期刊文献+

基于Argo资料的三维盐度场网格化产品重构 被引量:5

Reconstruction of three-dimensional gridded salinity product based on Argo data
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摘要 针对标准化海洋盐度场产品较为匮乏的事实,利用Argo温盐观测剖面与卫星遥感海表温度资料,采用时空权重插值和多变量DINEOF方法,对太平洋区域2000年1月至2008年12月的三维逐周盐度场进行重构。提出的重构方法有2个明显特色,一是采用时空权重插值与多变量DINEOF相结合的方法,弥补了时空权重插值结果中包含缺失数据的不足;二是引入卫星遥感海表温度,弥补了Argo可靠海表数据的缺乏。重构再分析产品与其他观测和数据产品的对比结果表明,重构产品不但能够抓住盐度分布的主要模态特征,而且可表现盐度不同时间尺度的变化特征,为海洋和气候研究提供了一种有用的标准化数据新产品。 Aiming at the shortage of standard salinity fields, based on Argo temperature/salinity profiles and salellite-derived sea surface temperature (SST), a combined technique of spatial-temperal weighted in- terpolation and multivariate data interpolating empirical orthogonal function (MDINEOF) was applied to reconstructing weekly three-dimensional salinity fields in the Pacific Ocean for the period from January 2000 to December 2008. The methodology that was used has two Obvious features: one is the combination of spatial-temporal weighted interpolation and MDINEOF methods to make up for the missing value in the spatial-temporal weighted interpolation, and the other is the inclusion of satellite-derived SST to make up for the lack of reliable surface data from Argo. Comparison with other observations and data products indi- cates that this gridded product captures the main patterns of the salinity distribution as well as its variabili- ty on various time scales, thus providing a useful new dataset for ocean and climate studies.
出处 《解放军理工大学学报(自然科学版)》 EI 北大核心 2012年第3期342-348,共7页 Journal of PLA University of Science and Technology(Natural Science Edition)
基金 国家973计划资助项目(2007CB816005) 中-加国际科技合作资助项目(2008DFA22230)
关键词 ARGO资料 多变量DINEOF 盐度 数据重构 时空权重插值 Argo data MDINEOF salinity data reconstruction spatial-temporal weighted interpolation
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参考文献18

  • 1ARGO SCIENCE TEAM. On the design and imple- mentation of Argo: an initial plan for a global array of profiling floats. International CLIVAR Projeet Office Report 21, GODAE Report 5[R]. Melbourne, Aus- tralia: GODAE International Project Office, 1998.
  • 2ARGO SCIENCE TEAM. Argo: the global array of profiling floats[R]ffKOBLINSKY C J, SMITH N R. Observing the Oceans in the 21st Century. Melbourne, Australia.. Godae Project Office, Bureau of Meteorolo- gy, 2001.
  • 3STOMMEL H. Note on the use of T-S correlation for dynamic height anomaly computations [J]. Journal of Marine Research, 1947(6) :85-92.
  • 4EMERY W J, DEWAR J S. Mean temperature-salini-ty, salinity-depth and temperature-depth curves for the North Atlantic and the North Paeifie[J]. Progress in Oceanography, 1982,11(3) :219-256.
  • 5TROCCOLI A, HAINES K. Use of the temperature- salinity relation in a data assimilation context [J]. Journal of Atmospheric and Oceanic Technology, 1999, 16(12) : 2011-2025.
  • 6SPARNOCCHIA S, PINARDI N, DEMIROV E. Multivariate empirical orthogonal function analysis of the upper thermoeline structure of the Mediterranean sea from observations and model simulations [J]. Annales Geophysieae, 2003,21 : 167-187.
  • 7王辉赞,张韧,王桂华,等.全球Argo浮标剖面观测资料质量再控制数据集用户手册[s].杭州:国家海洋局第二海洋研究所,2010.
  • 8LEVITUS S. World ocean atlas 2005[R]. WashingtonD C: NOAA Atlas NESDIS, US Goverment Printing Office, 2006.
  • 9ISHII M, KIMOTO M, SAKAMOTO K,et al. Steric sea level changes estimated from historical ocean sub- surface temperature and salinity analyses[J]. Journal of Oceanography, 2006,62 (2):155-170.
  • 10ALVERA-AZCA'RATE A, BARTH A, RIXEN M, et al. Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: Application to the Adriatic Sea[J]. Ocean Modelling, 2005,9 (4) : 325-346.

