Study Makes Storm Surge Predictions at Less Cost without Sacrificing Accuracy
(GoMRI)
May 8, 2014
Two scientists from the University of Texas provide an alternate modeling framework that incorporates selective detailed adjustments while calculations are in process to predict storm surge.
The addition of adaptive mesh refinement (AMR) algorithms to existing models addresses the need for quick and accurate information without being cost prohibitive. The researchers published their findings in the March 2014 edition of Ocean Modelling: Adaptive mesh refinement for storm surge.
Catastrophic weather incidents are increasing as is population growth along vulnerable coastlines, making improved forecasting a key initiative in the scientific community. Storm surge is a sudden and fast rise in sea level that accompanies tropical storms such as hurricanes and can cause devastating damage to both property and human life. Accurate predictions of the landward reach of storm surge is especially important for the Gulf of Mexico which has experienced extensive weather-related disasters. Since the Gulf is one of the major petroleum-producing areas of the United States, improved storm surge predictions can assist responders with hazards caused by broken pipelines and failures in storage structures along coastlines and the subsequent spreading of oil further inland.