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

../_images/bias_vs_change.png

Fig. 35 “Bias and change for each variable”

metricBias (RMSD of all gridpoints)Mean change (Future - Reference)
variableTemperature (K)Precipitation (kg/m2/s)Temperature (K)Precipitation (kg/m2/s)
dataset
CMIP5_ACCESS1-0_r1i1p13.19e+001.96e-052.36e+008.00e-09
CMIP5_BNU-ESM_r1i1p14.08e+001.87e-052.44e+002.96e-08
CMIP6_ACCESS-CM2_r1i1p1f13.75e+001.77e-052.87e+006.63e-07
CMIP6_ACCESS-ESM1-5_r1i1p1f13.01e+001.96e-052.63e+00-1.39e-07
CMIP6_AWI-CM-1-1-MR_r1i1p1f12.91e+001.80e-052.56e+007.67e-07
CMIP6_BCC-CSM2-MR_r1i1p1f14.22e+001.74e-052.64e+005.02e-07
CMIP6_CAMS-CSM1-0_r1i1p1f14.43e+001.84e-051.48e+004.89e-07
CMIP6_CESM2-WACCM_r1i1p1f12.95e+001.69e-052.33e+00-1.91e-07
CMIP6_CanESM5_r1i1p1f12.81e+001.69e-053.36e+002.10e-06
CMIP6_FGOALS-g3_r1i1p1f16.74e+001.80e-052.13e+005.95e-07
CMIP6_FIO-ESM-2-0_r1i1p1f13.02e+001.75e-052.07e+001.89e-07
CMIP6_MIROC6_r1i1p1f14.00e+001.74e-052.25e+00-2.45e-07
CMIP6_MPI-ESM1-2-HR_r1i1p1f12.98e+001.80e-051.84e+001.18e-07
CMIP6_MPI-ESM1-2-LR_r1i1p1f12.95e+001.78e-051.82e+002.52e-07
CMIP6_MRI-ESM2-0_r1i1p1f12.81e+001.71e-052.36e+005.75e-07
CMIP6_NESM3_r1i1p1f13.90e+001.83e-053.22e+003.60e-07
CMIP6_NorESM2-LM_r1i1p1f13.08e+001.70e-051.74e+00-4.97e-07
CMIP6_NorESM2-MM_r1i1p1f12.86e+001.67e-051.76e+00-7.65e-07