By Katie Koffman
On March 5, Dr. Brian Blanton of the Renaissance Computing Institute (RENCI) discussed coastal hazard and risk assessment with our class. He showed us various models used for forecasting and prediction of future climate events while explaining “the trap of binary thinking” regarding climate change. Dr. Blanton was a more technical speaker, but he did an excellent job explaining his research and making it understandable for those who approach climate change from a social sciences perspective.
Dr. Blanton began the discussion by explaining how we perceive risk, hazard, and consequences by demonstrating that binary thinking does not generally characterize how nature operates. On FEMA flood maps, he said, risks can be substantially underrepresented because areas are classified either “in” or “out” of the flood zone. However, when compared with historical damage patterns, many areas “outside” the FEMA floodplain experienced flooding. The primary purpose of the maps is for setting flood insurance rates, but they are often used for land use planning and determining where to live, as well as other unintended uses. The maps should serve as guidance for decision-making, he said, rather than flooding predictions.
We tend to use the word prediction and forecast interchangeably, Dr. Blanton said, but they indicate different things. A forecast should reflect both the likelihood that an event will occur as well as something about its uncertainty, such as “there is a 70% chance it will rain tomorrow.” A prediction is a statement that an event will occur, at some place and time, without recognition of underlying uncertainty. On the FEMA flood maps, the 100-year floodplain indicates areas that have a 1% chance each year to experience a catastrophic event. Often, people interpret this as an area that will experience a catastrophic flood only once every 100 years. The latter interpretation is problematic because it is not true, and does not convey anything about the uncertainty.
Hazard modelers such as Dr. Blanton create scenarios based on various factors that can increase the strength of tropical and extra-tropical coastal storms that impact coastal flooding and storm surge, such as climate change, sea-level rise and changing coastal geomorphology. Modelers use four baseline principles to forecast potential storm surge: base flood elevation, sea-level rise, still water elevation and high-risk coastal areas such as AE and VE zones. Other factors are taken into account that impact storm surges such as topography, coastal shape and vegetation coverage.
There are several computer models for simulating coastal storm surge due to tropical cyclones, with two being widely used. The National Weather Service developed the National Oceanographic and Atmospheric Administration’s model – the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model – to compute storm surge heights. The National Hurricane Center uses this model for storm surge guidance from tropical cyclones. The SLOSH model is advantageous because it operates at a relatively broad resolution and is relatively fast to run.
The second model, developed at the University of North Carolina at Chapel Hill and the University of Notre Dame, is the Advanced Circulation Model (ADCIRC). The model can be configured to represent very complex coastal areas at high resolution, thus providing coastal flooding guidance in much more detail. It also directly includes factors that are important for storm surge, such as river flows, interactions with wind-generated waves and fully dynamic astronomical tides, factors that the SLOSH model has historically not addressed. Because it is typically run at very high spatial resolution, it requires large high-performance computers and can calculate large quantities of output information.
Why are these models important? In many U.S. coastal areas, including North Carolina, hurricanes impacts may become larger in the future, as tropical systems may get more intense and carry more moisture. Additionally, several coastal cities such as Miami, Charleston and Virginia Beach are experiencing more frequent sunny-day, “nuisance” flooding. With more accurate information and an understanding of how various factors impact flooding, we can better mitigate the long-term effects of sea-level rise and climate change. This type of information is important because not all states facing flooding risks have made this a high priority. Local governments can understand the impacts of climate change and create better emergency management plans. Hazard modeling that can account for multiple factors is thus a powerful tool that increases our understanding of risk management and climate change.
Koffman is a first-year master’s degree candidate in the Department of City and Regional Planning at UNC-Chapel Hill, specializing in Land Use and Environmental Planning. Her research interests include climate change impacts on cities, resiliency and environmental justice. Koffman obtained a bachelor’s degree in International Studies and Spanish from Miami University (Ohio) and a master’s in Environmental Anthropology from North Carolina State University.