A new ensemble-based targeted observational method and its application in the TPOS 2020
作者机构：College of OceanographyHohai University Faculty of EnvironmentUniversity of Northern British ColumbiaPrince George Key Laboratory of Marine Hazards ForecastingMinistry of Natural ResourcesHohai University Innovation Group of Earth System ModelSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai) State Key Laboratory of Satellite Ocean Environment DynamicsSecond Institute of Oceanography
出 版 物：《National Science Review》 (国家科学评论(英文版))
年 卷 期：2023年第10卷第11期
页 面：138-147页
核心收录：
学科分类：08[工学] 0706[理学-大气科学] 0816[工学-测绘科学与技术]
基 金：supported by the National Natural Science Foundation of China (42130409, 41530961) the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)(311022006) the Global Change and Air-Sea Interaction II Program (GASI-01-WPACSTspr)
主 题：targeted observation ENSO TPOS data assimilation
摘 要：Ensemble Kalman filter-based targeted observation is one of the best methods for determining the optimal observational array for oceanic buoy deployment. This study proposes a new algorithm suitable for a‘cross-region and cross-variable’ approach by introducing a projection operator into the optimization process. A targeted observational analysis was conducted for El Ni?o–Southern Oscillation(ENSO) events in the tropical western Pacific for the Tropical Pacific Observation System(TPOS) 2020. The prediction target was at the Ni?o 3.4 region and the first 10 optimal observational sites detected reduced initial uncertainties by 70%, with the best observational array located where the Rossby wave signal dominates. At the vertical level, the most significant contribution was derived from observations near the *** study provides insights into understanding ENSO-related variability and offers a practical approach to designing an optimal mooring array. It serves as a scientific guidance for designing a TPOS observation network.
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