Sensitivity analysis with respect to observations in variational data assimilation for parameter estimation

被引:7
作者
Shutyaev, Victor [1 ,2 ,3 ]
Le Dimet, Francois-Xavier [4 ]
Parmuzin, Eugene [1 ,3 ]
机构
[1] Russian Acad Sci, Inst Numer Math, Gubkina 8, Moscow 119333, Russia
[2] RAS, Marine Hydrophys Inst, Federal State Budget Sci Inst, Kapitanskaya 2, Sevastopol, Crimea, Ukraine
[3] Moscow Inst Phys & Technol, 9 Inst Per, Dolgoprudnyi 141701, Moscow Region, Russia
[4] Univ Grenoble Alpes, LJK, 700 Ave Cent,38401 Domaine Univ St Martin dHeres, Grenoble, France
基金
俄罗斯科学基金会;
关键词
THEORETICAL ASPECTS; ADJOINT; MODEL;
D O I
10.5194/npg-25-429-2018
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find unknown parameters of the model. The observation data, and hence the optimal solution, may contain uncertainties. A response function is considered as a functional of the optimal solution after assimilation. Based on the second-order adjoint techniques, the sensitivity of the response function to the observation data is studied. The gradient of the response function is related to the solution of a nonstandard problem involving the coupled system of direct and adjoint equations. The nonstandard problem is studied, based on the Hessian of the original cost function. An algorithm to compute the gradient of the response function with respect to observations is presented. A numerical example is given for the variational data assimilation problem related to sea surface temperature for the Baltic Sea thermodynamics model.
引用
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页码:429 / 439
页数:11
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