A local particle filter and its Gaussian mixture extension implemented with minor modifications to the LETKF

A particle filter (PF) is an ensemble data assimilation method that does not assume Gaussian error distributions. Recent studies proposed local PFs (LPFs), which use localization, as in the ensemble Kalman filter, to apply the PF efficiently for high-dimensional dynamics. Among others, Penny and Miy...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Geoscientific Model Development 2022-11, Vol.15 (22), p.8325-8348
Hauptverfasser: Kotsuki, Shunji, Miyoshi, Takemasa, Kondo, Keiichi, Potthast, Roland
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A particle filter (PF) is an ensemble data assimilation method that does not assume Gaussian error distributions. Recent studies proposed local PFs (LPFs), which use localization, as in the ensemble Kalman filter, to apply the PF efficiently for high-dimensional dynamics. Among others, Penny and Miyoshi (2016) developed an LPF in the form of the ensemble transform matrix of the local ensemble transform Kalman filter (LETKF). The LETKF has been widely accepted for various geophysical systems, including numerical weather prediction (NWP) models. Therefore, implementing the LPF consistently with an existing LETKF code is useful.
ISSN:1991-9603
1991-959X
1991-962X
1991-9603
1991-962X
DOI:10.5194/gmd-15-8325-2022