Advanced

A real-time assimilation algorithm applied to near-surface ocean wind fields

Malmberg, Anders LU ; Holst, Jan LU and Holst, Ulla LU (2008) In Environmetrics 19(3). p.319-330
Abstract (Swedish)
Abstract in Undetermined

Marine operations depend on the ability to forecast suddenly appearing storms, and failures often cause great damage. As part of a sea-state alarm study, meteorological forecasts overlaid with satellite observations sent to ships have been found to be a useful too]. In this paper we present a real-time assimilation algorithm that extends this tool using statistical methods. The algorithm is applied to near-surface ocean wind fields. A Kalman filter based on a spatio-temporal state-space model provides a basis for emulation of the atmospheric model. The main contribution of this paper is the algorithm that makes it possible to use the information in the satellite observations over the full spatial... (More)
Abstract in Undetermined

Marine operations depend on the ability to forecast suddenly appearing storms, and failures often cause great damage. As part of a sea-state alarm study, meteorological forecasts overlaid with satellite observations sent to ships have been found to be a useful too]. In this paper we present a real-time assimilation algorithm that extends this tool using statistical methods. The algorithm is applied to near-surface ocean wind fields. A Kalman filter based on a spatio-temporal state-space model provides a basis for emulation of the atmospheric model. The main contribution of this paper is the algorithm that makes it possible to use the information in the satellite observations over the full spatial domain of interest at a real-time basis. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
real-time assimilation, spatio-temporal process, near-surface wind fields, Kalman filter
in
Environmetrics
volume
19
issue
3
pages
319 - 330
publisher
John Wiley & Sons
external identifiers
  • wos:000255854000007
  • scopus:42549103678
ISSN
1099-095X
DOI
10.1002/env.886
language
English
LU publication?
yes
id
6a3a7c61-cd19-45ab-a211-28122eb43354 (old id 943235)
date added to LUP
2008-01-24 12:18:32
date last changed
2017-01-01 04:42:05
@article{6a3a7c61-cd19-45ab-a211-28122eb43354,
  abstract     = {<b>Abstract in Undetermined</b><br/><br>
Marine operations depend on the ability to forecast suddenly appearing storms, and failures often cause great damage. As part of a sea-state alarm study, meteorological forecasts overlaid with satellite observations sent to ships have been found to be a useful too]. In this paper we present a real-time assimilation algorithm that extends this tool using statistical methods. The algorithm is applied to near-surface ocean wind fields. A Kalman filter based on a spatio-temporal state-space model provides a basis for emulation of the atmospheric model. The main contribution of this paper is the algorithm that makes it possible to use the information in the satellite observations over the full spatial domain of interest at a real-time basis.},
  author       = {Malmberg, Anders and Holst, Jan and Holst, Ulla},
  issn         = {1099-095X},
  keyword      = {real-time assimilation,spatio-temporal process,near-surface wind fields,Kalman filter},
  language     = {eng},
  number       = {3},
  pages        = {319--330},
  publisher    = {John Wiley & Sons},
  series       = {Environmetrics},
  title        = {A real-time assimilation algorithm applied to near-surface ocean wind fields},
  url          = {http://dx.doi.org/10.1002/env.886},
  volume       = {19},
  year         = {2008},
}