S114
Statistical Prediction of the Storm Surge Associated with Cool Weather Storms at The Battery, New York
Kamila Wisniewska, Hunter College, CUNY, Ridgewood, NY
The day to day weather in the New York Metropolitan Region during winter and early spring months is highly influenced by extratropical storm systems, which are generated by horizontal temperature gradients in the atmosphere as cold masses of Arctic air collide with warm and moist air from the subtropical regions. Often these events are accompanied by extreme weather conditions such as strong winds, heavy precipitation and extreme low temperatures and have severe impacts on the region, such as: flooding and snow blizzards. Storm surge associated with extratropical storm systems is one of the main factors contributing to inundation of costal areas. The New York region with its low elevation above the mean sea level will be especially vulnerable to the damage caused by these storms as the warming of climate and its associated sea level rise is expected to continue in the future.
A recent study Salmun et al. (2009) , conducted at the Laboratory for Marine and Atmospheric Research developed a climatology of the East Coast Cool-weather Storms (ECCSs) using data from National Data Buoy Center (NDBC) stations. The assessment of storms' impact on the region lead to the establishment of a linear relationship between values of significant wave heights recorded by the NDBC station 44025 (40.25 N 73.17W) and the values of storm surge at The Battery, New York water gauge station (40.42 N 74.08 W). The present study investigates the potential that these set of statistical correlations might have to predict storm surge at the Battery, New York.
To that end, the methodology developed in the previous work was applied to forecast surface pressure fields in order to provide a hindcast of ECCS events between February 2005 and December 2008. The set of three (48h, 24h, 12h) forecasts of surface pressure at location of buoy 44025 were examined, and the 12 hour forecast of storm events provided most accurate prediction of ECCSs at that location, identifying 41 storms over the period of study. The dates and the duration of the identified ECCSs were used to obtain the corresponding forecast of significant wave heights for each of the storm events. The ‘storm average' significant wave height was used in a statistical model to compute the average and the maximum storm surge estimates at The Battery, New York.
The differences between the obtained storm surge estimates and the observed surge at The Battery were compared to the difference between surge values predicted by NOAA Extratropical Water Level Forecast and the water gauge observations. A series of statistical F-tests revealed that the variance of the difference between statistical surge prediction and the observed values is less than variance of the difference between NOAA's deterministic surge prediction and the observed surge at the 95% significance level. This implies that the statistical surge prediction provided a better estimate of storm maximum storm surge than the deterministic prediction.
Poster Session , Student Poster Session
Sunday, 17 January 2010, 5:30 PM-7:00 PM, Exhibit Hall B2
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