Numerical solution to the problem of variational assimilation of operational observational data on the ocean surface temperature

被引:6
作者
Agoshkov, V. I. [1 ]
Lebedev, S. A. [2 ]
Parmuzin, E. I. [1 ]
机构
[1] Russian Acad Sci, Inst Numer Math, Moscow 119991, Russia
[2] Russian Acad Sci, Geophys Ctr, Moscow 119991, Russia
基金
俄罗斯基础研究基金会;
关键词
ALGORITHMS; DYNAMICS; MODEL;
D O I
10.1134/S000143380901006X
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The problem of variational assimilation of satellite observational data on the ocean surface temperature is formulated and numerically investigated in order to reconstruct surface heat fluxes with the use of the global three-dimensional model of ocean hydrothermodynamics developed at the Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), and observational data close to the data actually observed in specified time intervals. The algorithms of the numerical solution to the problem are elaborated and substantiated, and the data assimilation block is developed and incorporated into the global three-dimensional model. Numerical experiments are carried out with the use of the Indian Ocean water area as an example. The data on the ocean surface temperature over the year 2000 are used as observational data. Numerical experiments confirm the theoretical conclusions obtained and demonstrate the expediency of combining the model with a block of assimilating operational observational data on the surface temperature.
引用
收藏
页码:69 / 101
页数:33
相关论文
共 50 条
  • [21] Optimal solution error quantification in variational data assimilation involving imperfect models
    Shutyaev, V.
    Gejadze, I.
    Vidard, A.
    Le Dimet, F. -X.
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, 2017, 83 (03) : 276 - 290
  • [22] Improving sea surface temperature in a regional ocean model through refined sea surface temperature assimilation
    Iversen, Silje Christine
    Sperrevik, Ann Kristin
    Goux, Olivier
    OCEAN SCIENCE, 2023, 19 (03) : 729 - 744
  • [23] Using Sea Surface Temperature Observations to Constrain Upper Ocean Properties in an Arctic Sea Ice-Ocean Data Assimilation System
    Liang, Xi
    Losch, Martin
    Nerger, Lars
    Mu, Longjiang
    Yang, Qinghua
    Liu, Chengyan
    JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2019, 124 (07) : 4727 - 4743
  • [24] An optimal data assimilation method and its application to the numerical simulation of the ocean dynamics
    Belyaev, Konstantin
    Kuleshov, Andrey
    Tuchkova, Natalia
    Tanajura, Clemente A. S.
    MATHEMATICAL AND COMPUTER MODELLING OF DYNAMICAL SYSTEMS, 2018, 24 (01) : 12 - 25
  • [25] Estimation of the drag coefficient from the upper ocean response to a hurricane: A variational data assimilation approach
    Zedler, Sarah E.
    Kanschat, Guido
    Hoteit, Ibrahim
    Korty, Robert
    OCEAN MODELLING, 2013, 68 : 57 - 71
  • [26] AMOC variations in 1979-2008 simulated by NCEP operational ocean data assimilation system
    Huang, Boyin
    Xue, Yan
    Kumar, Arun
    Behringer, David W.
    CLIMATE DYNAMICS, 2012, 38 (3-4) : 513 - 525
  • [27] Joint Assimilation of Surface Temperature and L-Band Microwave Brightness Temperature in Land Data Assimilation
    Han, Xujun
    Franssen, Harrie-Jan Hendricks
    Li, Xin
    Zhang, Yanlin
    Montzka, Carsten
    Vereecken, Harry
    VADOSE ZONE JOURNAL, 2013, 12 (03):
  • [28] Improvements in tropical precipitation and sea surface air temperature fields in a coupled atmosphere-ocean data assimilation system
    Fujii, Yosuke
    Ishibashi, Toshiyuki
    Yasuda, Tamaki
    Takaya, Yuhei
    Kobayashi, Chiaki
    Ishikawa, Ichiro
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2021, 147 (735) : 1317 - 1343
  • [29] Mapping regional turbulent heat fluxes via variational assimilation of land surface temperature data from polar orbiting satellites
    Xu, Tongren
    He, Xinlei
    Bateni, Sayed M.
    Auligne, Thomas
    Liu, Shaomin
    Xu, Ziwei
    Zhou, Ji
    Mao, Kebiao
    REMOTE SENSING OF ENVIRONMENT, 2019, 221 (444-461) : 444 - 461
  • [30] Neural-Network-Based Data Assimilation to Improve Numerical Ocean Wave Forecast
    Deshmukh, Aditya N.
    Deo, M. C.
    Bhaskaran, Prasad K.
    Nair, T. M. Balakrishnan
    Sandhya, K. G.
    IEEE JOURNAL OF OCEANIC ENGINEERING, 2016, 41 (04) : 944 - 953