Filtern
Volltext vorhanden
- nein (3)
Dokumenttyp
- Wissenschaftlicher Artikel (3) (entfernen)
Sprache
- Englisch (3)
Gehört zur Bibliographie
- ja (3)
Schlagworte
- data assimilation (1)
- dimension independent bound (1)
- filter (1)
- high dimensional (1)
- localisation (1)
- nonlinear (1)
- stability and accuracy (1)
Institut
Concurrent observation technologies have made high-precision real-time data available in large quantities. Data assimilation (DA) is concerned with how to combine this data with physical models to produce accurate predictions. For spatial-temporal models, the ensemble Kalman filter with proper localisation techniques is considered to be a state-of-the-art DA methodology. This article proposes and investigates a localised ensemble Kalman Bucy filter for nonlinear models with short-range interactions. We derive dimension-independent and component-wise error bounds and show the long time path-wise error only has logarithmic dependence on the time range. The theoretical results are verified through some simple numerical tests.