Assessing uncertainties in modeling the climate of the Siberian frozen soils by contrasting CMIP6 and LS3MIP

Abstract

Climate models and their land components still exhibit notable discrepancies in frozen soil simulations. Contrasting the historical runs of seven land-only models of the Land Surface, Snow, and Soil Moisture Model Intercomparison Project (LS3MIP) with their Coupled Model Intercomparison Project Phase 6 (CMIP6) counterparts allowed quantifying the contributions of the land surface parameterization scheme and the atmospheric forcing to the discrepancies. The simulation capabilities were assessed using observational data from 152 sites in Siberia and reanalysis data. In the winter months (December, January, and February), the LS3MIP ensemble bias in 0.2 m soil temperature was larger than the CMIP6 bias (-3.6 vs.-2.7 °C). The spread of winter 0.2 m soil temperatures was also larger in the LS3MIP ensemble (4.6 °C) than in the CMIP6 ensemble (3.0 °C). For permafrost sites, for all CMIP6 simulations, the correlations between winter soil temperatures with observations were below 0.6, and the correlations for spring/autumn correlations of snow depth were below 0.8. In the CMIP6 simulations, the median 0.2 m soil temperature was 0.3 °C warmer than in the observations when the simulated soil temperature dropped below-5 °C. However, the LS3MIP simulations were colder, with a cold bias in the median of 0.7 °C. The biases of 2 m temperature in coupled simulations had an opposite sign and were amplified in magnitude compared to the biases of their soil temperatures, especially below 0 °C. Our results indicate that land-only models have limited capability in reproducing soil temperatures and snow depth under severe cold conditions (surface air temperature below-15 °C). Furthermore, four climate models and their land components underestimated the insulating role of snow. In cases with shallow snow depth (0-0.2 m), the models simulated air-soil temperature differences of up to 10 °C, whereas in situ measurements indicated even larger differences. The CMIP6 models tended to compensate for errors in their land component with errors in the atmospheric model component. Therefore, to improve frozen soil modeling in climate projections, a more accurate representation of the surface-soil insulation is essential.