中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 海洋研究所
  3. 中国科学院海洋研究所
  4. 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

文献类型：期刊论文

作者Du, Shuangying1,4; Zhang, Rong-Hua1,2,3
刊名ADVANCES IN ATMOSPHERIC SCIENCES
出版日期2024-04-05
页码14
关键词U-Net models wind stress anomalies ICM integration of AI and physical components
ISSN号0256-1530
DOI10.1007/s00376-023-3179-2
通讯作者Zhang, Rong-Hua(rzhang@nuist.edu.cn)
英文摘要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.
WOS关键词SEA-SURFACE TEMPERATURE ; TELECONNECTIONS ; VARIABILITY ; PREDICTION ; FORECASTS ; TIME
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
语种英语
WOS记录号WOS:001197362700002
出版者SCIENCE PRESS
源URL[http://ir.qdio.ac.cn/handle/337002/185082]  
专题海洋研究所_海洋环流与波动重点实验室
通讯作者Zhang, Rong-Hua
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Laosan Lab, Qingdao 266237, Peoples R China
3.Nanjing Univ Informat Sci & Technol, Sch Marine Sci, Nanjing 210044, Peoples R China
4.Chinese Acad Sci, Key Lab Ocean Circulat & Waves, Inst Oceanol, Qingdao 266071, Peoples R China
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.

入库方式： OAI收割

来源：海洋研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。