Abstract
Significant biases of coupled general circulation models (CGCMs) lead to considerable uncertainty in climate predictions and projections. Based on the historical simulations in the phase 5 of the Coupled Model Intercomparison Project (CMIP5), we identify that state-of-the-art CGCMs commonly simulate insufficient Indian summer monsoon (ISM) rainfall along with too weak monsoon circulations. Such ISM rainfall/circulation biases, however, are absent in the Atmospheric Model Intercomparison Project simulations forced by observed sea surface temperature (SST), suggesting that the common ISM biases are not intrinsic errors of the atmospheric models but arise from the interaction between the monsoon and the oceans. A multimodel statistical analysis further shows that the ISM rainfall/circulation biases in CMIP5 models can be traced back to the excessively cold SST over the northern Indian Ocean (NIO). The systemic cold SST biases in the NIO suppress local convective activity and reduce air temperature, resulting in a weak north–south thermal contrast in the mid-upper troposphere. This would induce an excessively weak ISM circulation and resultant insufficient monsoon rainfall. Furthermore, the dynamic effect of cold NIO SST biases on the ISM rainfall/circulation simulations is also confirmed through several sensitivity experiments by using the widely-applied Weather Research and Forecasting model. To the extent that the cold SST biases over the NIO may originate from an excessively strong Indian winter monsoon, improving the winter monsoon simulation is an important prerequisite for better summer climate simulations and predictions/projections over the broad ISM region.
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Acknowledgements
This work was supported jointly by the National Key Scientific Research Plan of China (Grant 2014CB953900), the National Natural Science Foundation of China (Grants 41605038, 41661144019, 41690123, and 41406026), the Natural Science Foundation of Guangdong Province (Grant 2015A030310224), the Guangzhou Joint Research Center for Atmospheric Sciences of CMA, the Guangdong Natural Science Funds for Distinguished Young Scholar (2015A030306008), the Youth Innovation Promotion Association CAS, the Pearl River S&T Nova Program of Guangzhou (201506010094), and the Open Project Program of State Key Laboratory of Tropical Oceanography (LTOZZ1603).
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Wang, Z., Li, G. & Yang, S. Origin of Indian summer monsoon rainfall biases in CMIP5 multimodel ensemble. Clim Dyn 51, 755–768 (2018). https://doi.org/10.1007/s00382-017-3953-x
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DOI: https://doi.org/10.1007/s00382-017-3953-x