NOAA Sea, Lake, and Overland Surges from Hurricanes (SLOSH)

NOAA Sea, Lake, and Overland Surges from Hurricanes (SLOSH)
Name	SLOSH
Developer	National Oceanic and Atmospheric Administration
Released	1980s
Latest release	Operational models updated periodically
Programming language	Fortran, C, Python (support tools)
Platform	Unix, Linux, Windows
License	Public domain (NOAA)

NOAA Sea, Lake, and Overland Surges from Hurricanes (SLOSH) is a numerical modeling system used to estimate storm surge heights and inundation areas associated with tropical cyclones and extratropical storms. It supports emergency management and meteorological decision-making by integrating bathymetry, topography, and meteorological inputs to produce surge forecasts and climatologies. SLOSH informs evacuation planning, flood risk assessment, and post-storm analysis across coastal regions and inland waterways.

Overview

SLOSH was developed by the National Oceanic and Atmospheric Administration in cooperation with the Federal Emergency Management Agency, the U.S. Army Corps of Engineers, and regional partners such as the National Hurricane Center. The model produces surge inflow and overland flooding scenarios for basins covering coastal areas like Florida, Louisiana, Texas, New Jersey, and the Gulf of Mexico, and addresses impacts on estuaries like the Chesapeake Bay and the Delaware Bay. Designed to run on platforms used by agencies including the National Weather Service, SLOSH outputs are used alongside products from the National Hurricane Center advisories, the Storm Prediction Center analyses, and regional emergency plans from municipal authorities such as the New York City Office of Emergency Management and the Los Angeles Office of Emergency Management when applicable to storm surge risk.

Model Design and Methodology

SLOSH solves depth-averaged two-dimensional hydrodynamic equations derived from shallow-water theory that incorporate Coriolis terms and nonlinear advection, similar in principle to methods used in tidal modeling by groups like the National Oceanography Centre and research at institutions such as the Scripps Institution of Oceanography and the Woods Hole Oceanographic Institution. Grids are configured as enclosed basins tailored to coastal counties, parishes, or metropolitan regions and are built from elevation datasets produced by agencies including the U.S. Geological Survey, the National Geodetic Survey, and the U.S. Army Corps of Engineers. Wind and pressure fields driving SLOSH runs are parameterized using storm parameters from the Hurricane Forecast System and track forecasts from the Global Forecast System, the European Centre for Medium-Range Weather Forecasts ensemble guidance, and operational inputs from the National Hurricane Center and the Joint Typhoon Warning Center when applied internationally. Numerically, SLOSH employs finite-difference schemes with wetting-and-drying algorithms comparable to approaches documented in literature from the American Meteorological Society and computational work at Los Alamos National Laboratory.

Applications and Uses

Emergency managers at agencies such as the Federal Emergency Management Agency and state offices like the Florida Division of Emergency Management use SLOSH inundation maps for evacuation zones, building codes developed in coordination with the International Code Council, and resilience planning undertaken by institutions like the Urban Land Institute. Engineers at the U.S. Army Corps of Engineers and academic researchers at universities such as Louisiana State University, University of Miami, and Massachusetts Institute of Technology apply SLOSH output for levee design, coastal restoration projects, and risk assessment studies funded by entities like the National Science Foundation and the Office of Naval Research. Insurance underwriters and reinsurance firms in markets such as New York City and London use SLOSH-informed scenarios alongside data from Risk Management Solutions and AIR Worldwide for catastrophe modeling. SLOSH also supports post-event forensic analyses following storms like Hurricane Katrina (2005), Hurricane Sandy (2012), and Hurricane Harvey (2017) to evaluate surge extents in collaboration with teams from the Centers for Disease Control and Prevention and the American Red Cross.

Accuracy and Limitations

SLOSH provides rapid surge estimates but has constraints documented by researchers at the National Center for Atmospheric Research and the Coastal and Estuarine Research Federation. Limitations arise from grid resolution, representation of complex bathymetry and man-made structures, and simplified physics that omit explicit wave setup and detailed sediment transport modeled by tools like Delft3D or SWAN. Accuracy depends on the quality of input tracks and intensity forecasts from the National Hurricane Center and on topographic datasets from the U.S. Geological Survey; errors in these inputs were notable during events such as Hurricane Ike (2008). Ensembles integrating SLOSH outputs with models like the Storm Surge Probabilistic Forecasting System and hindcast validation against tide gauge records maintained by the National Ocean Service help quantify uncertainty. Peer-reviewed evaluations in journals such as Monthly Weather Review and Journal of Coastal Research discuss bias, skill scores, and error propagation in surge estimation.

Data Sources and Products

Primary data inputs include bathymetry and topography from the National Oceanic and Atmospheric Administration’s National Centers for Environmental Information and the U.S. Geological Survey’s elevation programs, storm parameters from the National Hurricane Center, and boundary conditions informed by tide gauges operated by the National Ocean Service and the University of Hawaii Sea Level Center. Output products encompass maximum envelope of water (MEOW) datasets, maximum of the maximums (MOMs) climatologies, operational surge forecasts, inundation shapefiles, and graphical map layers distributed through platforms used by the National Weather Service and regional GIS teams like those at the New York City Department of Information Technology and Telecommunications. Datasets are integrated into decision support systems used by FEMA Region IV and similar regional offices.

Operational Implementation and History

SLOSH originated in the 1960s–1980s research continuum involving entities such as the U.S. Weather Bureau predecessor agencies and was operationalized by the National Weather Service with ongoing development by the National Oceanic and Atmospheric Administration and academic collaborators including Rutgers University and Texas A&M University. Operational adoption accelerated after major surge disasters, prompting partnerships with the Federal Emergency Management Agency and updates aligned with improvements in computing at centers like the National Centers for Environmental Prediction and the Office of Science and Technology Policy. SLOSH remains integrated into emergency operations centers across the United States and informs international capacity-building programs led by organizations such as the United Nations Office for Disaster Risk Reduction and regional meteorological services in the Caribbean and Pacific.

Category:Numerical weather prediction Category:Coastal engineering