EOF analysis of a time series with application to tsunami detection

Dynamics of Atmospheres and Oceans

Volumn 50, Issue 1, 2010, Pages 35-54

  Tolkova, Elena ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Detiding; Empirical Orthogonal Functions; Filtering; Tide prediction; Time series analysis; Tsunami

Indexed keywords

APRIORI; CONSTANT FUNCTIONS; CONTINUOUS PROCESS; DATA GAP; EMPIRICAL ORTHOGONAL FUNCTION; EMPIRICAL ORTHOGONAL FUNCTION ANALYSIS; EMPIRICAL ORTHOGONAL FUNCTIONS; FILTERING; FUNCTIONAL SPACES; HARMONIC CONTENTS; INHERENT STRUCTURES; SIGNAL PASSAGE; STATIONARY PROCESS; SUB-SPACES; TIDAL PROCESS; TIDAL SIGNALS; TIDE PREDICTION; TSUNAMI DETECTION; TSUNAMI WAVES;

BUOYS; FILTER BANKS; FORECASTING; FOURIER ANALYSIS; NANOFLUIDICS; OCEANOGRAPHY; ORTHOGONAL FUNCTIONS; PRINCIPAL COMPONENT ANALYSIS; SIGNAL DETECTION; TIME SERIES; TSUNAMIS;

TIME SERIES ANALYSIS;

BUOY SYSTEM; DETECTION METHOD; EMPIRICAL ANALYSIS; FORECASTING METHOD; STANDING WAVE; TIDAL MODELING; TIME SERIES ANALYSIS; TSUNAMI;

EID: 77953026896     PISSN: 03770265     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dynatmoce.2009.09.001     Document Type: Article

References (29)

1. Boyd J.D., Kennelly E.P., Pistek P. Estimation of EOF expansion coefficients from incomplete data. Deep Sea Res. P. I 1994, 41(10):1479-1488.
2. Emery W.J., Thomson R.E. Data Analysis Methods in Physical Oceanography 2001, Elsevier, Amsterdam.
3. Everson R., Sirovich L. Karhunen-Loeve procedure for gappy data. J. Opt. Soc. Am. A 1995, 12(8):1657-1664.
4. Foreman M.G.G., Crawford W.R., Marsden R.F. De-tiding: theory and practice. Quantitative Skill Assessment for Coastal Ocean Models. Coastal and Estuarine Studies, 47 1995, 203-239. American Geophysical Union, Washington, DC. D.R. Lynch, A.M. Davies (Eds.).
5. Hamming R.W. Digital Filters 1998, Dover Publications, Inc., Mineola, NY.
6. Kantha, L.H., Clayson, C.A., 1999. Numerical Models of Oceans and Oceanic Processes. Academic Press, 940 pp., ISBN: 0124340687, 9780124340688.
7. Kim K.-Y. Statistical prediction of cyclostationary process. J. Climate 2000, 13:1098-1115.
8. Kim K.-Y., North G.R. EOF-based linear prediction algorithm: theory. J. Climate 1998, 11:3046-3056.
9. Kim K.-Y., North G.R. EOF-based linear prediction algorithm: examples. J. Climate 1999, 12:2076-2092.
10. Kim K.-Y., North G.R., Huang J. EOFs of one-dimensional cyclostationary time series: computations, examples, and stochastic modeling. J. Atmos. Sci. 1996, 53(7):1007-1017.
11. Kulikov, E.A., 1990. Sea level measurements and tsunami forecasting. Sov. Meteorol. Hydrol., No. 6, 61-68.
12. Kulikov E.A., Rabinovich A.B., Spirin A.I., Poole S.L., Soloviev S.L. Measurement of tsunamis in the open ocean. Mar. Geodesy 1983, 6(3/4):311-329.
13. Kutzbach J.E. Empirical eigenvectors of sea-level pressure, surface temperature and precipitation complexes over North America. J. Appl. Meteorol. 1967, 6:791802.
14. Le Provost C., Genco M.-L., Lyard F. Modeling and predicting tides over the world ocean. Quantitative Skill Assessment for Coastal Ocean Models. Coastal and Estuarine Studies, 47 1995, 175-201. American Geophysical Union, Washington, DC. D.R. Lynch, A.M. Davies (Eds.).
15. Meinig, C., Stalin, S.E., Nakamura, A.I., Milburn, H.B., 2005. Real-time Deep-ocean Tsunami Measuring, Monitoring, and Reporting System: The NOAA DART II Description and Disclosure. http://nctr.pmel.noaa.gov/Dart/Pdf/DART_II_Description_6_4_05.pdf.
16. Mo K.C. Adaptive filtering and prediction of intraseasonal oscillations. Mon. Weather Rev. 2001, 129:802-817.
17. Mofjeld, H.O., 2009. Tsunami measurements. In: The Sea, vol. 15, Ch.7. Harvard University Press.
18. Mofjeld H.O., González F.I., Eble M.C., Newman J.C. Ocean tides in the continental margin off the Pacific Northwest shelf. J. Geophys. Res. 1995, 100:10789-10800.
19. Munk W.H., Cartwright D.E. Tidal spectroscopy and prediction. Philos. Trans. R. Soc. Lond. A: Math. Phys. Sci. 1966, 259:533-581.
20. Pairaud I., Auclair F. Combined wavelet and principal component analysis (WEof) of a scale-oriented model of coastal ocean gravity waves. Dyn. Atmos. Oceans 2005, 40:254-282.
21. Ponchaut F., Lyard F., Le Provost C. An analysis of the tidal signal in the WOCE sea level dataset. J. Atmos. Oceanic Technol. 2001, 18:77-91.
22. Rabinovich A.B., Thomson R.E. The 26 December 2004 Sumatra tsunami: analysis of tide gauge data from the World Ocean. Part 1. Indian Ocean and South Africa. Pure Appl. Geophys. 2007, 164(2/3):261-308.
23. Rabinovich A.B., Thomson R.E., Stephenson F.E. The Sumatra tsunami of 26 December 2004 as observed in the North Pacific and North Atlantic oceans. Surv. Geophys. 2006, 27:647-677.
24. Raick C., Beckers J.-M., Soetaert K., Grgoire M. Can principal component analysis be used to predict the dynamics of a strongly non-linear marine biogeochemical model?. Ecol. Model. 2006, 196(3/4):345-364.
25. Thomson R.E., Rabinovich A.B., Krassovski M.V. Double jeopardy: Concurrent arrival of the 2004 Sumatra tsunami and storm-generated waves on the Atlantic coast of the United States and Canada, 34. Geophys. Res. Lett. 2007, 34:L15607. doi:10.1029/2007GL030685.
26. Titov, V.V., 2009. Tsunami forecasting. In: The Sea, vol. 15, Ch. 12. Harvard University Press.
27. Tolkova E. Principal component analysis of tsunami buoy record: tide prediction and removal. Dyn. Atmos. Oceans 2009, 46(1-4):62-82.
28. Vautard R., Ghil M. Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series. Physica D: Nonlinear Phenom. 1989, 35(3):395-424.
29. Vautard R., Yiou P., Ghil M. Singular-spectrum analysis: a toolkit for short, noisy chaotic signals. Physica D: Nonlinear Phenom. 1992, 58(1-4):95-126.