Improvement of an extended ensemble coupled data Assimilation-Forecast system and its application in El Nino diversity predictions

doi:10.1016/j.ocecoaman.2023.106917

IOCAS-IR > 海洋环流与波动重点实验室

	Improvement of an extended ensemble coupled data Assimilation-Forecast system and its application in El Nino diversity predictions
	Gao, Yanqiu 1,2; Zhang, Jicai 3; Liu, Kui 4; Chen, Haibo 5; Xu, Minjie 6
	2024
发表期刊	OCEAN & COASTAL MANAGEMENT
ISSN	0964-5691
卷号	247 页码:15
通讯作者	Zhang, Jicai(jicai_zhang@163.com) ; Liu, Kui(liukui@sio.org.cn)
摘要	The El Nin similar to o-Southern Oscillation (ENSO) can cause climate anomalies on a global scale, and further affect human life and activities in coastal zones. Therefore, its forecast is of great significance for early disaster warning and coastal management. However, the frequent occurrence of central Pacific (CP) El Nin similar to o events increases the diversity and complexity of ENSO, severely reducing its prediction efficiency. In this study, an extended ensemble coupled data assimilation-forecast system was employed to investigate the prediction of different types of El Nin similar to o events, including eastern Pacific (EP) and CP events. The extended system was based on the fifthgeneration Lamont-Doherty Earth Observation (LDEO5) model, in which an advanced ensemble Kalman filter was used to construct a multisource data assimilation system, and a stochastic optimal method was used to measure the influence of atmospheric stochastic processes on model prediction errors. The extended system was used to predict two types of El Nin similar to o events that occurred between January 1950 and December 2018. The results showed that the extended system was generally able to predict EP events with a higher accuracy than CP events for all lead times. The extended system successfully predicted the mature phase of EP events up to 12 months in advance but could only predict the mature phase of CP events up to 6 months in advance. The extended system was also able to depict the evolution of both EP and CP events, although the sea surface temperature anomalies were underestimated. The extended system not only provides a useful platform for improving ENSO prediction accuracies in association with El Nin similar to o diversity but also provides an important tool for disaster early warning and coastal management.
关键词	Ensemble Kalman filter Data assimilation Forecast system
DOI	10.1016/j.ocecoaman.2023.106917
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[41876086] ; National Natural Science Foundation of China[42227901] ; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)[SML2021SP314] ; Scientific Research Fund of the Second Institute of Oceanography, MNR[JG 1809] ; Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)[311022006]
WOS研究方向	Oceanography ; Water Resources
WOS类目	Oceanography ; Water Resources
WOS记录号	WOS:001165126000001
出版者	ELSEVIER SCI LTD
WOS关键词	WESTERLY WIND BURSTS ; ENSO PREDICTION ; NIO EVENTS ; TROPICAL PACIFIC ; PREDICTABILITY ; OCEAN ; MODEL ; FREQUENCY ; PROGRESS ; IMPACTS
引用统计
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/184599
专题	海洋环流与波动重点实验室
通讯作者	Zhang, Jicai; Liu, Kui
作者单位	1.Minist Nat Resources, Inst Oceanog 2, State Key Lab Satellite Ocean Environm Dynam, Hangzhou, Peoples R China 2.Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai, Peoples R China 3.East China Normal Univ, State Key Lab Estuarine & Coastal Res, Shanghai, Peoples R China 4.Ningbo Inst Oceanog, Ningbo, Peoples R China 5.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China 6.Yantai Univ, Sch Ocean, Yantai, Peoples R China
推荐引用方式 GB/T 7714	Gao, Yanqiu,Zhang, Jicai,Liu, Kui,et al. Improvement of an extended ensemble coupled data Assimilation-Forecast system and its application in El Nino diversity predictions[J]. OCEAN & COASTAL MANAGEMENT,2024,247:15.
APA	Gao, Yanqiu,Zhang, Jicai,Liu, Kui,Chen, Haibo,&Xu, Minjie.(2024).Improvement of an extended ensemble coupled data Assimilation-Forecast system and its application in El Nino diversity predictions.OCEAN & COASTAL MANAGEMENT,247,15.
MLA	Gao, Yanqiu,et al."Improvement of an extended ensemble coupled data Assimilation-Forecast system and its application in El Nino diversity predictions".OCEAN & COASTAL MANAGEMENT 247(2024):15.