Data assimilation framework: Linking an open data assimilation library (OpenDA) to a widely adopted model interface (OpenMI)
2014
Ridler, Marc E. | van Velzen, Nils | Hummel, Stef | Sandholt, Inge | Falk, Anne Katrine | Heemink, Arnold | Madsen, Henrik
Data assimilation optimally merges model forecasts with observations taking into account both model and observational uncertainty. This paper presents a new data assimilation framework that enables the many Open Model Interface (OpenMI) 2.0 .NET compliant hydrological models already available, access to a robust data assimilation library. OpenMI is an open standard that allows models to exchange data during runtime, thus transforming a complex numerical model to a ‘plug and play’ like component. OpenDA is an open interface standard for a set of tools, filters, and numerical techniques to quickly implement data assimilation. The OpenDA–OpenMI framework is presented and tested on a synthetic case that highlights the potential of this new framework. MIKE SHE, a distributed and integrated hydrological model is used to assimilate hydraulic head in a catchment in Denmark. The simulated head over the entire domain were significantly improved by using an ensemble based Kalman filter.
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