Innovation-Weight Parametrization in Data Assimilation: Formulation & Analysis with NAVDAS-AR/NAVGEM
Published In
IFAC-PapersOnLine
Document Type
Citation
Publication Date
12-22-2016
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 Navys Global Environmental Model (NAVGEM).
Locate the Document
DOI
10.1016/j.ifacol.2016.10.159
Persistent Identifier
http://archives.pdx.edu/ds/psu/20547
Citation Details
Daescu, D., Langland, R. (2016). Innovation-Weight Parametrization in Data Assimilation: Formulation & Analysis with NAVDAS-AR/NAVGEM, IFAC-PapersOnLine, 49 (18), 176-181.
Description
© 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.