Added value of the regionally coupled model ROM in the East Asian summer monsoon modeling
The performance of the regional atmosphere-ocean coupled model ROM (REMO-OASIS-MPIOM) is compared with its atmospheric component REMO in simulating the East Asian summer monsoon (EASM) during the time period 1980–2012 with the following results being obtained. (1) The REMO model in the standalone configuration with the prescribed sea surface conditions produces stronger low-level westerlies associated with the South Asian summer monsoon, an eastward shift of the western Pacific subtropical high (WPSH) and a wetter lower troposphere, which jointly lead to moisture pathways characterized by stronger westerlies with convergence eastward to the western North Pacific (WNP). As a consequence, the simulated precipitation in REMO is stronger over the ocean and weaker over the East Asian continent than in the observational datasets. (2) Compared with the REMO results, lower sea surface temperatures (SSTs) feature the ROM simulation with enhanced air-sea exchanges from the intensified low-level winds over the subtropical WNP, generating an anomalous low-level anticyclone and hence improving simulations of the low-level westerlies and WPSH. With lower SSTs, ROM produces less evaporation over the ocean, inducing a drier lower troposphere. As a result, the precipitation simulated by ROM is improved over the East Asian continent but with dry biases over the WNP. (3) Both models perform fairly well for the upper level circulation. In general, compared with the standalone REMO model, ROM improves simulations of the circulation associated with the moisture transport in the lower- to mid-troposphere and reproduces the observed EASM characteristics, demonstrating the advantages of the regionally coupled model ROM in regions where air-sea interactions are highly relevant for the East Asian climate.
The anonymous reviewers are thanked for their constructive comments, which greatly improved this paper. We also thank Dr. Xiuhua Zhu and Dr. Torsten Weber for their extensive advices. We are grateful to ECMWF, NASA, and NOAA for access to their data products. The study was realized through access to the computing resources from the German Climate Computing Center (DKRZ).
The authors acknowledge the joint financial support of the National Key R&D Program of China (Grant No. 2017YFC1502002), the National Natural Science Foundation of China (Grant Nos 41575104 and 41805056), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant No. KYCX17_0875), the Scientific Research Foundation of CUIT (KYTZ201730), the Project Supported by Scientific Research Fund of Sichuan Provincial Education Department (18ZB0112), the Open Research Fund Program of KLME, NUIST (KLME201809), the PRIMAVERA project funded by the European Union’s Horizon 2020 program (Grant Agreement No. 641727), the state assignment of FASO Russia (Theme Nos 0149-2018-0014 and 0149-2019-0015), and the China Scholarship Council (Nos 201608320193 and 201808510009).
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