利用资料同化方法优化观测系统的空间布局:以泰国湾为例

史军强; 尹训强; 乔方利

doi:10.3969/j.issn.0253-4193.2018.02.002

利用资料同化方法优化观测系统的空间布局:以泰国湾为例

doi: 10.3969/j.issn.0253-4193.2018.02.002

1.
中国海洋大学海洋与大气学院, 山东青岛 266100;国家海洋局第一海洋研究所, 山东青岛 266061;青岛海洋科学与技术国家实验室区域海洋动力学与数值模拟功能实验室, 山东青岛 266237
2.
国家海洋局第一海洋研究所, 山东青岛 266061;青岛海洋科学与技术国家实验室区域海洋动力学与数值模拟功能实验室, 山东青岛 266237
3.
国家海洋局第一海洋研究所, 山东青岛 266061;青岛海洋科学与技术国家实验室区域海洋动力学与数值模拟功能实验室, 山东青岛 266237;海洋环境科学和数值模拟国家海洋局重点实验室, 山东青岛 266061

基金项目: 中国-东盟海上合作基金项目"东南亚海洋环境预报与灾害预警系统建设"；国家自然科学基金委员会-山东省人民政府联合资助海洋科学研究中心项目（U1606405）；青岛海洋科学与技术国家实验室重大科研专项"海洋与气候系统数值模拟平台建设关键技术"（2016ASKJ16）

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出版历程
- 收稿日期: 2017-02-13

Optimizing the spatial ocean observation system based on data assimilation assessment: the Gulf of Thailand as an example

1.
College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China;The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
2.
The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
3.
The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China;Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China;Key Laboratory of Marine Sciences and Numerical Modeling, State Oceanic Administration, Qingdao 266061, China

摘要

摘要: 海洋观测费用高昂，设计科学高效的观测系统可以充分发挥观测的效能。本文以泰国湾高频地波雷达观测系统为例，利用数据同化方法对观测系统进行了最优布局。首先基于FVCOM海洋数值模式建立了泰国湾海域高分辨率三维斜压水动力模式，在此基础上利用一种改进的高效集合卡曼滤波同化方法对岸基高频地波雷达表层海流观测系统开展观测效能评估数值实验。通过观测区域的不同组合方式将3个区域的雷达表层海流数据同化到数值模式中，实验结果表明，岸基高频地波雷达表层海流观测系统可有效降低高分辨数值模式的海流模拟误差。但不同观测区域的组合提供的观测数据对改善海流模拟的作用存在明显差别，泰国湾现有观测系统雷达站位布设方式应进一步优化。本文最后给出了研究区域最优观测站位的布局方案，可作为下一步观测系统进行布局调整的指导。
- 观测系统优化设计 /
- 泰国湾 /
- 高频地波雷达
Abstract: The cost for ocean observation system is very high, and the scientific design of observation system can make it effective. Taking the high frequency radar system of the Gulf of Thailand as an example, we established a three-dimensional ocean circulation model using FVCOM. A series of evaluation numerical experiments were carried out to assess the performance of the existing observational radar system. The simulated surface current data in three observation regions were assimilated by means of various combinations using an efficient ensemble Kalman filter data assimilation method. The experimental results showed that the coastal surface current observation system plays a quite positive role in improving the current simulation in the whole domain, although the observation only covers small parts of this area. The existing observation system is helpful for ocean circulation simulation and forecast. However, the improvement effect for three observation regions was quite different, which means the current observation system is not effective and need to be optimized. In addition, this study used the ensemble transform Kalman filter optimal observation scheme to explore the ideal deployment of observational stations, which could be a useful guidance for future re-design of this observation system.
- optimizing oceanic observation system /
- Gulf of Thailand /
- high frequency radar

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参考文献(23)

Ballabrera-Poy J, Hackert E, Murtugudde R, et al. An observing system simulation experiment for an optimal moored instrument array in the tropical Indian ocean[J]. Journal of Climate, 2007, 20(13):3284-3299.

She Jun, Hoyer J L, Larsen J. Assessment of sea surface temperature observational networks in the Baltic Sea and North Sea[J]. Journal of Marine Systems, 2007, 65(1/4):314-335.

Fu W, Høyer J L, She J. Assessment of the 3-D temperature and salinity observational networks in the Baltic Sea and North Sea[J]. Ocean Science Discussions, 2010, 7(5):1627-1668.

Sakov P, Oke P R. Objective array design:application to the tropical indian ocean[J]. Journal of Atmospheric and Oceanic Technology, 2008, 25(5):794-807.

