The California coastal wave monitoring and prediction system

• Published in: Coastal engineering (Amsterdam) Vol. 116; pp. 118 - 132
• Main Authors: O'Reilly, W.C., Olfe, Corey B., Thomas, Julianna, Seymour, R.J., Guza, R.T.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2016
• Subjects: Longshore radiation stress; Ocean waves; Wave buoys; Wave models; Wave refraction; Wave runup; Wave models; Wave refraction; Wave runup; Wave buoys; Longshore radiation stress; Ocean waves
• ISSN: 0378-3839; 1872-7379
• DOI: 10.1016/j.coastaleng.2016.06.005

A decade-long effort to estimate nearshore (20m depth) wave conditions based on offshore buoy observations along the California coast is described. Offshore, deep water directional wave buoys are used to initialize a non-stationary, linear, spectral refraction wave model. Model hindcasts of spectral parameters commonly used in nearshore process studies and engineering design are validated against nearshore buoy observations seaward of the surfzone. The buoy-driven wave model shows significant skill at most validation sites, but prediction errors for individual swell or sea events can be large. Model skill is high in north San Diego County, and low in the Santa Barbara Channel and along the southern Monterey Bay coast. Overall, the buoy-driven model hindcasts have relatively low bias and therefore are best suited for quantifying mean (e.g. monthly or annual) nearshore wave climate conditions rather than extreme or individual wave events. Model error correlation with the incident offshore wave energy, and between neighboring validation sites, may be useful in identifying sources of regional modeling errors. •A method to estimate California nearshore wave energy and directional moments using offshore buoy observations is described.•Wave buoys initialize a spectral refraction model to predict wave parameters commonly used in engineering design.•The buoy-driven wave model shows significant skill, but prediction errors for individual swell or sea events can be large.•The hindcasts have low bias and are best suited for quantifying mean monthly or annual nearshore wave climate conditions.