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Adding CMIP7 version of recipe_seaice_sensitivity.yml (#4453)
Co-authored-by: Bouwe Andela <b.andela@esciencecenter.nl>
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doc/sphinx/source/recipes/recipe_seaice_sensitivity.rst

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Recipe settings
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~~~~~~~~~~~~~~~
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Years to be evaluated are specified in the ``extract_test_period`` preprocessor. Arctic sea ice is evaluated using data from September, and Antarctic sea ice is evaluated using annually meaned data. This can be amended by changing the preprocessor for each variable (shown below).
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Years to be evaluated are specified with the ``start_year`` and ``end_year`` keywords in the model dataset section, which are automatically duplicated into the observational datasets section.
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.. code-block:: yaml
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model_defaults: &model_defaults { ..., start_year: &data_start 1979, end_year: &data_end 2014}
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Pre-calculated values for the mean sensitivity of sea ice area to global warming (and an associated standard deviation and plausible range) can be entered be for both arctic and antarctic diagnostics (more details are given in the "References" section below).
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.. code-block:: yaml
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diagnostics:
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arctic:
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scripts:
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sea_ice_sensitivity_script:
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observations:
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observation_period:
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start_year:
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end_year:
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sea_ice_sensitivity:
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mean:
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standard deviation:
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plausible range:
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If the years to be evaluated differ from those specified for pre-calculated observational values for either hemisphere, then the "observational period" is assumed to be a subset of the dataset evaluation period and all statistics will be calculated for both periods, with these results shown as two halves of the sensitivity (one dimensional) plot. The two dimensional plot will only use values from the entire evaluation period.
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Arctic sea ice is evaluated using data from September, and Antarctic sea ice is evaluated using annually meaned data. This can be amended by changing the preprocessor for each variable (shown below).
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.. code-block:: yaml
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pp_arctic_sept_sea_ice:
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extract_time:
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start_day: 1
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start_month: 1
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start_year: 1979
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end_day: 31
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end_month: 12
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end_year: 2014
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extract_month:
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month: 9
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extract_region:
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# ESMValTool
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---
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documentation:
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title: Sea ice sensitivity
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description: |
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Recipe for quantifying the sensitivity of sea ice to global warming.
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Siconc data is summed for each hemisphere and then compared to the
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change in globally meaned, annually meaned surface air temperature.
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In the northern hemisphere, September sea ice data is used.
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In the southern hemisphere, annual mean sea ice data is used.
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Two plots are produced for each hemisphere, one showing the gradient
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of the direct regression of sea ice area over temperature, and the
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other showing the two separate trends over time.
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authors:
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- parsons_naomi
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- sellar_alistair
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- blockley_ed
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maintainer:
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- parsons_naomi
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# The default period has been chosen to end in 2020 as this is the last year available in the sea ice observations
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model_defaults: &model_defaults {activity: CMIP, project: CMIP7, exp: historical, start_year: &data_start 1979, end_year: &data_end 2020}
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model_datasets: &model_datasets
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- {<<: *model_defaults, dataset: MOCK-MODEL-LL, institute: MOHC, ensemble: r1i1p1f3, exp: 1pctCO2, grid: g100, label_dataset: True}
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obs_defaults: &obs_defaults { project: OBS, observation: True, tier: 2, start_year: *data_start, end_year: *data_end}
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tasa_obs: &tasa_obs
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- { <<: *obs_defaults, dataset: HadCRUT5, type: ground, version: 5.0.1.0-analysis, mip: Amon }
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- { <<: *obs_defaults, dataset: NOAAGlobalTemp, type: ground, version: v5.0.0, mip: Amon }
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arctic_siconc_obs: &arctic_siconc_obs
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- { <<: *obs_defaults, dataset: OSI-450-nh, type: reanaly, version: v3, mip: OImon}
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antarctic_siconc_obs: &antarctic_siconc_obs
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- { <<: *obs_defaults, dataset: OSI-450-sh, type: reanaly, version: v3, mip: OImon}
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preprocessors:
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nh_total_area:
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&nh_total_area
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extract_region:
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start_longitude: 0
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end_longitude: 360
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start_latitude: 0
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end_latitude: 90
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area_statistics:
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operator: sum
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convert_units:
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units: 1e6 km2
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sh_total_area:
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&sh_total_area
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extract_region:
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start_longitude: 0
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end_longitude: 360
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start_latitude: -90
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end_latitude: 0
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area_statistics:
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operator: sum
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convert_units:
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units: 1e6 km2
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global_mean:
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&global_mean
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area_statistics:
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operator: mean
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annual_mean:
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&annual_mean
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annual_statistics:
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operator: mean
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extract_sept:
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&extract_sept
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extract_month:
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month: 9
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pp_arctic_sept_sea_ice:
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<<: *extract_sept
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<<: *nh_total_area
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pp_antarctic_avg_ann_sea_ice:
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<<: *annual_mean
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<<: *sh_total_area
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pp_avg_ann_global_temp:
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<<: *global_mean
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<<: *annual_mean
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diagnostics:
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arctic:
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description: Plots September sea ice sensitivity above 0 latitude in millions of square kilometres
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variables:
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siconc: &siconc
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preprocessor: pp_arctic_sept_sea_ice
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mip: seaIce
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frequency: mon
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region: glb
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branding_suffix: tavg-u-hxy-u
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additional_datasets:
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*model_datasets
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siconc_obs:
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<<: *siconc
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short_name: siconc
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additional_datasets:
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*arctic_siconc_obs
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tas: &tas
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preprocessor: pp_avg_ann_global_temp
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mip: atmos
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frequency: mon
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region: glb
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branding_suffix: tavg-h2m-hxy-u
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additional_datasets:
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*model_datasets
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tasa_obs: &tasa
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<<: *tas
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short_name: tasa
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additional_datasets:
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*tasa_obs
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scripts:
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sea_ice_sensitivity_script:
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script: seaice/seaice_sensitivity.py
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observations:
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observation_period:
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start_year: 1979
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end_year: 2014
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sea_ice_sensitivity:
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mean: -4.01
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standard_deviation: 0.32
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plausible_range: 1.28
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antarctic:
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description: Plots annual mean sea ice sensitivity below 0 latitude in millions of square kilometres
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variables:
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siconc:
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<<: *siconc
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preprocessor: pp_antarctic_avg_ann_sea_ice
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additional_datasets:
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*model_datasets
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siconc_obs:
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<<: *siconc
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short_name: siconc
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preprocessor: pp_antarctic_avg_ann_sea_ice
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additional_datasets:
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*antarctic_siconc_obs
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tas:
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<<: *tas
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tasa_obs:
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<<: *tasa
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scripts:
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sea_ice_sensitivity_script:
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script: seaice/seaice_sensitivity.py

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