Loss estimates and financial impact prediction more accurate
Aon Benfield’s Impact Forecasting catastrophe modelling arm has updated its storm surge model with data from hurricane Sandy.
The model now lets insurers and reinsurers better calculate loss estimates and gauge the financial impact of a storm surge reoccurrence.
The updated model includes a function to consider the entire lifecycle of a tropical system before and during landfall to allow better modelling of surge behavior for historical hurricanes. Impact Forecasting dubs this SLOSH (Sea, Lake and Overland Surge from Hurricanes).
The software has also been improved to include storm surge loss estimates for 26,000 wind events from Impact Forecasting’s US hurricane model, considering different central pressures, radius of maximum winds, location, direction and speed.
Finally, the storm surge model has been improved to consider a building’s construction and maps water height to a damage ratio.
Impact Forecasting head of research and development Siamak Daneshvaran said: “Sandy showed that storm surge losses can be the dominating cause of loss, as opposed to wind, during a large hurricane event.
“In the last several years we have calibrated our implemented version of SLOSH - along with our proprietary wind-field model - while utilizing data using tide gauges. Our validation on both a hazard and loss level shows that SLOSH is very efficient for a stochastic model and is also reasonably accurate for storm surge risk analysis.”
Impact Forecasting president Steve Jakubowski said: “Soon after Hurricane Katrina, Impact Forecasting began work to implement SLOSH technology into our storm surge model. The model’s performance with Hurricane Ike in 2008, and again with Hurricane Sandy in 2012, proved to be the most accurate and reliable in the modeling industry.
“It is now more important than ever to respond to these large events by researching, developing and implementing flood catastrophe models that can better analyze the hazard of hurricane coastal and inland riverine flooding. We have also been applying damage functions specifically for flood inundation, which allow insurers and reinsurers to better understand their flood risk.”