二级参考文献7

  • 1Beckers J M, Rixen M. EOF calculations and data filling from incomplete oceanographic datasets [J]. Journal of Atmospheric and Oceanic Technology ,2003,20(12) : 1839-1856.
  • 2王桂华,刘增宏,许建平.利用Argo资料重构太平洋三维温盐场和流场[A].见:许建平主编.Argo应川研究论文集[C].北京:海洋出版社,2006,16-25.
  • 3Kondrashov D, Ghil M. Spatio-temporal filling of missing points in geophysical data sets[J]. Nonlinear Processes in Geophysics ,2006,13(2):151-159.
  • 4Kondrashov D, Ghil M. Reply to T Schneider' s comment on "Spatio-temporal filling of missing points in geophysical data sets" [J]. Nonlinear Processes in Geophysics ,2007,14(1) :3-4.
  • 5Broomhead D S, King G P. Extracting qualitative dynamics from experimental data[J]. Physica D, 1986,20(2/3) :217-236.
  • 6江志红,丁裕国,屠其璞.基于PC-CCA方法的气象场资料插补试验[J].南京气象学院学报,1999,22(2):141-148. 被引量:11
  • 7江志红,丁裕国,屠其璞.气象场序列几种插补方案的对比试验[J].南京气象学院学报,1999,22(3):352-359. 被引量:10

共引文献16

同被引文献74

  • 1朱会义,刘述林,贾绍凤.自然地理要素空间插值的几个问题[J].地理研究,2004,23(4):425-432. 被引量:179
  • 2郭晶,刘广军,郭磊,董绪荣.基于3D^+-TPR-tree的点目标全时段移动索引设计[J].测绘学报,2006,35(3):267-272. 被引量:4
  • 3杨胜龙,周甦芳,崔雪森,伍玉梅,张晶.Argo数据研究应用现状与发展趋势[J].海洋渔业,2007,29(4):355-359. 被引量:12
  • 4陈大可,许建平,马继瑞,陈显尧,王桂华,王伟,韩桂军,张启龙,袁耀初,周伟东.全球实时海洋观测网(Argo)与上层海洋结构、变异及预测研究[J].地球科学进展,2008,23(1):1-7. 被引量:18
  • 5Hurlburt H E. Dynamic transfer of simulated altimeter data into subsurface information by a numerical ocean model[J]. Journal of Geophysical Research Atmospheres, 1986,91(C2) : 2372-2400.
  • 6Haines K, Malanotte-Rizzoli P, Young R E, et al. A comparison of two methods for the assimilation of altimeter data into a shallow- water model[J]. Dynamics of Atmospheres & Oceans, 1993,17 ( 2- 3):89-133.
  • 7Cooper M, Haines K. Altimetric assimilation with water property conservation[J]. Journal of Geophysical Research, 1996,101 ( 101 ) : 1059-1078.
  • 8Chen D,Zebiak S E,Cane M A,et al. Initialization and Pre-dictability of a Coupled ENSO Forecast Model[J]. Monthly Weather Review, 1997,125 (5) : 773-788.
  • 9Syu H H,Neelin J D. ENSO in a hybrid coupled model. Part II: prediction with piggyback data assimilation[J]. Climate Dynamics, 1999,16( 1 ) : 35-48.
  • 10Tang Y, Kleeman R. A new strategy for assimilating SST data for ENSO predictions [J]. Geophysical Research Letters, 2002,29 (17) :22-1-22-4.

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