Disasters—from hurricanes and floods in the east to landslides in the mountains to ice storms in the central Piedmont—are a prime example of a multifaceted issue that no single discipline can effectively address. And they are costly: Between 1980 and 2005, North Carolina suffered more than 20 weather-related disasters that caused at least $1 billion in damage, according to NOAA’s National Climate Data Center. It is one of four states, along with Florida, Georgia and Alabama, to endure more than 20 billion-dollar weather disasters during that time.
RENCI’s disaster research efforts bring together disparate technologies and communities to address the challenges related to disaster: scientists who develop atmospheric, hydrologic and storm surge models; agencies that put together evacuation plans; topographical and historic data; transportation models; wireless and sensor technologies and high-end computers that model scenarios in real-time.
“This is no small effort. We are integrating models in ways that have never been done before. We are bringing together data sources and creating new data sources and we’re working to vastly improve communications during disasters,” says Ken Galluppi, who leads RENCI’s disaster research projects. “In the long run, this work should help our state develop more comprehensive disaster plans that can save lives and reduce the economic impact of disasters.”
Launched about a year ago, RENCI’s disaster research focuses on four areas critical to North Carolina:
- Flooding and landslides. The ability to accurately predict floods in the wake of hurricanes and other severe storms is essential in a state that endures tropical storms from the Atlantic as well as those that move up from the Gulf of Mexico into the Appalachians. Working with scientists across the state, RENCI is developing a new storm modeling and forecasting system that merges atmospheric and hydrology data with coastal storm surge data.Called HydroMet, this new system combines a North Carolina version of the Weather Research and Forecasting (WRF) model, which models atmospheric conditions such as wind speed, direction and temperature, humidity and pressure, with the Regional Hydro-Ecologic Simulation System (RHESSYS), which models water levels on land and water runoff patterns, and the ADCIRC model, which shows the height of storm surges that hit the coast during severe weather. HydroMet models will have nine times the resolution of National Weather Service forecasts, making it possible to zero in on storm effects in a 4-kilometer radius. Within the next few weeks, RENCI will begin producing 24-hour HydroMet forecasts using its IBM Blue Gene computing system, Ocracoke.A team of scientists from UNC-Chapel Hill, NC State, the UNC Marine Sciences Institute, the Carolina Environmental Program at UNC-Chapel Hill, UNC-Asheville, and the State Climate Office of North Carolina work with RENCI on development and implementation of HydroMet.
- Disaster Infrastructure. During a disaster, roads flood, and power lines and even cell phone towers can be damaged or destroyed. How can first responders communicate and carry out evacuation and rescue plans? RENCI’s experimental emergency response vehicle is a prototype system for keeping people connected and safe during disasters.This custom-built flatbed truck is equipped with a mobile wireless network activated via a retractable helium balloon, a satellite dish, and a remote-controlled helicopter designed for search and rescue missions. The vehicle can be deployed in emergency situations to enable wireless communications between first responders when electrical and phone lines are down and to assist in search and rescue operations. It also serves as a demonstration and teaching tool for emergency response teams looking to use innovative technologies to safeguard people and property. The vehicle will be deployed by March.A RENCI team already has tested its unmanned aerial vehicle (UAV). Equipped with a digital camera and programmed to receive transmissions from battery operated, low-power sensors in remote locations, the UAV can gather data from areas too dangerous or too remote to be reached by humans. In the case of a hurricane or severe storm, for example, it can compile sensor data to pinpoint the location of flood damage or mudslides. If a chemical spill were to occur, the UAV can scatter sensors in the effected area and record soil contamination levels.
- Command and Control. Improved forecasting and disaster planning and response depend on plentiful, high-quality, up-to-date data. North Carolina already collects data from more than 2,000 sensors dispersed throughout the state. Still, some areas of the state have minimal sensor coverage and aggregating and using the data can be difficult. RENCI plans to develop and implement the North Carolina Sensor Data Bus, which will gather sensor data and feed it into a RENCI-hosted data hub. Initially, the data hub will be used to compile HydroMet models and by the State Climate Office at NC State in climate research and forecasting. Additional users could be mapping services, communities developing disaster plans or farmers needing information for agricultural decision-making.Once the data hub system is in place it will become the data backbone supporting next-generation emergency operations centers across the state. These centers, part of RENCI’s long-range plans, will be linked via 10-gigabit network connections and able to store and process terabytes of data.
- Icing Prediction. When an ice storm hit the Triangle area in December 2002, thousands of homes lost power. Worse, utility trucks were slowed in their efforts to restore power because many were located outside the affected area and couldn’t travel on ice-covered roads. A better ability to predict ice storms means better planning and quicker restoration of essential services. RENCI is deploying a micro rain radar (MRR)—one of only five in the U.S—to improve ice storm prediction. The radar detects rain in the atmosphere can detect how high above the ground that rain will freeze—the freezing line. Above the freezing line, moisture is frozen, and how close to the surface that line is determines whether precipitation falls as rain, freezing rain or snow.The MRR will be mobile enough to move to move as conditions demand, but will be located near Greensboro, in the heart of the area most frequently hit by ice storms. It will give the National Weather Service a needed data point in that area and will help in determining where and when ice is likely to hit. The radar data will be collected by an on-site computer and transferred via a cell phone network to a RENCI server and then displayed on website. The system will update in minutes and be accessible from the web to forecasters, planners, utility companies, rescue workers and government officials.