文章基本信息

标题：Innovation-Weight Parametrization in Data Assimilation: Formulation & Analysis with NAVDAS-AR/NAVGEM
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作者：Dacian N. Daescu ; Dacian N. Daescu ; Rolf H. Langland 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：18
页码：176-181
DOI：10.1016/j.ifacol.2016.10.159
语种：English
出版社：Elsevier
摘要：Abstract: An innovation-weight parametrization is introduced as a practical approach to account for deficiencies in the representation of both background error and observation error covariance in a variational data assimilation system. The adjoint-based evaluation of the forecast error sensitivity provides a computationally efficient diagnosis to observation-space distributed parameters and guidance for tuning the analysis Kalman gain operator. Theoretical aspects are discussed and preliminary results are presented with the adjoint versions of the Naval Research Laboratory Atmospheric Variational Data Assimilation System-Accelerated Representer (NAVDAS-AR) and the Navy’s Global Environmental Model (NAVGEM).
关键词：KeywordsParameter EstimationState EstimationApplicationsPerformance Issues