Toward a global ocean data assimilation system based on ensemble optimum interpolation: altimetry data assimilation experiment

被引:12
|
作者
Fu, Weiwei [1 ]
Zhu, Jiang [2 ]
Yan, Changxiang [2 ]
Liu, Hailong [3 ]
机构
[1] Chinese Acad Sci, Inst Atmospher Phys, Nansen Zhu Int Res Ctr NZC, Beijing 100029, Peoples R China
[2] Chinese Acad Sci, Inst Atmospher Phys, ICCES, Beijing 100029, Peoples R China
[3] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China
基金
中国国家自然科学基金;
关键词
Data assimilation; EnOI; GODAE; Satellite altimetric data; Global ocean; EXTENDED KALMAN FILTER; 4-DIMENSIONAL VARIATIONAL ASSIMILATION; GENERAL-CIRCULATION MODEL; SEA-SURFACE TEMPERATURE; TROPICAL PACIFIC-OCEAN; NORTH-ATLANTIC; IN-SITU; PART I; EDDY; IMPLEMENTATION;
D O I
10.1007/s10236-009-0206-5
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
A global ocean data assimilation system based on the ensemble optimum interpolation (EnOI) has been under development as the Chinese contribution to the Global Ocean Data Assimilation Experiment. The system uses a global ocean general circulation model, which is eddy permitting, developed by the Institute of Atmospheric Physics of the Chinese Academy of Sciences. In this paper, the implementation of the system is described in detail. We describe the sampling strategy to generate the stationary ensembles for EnOI. In addition, technical methods are introduced to deal with the requirement of massive memory space to hold the stationary ensembles of the global ocean. The system can assimilate observations such as satellite altimetry, sea surface temperature (SST), in situ temperature and salinity from Argo, XBT, Tropical Atmosphere Ocean (TAO), and other sources in a straightforward way. As a first step, an assimilation experiment from 1997 to 2001 is carried out by assimilating the sea level anomaly (SLA) data from TOPEX/Poseidon. We evaluate the performance of the system by comparing the results with various types of observations. We find that SLA assimilation shows very positive impact on the modeled fields. The SST and sea surface height fields are clearly improved in terms of both the standard deviation and the root mean square difference. In addition, the assimilation produces some improvements in regions where mesoscale processes cannot be resolved with the horizontal resolution of this model. Comparisons with TAO profiles in the Pacific show that the temperature and salinity fields have been improved to varying degrees in the upper ocean. The biases with respect to the independent TAO profiles are reduced with a maximum magnitude of about 0.25A degrees C and 0.1 psu for the time-averaged temperature and salinity. The improvements on temperature and salinity also lead to positive impact on the subsurface currents. The equatorial under current is enhanced in the Pacific although it is still underestimated after the assimilation.
引用
收藏
页码:587 / 602
页数:16
相关论文
共 50 条
  • [1] Toward a global ocean data assimilation system based on ensemble optimum interpolation: altimetry data assimilation experiment
    Weiwei Fu
    Jiang Zhu
    Changxiang Yan
    Hailong Liu
    [J]. Ocean Dynamics, 2009, 59 : 587 - 602
  • [2] Ensemble-based global ocean data assimilation
    Nadiga, Balasubramanya T.
    Casper, W. Riley
    Jones, Philip W.
    [J]. OCEAN MODELLING, 2013, 72 : 210 - 230
  • [3] GLOBAL DATA ASSIMILATION BY LOCAL OPTIMUM INTERPOLATION
    MCPHERSON, RD
    BERGMAN, KH
    KISTLER, RE
    RASCH, GE
    GORDON, D
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 1977, 58 (01) : 123 - 123
  • [4] The Global Ocean Data Assimilation Experiment
    Smith, NR
    [J]. REMOTE SENSING AND APPLICATIONS: EARTH, ATMOSPHERE AND OCEANS, 2000, 25 (05): : 1089 - 1098
  • [5] Ocean data assimilation: a case for ensemble optimal interpolation
    Oke, Peter R.
    Brassington, Gary B.
    Griffin, David A.
    Schiller, Andreas
    [J]. AUSTRALIAN METEOROLOGICAL AND OCEANOGRAPHIC JOURNAL, 2010, 59 : 67 - 76
  • [6] GODAE The Global Ocean Data Assimilation Experiment
    Bell, Michael J.
    Lefebvre, Michel
    Le Traon, Pierre-Yves
    Smith, Neville
    Wilmer-Becker, Kirsten
    [J]. OCEANOGRAPHY, 2009, 22 (03) : 14 - 21
  • [7] Satellite altimetry data assimilation in the OCCAM global ocean model
    Fox, AD
    Haines, K
    de Cuevas, BA
    [J]. PHYSICS AND CHEMISTRY OF THE EARTH PART A-SOLID EARTH AND GEODESY, 1999, 24 (04): : 375 - 380
  • [8] The Impacts of the Application of the Ensemble Optimal Interpolation Method in Global Ocean Wave Data Assimilation
    Wu, Mengmeng
    Wang, Hui
    Wan, Liying
    Wang, Juanjuan
    Wang, Yi
    Wang, Jiuke
    [J]. ATMOSPHERE, 2023, 14 (05)
  • [9] Perspectives from the global ocean data assimilation experiment
    Smith, Neville
    [J]. OCEAN WEATHER FORECASTING: AN INTEGRATED VIEW OF OCEANOGRAPHY, 2006, : 1 - 17
  • [10] An Ensemble Ocean Data Assimilation System for Seasonal Prediction
    Yin, Yonghong
    Alves, Oscar
    Oke, Peter R.
    [J]. MONTHLY WEATHER REVIEW, 2011, 139 (03) : 786 - 808