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Parallelization in the time dimension of four‐dimensional variational data assimilation
Author(s) -
Fisher Michael,
Gürol Selime
Publication year - 2017
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.2997
Subject(s) - data assimilation , saddle point , computer science , dimension (graph theory) , constraint (computer aided design) , automatic parallelization , saddle , simple (philosophy) , algorithm , divergence (linguistics) , parallelism (grammar) , geostrophic wind , mathematical optimization , parallel computing , mathematics , geometry , meteorology , physics , philosophy , linguistics , epistemology , compiler , programming language , mechanics , pure mathematics
The current evolution of computer architectures towards increasing parallelism requires a corresponding evolution towards more parallel data assimilation algorithms. In this article, we consider parallelization of weak‐constraint four‐dimensional variational data assimilation (4D‐Var) in the time dimension. We categorize algorithms according to whether or not they admit such parallelization and introduce a new, highly parallel weak‐constraint 4D‐Var algorithm based on a saddle‐point representation of the underlying optimization problem. The potential benefits of the new saddle‐point formulation are illustrated with a simple two‐level quasi‐geostrophic model.