Fig 1.
An illustrative example of pattern scaling for annual mean precipitation in a single model (in this case, CESM2-WACCM) over the historical period.
Top left shows the slopes (precipitation per degree global average temperature change) of the regression lines at each grid point (mm day−1 K−1). Top right shows the intercepts of the regression lines (mm day−1). Bottom left shows the generated precipitation (P(x)) time series calculated as where m(x) is slope,
is global mean temperature averaged over the last 20 years of simulation (for the historical period 1995–2014), b(x) is intercept, and x is the spatial dimension. Bottom right shows the residual (mm day−1) of generated minus the actual model output, again averaged over the last 20 years of simulation.
Table 1.
The number of models available via Pangeo for each scenario/variable combination.
60 models had their output available in Pangeo at the time of our analysis.
Fig 2.
In each grid box, percentage of models where the surface air temperature (tas) residual for annual mean pattern scaling is within one standard deviation of the model output.
Fig 3.
As in Fig 2 but for precipitation (pr).
Fig 4.
As in Fig 2 but for surface relative humidity (hurs).
Fig 5.
An aggregate of Figs 2–4 illustrating for each grid point the number of scenarios for which the value (percent of models within one standard deviation of baseline) is at least 90%.
Fig 6.
Box plot of root mean square error (RMSE) of pattern scaling, calculated as the number of standard deviations the generated output is from the actual model output (calculated over the last 20 years of simulation), for each scenario (panels) and for temperature (tas), precipitation (pr), and relative humidity (hurs) in a variety of regions.
Red lines indicate the median model, blue boxes indicate the inter-quartile range, and whiskers indicate the full model range. Because so few models participated in ssp434, we show the RMSE values for each model.
Fig 7.
Heatmap of the number of standard deviations (colors) the generated output is from the actual model output for each model in each scenario (panels; calculated from the last 20 years of each simulation) for temperature (tas), precipitation (pr), and relative humidity (hurs) in a variety of regions.
White squares (marked by NaN) indicate that there is no model output available for that model/variable combination on Pangeo.
Fig 8.
Climatology of monthly climatology surface air temperature (°C) residuals (generated output minus actual model output) calculated over six different regions of the globe.
Each line indicates a model/scenario combination (values shown are averages over the last 20 years of simulation), and the thick black line indicates the average over all models/scenarios. x-axis indicates the month of the climatology.
Fig 9.
As in Fig 8 but for precipitation (mm day−1).
Fig 10.
As in Fig 8 but for surface relative humidity (%).