Accessibility navigation


Efficient fully nonlinear data assimilation for geophysical fluid dynamics

Van Leeuwen, P. J. and Ades, M. (2013) Efficient fully nonlinear data assimilation for geophysical fluid dynamics. Computers & Geosciences, 55. pp. 16-27. ISSN 0098-3004

[img]
Preview
Text - Accepted Version
· Please see our End User Agreement before downloading.

4Mb

To link to this article DOI: 10.1016/j.cageo.2012.04.015

Abstract/Summary

A potential problem with Ensemble Kalman Filter is the implicit Gaussian assumption at analysis times. Here we explore the performance of a recently proposed fully nonlinear particle filter on a high-dimensional but simplified ocean model, in which the Gaussian assumption is not made. The model simulates the evolution of the vorticity field in time, described by the barotropic vorticity equation, in a highly nonlinear flow regime. While common knowledge is that particle filters are inefficient and need large numbers of model runs to avoid degeneracy, the newly developed particle filter needs only of the order of 10-100 particles on large scale problems. The crucial new ingredient is that the proposal density cannot only be used to ensure all particles end up in high-probability regions of state space as defined by the observations, but also to ensure that most of the particles have similar weights. Using identical twin experiments we found that the ensemble mean follows the truth reliably, and the difference from the truth is captured by the ensemble spread. A rank histogram is used to show that the truth run is indistinguishable from any of the particles, showing statistical consistency of the method.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > National Centre for Earth Observation (NCEO)
Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
ID Code:35769
Publisher:Elsevier

Download Statistics for this item.

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation