2D.4 Storm surge modelling for the Northern Yucatan Peninsula

Monday, 31 March 2014: 11:15 AM
Garden Ballroom (Town and Country Resort )
WILMER Rey-Sanchez Sr., Instituto de Ingenieria, UNAM, Campus Sisal, Yucatan, Sisal,Yucatan, Yucatan, Mexico; and P. Salles and E. T. Mendoza

The Yucatan Peninsula (Mexico) is affected by frequent hydrometereological phenomena such as cold fronts from high pressure systems known as Nortes (September to May), as well as tropical cyclones (TC, from August to October).These natural phenomena are characterized by strong winds that generate storm surge and extreme waves which can potentially affect the low lying coastal zone causing beach erosion and flooding of large areas, which in turn derive into the loss of natural habitat (beaches and mangroves) displacement of hundreds of coastal residents and infrastructure damage or loss.

In recent times two major hurricanes made landfall in the Peninsula (Isidore in September 2002 and Wilma in October, 2005), causing heavy infrastructure damage, as well as cattle swine production loss. Although hurricanes are highly energetic these are not very frequent, on the other hand cold fronts are very frequent during the autumn and winter seasons with approximately 40 events per year, and can also produce surges that affect the low lying coast.

In this sense, this study is focused on modeling the storm surge generated by the strongest hurricanes (Isidore and Wilma) and some cold fronts which have impacted directly the Yucatan Peninsula in order to map flood prone areas.

Using first numerical modeling, this study focuses on the analysis of the evolution of storm surges generated by hurricanes (Isidore and Wilma) and cold fronts that impacted directly the Northern Yucatan Peninsula. Then, based on a high resolution digital elevation model for the entire coastline (341 km), inundation- prone areas were mapped.

Based on information from NOAA's database HURDAT (maximum wind velocity, radio of maximum wind, and central and ambient pressure http://www.aoml.noaa.gov/hrd/hurdat/) and using the SLOSH parametric wind model (Jelesnianski et al. 1992) wind fields were generated. The pressure field was generated using the Holland pressure distribution model (Holland 1980) with a B parameter taken from Vickery and Wadhera (2008). Both, the wind and pressure fields were used as forcing for the 2D, depth-averaged hydrodynamic model Mike 21. The model validated with satellite altimetry data (Envisat mission; orbital cycle 9) from the e-surge consortium (http://www.storm-surge.info/esurge-consortium).

For the Nortes, a 30 years wave hindcast (Appendini et.al 2012) was used to identify storm events, based on their storm energy content (Mendoza and Jiménez, 2009). Given their high occurrence, they represent a good dataset to perform statistical and extreme analysis from the resulting storm surges. The hydrodynamic model was forced with wind and pressure from the Climate Forecast System Reanalysis (CFSR), and calibrated and validated with data from tide gauges in the area.

This work is part of a study to determine the flooding risk in the Northern Yucatán Peninsula.

REFERENCES Appendini, C., Torres-Freyermuth,A., Oropeza, F., Salles, P., López, J., and Mendoza, E.T. 2012. Wave modeling performance in the Gulf of Mexico and Western Caribbean: Wind reanalyses assessment. Applied Ocean Research 39: 20-30

Jelesnianski, C. P., Chen, J., and Shaffer, W.A.1992. SLOSH: Sea Lake, and overland surges from hurricanes. NOOAA Tech. Rep. NWS 48, NOAA/AOLM Library, Miami, Fla.

Holland, G. J. 1980. An analytic model of wind and pressure profiles in hurricanes. Mon. weather Rev. 108:1212-1218.

Vickery, P.J., and D. Wathera (2008). Statistical models of Holland pressure profile parameters and radius to maximum winds of hurricanes form flight level pressure and H*wind data. J. Appl. Meteorol., 47: 2497-2597.

Mendoza, E. T. and Jiménez, J.A. 2009. Regional geomorphic vulnerability analysis to storms for Catalan beaches. Proceedings of the Institution of Civil Engineering: Maritime Engineering, ICE. 162 (3): 127-135.

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