1. Motivation Method ‘Ground Truth’ tests Electro-optical Estimation of Wave Dissipation Rob Holman, Oregon State University

2. Why We Care About Dissipation Dissipation is the dominant remote sensing signal Dissipation is key to energy and momentum fluxes Dissipation would be a powerful DA variable. DARLA is exploring both Q b and roller length methods.

3. Why We Care About Dissipation Dissipation is key to radiation stress gradients that drive circulation within the surf zone: f b can be estimated from breaker detections, while h is estimated from cBathy All can be derived from all remote sensing modalities Janssen and Battjes, 2007: where f b is the frequency of breaking (=N b /tau).

4. Breaker Detection 1.Based on cross-shore time stacks

5. Breaker Detection 1.Based on cross-shore time stacks 2.De-propagate waves using celerity from cBathy

6. Breaker Detection 1.Based on cross-shore time stacks 2.De-propagate waves using celerity from cBathy 3.Detection of rising edges using Sobel filter

7. Oregon State University Comparison to ‘Ground Truth’ Do manual breaker counts at five positions y = 690, 09/09/10, Duck

8. Oregon State University Comparison of Manual and Automated Breaker Counts Manual Difference Automatic T p = 12.5s H s = 0.87m

9. Oregon State University Comparison of Manual and Automated Breaker Counts 95% sure #breakers correct to within 5% for y > 300m (10% for y > 500m for strong storm with mostly 100% breaking) T p = 5.6 s H s = 1.06 m

10. Oregon State University Products: Breaker PDFs Individual wave detection x - 320 mx - 244 m x - 112 m x - 156 m Red = N b Blue = N Tot Green = Rayleigh Theory

11. Oregon State University Comparison of Q b With Timex

12. Oregon State University Comparison of Q b With Timex

13. Oregon State University Comparison of Q b With SWAN Dissipation

14. Comparison With SWIFT Dissipation Data Create EO time series from cBathy time series collections for SWIFT trajectory (x,y,t)

15. Comparison With SWIFT Dissipation Data SWIFT dissipation Argus intensity

16. Comparison With SWIFT Dissipation Data SWIFT breaker detects Argus intensity Good agreement with SWIFT manual counts Working on comparison with actual dissipation time series.

17. Fusion with Radar, DA with Models Radar Time Exposure (Diaz and Haller) ROMS Dissipation (Moghimi and Ozkan-Haller)

18. Summary Dissipation is a dominant remote sensing signal and a key dynamical variable All the component variables can be estimated remotely, hence so can dissipation Struggling with finding ground truth