On the 4D Variational Data Assimilation with Constraint Conditions

被引：0

作者：

Zhu K. ^{[1
]}

机构：

[1] Chengdu Univ. of Info. Technology

来源：

Advances in Atmospheric Sciences | 2001年 / 18卷 / 6期

基金：

中国国家自然科学基金;

关键词：

Constraint conditions; Finite-element model; Penalty methods; Variational data assimilation;

D O I：

10.1007/s00376-001-0028-y

中图分类号：

学科分类号：

摘要：

An investigation is carried out on the problem involved in 4D variational data assimilation (VDA) with constraint conditions based on a finite-element shallow-water equation model. In the investigation, the adjoint technology, penalty method and augmented Lagrangian method are used in constraint optimization field to minimize the defined constraint objective functions. The results of the numerical experiments show that the optimal solutions are obtained if the functions reach the minima. VDA with constraint conditions controlling the growth of gravity oscillations is efficient to eliminate perturbation and produces optimal initial field. It seems that this method can also be applied to the problem in numerical weather prediction.

引用

页码：1131 / 1145

页数：14

共 15 条

[1]

Chou J., Study on use of historical data in numerical weather prediction, Science in China, 6, pp. 635-644, (1974)

[2]

Courtier P., Talagrand O., Variational assimilation of meteorological observations with the adjoint vorticity equation, Part II: Numerical results, Quart. J. Roy. Meteor. Soc., 113, pp. 1329-1347, (1987)

[3]

Derber J.C., The use of adjoint equations to solve a variational adjustment problem with advective constraints, Tellus, 37 A, pp. 309-322, (1985)

[4]

Erik A., Haseler J., Et al., The ECMWF implementation of three-dimensional variational assimilation (3D-Var) III: Experimental results, Quart. J. Roy. Meteor. Soc., 124, pp. 1831-1860, (1998)

[5]

Grammeltvedt A., Asurvey of a finite-difference schemes for the primitive equations for a barotropic fluid, Mon. Wea. Rev., 97, pp. 384-404, (1969)

[6]

Gu Z., Equivalent feature of weather prognosis with forecast by surface historical weather evolvement on initial value, Atca Meteorologica Sinica, 29, 2, pp. 176-186, (1958)

[7]

Liu D.C., Nocedal J., On the limited memory BFGS method for large scale optimization, Mathematical Programming, 45, pp. 503-528, (1989)

[8]

Machenhauer B., On the dynamics of gravity oscillations in a shallow water model, with applications to normal mode initialization, Contrib. Atmos. Phys., 50, pp. 253-271, (1977)

[9]

Raymond W.H., Aune R.M., Improved precipitation forecast using parameterized precipitation drag in a hydrostatic forecast model, Mon. Wea. Rev., 126, pp. 693-710, (1998)

[10]

Sasaki Y., Some basic formalisms in numerical variational analysis, Mon. Wea, Rev., 98, pp. 875-883, (1970)

← 1 2 →