Fourty years of wave hindcast using Wave Watch III model and calibration with several data sources at the Caribbean Sea
DOI:
https://doi.org/10.26640/22159045.200Keywords:
Wave hindcast, wave data, numerical modeling, wind wave modelsAbstract
This paper describes the first approach to wave climatology, in the project called Interaction between the Atmosphere-Ocean-Land Processes in the Colombian Caribbean Sea. The main objective is to improve the data of sea level and wave climatology for the Colombian Caribbean waters. To do this, the 40-year global atmospheric Reanalysis 1 (resolution of 1.8º x 1.905º and 4 times daily) carried out by the National Center for Environmental Prediction and The National Center for Atmospheric Research (NCEPNCAR) Centers has been used to force the WaveWatchIII™ model to produce time series of significance wave height (Hs) and Period (T). The hindcast values have been corrected with information from different sources to achieve more accuracy of the data. The available data, including wind, wave and sea-level data, instrumental data from buoys (NOAA: 41018 and 42058, among others) in the Caribbean region, satellite data extracted from TOPEX/POSEIDON and Jason 1, and visual wave data provided by ships of opportunity. Statistical analysis of the produced wave hind cast was performed in order to provide information about the climatological trends in the Caribbean Sea and coastal areas. The results show how the annual cycle of the wave presents a bimodal behavior associated with the behavior of northeast trade winds showing two periods of strong winds and waves (low precipitations) and two periods of weak winds and waves(high rain fall).The spatial distribution of the waves shows a central area in the Caribbean with the higher values of significant wave height (Hs) associated with the so called San Andrés Low - level jet and a coastal area located between Cartagena and Santa Marta. These results are consistent with a few papers presented by other authors who obtained significant wave heights of about 2.5 meters for dry season in the region of Bocas de Ceniza in Barranquilla.Downloads
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References
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[18] Nordenstrom, N. Methods for predicting long term distributions of wave loads and probability of failure of ships, appendix II, Relationships between visually estimated and theoretical wave heights and periods. Research Report 69-22-S, Det Norski Veritas. 1969.
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[21] Montoya R.D y Osorio A. Los modelos de generación de oleaje de viento: Características, evolución y futuras aplicaciones en Colombia. En: Avances en recursos hidráulicos. 2007; 15: 47-74.
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[23] Hasselmann, K. Acriterion for non-linear wave stability. J. Fluid Mech. 1967; 30:737–739.
[24] Caires, S., Steri, A.Bidlot, J.R., Graham, N., and Swail, V. Intercomparison of different wind-wave Reanalysis. Journal of Climate. 2004; 17: 1893-1913.
[25] Montoya R.D., Osorio A.,Ortiz J.C, and Ocampo, F. Importance of accurate background winds combined with hurricane wind models: Case study of Hurricane Katrina. Waves In Shallow Environments (WISE Meeting). Ensenada, B.C. Mexico. 2009.
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[27] Komen, G.J., Hasselmann, S. y Hasselmann, K. On the existence of a fully developed wind-sea spectrum, J. Phys. Oceanogr. 1984; 14: 1271-1285.
[28] Hasselmann, S., Hasselmann, K.J., Allender H. y Barnett, T.P. Computations and parameterizations of the nonlinear energy transfer in a gravity-wave spectrum. Part II: Parameterizations of the nonlinear energy transfer for application in wave models. J. Phys. Oceanogr. 1985; 15: 1378- 1391.
[29] Hasselmann, K., Barnett, T. P., Bouws, E., Carlson, H., Cartwright, D. E., Enke, K., Ewing, J. A., Gienapp, H., Hasselmann, D. E., Kruseman, P.,Meerburg, A., Muller, P., Olbers, D. J., Richter, K., Sell, W. and Walden, H. Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP), Dtsch. Hydrogh. Z. Suppl. 1973; 12: A8.
[30] Crosby et al. Aproposed definition for vector correlation in geophysics: Theory and application. Journal of atmospheric and ocean technology. American meteorological society. 1992; 10: 355-367.
[31] Detzius, R. Extension of correlations methods and the method of least squares to vectors. Sitzungsber. Akad. Wiss. 1916; 125(IIa): 3-20.
[32] Sverdrup, H. U. On correlation between vectors with applications to meteorological problems. Meteor. Z. 1917; 34: 285-291.
[33] Hotelling, H. Relations between two sets of variables. Biometrika. 1936; 28: 321-377.
