Both polar and topography-featured regions such as the Tibetan Plateau play essential roles in the mean state, variability, and long-term trend of global climate system. Therefore, correct simulation of the climate over these regions is pivotal for better understanding and even predicting the climate variability and changes on various time scales. However, a recent study by the Innovation Team for Ocean-Land-Atmosphere Interaction and Global Effect of the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) found that there exist polar and topographic amplifications in the simulation of surface temperature by climate models, and hence more efforts are needed to improve the models’ capability of better simulation over these key regions of the global climate system.

It is shown that similarity exists in the spatial patterns of the intermodel spread, mean absolute errors, and absolute mean errors of surface temperature simulations in climate ensembles. Therefore, one may use the intermodel spread to help understand the mean model biases. The authors found that the regions with maximum surface temperature spread (TS-SPREAD) were mainly located in the northern polar (NP) and southern polar (SP) regions, and those regions with large orographic features such as the Tibetan Plateau, indicating polar and topographic amplifications of TS-SPREAD in climate models. In the paper, the authors reveal the process-chains that lead to the spatial pattern and seasonality of amplified TS-SPREAD over these regions.

Figure 1: Intermodel spread of the convergence of atmospheric energy transport (AET) in CMIP6 models (W/m2). The first row is the spread averaged over June, July, and August (JJA), and the second row is averaged over December, January, and February (DJF). Positive values denote that warm models have stronger convergence of AET, and negative values mean that warm models have stronger divergence of AET. Inside the red circles (or box) in each column from the left to the right is the spread for the NP, SP, and TP regions, respectively.

The authors stated that sea ice contributes to the TS-SPREAD over the NP and SP oceans, not in a direct way, but by its coupling with ocean storage, as well as interseasonal heat release through turbulent fluxes and the horizontal heat transport, both across the border of and inside the polar regions. They also provided a method to distinguish the role of local versus nonlocal contributions to the TS-SPREAD and the spreads in sea ice and land snow/ice.

This work entitled “Polar and Topographic Amplifications of Intermodel Spread of Surface Temperature in Climate Models” has been published in Journal of Geophysical Research - Atmospheres in February 2023. Dr. Jianhua Lu, from the School of Atmospheric Sciences of Sun Yat-sen University and the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), and his graduate student Tao Wang are respectively the corresponding author and the first author.

This study was jointly supported by the National Natural Science Foundation of China, the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), and the Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies.

Paper link:https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022JD037509