Storm Surge Research Group
The Stony Brook Storm Surge Research Group is developing a real-time weather and ocean storm surge prediction system which can be used for a variety of purposes. Such uses include hurricane and nor ‘easter flooding predictions and alerts, water quality and effluent dispersion, the feasibility of building storm surge barriers to protect the New York Metropolitan region from storm damage and coastal flooding in an era of global climate change and rising sea level.
For a more detailed description, visit the project website.
- Malcolm J. Bowman – Physical Oceanography, Group Leader- firstname.lastname@example.org
- Brian Colle – Mesoscale Meteorology email@example.com
- Charles Flagg – Coastal Oceanography firstname.lastname@example.org
- Hamish Bowman – Model integration and development hamish.bowman at otago.ac.nz
Acknowledgements for Past Contributions:
- Frank Buonaiuto – Coastal Geology email@example.com
- Robert E. Wilson – Physical oceanography firstname.lastname@example.org
- Jindong Wang – Physical Oceanography (PhD Student) jdandx at gmail.com
- Tom Diliberto – Atmospheric Science (MS Student) tom.diliberto at gmail.com
- Robert Hunter – Software Development (BS Student)
- Roger Flood – Marine geology email@example.com
- Alexander Mintz – Website Development (BA Student) alexander.mintz at gmail.com
- Douglas Hill- Coastal Hydrology
- Alexandra Santiago – Research support
- Jian Kuang – Modeling support (MS student in applied math) kuangjian2011 at gmail com
- Keith Roberts – Statistical analyses (MS student in atmospheric science)
- Michael Colbert – Storm surge barrier modeling (Honors College student)
- Sam Fey – Tidal analysis (BS physics student)
Funded by Stony Brook Storm Surge Research Group Partners
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The New York Metropolitan region is vulnerable to coastal flooding and large-scale damage to city infrastructure from hurricanes and nor’easters. Much of this region lies less than three meters above mean sea level; in total this includes an area of about 260 square kilometers. Within this area lies critical infrastructure such as hospitals, airports, railroad and subway station entrances, highways, water treatment outfalls and combined sewer outfalls at or near sea level.
Recent storms have already revealed the intrinsic potential for disaster in this region. For example the nor’easter of December 1992 flooded the entrance of the Hoboken Path train station with seawater, short-circuiting the electric trains and city subways, and shutting down the entire system. Fortunately, no lives were lost but there would have been fatalities if the sea had risen another foot. During this century, rising sea level will aggravate storm surges along the New York City metro region coast, causing more severe flooding and increasing the frequency of these floods.
In response to investigating these threats, the Stony Brook Storm Surge Research Group was formed in 2002 with support from New York Sea Grant, New York City Department of Environmental Protection, HydroQual Inc., and the Eppley Foundation for Research. This website is being developed as a coastal early warning system for emergency response against flooding in Metropolitan New York.
This website displays observed, astronomical and predicted sea level variations at key NOAA tide stations on the northeastern coastline with an emphasis on New York Harbor. Our storm surge prediction model (SBSS Version 1) consists of the Stony Brook 12-km MM5 mesoscale weather prediction model coupled to the ADCIRC ocean circulation model. The model predicts winds, pressure, tides, storm surge and currents with a 50-hr time horizon. The MM5 model is run twice daily and the output is used as input for ADCIRC. The water level predictions and observations are updated at 3am and 3pm daily. The predictions are 5hrs behind real time due to the model’s run time.
The Version 1 model has been validated against two major storm events; Hurricane Floyd (15-19 Sept. 1999) and the 25 December 2002 nor’easter, as well as real-time verification throughout a winter season (Bowman et al., 2004,2005).