[34] Court, A. Wind correlation and regression. AFCRC TN-58-230.ContractAF19(604)-2060. Cooperative Research Foundation. 1958; 16.
[35] Hooper, J.W. Simultaneous equations and canonical correlation theory. Econométrica. 1959; 27:245-256.
[36] Jupp, P. E.; Mardia, K. V. Ageneral correlation coefficient for a directional data and related regression problems. Biometrika. 1980; 67: 163-173.
[37] Crosby, D.S., L.C. Breaker, and W.H. Gemmill, 1990: A definition for vector de correlation and its application to marine surface winds. National Meteorological Center Office Note. 1990; 365:50.
[38] Vidal, C. et al. Determinación de los regímenes medios direccionales de altura de ola a partir de datos visuales, GIOC. 2001.
[39] Amador J.A. Aclimatic feature of the tropical Americas: The trade wind easterly jet. Top Meteor Oceanogr. 1998; 5(2):1–13.
[40] Amador J.A., Magana V. Dynamics of the low level jet over the Caribbean Sea. Preprints, the 23rd conference on hurricanes and tropical meteorology, American Meteorological Society. 1999; 868–869.
[41] Poveda G, Mesa O.J. The low level westerly jet (Choco jet) and two other jets in Colombia: climatology and variability during ENSO phases (in Spanish). Rev Academia Colomb Cienc. 1999; 23(89):517–528.
[42] Poveda G., Waylen P.R., Pulwarty R.S. Annual and interannual variability of the present climate in northern South America and southern Mesoamerica. Palaeogeogr Palaeoclimatol Palaeoecol. 2006; 234:3–27.
[43] Bernal G., Poveda G., Roldán P. & Andrade C. Patrones de variabilidad de las temperaturas superficiales del mar en la Costa Caribe Colombiana. Rev. Acad. Colomb. Cienc. 2006;30 (115): 195- 208.
[44] Wang, C. Variability of the Caribbean Low-Level Jet and its relations to climate. Clim Dyn 2007; 29:411-422.
[45] Poveda, G,Velez J.I,Mesa O.J, Hoyos C.D, Mejia J.F, Barco O.J y Correa P.L. Influencia de fenómenos macroclimáticos sobre el ciclo anual de la hidrología colombiana: Cuantificación lineal, no lineal y percentiles probabilísticos, meteorología colombiana. 2002b; 6:121-130.
[46] Gil, M.M, y Quiceno, N. La influencia del fenómeno El Niño/Oscilación del Sur sobre el ciclo anual de la hidroclimatología de Colombia, Trabajo Dirigido de Grados, Ingeniería Civil, Facultad de Minas, Universidad Nacional de Colombia, Sede Medellín. 1997.
[47] Ruiz, M. y G. Bernal. (En prep). Variabilidad estacional del viento sobre la Cuenca Colombia, mar Caribe. Revista Avances en Recursos Hidráulicos.
48] Montoya, R.D, Osorio, A.F y Mesa, J.C. Influencia de las parametrizaciones empleadas para los términos fuente sumidero de energía en la modelación del oleaje en el Caribe colombiano. XIII Seminario Nacional De Ciencia y Tecnología del Mar SENALMAR 2008.
[49] Giraldo, L, y Lonin S. Cálculo del oleaje y el transporte de sedimentos en la costa Caribe colombiana. Boletín Científico del CIOH. 1997; 18, 39 -49.56.
[2] Agudelo P., Restrepo A.F, Molares R., Tejada C.E, Torres R., Osorio A.F. Determinación del clima de oleaje medio y extremal en el Caribe colombiano, Boletín Científico CIOH. 2006; 23: 33-45.
[3] Lonin S., Tuchkovenko Y., Lonina I. Utilización del modelo Nedwam para el cálculo y pronóstico del oleaje en el mar Caribe. Boletín Científico CIOH. 1996; 17: 37-45.
[4] Torres R. y Lonin S. Estudio del espectro de oleaje en el Caribe observado con boyas y su representación en el espectro JONSWAP. Boletín Científico CIOH. 2007a; 25: 8-18.
[5] Torres R. y Lonin S. Construcción de espectros de oleaje en el Caribe a partir de mediciones satelitales. Boletín Científico CIOH. 2007b; 25: 19-31.
[6] Komen GJ, Cavaleri L, Donelan M, Hasselmann K, Hasselmann S and Janssen PAEM. Dynamics and Modellin of Ocean Waves. Cambridge University Press. 1994.