叶冬, 王瑞文. 基于集合同化方法的南海北部最优观测实验[J]. 海洋通报, 2011, 30(3):252-257. Ye Dong, Wang Ruiwen. Optimal observation experiment in the northern South China Sea based on the ensemble assimilation method[J]. Marine Science Bulletin, 2011, 30(3):252-257.

王瑞文, 叶冬. 中国近海现场海洋观测系统设计评估[J]. 海洋通报, 2012, 31(2):121-130. Wang Ruiwen, Ye Dong. Assessment on the design of in-situ ocean observing system in Chinese marginal seas[J]. Marine Science Bulletin, 2012, 31(2):121-130.

Panteleev G, Yaremchuk M, Francis O, et al. Configuring high frequency radar observations in the Southern Chukchi Sea[J]. Polar Science, 2013, 7(7):72-81.

Panteleev G, Yaremchuk M, Stroh J, et al. Optimization of the High-Frequency Radar Sites in the Bering Strait Region[J]. Journal of Atmospheric and Oceanic Technology, 2015, 32(2):297-309.

Chen C S, Beardsley R C, Cowles G. An unstructured grid, finite-volume coastal ocean model:FVCOM User Manual, Second edition[J]. Oceanography, 2006, 19(1):78-89.

Weatherall P, Marks K M, Jakobsson M, et al. A new digital bathymetric model of the world's oceans[J]. Earth and Space Science, 2016, 2(8):331-345.

Yin Xunqiang, Qiao Fangli, Shu Qi. Using ensemble adjustment Kalman filter to assimilate Argo profiles in a global OGCM[J]. Ocean Dynamics, 2011, 61(7):1017-1031.

Pawlowicz R, Beardsley B, Lentz S. Classical tidal harmonic analysis including error estimates in MATLAB using T_TIDE[J]. Computers & Geosciences, 2002, 28(8):929-937.

Atlas R, Hoffman R N, Ardizzone J, et al. Development of a new cross-calibrated multiplatform (CCMP) ocean surface wind product[C]//Paper presented at AMS 13th Conference on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface (IOAS-AOLS). Phoenix, AZ:AMS, 2009.

Scott J, Wentz F J, Hoffman R N, et al. Improvements and advances to the cross-calibrated multi-platform (CCMP) ocean vector wind analysis (V2.0 release)[C]//AGU Ocean Sciences Meeting. Washington DC:AGU, 2016.

Saha S, Moorthi S, Wu X, et al. The NCEP Climate Forecast System Version 2[J]. Journal of Climate, 2014, 27(6):2185-2208.

Kara A B, Barron C N, Wallcraft A J, et al. Advantages of fine resolution SSTs for small ocean basins:Evaluation in the Black Sea[J]. Journal of Geophysical Research:Atmospheres, 2008, 113(C8):C08013.

Chen Xue'en, Zhan Peng, Chen Jinrui, et al. Numerical study of current fields near the Changjiang Estuary and impact of Quick-EnKF assimilation[J]. Acta Oceanologica Sinica, 2011, 30:33.

Zhao Jian, Chen Xue'en, Xu Jianling, et al. Assimilation of surface currents into a regional model over Qingdao coastal waters of China[J]. Acta Oceanologica Sinica, 2013, 32(7):21-28.

Parrish D F, Derber J C. The National Meteorological Center's spectral statistical-interpolation analysis system[J]. Monthly Weather Review, 1992, 120(8):1747-1763.

Rabier F, Mcnally A, Andersson E, et al. The ECMWF implementation of three-dimensional variational assimilation (3D-Var). Ⅱ:Structure functions[J]. Quarterly Journal of the Royal Meteorological Society, 1998, 124(550):1809-1829.

Stansfield K, Garrett C. Implications of the salt and heat budgets of the Gulf of Thailand[J]. Journal of Marine Research, 1997, 55(5):935-963.

刘科峰, 蒋国荣, 陈奕德, 等. 基于卫星漂流浮标的南海表层海流观测分析[J]. 热带海洋学报, 2014, 33(5):13-21. Liu Kefeng, Jiang Guorong, Chen Yide, et al. Analysis of upper-ocean surface currents of the South China Sea derived from satellite-tracked drifter data[J]. Journal of Tropical Oceanography, 2014, 33(5):13-21.

Buranapratheprat A, Luadnakrob P, Yanagi T, et al. The modification of water column conditions in the Gulf of Thailand by the influences of the South China Sea and monsoonal winds[J]. Continental Shelf Research, 2016, 118:100-110.

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