Scheda di dettaglio – i prodotti della ricerca
| Dato | Valore |
|---|---|
| Title | A new data assimilation technique based on ensemble Kalman filter and Brownian bridges: An application to Richards' equation |
| Abstract | In this paper a new data assimilation technique is proposed which is based on the ensemble Kalman filter (EnKF). Such a technique will be effective if few observations of a dynamical system are available and a large model error occurs. The idea is to acquire a fine grid of synthetic observations in two steps: (1) first we interpolate the real observations with suitable polynomial curves; (2) then we estimate the relative measurement errors by means of Brownian bridges. This technique has been tested on the Richards' equation, which governs the water flow in unsaturated soils, where a large model error has been introduced by solving the Richards' equation by means of an explicit numerical scheme. The application of this technique to some synthetic experiments has shown improvements with respect to the classical ensemble Kalman filter, in particular for problems with a large model error. |
| Source | Computer physics communications 208, pp. 43–53 |
| Keywords | Data assimilation; Ensemble Kalman filter; Brownian bridges; Richards' equation |
| Journal | Computer physics communications |
| Editor | North-Holland, Amsterdam, Paesi Bassi |
| Year | 2016 |
| Type | Articolo in rivista |
| DOI | 10.1016/j.cpc.2016.07.025 |
| Authors | Marco Berardi (a) , Andrea Andrisani (b) , Luciano Lopez (b, a), Michele Vurro (a) |
| Text | 358531 2016 10.1016/j.cpc.2016.07.025 Scopus 2 s2.0 84991247810 ISI Web of Science WOS WOS 000384858600005 Data assimilation; Ensemble Kalman filter; Brownian bridges; Richards equation A new data assimilation technique based on ensemble Kalman filter and Brownian bridges An application to Richards equation Marco Berardi a , Andrea Andrisani b , Luciano Lopez b, a , Michele Vurro a a Istituto di Ricerca sulle Acque, Consiglio Nazionale delle Ricerche, via F. De Blasio 5, 70132, Bari, Italy b Dipartimento di Matematica, Universita degli Studi di Bari Aldo Moro, via E. Orabona 4, 70125 Bari, Italy In this paper a new data assimilation technique is proposed which is based on the ensemble Kalman filter EnKF . Such a technique will be effective if few observations of a dynamical system are available and a large model error occurs. The idea is to acquire a fine grid of synthetic observations in two steps 1 first we interpolate the real observations with suitable polynomial curves; 2 then we estimate the relative measurement errors by means of Brownian bridges. This technique has been tested on the Richards equation, which governs the water flow in unsaturated soils, where a large model error has been introduced by solving the Richards equation by means of an explicit numerical scheme. The application of this technique to some synthetic experiments has shown improvements with respect to the classical ensemble Kalman filter, in particular for problems with a large model error. 208 Published version http //www.sciencedirect.com/science/article/pii/S0010465516302132 A new data assimilation technique based on ensemble Kalman filter and Brownian bridges An application to Richards equation Berardi_CPC_2016_online_version.pdf Articolo in rivista North Holland 0010 4655 Computer physics communications Computer physics communications Comput. phys. commun. LOPEZ LUCIANO marco.berardi BERARDI MARCO michele.vurro VURRO MICHELE |