[7] Tolman H. L. User manual and system documentation of WAVEWATCH-III version 2.22. NOAA/ NWS / NCEP/ MMAB Technical Note. 2002; 222: 133.
[8] SWAN. Technical Documentation. Delft University of Technology, Version 40.51A. 2007: 111.
[9] Caires, S.; Sterl A. Validation of ocean wind and wave data using triple collocation, J. Geophys. Res. 2003; 108(C3), 3098.
[10] Cavaleri, Land Sclavo, M. The calibration of wind and wave model data in the Mediterranean sea. Coastal Engineering. 2006; 53: 613-627.
[11] Dobson E, Monaldo F, Goldhirsh J and Wilkerson J . Validation of Geosat derived wind speeds and significant wave heights using buoy data,J. Geophy. Res. 1987; 92: 10719–10731.
[12] Duchossois, G. The ERS-1 mission objectives. ESABull. 1991; 65: 16–25.
[13] Fu, L.L., Christensen, E.J., Yamarone, C.A., Lefebvre, M., Menard, Y., Escudier, P. TOPEX–POSEIDON mission overview. J. Geophys. Res.1994; 99 (C12): 24369–24381.
[14] Krogstad, H. E; Barstow, S. F . Satellite wave measurements for coastal engineering applications. Coastal Engineering. 1999; 37: 283-307.
[15] Del Balzo, D. R.,Schultz, J.R. and Earle, M.D. Stochastic time-series simulation of wave parameters using ship observations. Ocean Engineering. 2003; 30: 1417–1432.
[16] Cartwright, D.E. Committee 1, environmental conditions. Report of the Third International Ship Structures Congress, Det Norski Veritas.1967.
[17] Hogben, N., Lumb, F.E. Ocean wave statistics. National Physical Laboratory Report, Her Majesty's Stationery Office, UK. 1967.
[18] Nordenstrom, N. Methods for predicting long term distributions of wave loads and probability of failure of ships, appendix II, Relationships between visually estimated and theoretical wave heights and periods. Research Report 69-22-S, Det Norski Veritas. 1969.
[19] Wilkerson, J.C., Earle, M.D. Astudy of differences between environmental reports by ships in the voluntary observing program and measurements from NOAA buoys. Journal of Geophysical Research. 1990; 95: 3373–3385.
[20] Gulev, S.K., Hasse, L. North Atlantic wind waves and wind stress fields from voluntary observing ship data. Journal of Physical Oceanography. 1998; 28: 1107–1130.
[21] Montoya R.D y Osorio A. Los modelos de generación de oleaje de viento: Características, evolución y futuras aplicaciones en Colombia. En: Avances en recursos hidráulicos. 2007; 15: 47-74.
[22] Tolman, H.L. A third-generation model for wind waves on slowly varying, unsteady and inhomogeneous depth and currents. Journal of Physical Oceanography. 1991; 21: 782–797.54Referencias bibliográficasOsorio et al.: Reconstrucción de cuarenta años de datos de oleaje en el mar Caribe
[23] Hasselmann, K. Acriterion for non-linear wave stability. J. Fluid Mech. 1967; 30:737–739.
[24] Caires, S., Steri, A.Bidlot, J.R., Graham, N., and Swail, V. Intercomparison of different wind-wave Reanalysis. Journal of Climate. 2004; 17: 1893-1913.
[25] Montoya R.D., Osorio A.,Ortiz J.C, and Ocampo, F. Importance of accurate background winds combined with hurricane wind models: Case study of Hurricane Katrina. Waves In Shallow Environments (WISE Meeting). Ensenada, B.C. Mexico. 2009.
[26] Snyder, R. L., Dobson, F. W., Elliott, J. A. y Long, R.B. Array measurements of atmospheric pressure fluctuations above surface gravity waves. J. Fluid Mech. 1981; 102: 1–59.
[27] Komen, G.J., Hasselmann, S. y Hasselmann, K. On the existence of a fully developed wind-sea spectrum, J. Phys. Oceanogr. 1984; 14: 1271-1285.
[28] Hasselmann, S., Hasselmann, K.J., Allender H. y Barnett, T.P. Computations and parameterizations of the nonlinear energy transfer in a gravity-wave spectrum. Part II: Parameterizations of the nonlinear energy transfer for application in wave models. J. Phys. Oceanogr. 1985; 15: 1378- 1391.
