Net Surface Energy Flux over the Globe and Asian Monsoon Region from CMIP6 High-Resolution Models

Abstract

The net surface energy flux (F_s) is critical to the Earth’s energy budget and surface processes, but its simulation remains uncertain in global and regional scales. This study investigates simulated F_s biases and sources globally and in the Asian monsoon region (AMR) using CMIP6 HighResMIP atmospheric models. Globally, the multi-model mean can reproduce the observed global multiannual mean F_s. The majority of models overestimate the annual mean F_s, net surface shortwave radiation (SW_s) and longwave radiation (LW_s) but underestimate the turbulent heat flux (THF). In AMR, the F_s is predominantly upward during winter and downward during summer owing to the seasonal variation in SW_s and THF. 95% of the winter F_s bias over AMR comes from THF primarily due to the latent heat flux bias. SW_s and THF contribute 40%~90% and 70%~90% to summer F_s bias, respectively. The systematic biases of SW_s and LW_s can be attributed to biases in circulation patterns and cloud cover, while biases in THF are primarily influenced by the near-surface processes. The high-resolution models perform well in F_s, THF, and low-level circulation, particularly in DJF. The winter multi-model mean error is reduced by 21.5%~63.6% in F_s and 25.5%~76.7% in THF across three subregions of AMR. Seven out of nine high-resolution models show higher skill scores of winter F_s and THF than their low-resolution counterparts in SA, with corresponding model number being 8 (F_s) and 7 (THF) in both EA and WNP. This study reveals the advantages of increased horizonal resolution in the F_s simulation.