A study on data assimilation for the vertical distribution of sea temperature

Han Guijun; He Bairong; Ma Jirui; Li Dong

Article Contents

Article Navigation > Haiyang Xuebao > 2000 > 22(4): 1-7

Han Guijun, He Bairong, Ma Jirui, Li Dong. A study on data assimilation for the vertical distribution of sea temperature[J]. Haiyang Xuebao, 2000, 22(4): 1-7.

Citation:

Han Guijun, He Bairong, Ma Jirui, Li Dong. A study on data assimilation for the vertical distribution of sea temperature[J]. Haiyang Xuebao, 2000, 22(4): 1-7.

Han Guijun, He Bairong, Ma Jirui, Li Dong. A study on data assimilation for the vertical distribution of sea temperature[J]. Haiyang Xuebao, 2000, 22(4): 1-7.

Citation:

Han Guijun, He Bairong, Ma Jirui, Li Dong. A study on data assimilation for the vertical distribution of sea temperature[J]. Haiyang Xuebao, 2000, 22(4): 1-7.

PDF( 381 KB)

A study on data assimilation for the vertical distribution of sea temperature

1.
National Marine Data and Information Service, State Oceanic Administration, Tianjin 300171;Institute of Ocenology, Chinese Academy of Sciences, Qingdao 266071
2.
College of Mathematical Science, Nankai University, Tianjin 300071
3.
National Marine Data and Information Service, State Oceanic Administration, Tianjin 300171

Received Date: 1999-03-23
Rev Recd Date: 1999-08-25

Abstract

Abstract

In order to provide more accurate initial field for numerical predict of the sea temperature the adjoins method is used to assimilate the sea temperature observations into one-dimensional sea temperature model in this paper.How to establish the adjoint model is discussed by using the Gâteaux differential of function and the concepts of the adjoint operators in Hibert space.At the same time it is verified that selecting proper finite difference scheme can ensure discrete form remaining the same adjoint relationship to continuous form of the model.The numerical resuits describing the varying sea temperature field are illustr ated.
- Sea temperature,
- data assimilation,
- adjoint method

FullText(HTML)

References(7)

References

Thacker W C, Long R B. Fitting dynamics to data. J Geophys Res, 1989, 93:1 227～1 240

Le Dimet F X. Determination of the adjoint of a numerical weather prediction model. Manuscript

雷晋干,陈铭俊,匡蛟勋等数值分析的泛函方法.北京:高等教育出版社,1995

Talagrand O, Courtier P. Variational assimilation of meteorological observations with the adjoint vorticity equation I. Theory. O J R MeterolSoc, 1987, 113:1 311～1 328

王宗山,徐伯昌,金梅兵等渤海、黄海强温跃层数值预报模式.黄渤海海洋,1996,14(3):75～85

Dong C Liu, Jorge Nocedal. On the limited memory BFGS method for large scale optimization. Mathematical Programming, 1989, 45:503～528

Yuanfu Xie. A brief introduction of projects at forecasting systems laboratory NOAA, USA. Technical Report, 1998

Relative Articles

Supplements(0)

Cited By

Proportional views