Bayesian Estimates of the Snow Cover Extent in Eurasia in the 21st Century Based on the Calculations with the CMIP6 Ensemble of Climate Models.

Based on the results of calculations with the CMIP6 ensemble of global climate models, quantitative estimates of changes in the snow cover extent (SCE) in Eurasia in the 21st century are obtained under SSP2-4.5 and SSP5-8.5 scenarios of anthropogenic impacts using the Bayesian approach. The contribution (weight) of the models to the overall ensemble estimates has been determined by the accuracy of reproduction of the long-term average, trend, and interannual variability of the SCE in Eurasia from satellite data. The largest intermodel variations in the estimates, increasing during the summer and fall months, are associated with the reproduction of the trend component and interannual variability (variance) of the SCE in Eurasia, as well as with equal-weighted averaging. It is shown that, when Bayesian weights are used, the uncertainty of snow cover area estimates can be halved compared to the ensemble average with model weights being equal. The ensemble estimates of the SCE obtained by using combined Bayesian weights exceed the corresponding estimates during equal-weighted averaging. [ABSTRACT FROM AUTHOR]