Evaluation of CMIP6 Global Climate Models for Simulating Land Surface Energy and Water Fluxes During 1979–2014

• Published in: Journal of Advances in Modeling Earth Systems
• Main Authors: Jianduo Li, Chiyuan Miao, Wei Wei, Guo Zhang, Lijuan Hua, Yueli Chen, Xiaoxiao Wang
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union (AGU) 2021
• Subjects: land surface model; CMIP6; water flux; energy flux; model evaluation; Physical geography; GB3-5030; Oceanography; GC1-1581; Greenland; Antarc*; Antarctica
• Online Access: https://doi.org/10.1029/2021MS002515; https://doaj.org/article/7857a87783494c7d8192afd2a64835d3

Abstract This study examined the overall performance of the climate models in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating the key energy and water fluxes over land. For this purpose, this study selected multiple land flux products as reference data sets and assessed the global spatial means, patterns, trends, seasonal cycles, and regional mean estimates of the sensible heat (SH), latent heat (LH), net radiation (RN), runoff (RF), and precipitation (PR) simulated by 32 CMIP6 models in recent decades. The global (Antarctica, Greenland, and hot deserts are not included) mean SH, LH, RN, RF, and PR simulated by the CMIP6 models are 37.55 ± 4.81 W m−2, 49.88 ± 5.31 W m−2, 89.10 ± 4.45 W m−2, 351.31 ± 95.28 mm yr−1, and 948.35 ± 88.77 mm yr−1, respectively. The ensemble median of CMIP6 simulations (CMIP6‐MED) can provide robust estimates of global and regional land fluxes, which are within the ranges given by the reference data sets, and highly consistent spatiotemporal patterns of these fluxes. The comparison of CMIP6‐MED with the first preferred reference data sets shows that CMIP6‐MED generally overestimates the water and energy fluxes over land, except for the simulated RF and PR in the Amazon region. The most disagreements between CMIP6‐MED and the reference data sets occur in South America (particularly the Amazon region) and the Tibetan Plateau. Finally, the sources of model biases are discussed. It is suggested that current land flux products should be widely used to optimize the structures and parameters of climate models in future work.