Estimating Coastal Winds by Assimilating High-Frequency Radar Spectrum Data in SWAN
Abstract
:1. Introduction
2. The Models
2.1. SWAN Wave Model
2.2. HF Radar Scattering Model
3. The Assimilation Framework
3.1. Cost Function
3.2. Adjoint Models
3.3. Implementation
- The adjoint solution is calculated using the error in the most recent prediction as input;
- Using the adjoint solution, the gradient is determined;
- The conjugate-gradient descent algorithm is used to calculate a new estimate of the wind field and ;
- The SWAN model is run with corrected inputs and a new wave-spectrum prediction for the region is generated;
- The forward HF radar model is run with the new spectrum as input and a new prediction of the data is generated.
4. Results
4.1. Problem Setup
4.2. HF Radar Data Description
4.3. Comparisons to Buoy Wave Data
4.4. Comparisons to Buoy Wind Data
5. Discussion and Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
HFR | High-Frequency Radar |
SWAN | Simulating WAves Nearshore |
CODAR | Coastal Ocean Dynamics Applications Radar |
NDBC | National Data Buoy Center |
COAMPS | Coupled Ocean Atmosphere Modeling and Prediction System |
NCOM | Navy Coastal Ocean Model |
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Station | ||||||
---|---|---|---|---|---|---|
() | () | () | () | () | () | |
46217 | 0.67 m | 3.13 m | −0.16 s | 2056 s | −8.67° | 93.18° |
(1.05 m) | (0.40 m) | (6.77 s) | (1.36 s) | (180.80°) | (102.59°) |
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Muscarella, P.; Brunner, K.; Walker, D. Estimating Coastal Winds by Assimilating High-Frequency Radar Spectrum Data in SWAN. Sensors 2021, 21, 7811. https://doi.org/10.3390/s21237811
Muscarella P, Brunner K, Walker D. Estimating Coastal Winds by Assimilating High-Frequency Radar Spectrum Data in SWAN. Sensors. 2021; 21(23):7811. https://doi.org/10.3390/s21237811
Chicago/Turabian StyleMuscarella, Philip, Kelsey Brunner, and David Walker. 2021. "Estimating Coastal Winds by Assimilating High-Frequency Radar Spectrum Data in SWAN" Sensors 21, no. 23: 7811. https://doi.org/10.3390/s21237811