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Space-Time Prediction of Ocean Winds

Malmberg, Anders LU (2005)
Abstract
The topic of this thesis is inspired by an



experiment in which a vessel, laying a submarine cable, was



provided with forecasts overlaid with satellite observations of



significant wave height. During the operation, the



vessel was close to



an adverse weather area and the personnel on board could confirm that



the forecast was not as close to the "ground truth" as the satellite



observation was. One of the outcomes of this experiment was the



suggestion to develop a method providing forecasts merged with



satellite observations. In this thesis such a method is developed... (More)
The topic of this thesis is inspired by an



experiment in which a vessel, laying a submarine cable, was



provided with forecasts overlaid with satellite observations of



significant wave height. During the operation, the



vessel was close to



an adverse weather area and the personnel on board could confirm that



the forecast was not as close to the "ground truth" as the satellite



observation was. One of the outcomes of this experiment was the



suggestion to develop a method providing forecasts merged with



satellite observations. In this thesis such a method is developed for



near-surface ocean winds.



The thesis consists of four papers (Paper A-D). The contribution



of Paper A and B is the development of a statistical framework,



in which forecasts



and satellite observations in a bounded area are merged and a measure



of uncertainty is



provided.



A dimension-reduced Kalman filter is used as an emulator of



the atmospheric dynamics. This is considered in Paper A.



The method of merging Kalman filter forecasts with satellite



measurements is developed in Paper B.



Closely related to Paper A and B is the problem of modelling the



covariance structure of residuals taken as differences between



forecasts and satellite measurements. Two isotropic covariance functions



belonging to the Matern family are used. However,



neither of the functions seem



to properly model the residual field. The contribution of Paper C is an



explorative study and it forms a basis for further research.



Finally, Paper D models the dynamics of a spatio-temporal process



based on an image warping approach. Image warping models the dynamics through



the movement of a set of control points. As well as allowing affine



transformations, the model also allows for non-linear dynamics. The main



contribution of this paper is the formulation of a penalized



likelihood which is used to estimate the model. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Guttorp, Peter, Department of Statistics, University of Seattle
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Statistics, operations research, image warping, thin-plate splines., near-surface ocean winds, variogram parameters, Space-time Kalman filtering, real-time assimilation, residual wind speed, actuarial mathematics, programming, Statistik, operationsanalys, programmering, aktuariematematik
pages
140 pages
publisher
KFS AB
defense location
Matematikcentrum, Sölvegatan 18, sal MH:A, Lunds Tekniska Högskola
defense date
2005-05-13 09:15
ISSN
1404-0034
ISBN
91-628-6489-0
language
English
LU publication?
yes
id
4796e7b4-f4d2-4b36-8316-03b0c87a613c (old id 544667)
date added to LUP
2007-09-27 15:55:04
date last changed
2016-09-19 08:44:58
@phdthesis{4796e7b4-f4d2-4b36-8316-03b0c87a613c,
  abstract     = {The topic of this thesis is inspired by an<br/><br>
<br/><br>
experiment in which a vessel, laying a submarine cable, was<br/><br>
<br/><br>
provided with forecasts overlaid with satellite observations of<br/><br>
<br/><br>
significant wave height. During the operation, the<br/><br>
<br/><br>
vessel was close to<br/><br>
<br/><br>
an adverse weather area and the personnel on board could confirm that<br/><br>
<br/><br>
the forecast was not as close to the "ground truth" as the satellite<br/><br>
<br/><br>
observation was. One of the outcomes of this experiment was the<br/><br>
<br/><br>
suggestion to develop a method providing forecasts merged with<br/><br>
<br/><br>
satellite observations. In this thesis such a method is developed for<br/><br>
<br/><br>
near-surface ocean winds.<br/><br>
<br/><br>
The thesis consists of four papers (Paper A-D). The contribution<br/><br>
<br/><br>
of Paper A and B is the development of a statistical framework,<br/><br>
<br/><br>
in which forecasts<br/><br>
<br/><br>
and satellite observations in a bounded area are merged and a measure<br/><br>
<br/><br>
of uncertainty is<br/><br>
<br/><br>
provided.<br/><br>
<br/><br>
A dimension-reduced Kalman filter is used as an emulator of<br/><br>
<br/><br>
the atmospheric dynamics. This is considered in Paper A.<br/><br>
<br/><br>
The method of merging Kalman filter forecasts with satellite<br/><br>
<br/><br>
measurements is developed in Paper B.<br/><br>
<br/><br>
Closely related to Paper A and B is the problem of modelling the<br/><br>
<br/><br>
covariance structure of residuals taken as differences between<br/><br>
<br/><br>
forecasts and satellite measurements. Two isotropic covariance functions<br/><br>
<br/><br>
belonging to the Matern family are used. However,<br/><br>
<br/><br>
neither of the functions seem<br/><br>
<br/><br>
to properly model the residual field. The contribution of Paper C is an<br/><br>
<br/><br>
explorative study and it forms a basis for further research.<br/><br>
<br/><br>
Finally, Paper D models the dynamics of a spatio-temporal process<br/><br>
<br/><br>
based on an image warping approach. Image warping models the dynamics through<br/><br>
<br/><br>
the movement of a set of control points. As well as allowing affine<br/><br>
<br/><br>
transformations, the model also allows for non-linear dynamics. The main<br/><br>
<br/><br>
contribution of this paper is the formulation of a penalized<br/><br>
<br/><br>
likelihood which is used to estimate the model.},
  author       = {Malmberg, Anders},
  isbn         = {91-628-6489-0},
  issn         = {1404-0034},
  keyword      = {Statistics,operations research,image warping,thin-plate splines.,near-surface ocean winds,variogram parameters,Space-time Kalman filtering,real-time assimilation,residual wind speed,actuarial mathematics,programming,Statistik,operationsanalys,programmering,aktuariematematik},
  language     = {eng},
  pages        = {140},
  publisher    = {KFS AB},
  school       = {Lund University},
  title        = {Space-Time Prediction of Ocean Winds},
  year         = {2005},
}