Audrey Casper

Rip currents, fast offshore-directed flows, are the leading cause of death and rescues on surf beaches worldwide. Rip currents come in several types, including bathymetric rip currents that form when waves break on sandbars interspersed with channels, and transient rip currents that form when there are breaking waves coming from multiple directions.

The National Oceanographic and Atmospheric Administration (NOAA) seeks to minimize the threat of rip currents by providing rip current hazard likelihood forecasts based on environmental conditions from the Nearshore Wave Prediction System. Because the NOAA model was developed and tested in an area where bathymetric rip currents may be the most prevalent type of rip current, the model’s performance in regions where other types of rip currents may be more ubiquitous (e.g., transient rip currents) remains unknown. When developing a research question, we wondered: In cases where the NOAA model’s predictions are inconsistent with lifeguard observations, is the NWPS input conducive for transient rip current activity?

My project involved using Python to evaluate the performance of the NOAA model. We did this by comparing its predicted rip current probabilities with lifeguard observations of bathymetric and transient rip currents from Salt Creek Beach, California. Additionally, I compared the NOAA statistical model estimates with physical-based parameterizations of bathymetric and transient rip current speeds. The results suggested that though the NOAA predictions performed well at most times, they under-forecasted hazardous rip currents during times with large wave directional spread when lifeguards observed transient rip currents.