[29] Hasselmann, K., Barnett, T. P., Bouws, E., Carlson, H., Cartwright, D. E., Enke, K., Ewing, J. A., Gienapp, H., Hasselmann, D. E., Kruseman, P.,Meerburg, A., Muller, P., Olbers, D. J., Richter, K., Sell, W. and Walden, H. Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP), Dtsch. Hydrogh. Z. Suppl. 1973; 12: A8.
[30] Crosby et al. Aproposed definition for vector correlation in geophysics: Theory and application. Journal of atmospheric and ocean technology. American meteorological society. 1992; 10: 355-367.
[31] Detzius, R. Extension of correlations methods and the method of least squares to vectors. Sitzungsber. Akad. Wiss. 1916; 125(IIa): 3-20.
[32] Sverdrup, H. U. On correlation between vectors with applications to meteorological problems. Meteor. Z. 1917; 34: 285-291.
[33] Hotelling, H. Relations between two sets of variables. Biometrika. 1936; 28: 321-377.
[34] Court, A. Wind correlation and regression. AFCRC TN-58-230.ContractAF19(604)-2060. Cooperative Research Foundation. 1958; 16.
[35] Hooper, J.W. Simultaneous equations and canonical correlation theory. Econométrica. 1959; 27:245-256.
[36] Jupp, P. E.; Mardia, K. V. Ageneral correlation coefficient for a directional data and related regression problems. Biometrika. 1980; 67: 163-173.
[37] Crosby, D.S., L.C. Breaker, and W.H. Gemmill, 1990: A definition for vector de correlation and its application to marine surface winds. National Meteorological Center Office Note. 1990; 365:50.
[38] Vidal, C. et al. Determinación de los regímenes medios direccionales de altura de ola a partir de datos visuales, GIOC. 2001.
[39] Amador J.A. Aclimatic feature of the tropical Americas: The trade wind easterly jet. Top Meteor Oceanogr. 1998; 5(2):1–13.
[40] Amador J.A., Magana V. Dynamics of the low level jet over the Caribbean Sea. Preprints, the 23rd conference on hurricanes and tropical meteorology, American Meteorological Society. 1999; 868–869.
[41] Poveda G, Mesa O.J. The low level westerly jet (Choco jet) and two other jets in Colombia: climatology and variability during ENSO phases (in Spanish). Rev Academia Colomb Cienc. 1999; 23(89):517–528.
[42] Poveda G., Waylen P.R., Pulwarty R.S. Annual and interannual variability of the present climate in northern South America and southern Mesoamerica. Palaeogeogr Palaeoclimatol Palaeoecol. 2006; 234:3–27.
[43] Bernal G., Poveda G., Roldán P. & Andrade C. Patrones de variabilidad de las temperaturas superficiales del mar en la Costa Caribe Colombiana. Rev. Acad. Colomb. Cienc. 2006;30 (115): 195- 208.
[44] Wang, C. Variability of the Caribbean Low-Level Jet and its relations to climate. Clim Dyn 2007; 29:411-422.
[45] Poveda, G,Velez J.I,Mesa O.J, Hoyos C.D, Mejia J.F, Barco O.J y Correa P.L. Influencia de fenómenos macroclimáticos sobre el ciclo anual de la hidrología colombiana: Cuantificación lineal, no lineal y percentiles probabilísticos, meteorología colombiana. 2002b; 6:121-130.
[46] Gil, M.M, y Quiceno, N. La influencia del fenómeno El Niño/Oscilación del Sur sobre el ciclo anual de la hidroclimatología de Colombia, Trabajo Dirigido de Grados, Ingeniería Civil, Facultad de Minas, Universidad Nacional de Colombia, Sede Medellín. 1997.
[47] Ruiz, M. y G. Bernal. (En prep). Variabilidad estacional del viento sobre la Cuenca Colombia, mar Caribe. Revista Avances en Recursos Hidráulicos.
48] Montoya, R.D, Osorio, A.F y Mesa, J.C. Influencia de las parametrizaciones empleadas para los términos fuente sumidero de energía en la modelación del oleaje en el Caribe colombiano. XIII Seminario Nacional De Ciencia y Tecnología del Mar SENALMAR 2008.
[49] Giraldo, L, y Lonin S. Cálculo del oleaje y el transporte de sedimentos en la costa Caribe colombiana. Boletín Científico del CIOH. 1997; 18, 39 -49.56.
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How to Cite
Fourty years of wave hindcast using Wave Watch III model and calibration with several data sources at the Caribbean Sea. (2009). CIOH Scientific Bulletin, 27, 37-56. https://doi.org/10.26640/22159045.200
