Space-Time Prediction of Ocean Winds
(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:
https://lup.lub.lu.se/record/544667
- author
- Malmberg, Anders LU
- supervisor
-
- Ulla Holst LU
- opponent
-
- Professor Guttorp, Peter, Department of Statistics, University of Seattle
- organization
- publishing date
- 2005
- 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 09:15:00
- ISBN
- 91-628-6489-0
- language
- English
- LU publication?
- yes
- id
- 4796e7b4-f4d2-4b36-8316-03b0c87a613c (old id 544667)
- date added to LUP
- 2016-04-01 16:53:21
- date last changed
- 2018-11-21 20:44:59
@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}},
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}},
language = {{eng}},
publisher = {{KFS AB}},
school = {{Lund University}},
title = {{Space-Time Prediction of Ocean Winds}},
year = {{2005}},
}