | +--------------------------------- |
| 83 | + |
| 84 | +None |
| 85 | + |
| 86 | +References |
| 87 | +---------- |
| 88 | + |
| 89 | +* Huntingford, C., Cox, P. An analogue model to derive additional climate |
| 90 | + change scenarios from existing GCM simulations. |
| 91 | + Climate Dynamics 16, 575–586 (2000). https://doi.org/10.1007/s003820000067 |
| 92 | + |
| 93 | +* Mathison, C. T. et al. A rapid application emissions-to-impacts tool |
| 94 | + for scenario assessment: Probabilistic Regional Impacts from Model patterns |
| 95 | + and Emissions (PRIME). |
| 96 | + EGUsphere [preprint], (2024). https://doi.org/10.5194/egusphere-2023-2932 |
| 97 | + |
| 98 | +Example plots |
| 99 | +------------- |
| 100 | + |
| 101 | +.. _fig_climate_patterns_2: |
| 102 | +.. figure:: /recipes/figures/climate_patterns/patterns.png |
| 103 | + :align: center |
| 104 | + :width: 80% |
| 105 | + |
| 106 | + Patterns generated for CMIP6 models, gridded view. Patterns are shown per |
| 107 | + variable, for the month of January. |
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