气候变化领域集成服务门户(CCPortal): Role of SST feedback in the prediction of the boreal summer monsoon intraseasonal oscillation

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DOI	10.1007/s00382-019-04753-w
	Role of SST feedback in the prediction of the boreal summer monsoon intraseasonal oscillation
	Zhang Y.; Hung M.-P.; Wang W.; Kumar A.
发表日期	2019
ISSN	0930-7575
起始页码	3861
结束页码	3875
卷号	53 期号:2020-07-08
英文摘要	This study investigates the impact of different specification of the underlying sea surface temperature (SST) on the prediction of intraseasonal rainfall variation associated with strong Monsoon Intraseasonal Oscillation (MISO) events in the northern Indian Ocean. A series of forecast experiments forced with observed hourly, daily, or seasonal SSTs are performed for three selected strong MISO events using the National Centers for Environmental Predictions (NCEP) atmospheric Global Forecast System (GFS). The comparison between these GFS forecasts shows that the intraseasonal SST variability is more important than its diurnal variability in the MISO prediction. The GFS experiments forced with daily SST which includes intraseasonal variability has higher prediction skill and faster speed in the northward propagation of the MISO intraseasonal rainfall anomalies than those forced with seasonal SST that do not include intraseasonal variability. No significant difference is found in the MISO prediction when GFS was forced by SST with or without SST diurnal cycle. The GFS runs forced with warmer and colder seasonal SSTs which mimic possible biases in SST prediction have comparable skill in the MISO prediction. A modified version of the NCEP Climate Forecast System coupled model (CFSm5) with 1- and 10-m vertical resolutions in the upper ocean is then used to examine their performance in the MISO prediction when all aspects of SST are actively included. The CFSm5 with 1-m vertical resolution in the upper ocean (CFSm501) shows larger amplitude of intraseasonal SST anomaly, with higher prediction skill in both intraseasonal SST and rainfall than the CFSm5 with the typical 10-m vertical resolution in the upper ocean (CFSm510) does. Compared with the uncoupled GFS, both CFSm501 and CFSm510, despite errors in predicted SSTs, have better prediction skill and more reasonable rainfall variability, which is attributed to the inclusion of active air–sea interaction. These results suggest the importance of intraseasonal variability of SST and air–sea interaction in improving the intraseasonal rainfall prediction associated with the MISO. © 2019, This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection.
语种	英语
scopus关键词	air-sea interaction; climate feedback; climate oscillation; climate prediction; diurnal variation; monsoon; precipitation (climatology); sea surface temperature; seasonal variation; Indian Ocean; Indian Ocean (North)
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/145963
作者单位	ESSIC, University of Maryland, College Park, MD, United States; NOAA/NWS/NCEP Climate Prediction Center, 5380 University Research Court, College Park, MD, United States; Chinese Culture University, Taipei, Taiwan
推荐引用方式 GB/T 7714	Zhang Y.,Hung M.-P.,Wang W.,et al. Role of SST feedback in the prediction of the boreal summer monsoon intraseasonal oscillation[J],2019,53(2020-07-08).
APA	Zhang Y.,Hung M.-P.,Wang W.,&Kumar A..(2019).Role of SST feedback in the prediction of the boreal summer monsoon intraseasonal oscillation.Climate Dynamics,53(2020-07-08).
MLA	Zhang Y.,et al."Role of SST feedback in the prediction of the boreal summer monsoon intraseasonal oscillation".Climate Dynamics 53.2020-07-08(2019).