contributor author | Hoteit, I. | |
contributor author | Pham, D-T. | |
contributor author | Triantafyllou, G. | |
contributor author | Korres, G. | |
date accessioned | 2017-06-09T16:20:49Z | |
date available | 2017-06-09T16:20:49Z | |
date copyright | 2008/01/01 | |
date issued | 2008 | |
identifier issn | 0027-0644 | |
identifier other | ams-66201.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4207510 | |
description abstract | This paper introduces a new approximate solution of the optimal nonlinear filter suitable for nonlinear oceanic and atmospheric data assimilation problems. The method is based on a local linearization in a low-rank kernel representation of the state?s probability density function. In the resulting low-rank kernel particle Kalman (LRKPK) filter, the standard (weight type) particle filter correction is complemented by a Kalman-type correction for each particle using the covariance matrix of the kernel mixture. The LRKPK filter?s solution is then obtained as the weighted average of several low-rank square root Kalman filters operating in parallel. The Kalman-type correction reduces the risk of ensemble degeneracy, which enables the filter to efficiently operate with fewer particles than the particle filter. Combined with the low-rank approximation, it allows the implementation of the LRKPK filter with high-dimensional oceanic and atmospheric systems. The new filter is described and its relevance demonstrated through applications with the simple Lorenz model and a realistic configuration of the Princeton Ocean Model (POM) in the Mediterranean Sea. | |
publisher | American Meteorological Society | |
title | A New Approximate Solution of the Optimal Nonlinear Filter for Data Assimilation in Meteorology and Oceanography | |
type | Journal Paper | |
journal volume | 136 | |
journal issue | 1 | |
journal title | Monthly Weather Review | |
identifier doi | 10.1175/2007MWR1927.1 | |
journal fristpage | 317 | |
journal lastpage | 334 | |
tree | Monthly Weather Review:;2008:;volume( 136 ):;issue: 001 | |
contenttype | Fulltext | |