A Regression-Based Approach for Cool-Season Storm Surge Predictions along the New York–New Jersey Coast

Abstract

A multilinear regression (MLR) approach is developed to predict 3-hourly storm surge during the coolseason months (1 October-31 March 31) between 1979 and 2012 using two different atmospheric reanalysis datasets and water-level observations at three stations along the New York-New Jersey coast (Atlantic City, New Jersey; the Battery in New York City; and Montauk Point, New York). The predictors of the MLR are specified to represent prolonged surface wind stress and a surface sea level pressure minimum for a boxed region near each station. The regression underpredicts relatively large ($95th percentile) storm maximum surge heights by 6.0%-38.0%. A bias-correction technique reduces the average mean absolute error by 10%-15% at the various stations for storm maximum surge predictions. Using the same forecast surface winds and pressures from the North American Mesoscale (NAM) model between October and March 2010-14, raw and bias-corrected surge predictions at the Battery are compared with raw output from a numerical hydrodynamic model's [the Stevens Institute of Technology New York Harbor Observing and Prediction System (SIT-NYHOPS)] predictions. The accuracy of surge predictions between the SIT-NYHOPS output and biascorrected MLR model at the Battery are similar for predictions that meet or exceed the 95th percentile of storm maximum surge heights.

A Review of Historical and Future Changes of Extratropical Cyclones and Associated Impacts Along the US East Coast

“…For example, one could use bias-corrected GCM output around an area of interest and develop statistical approaches relating storm surge at a point to the winds and pressures in that region. Roberts et al [163] developed a multi-linear regression approach to predict storm surge at the Battery, NYC. For a specified region to the east and southeast of the Battery, prolonged surface stress and sea level pressure minimum are used as predictors.…”

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

“…Over the last two decades, much of the scientific research estimating risk of TC occurrences focuses on univariate risk, or the risk of experiencing a particular TC characteristic, such as wind speeds [ Chu and Wang , ] or storm surges [ Irish et al , ]. Storm surge research is also not limited exclusively to TC impacts, and predictions have been made about cool‐season storm surge along the New York‐New Jersey seaboard [ Roberts et al , ]. Here the focus is on modeling the combined statistical risk of two major TC characteristics, the nearshore wind speed, defined by the 18 h along‐track maximum observed wind speed, and peak storm surge using an extreme value copula approach.…”

Comparing hurricane and extratropical storm surge for the Mid-Atlantic and Northeast Coast of the United States for 1979–2013

“…The study also examined the path of hurricanes and ETCs creating surge in NYC, but did not compare the impact of the two storm types. Roberts et al (2015) studied the importance of wind direction and shear in generating coastal impacts for NYC, as did Warner et al (2012) for Long Bay, South Carolina. The role of storms in surge has also been examined north of NYC, as seen in Butman et al (2008), who ranked storms by wave-generated bottom stress observed in Massachusetts Bay.…”