Seasonal autoregressive modeling of a skew storm surge series

Ocean Modelling

Volumn 47, Issue , 2012, Pages 41-54

  Weiss, Jérôme ^a,b   Bernardara, Pietro ^a,b   Andreewsky, Marc ^a   Benoit, Michel ^a,b  

^a EDF R AND D   (France)

^b Universite Paris Est   (France)

Author keywords

Extreme surge level; Long term simulations; Seasonal autoregressive models; Skew surge; Surge correlation; Western Europe

Indexed keywords

AUTO REGRESSIVE MODELS; EXTREME SURGE LEVEL; LONG TERM SIMULATION; SKEW SURGE; WESTERN EUROPE;

FLOODS; STOCHASTIC MODELS; STORMS;

COMPUTER SIMULATION;

COMPUTER SIMULATION; CORRELATION; ESTIMATION METHOD; GAUSSIAN METHOD; HARBOR; NUMERICAL MODEL; REGRESSION ANALYSIS; SEASONAL VARIATION; STOCHASTICITY; STORM SURGE;

ATLANTIC OCEAN; ENGLISH CHANNEL; NORTH SEA; WESTERN EUROPE;

EID: 84857667763     PISSN: 14635003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ocemod.2012.01.005     Document Type: Article

References (58)

1. Abraham B., Balakrishna N. Inverse Gaussian autoregressive models. Journal of Time Series Analysis 1999, 20:605-618.
2. Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control 1974, 19:716-723.
3. Alvarez A., Orfila A., Basterretxea G., Tintore J., Vizoso G., Fornes A. Forecasting front displacements with a satellite based ocean forecasting (SOFT) system. Journal of Marine Systems 2007, 65:299-313.
4. álvarez Fanjul E., Pérez B., Rodríguez Sánchez-Arévalo I. NIVMAR: a storm-surge forecasting system for Spanish waters. Scientia Marina 2001, 60:145-154.
5. Anderson P.L., Meerschaert M.M. Modeling river flows with heavy tails. Water Resource Research 1998, 34:2271-2280.
6. Bajo M., Umgiesser G. Storm surge forecast through a combination of dynamic and neural network models. Ocean Modelling 2010, 33:1-9.
7. Bardet L., Duluc C.-M., Rebour V., L'Her J. Regional frequency analysis of extreme storm surges along the French coast. Natural Hazards and Earth System Sciences 2011, 11:1627-1639.
8. Barndorff-Nielsen O.E. Normal inverse Gaussian distributions and stochastic volatility modelling. Scandinavian Journal of Statistics 1997, 24:1-13.
9. Bernardara P., Andreewsky M., Benoit M. Application of the regional frequency analysis to the estimation of extreme storm surges. Journal of Geophysical Research 2011, 116:1-11.
10. Bernardara P., De Michele C., Rosso R. A simple model of rain in time: an alternating renewal process of wet and dry states with a fractional (non-gaussian) rain intensity. Atmospheric Research 2006, 84:291-301.
11. Bernardara P., Schertzer D., Sauquet E., Tchiguirinskaia I., Lang M. The flood probability distribution tail: how heavy is it?. Stochastic Environmental Research and Risk Assessment 2008, 22:107-122.
12. Bondon P. Estimation of autoregressive models with epsilon-skew-normal innovations. Journal of Multivariate Analysis 2009, 100:1761-1776.
13. Box G.E.P., Jenkins G.M. Time Series Analysis, Forecasting and Control 1976, Holden Day, San Francisco.
14. Breaker L.C., Brewster J.K. Predicting offshore temperatures in Monterey Bay based on coastal observations using linear forecast models. Ocean Modelling 2009, 27:82-97.
15. Brockwell P.J., Davis R.A. Introduction to Time Series and Forecasting 1996, Springer. second ed.
16. De Haan L. On Regular Variation and its Application to Weak Convergence of Sample Extremes 1970, CWI Tract, Amsterdam, 32.
17. Dixon, M.J., Tawn, J.A., 1994. Extreme Sea Levels at the UK A Class Sites: Site by Site Analysis. Proudman Oceanographic Laboratory.
18. El Adlouni S., Bobée B., Ouarda T.B.M.J. On the tails of extreme event distributions in hydrology. Journal of Hydrology 2008, 355:16-33.
19. Eriksson A., Ghysels E., Wang F. The normal inverse Gaussian distribution and the pricing of derivatives. The Journal of Derivatives 2009, 16:23-37.
20. Figueroa-Lopez, J.E., Lancette, S.R., Lee, K., Mi, Y., 2011. Estimation of NIG and VG models for high frequency financial data. Handbook for Modeling High-Frequency Data in Finance. J. Wiley.
21. Fisher, R., Tippet, L., 1928. On the estimation of the frequency distribution of the largest or smallest member of a sample. Proceedings of the Cambridge Philosophical Society.
22. Fréchet M. Sur la lois de probabilité de l'écart maximum. Annales de la société polonaise de mathématique (in French) 1928, 6:93-122.
23. Gnedenko B. Sur la distribution limite du terme maximum d'une série aléatoire (in French). Annals of Mathematics 1943, 44:423-453.
24. Gumbel E.J. Statistics of Extremes 1958, Columbia University Press, New York.
25. Hawkes P.J., Gonzales-Marco D., Sanchez-Arcilla A., Prinos P. Best practice for the estimation of extremes: a review. Journal of Hydraulic Research 2008, 46:324-332.
