Variational Methods of Data Assimilation and Inverse Problems for Studying the Atmosphere, Ocean, and Environment

被引：23
|
作者：
Penenko, V. V. [1 ,2 ]
机构：
[1] Russian Acad Sci, Siberian Branch, Inst Computat Math & Math Geophys, Pr Akad Lavrenteva 6, Novosibirsk 630090, Russia
[2] Novosibirsk State Univ, Novosibirsk 630090, Russia
来源：
NUMERICAL ANALYSIS AND APPLICATIONS | 2009年 / 2卷 / 04期
基金：
俄罗斯基础研究基金会;
关键词：
variational principles; data assimilation; adjoint problems; sensitivity analysis; uncertainty assessment; inverse problems; models of atmospheric dynamics and chemistry;
D O I：
10.1134/S1995423909040065
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Methods for the combined use ofmathematical models and observational data for studying and forecasting the evolution of natural processes in the atmosphere, ocean, and environment are presented. Variational principles for estimation of functionals defined on a set of functions of state, parameters and sources of models of processes are a theoretical background. Mathematical models with allowance for uncertainties are considered as constraints to the class of functions. Attention is focused on methods of successive data assimilation and on inverse problems.
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页码：341 / 351
页数：11
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