Surf Zone Waves at the Onset of Breaking: 2. Predicting Breaking and Breaker Type

This is the second of a two‐part series concerning remote observation and wave‐by‐wave analysis of the onset of breaking for spilling and plunging waves in the surf zone. Nearshore phase‐averaged and phase‐resolving wave models parameterize and directly simulate wave breaking and require realistic critical values of key wave parameters, such as the depth‐limited breaking index γ, steepness, or phase speed to initialize wave breaking. Using LIDAR line‐scans and infrared imagery, we observe over 1,600 breaking waves at the US Army Corps of Engineers Field Research Facility (FRF) in Duck, NC, and examine these parameters on a wave‐by‐wave basis at the onset of breaking for 413 spilling and 111 plunging waves. We find that γ is maximum near the onset of breaking at values consistent with those previously observed at the FRF, but that γ for plunging waves (0.73 ≤ γP ≤ 0.81) is greater than γ for spilling waves (0.63 ≤ γS ≤ 0.71). Direct estimates of wave face slope are maximum at the onset of breaking, approximately 22° for spilling and 30° for plunging waves. Using the relationship between γ and wave face slope, we develop a threshold for the onset of breaking that is a linear function of the two parameters. Wave face slope and γ are further used together to quantify whether a spilling‐ or plunging‐type breaker is more likely. We test the Miche steepness limit on our depth‐limited breaking data and find it correctly predicts only 10% of the plunging breakers and none of the spilling breakers in the surf zone. Plain Language Summary Breaking waves are one of the primary factors responsible for nearshore currents and erosion, two processes that are important for swimmer and boater safety and coastal resilience. To predict these phenomena, scientists use computer models and must make decisions about how to include the impact of breaking waves in those models. Often, a single critical value acts as an “on‐off” switch for breaking, even though measurements in the field reveal a more complicated story. This study uses a scanning laser and infrared cameras to measure breaking waves at the beach and analyzes what factors, such as wave height, water depth, and wave slope, are important predictors of breaking. We find that breaking is best predicted by using the ratio of wave height to water depth and the wave slope together, and that breaking should be modeled using a continuum, rather than an “on‐off” switch. Further, we can use the same factors to predict the type of