A simple method for integrating a complex model into an ensemble data assimilation system using MPI. (June 2015)

• Record Type: Journal Article
• Authors: Browne, P.A.; Wilson, S.
• Is Part Of: Environmental modelling & software. Volume 68(2015:Jun.)
• Page Start: 122
• Page End: 128
• Publication Date: 2015-06
• Subjects: Data assimilation -- Model coupling -- MPI; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.02.003
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: This paper details a strategy for modifying the source code of a complex model so that the model may be used in a data assimilation context, and gives the standards for implementing a data assimilation code to use such a model. The strategy relies on keeping the model separate from any data assimilation code, and coupling the two through the use of Message Passing Interface (MPI) functionality. This strategy limits the changes necessary to the model and as such is rapid to program, at the expense of ultimate performance. The implementation technique is applied in different models with state dimension up to .2.7 × 10 8 The overheads added by using this implementation strategy in a coupled ocean-atmosphere climate model are shown to be an order of magnitude smaller than the addition of correlated stochastic random errors necessary for some nonlinear data assimilation techniques. Highlights: We introduce an MPI coupling of a model and an ensemble data assimilation system. We show the full changes to the Lorenz 1963 model that implement the MPI coupling. The MPI coupling method is shown to exhibit perfect scaling on large-scale examples.