U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies

doi:10.1007/s00376-023-3179-2

IOCAS-IR > 海洋环流与波动重点实验室

	U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies
	Du, Shuangying 1,4; Zhang, Rong-Hua2,3,4
	2024-04-05
发表期刊	ADVANCES IN ATMOSPHERIC SCIENCES
ISSN	0256-1530
页码	14
通讯作者	Zhang, Rong-Hua([email protected])
摘要	El Nino-Southern Oscillation (ENSO) is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific, and numerous dynamical and statistical models have been developed to simulate and predict it. In some simplified coupled ocean-atmosphere models, the relationship between sea surface temperature (SST) anomalies and wind stress (tau) anomalies can be constructed by statistical methods, such as singular value decomposition (SVD). In recent years, the applications of artificial intelligence (AI) to climate modeling have shown promising prospects, and the integrations of AI-based models with dynamical models are active areas of research. This study constructs U-Net models for representing the relationship between SSTAs and tau anomalies in the tropical Pacific; the UNet-derived tau model, denoted as tau UNet, is then used to replace the original SVD-based tau model of an intermediate coupled model (ICM), forming a newly AI-integrated ICM, referred to as ICM-UNet. The simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial Pacific. In the ocean-only case study, the tau UNet-derived wind stress anomaly fields are used to force the ocean component of the ICM, the results of which also indicate reasonable simulations of typical ENSO events. These results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling studies. Furthermore, the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies.
关键词	U-Net models wind stress anomalies ICM integration of AI and physical components
DOI	10.1007/s00376-023-3179-2
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China (NFSC)[42030410]; National Natural Science Foundation of China (NFSC)[LSKJ202202402]; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB40000000]; Startup Foundation for Introducing Talent of NUIST
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:001197362700002
出版者	SCIENCE PRESS
WOS关键词	SEA-SURFACE TEMPERATURE ; TELECONNECTIONS ; VARIABILITY ; PREDICTION ; FORECASTS ; TIME
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/185083
专题	海洋环流与波动重点实验室
通讯作者	Zhang, Rong-Hua
作者单位	1.Chinese Acad Sci, Key Lab Ocean Circulat & Waves, Inst Oceanol, Qingdao 266071, Peoples R China 2.Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing 210044, Peoples R China 3.Laosan Lab, Qingdao 266237, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
第一作者单位	海洋环流与波动重点实验室
推荐引用方式 GB/T 7714	Du, Shuangying,Zhang, Rong-Hua. U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies[J]. ADVANCES IN ATMOSPHERIC SCIENCES,2024:14.
APA	Du, Shuangying,&Zhang, Rong-Hua.(2024).U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies.ADVANCES IN ATMOSPHERIC SCIENCES,14.
MLA	Du, Shuangying,et al."U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies".ADVANCES IN ATMOSPHERIC SCIENCES (2024):14.