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Quick insights for climate impact researchers

Overview

Many impact researchers do not have the time and finances to use a large ensemble of climate model runs for their impact analysis. To get an idea of the range of impacts of climate change it also suffices to use a small number of climate model runs. In case a system is only sensitive to annual temperature, one can select a run with a high change and one with a low change of annual temperature, preferably both with a low bias.

This recipe calculates the bias with respect to observations, and the change with respect to a reference period, for a wide range of (CMIP) models. These metrics are tabulated and also visualized in a diagram.

Available recipes and diagnostics

Recipes are stored in esmvaltool/recipes/

  • recipe_impact.yml

Diagnostics are stored in esmvaltool/diag_scripts/

  • impact/bias_and_change.py: tabulate and visualize bias and change.

User settings in recipe

  1. Script impact.py

    Required settings for variables

    • tag: 'model' or 'observations', so the diagnostic script knows which datasets to use for the bias calculation. This must be specified for each dataset.

    Optional settings for preprocessor

    • Region and time settings (both for the future and reference period) can be changed at will.

Variables

  • tas (atmos, mon, longitude latitude time)
  • pr (atmos, mon, longitude latitude time)
  • any other variables of interest

Observations and reformat scripts

  • ERA5 data can be used via the native6 project.

References

  • None

Example plots

"Bias and change for each variable"

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