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Sensitivity analysis with respect to observations in variational data assimilation for parameter estimation  id статьи: 458
Тип публикации
статья в журнале
Язык
En
Журнал
Nonlinear Processes in Geophysics

ISSN:1023-5809
Год
2018
Выходные данные
том 25
выпуск 2
страницы 429-439
Авторы
Le Dimet, FX.1
Parmuzin, E.I.2
EDN
Абстракт
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.
Ключевые слова
THEORETICAL ASPECTS, ADJOINT, MODEL
Дата занесения
2020-05-07 10:20:08
Scopus
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