气候变化领域集成服务门户(CCPortal): Seasonal prediction skills in the CAMS-CSM climate forecast system

CCPortal

DOI	10.1007/s00382-021-05848-z
	Seasonal prediction skills in the CAMS-CSM climate forecast system
	Liu B.; Su J.; Ma L.; Tang Y.; Rong X.; Li J.; Chen H.; Liu B.; Hua L.; Wu R.
发表日期	2021
ISSN	0930-7575
英文摘要	The seasonal prediction skills in the CAMS-CSM (the acronym stands for the Chinese Academy of Meteorological Sciences Climate System Model) climate forecast system is evaluated with a set of retrospective forecast experiments during the period of 1981–2019. The CAMS-CSM, which has been registered for the sixth phase of the coupled model intercomparison project (CMIP6), is an atmosphere–ocean–land–sea ice fully coupled general circulation model. The assimilation scheme used in the forecast system is the 3-dimentional nudging, including both the atmospheric and oceanic components. The analyses mainly focus on the seasonal predictable skill of sea surface temperature, 2-m air temperature, and precipitation anomalies. The analyses revealed that the model shows a good prediction skill for the SST anomalies, especially in the tropical Pacific, in association with El Niño-Southern Oscillation (ENSO) events. The anomaly correlation coefficient (ACC) score for ENSO can reach 0.75 at 6-month lead time. Furthermore, the extreme warm/cold Indian Ocean dipole (IOD) events are successfully predicted at 3- and even 6-month lead times. The whole ACC of IOD events between the observation and the prediction can reach 0.51 at 2-month lead time. There are reliable seasonal prediction skills for 2-m air temperature anomalies over most of the Northern Hemisphere, where the correlation is mainly above 0.4 at 2-month lead time, especially over the East Asia, North America and South America. However, the seasonal prediction for precipitation still faces a big challenge. The source of precipitation predictability over the East Asia can be partly related to strong ENSO events. Additionally, the anomalous anticyclone over the western North Pacific (WPAC) which connects the ENSO events and the East Asian summer monsoon (EASM) can be well predicted at 6-month lead time. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	Climate anomalies; Ensemble hindcast; ENSO; Seasonal prediction
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/183416
作者单位	State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences, Beijing, China; State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, China; Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; School of Earth Sciences, Zhejiang University, Hangzhou, Zhejiang, China
推荐引用方式 GB/T 7714	Liu B.,Su J.,Ma L.,et al. Seasonal prediction skills in the CAMS-CSM climate forecast system[J],2021.
APA	Liu B..,Su J..,Ma L..,Tang Y..,Rong X..,...&Wu R..(2021).Seasonal prediction skills in the CAMS-CSM climate forecast system.Climate Dynamics.
MLA	Liu B.,et al."Seasonal prediction skills in the CAMS-CSM climate forecast system".Climate Dynamics (2021).