The combined risk of extreme tropical cyclone winds and storm surges along the U.S. Gulf of Mexico Coast

Abstract Seasonal hurricane forecasts are continuing to develop skill, although they are still subject to large uncertainties. This study uses a new methodology of cross-correlating variables against empirical orthogonal functions (EOFs) of the hurricane track density function (HTDF) to select predictors. These predictors are used in a regression model for forecasting seasonal named storm, hurricane, and major hurricane activity in the entire Atlantic, the Caribbean Sea, and the Gulf of Mexico. In addition, a scheme for predicting landfalling tropical systems along the U.S. Gulf of Mexico, southeastern, and northeastern coastlines is developed, but predicting landfalling storms adds an extra layer of uncertainty to an already complex problem, and on the whole these predictions do not perform as well. The model performs well in the basin-wide predictions over the entire Atlantic and Caribbean, with the predictions showing an improvement over climatology and random chance at a 95% confidence level. Over the Gulf of Mexico, only named storms showed that level of predictability. Predicting landfalls proves more difficult, and only the prediction of named storms along the U.S. southeastern and Gulf coasts shows an improvement over random chance at the 95% confidence level. Tropical cyclone activity along the U.S. northeastern coast is found to be unpredictable in this model; with the rarity of events, the model is unstable.

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Mesohaline Submerged Aquatic Vegetation Survey Along the U.S. Gulf of Mexico Coast, 2001 and 2002: A Salinity Gradient Approach

Gulf of Mexico Science ◽

10.18785/goms.2701.02 ◽

2009 ◽

Vol 27 (1) ◽

Cited By ~ 6

Author(s):

Joy H. Merino ◽

Jacoby Carter ◽

Sergio L. Merino

Keyword(s):

Gulf Of Mexico ◽

Submerged Aquatic Vegetation ◽

Aquatic Vegetation ◽

Salinity Gradient ◽

Vegetation Survey ◽

Mexico Coast ◽

Gradient Approach ◽

The U.S

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An Empirical Analysis on the Relationship between Tropical Cyclone Size and Storm Surge Heights along the U.S. Gulf Coast

Earth Interactions ◽

10.1175/2013ei000558.1 ◽

2014 ◽

Vol 18 (8) ◽

pp. 1-15 ◽

Cited By ~ 16

Author(s):

Hal F. Needham ◽

Barry D. Keim

Keyword(s):

Tropical Cyclone ◽

Hurricane Katrina ◽

Storm Surge ◽

Empirical Analysis ◽

Gulf Coast ◽

Inverse Correlation ◽

Storm Surges ◽

Wind Fields ◽

The U.S

Abstract In the past decade, several large tropical cyclones have generated catastrophic storm surges along the U.S. Gulf and Atlantic Coasts. These storms include Hurricanes Katrina, Ike, Isaac, and Sandy. This study uses empirical analysis of tropical cyclone data and maximum storm surge observations to investigate the role of tropical cyclone size in storm surge generation. Storm surge data are provided by the Storm Surge Database (SURGEDAT), a global storm surge database, while a unique tropical cyclone size dataset built from nine different data sources provides the size of the radius of maximum winds (Rmax) and the radii of 63 (34 kt), 93 (50 kt), and 119 km h−1 (64 kt) winds. Statistical analysis reveals an inverse correlation between storm surge magnitudes and Rmax sizes, while positive correlations exist between storm surge heights and the radius of 63 (34 kt), 93 (50 kt), and 119 km h−1 (64 kt) winds. Storm surge heights correlate best with the prelandfall radius of 93 km h−1 (50 kt) winds, with a Spearman correlation coefficient value of 0.82, significant at the 99.9% confidence level. Many historical examples support these statistical results. For example, the 1900 Galveston hurricane, the 1935 Labor Day hurricane, and Hurricane Camille all had small Rmax sizes but generated catastrophic surges. Hurricane Katrina provides an example of the importance of large wind fields, as hurricane-force winds extending 167 km [90 nautical miles (n mi)] from the center of circulation enabled this large storm to generate a higher storm surge level than Hurricane Camille along the same stretch of coast, even though Camille’s prelandfall winds were slightly stronger than Katrina’s. These results may be useful to the storm surge modeling community, as well as disaster science and emergency management professionals, who will benefit from better understanding the role of tropical cyclone size for storm surge generation.

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