Abstract
The basis for including EOF (empirical orthogonal functions) in storm surge computations consists of the presented equations of the multiple dynamic regression system. The use of EOF is then the best mathematical tool for minimizing the number of substitute predictors in the system. The components of the atmospheric pressure, wind and sea level fields are introduced as predictors. There are two approaches to the computations. The first one is to work out a dynamic statistical model only for storm surges. The other one is to create a joint model for everyday sea level changes and for storm surges. These two models are presented as an example of computations for the Baltic Sea and protection of the depression area around the Vistula estuary. The advantages, disadvantages and problems in formulating the models are discussed.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Aitken, A. C. (1935) ‘On least squares and linear combination of observations’, Proc. Royal Society of Edinburgh, 55, pp. 42–48.
Golub, G.H., and Heath, M. (1979) ‘Generalized cross-validation as a method for choosing a good ridge parameter’, Technometrix, 21, pp. 215–223.
Holmström, I., and Stokes, J. (1978) Statistical forecasting of sea level changes in the Baltic, Swedish Meteorological and Hydrological Institute, Report RMK 9, 20 pp.
Institute of Meteorology and Water Management, Maritime Branch, (1983) Measurement Data, Gdynia, (unpublished).
Kaiman, R. E. (1958) ‘Design of a self-optimizing control system’, Trans. ASME, 80, pp. 458–478.
Lachenbruch, P. A., and Goldstein, M. (1979) ‘Discriminant analysis’, Biometrics, 35, pp. 69–85.
Nyberg, L. (1983) ‘Sea level forecast with an EOF model’, Proc. Intern. Symp. North Sea Dynamics, Springer-Verlag, pp. 185–199.
Ozga-Zielińska, M. (1976) ‘Structure and operator functions of mathematical models of hydrological systems’, Journ. Hydr. Sci., 3, pp. 1–22.
Preisendorfer, R. W., and Mobley, C. D. (1988) Principal component analysis in meteorology and oceanography, Elsevier Scientific Publishing Company, New York, 425 pp.
Solov, A. R. (1987) ‘The applications of eigenanalysis to tide gauge records of relative sea level’, Continent. Shelf Res., 7, pp. 629–641.
Törnevik, H. (1977) ‘Application of empirical orthogonal functions to sea level forecasting’, ECMWF Workshop Empirical Orthogonal Functions in Meteor., pp. 112–133.
Wróblewski, A. (1986) ‘Application of EOF to computation of the storm surges on the Polish Baltic Coast in January 1983’, Acta Geophys. Vol., 34, pp. 63–75.
Wróblewski, A. (1990) ‘Statistical forecasting of random dynamic processes in the near-shore zone of the Southern Baltic’ (in Polish), Ossolineum, Wroclaw, 126 pp.
Wróblewski, A. (1991) ‘Sea level and storm surge forecasting in the Southern Baltic’, Oceanologia, 31, pp. 5–23
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1994 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Wróblewski, A. (1994). Empirical Orthogonal Functions (EOF) method in determining and forecasting storm floods in the coastal zones of the sea. In: Rossi, G., Harmancioğlu, N., Yevjevich, V. (eds) Coping with Floods. NATO ASI Series, vol 257. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1098-3_29
Download citation
DOI: https://doi.org/10.1007/978-94-011-1098-3_29
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-4480-6
Online ISBN: 978-94-011-1098-3
eBook Packages: Springer Book Archive