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A real-time assimilation algorithm applied to near-surface ocean winds

Malmberg, Anders LU ; Holst, Jan LU and Holst, Ulla LU (2004) In Preprint without journal information
Abstract
Marine operations depend on the ability to forecast suddenly appearing storms and failures often cause great damage. As a part of a sea state alarm study, meteorological forecasts overlaid with satellite measurements sent to ships have been found to be a useful tool. 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 zonal wind speeds.

The meteorological model is emulated using a Kalman filter technique. Together with a spatio-temporal state-space model the filter allows us to obtain forecasts which are overlaid with satellite measurements using a kriging method. Examples of overlays together with their statistical... (More)
Marine operations depend on the ability to forecast suddenly appearing storms and failures often cause great damage. As a part of a sea state alarm study, meteorological forecasts overlaid with satellite measurements sent to ships have been found to be a useful tool. 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 zonal wind speeds.

The meteorological model is emulated using a Kalman filter technique. Together with a spatio-temporal state-space model the filter allows us to obtain forecasts which are overlaid with satellite measurements using a kriging method. Examples of overlays together with their statistical uncertainties are presented and discussed. (Less)
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author
; and
organization
publishing date
type
Contribution to journal
publication status
unpublished
subject
in
Preprint without journal information
issue
2004:34
publisher
Manne Siegbahn Institute
ISSN
0348-7911
language
English
LU publication?
yes
id
5ccf8cde-8a37-4508-8787-f1d3f34b3db4 (old id 929328)
date added to LUP
2016-04-04 09:23:25
date last changed
2018-11-21 20:52:46
@article{5ccf8cde-8a37-4508-8787-f1d3f34b3db4,
  abstract     = {{Marine operations depend on the ability to forecast suddenly appearing storms and failures often cause great damage. As a part of a sea state alarm study, meteorological forecasts overlaid with satellite measurements sent to ships have been found to be a useful tool. 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 zonal wind speeds. <br/><br>
The meteorological model is emulated using a Kalman filter technique. Together with a spatio-temporal state-space model the filter allows us to obtain forecasts which are overlaid with satellite measurements using a kriging method. Examples of overlays together with their statistical uncertainties are presented and discussed.}},
  author       = {{Malmberg, Anders and Holst, Jan and Holst, Ulla}},
  issn         = {{0348-7911}},
  language     = {{eng}},
  number       = {{2004:34}},
  publisher    = {{Manne Siegbahn Institute}},
  series       = {{Preprint without journal information}},
  title        = {{A real-time assimilation algorithm applied to near-surface ocean winds}},
  year         = {{2004}},
}