Regional ensemble of CMIP6 global climate models for Sakha (Yakutia) Republic, Northern Eurasia

Abstract

Future climate projections based on multi-model ensemble approach are seen as more reliable, but not all models are equally performant at reproducing climate features at a regional scale. An optimal regional GCM ensemble was developed for Sakha (Yakutia) Republic based on error statistics and spatial correlation metrics. Historical Coupled Model Intercomparison Project, version 6 (CMIP6) simulations from 48 global climate models (GCMs) were used to evaluate model quality compared to mean annual air temperature (MAAT) reanalysis data for 1961–1990, 1971–2000 and 1981–2010 reference periods, and the MAAT change between 1961-1990 and 1981–2010, ΔT81-61. The best-performing reanalysis, GHCN-CAMS, was validated using observational data. This five-member ensemble includes CESM2-WACCM, CMCC-ESM2, CNRM-CM6-1-HR, INM-CM5-0, MPI-ESM1-2-HR models, weighted by Pearson's coefficient of spatial correlation between observed and modeled ΔT81-61 fields. Model weighting based on spatial correlation metrics improved the performance of the developed multi-model regional ensemble, which can be used in projecting future climate under different climate change scenarios.