A real-time assimilation algorithm applied to near-surface ocean wind fields
(2008) In Environmetrics 19(3). p.319-330- Abstract
- 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... (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:
https://lup.lub.lu.se/record/943235
- author
- Malmberg, Anders LU ; Holst, Jan LU and Holst, Ulla LU
- organization
- publishing date
- 2008
- 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 Inc.
- external identifiers
-
- wos:000255854000007
- scopus:42549103678
- ISSN
- 1099-095X
- DOI
- 10.1002/env.886
- language
- English
- LU publication?
- yes
- additional info
- publicerad online 6 nov.2007
- id
- 6a3a7c61-cd19-45ab-a211-28122eb43354 (old id 943235)
- date added to LUP
- 2016-04-01 11:57:24
- date last changed
- 2022-01-26 20:43:55
@article{6a3a7c61-cd19-45ab-a211-28122eb43354, abstract = {{Abstract in Undetermined<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}}, keywords = {{real-time assimilation; spatio-temporal process; near-surface wind fields; Kalman filter}}, language = {{eng}}, number = {{3}}, pages = {{319--330}}, publisher = {{John Wiley & Sons Inc.}}, series = {{Environmetrics}}, title = {{A real-time assimilation algorithm applied to near-surface ocean wind fields}}, url = {{http://dx.doi.org/10.1002/env.886}}, doi = {{10.1002/env.886}}, volume = {{19}}, year = {{2008}}, }