Quick insights for climate impact researchers#
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/
Diagnostics are stored in esmvaltool/diag_scripts/
impact/bias_and_change.py: tabulate and visualize bias and change.
User settings in recipe#
Required settings for variables
'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.
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.
|metric||Bias (RMSD of all gridpoints)||Mean change (Future - Reference)|
|variable||Temperature (K)||Precipitation (kg/m2/s)||Temperature (K)||Precipitation (kg/m2/s)|