26. Higaki M., Hayashibara H., Nozaki F. Outline of the Storm Surge Prediction Model at the Japan Meteorological Agency RSMC Tokyo-Typhoon Center Technical Review. 2009, 11:25-38.
27. Hipel K.W., McLeod A.I. Time Series Modelling of Water Resources and Environmental Systems 1994, Elsevier, New York.
28. Hughes G.L., Subba Rao S., Subba Rao T. Statistical analysis and time series models for minimum and maximum temperatures in the Antarctic Peninsula. Proceedings of the Royal Society A 2006, 463:241-259.
29. Jensen M.B., Lunde A. The NIG-S&ARCH Model: a fat tailed, stochastic, and autoregressive conditional heteroskedastic volatility model. The Econometrics Journal 2001, 4:319-342.
30. Kwan A.C.C., Sim A.-B., Wu Y. A comparative study of the finite-sample performance of some portmanteau tests for randomness of a time series. Computational Statistics & Data Analysis 2005, 48:391-413.
31. Kyselý J. Probability estimates of extreme temperature events: stochastic modelling approach vs. extreme value distribution. Studia Geophysica et Geodaetica 2002, 46:93-112.
32. Ledolter J. A general class of stochastic models for hydrologic sequences. Journal of Hydrology 1978, 36:309-325.
33. Lencioni, P., Benque, J.P., Coeffe, Y., 1982. Examples of storm surge prediction models. In: 18th International Conference on Coastal Engineering (ICCE 1982), Cape Town, South Africa.
34. Li W.K., McLeod A. ARMA modelling with non-Gaussian innovations. Journal of Time Series Analysis 1988, 9:155-168.
35. Ljung G.M., Box G.E.P. On a measure of lack of fit in time series models. Biometrika 1978, 65:297-303.
36. McLeod A.I. Diagnostic checking periodic autoregression models with application. The Journal of Time Series Analysis 1995, 15:221-233.
37. Monbet V., Ailliot P., Prevosto M. Survey of stochastic models for wind and sea state time series. Probabilistic Engineering Mechanics 2007, 22:113-126.
38. Newbold P. The principles of the box-Jenkins approach. Operational Research Quarterly 1975, 26:397-412.
39. Oigard T.A., Hanssen A., Hansen R.E., Godtliebsen F. EM-estimation and modeling of heavy-tailed processes with the multivariate normal inverse Gaussian distribution. Signal Processing 2005, 85:1655-1673.
40. Olbert A., Hartnett M. Storms and surges in Irish coastal waters. Ocean Modelling 2010, 34:50-62.
41. Paradis D., Ohla P., Daniel P. Operational storm surges forecasting in an estuary. Marine Geodesy 2009, 32:166-177.
42. Petaccia S., Serravall R., Pellicano F. Improved method for sea level forecasting at Venice (Northern Adriatic Sea). Communications in Nonlinear Science and Numerical Simulation 2006, 11:281-296.
43. Pindyck R.S., Rubinfeld D.L. Econometric Models and Economic Forecasts 1991, McGraw-Hill, New York. third ed.
44. Röske F. Sea level forecasts using neural networks. Ocean Dynamics 1997, 49:71-99.
45. Sabo J.L., Post D.M. Quantifying periodic, stochastic, and catastrophic environmental variation. Ecological Monographs 2008, 78:19-40.
46. Salas J.D., Boes D.C., Smith R.A. Estimation of ARMA models with seasonal parameters. Water Resource Research 1982, 18:1006-1010.
47. Salberg, A.B., Swami, A., Oigard, T.A., Hanssen, A., 2001. The normal inverse Gaussian distribution as a model for MUI. In: 35th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA.
48. Schwarz G. Estimating the dimension of a model. Annals of Statistics 1978, 6:461-464.
49. Simon B. La marée océanique côtière 2007, Editions de l'Institut Océanographique.
50. Tawn J.A. Estimating probabilities of extreme sea-levels. Applied Statistics 1992, 41:77-93.
51. Tesfaye, Y.G., Meerschaert, M.M., Anderson, P.L., 2006. Identification of periodic autoregressive moving average models and their application to the modeling of river flows. Water Resource Research 42.
52. Todd L., Walton J. Short term surge storm forecasting. Journal of Coastal Research 2005, 21:421-429.
53. Tomohiro, Y., Mase, H., Kunitomi, S., Mori, N., Hayashi, Y., 2010. Stochastic typhoon model and its application to future typhoon projection. ICCE 2010, Shangai.
54. Trindade A.A., Zhu Y., Andrews B. Time series models with asymmetric Laplace innovations. Journal of Statistical Computation and Simulation 2010, 80:1317-1333.
55. Vecchia A.V., Ballerini R. Testing for periodic autocorrelations in seasonal time series data. Biometrika 1991, 78:53-63.
56. Walh, T., Jensen, J., Mudersbach, C., 2010. A multivariate statistical model for advanced storm surge analyses in the North Sea. In: 32nd International Conference on Coastal Engineering (ICCE), Shanghai.
57. Yang Y. Can the strengths of AIC and BIC Be shared? A conflict between model identification and regression estimation. Biometrika 2005, 92:937-950.
58. You S., Seo J. Storm surge prediction using an artificial neural network model and cluster analysis. Natural Hazards 2009, 57:97-114.