A Program to Develop Coastal Ocean Dynamics Applications Radar for Offshore Wave, Current, and Wind Monitoring

1983 ◽  
Author(s):  
M.W. Spillane ◽  
O.H. Oakley ◽  
M.W. Evans ◽  
B.J. Lipa ◽  
D.E. Barrick
Keyword(s):  
Coastal Ocean ◽  
Ocean Dynamics ◽  
Offshore Wave

Coastal ocean dynamics

Eos ◽  
1983 ◽  
Vol 64 (36) ◽  
pp. 538 ◽  
Author(s):  
J. Allen ◽  
R. Beardsley ◽  
W. Brown ◽  
D. Cacchione ◽  
R. Davis ◽  
...  
Keyword(s):  
Coastal Ocean ◽  
Ocean Dynamics

Relaxation from upwelling in the Coastal Ocean Dynamics Experiment

1987 ◽  
Vol 92 (C2) ◽  
pp. 1683 ◽  
Author(s):  
Uwe Send ◽  
Robert C. Beardsley ◽  
Clinton D. Winant
Keyword(s):  
Coastal Ocean ◽  
Ocean Dynamics

Coastal ocean dynamics reduce the export of microplastics to the open ocean

2020 ◽  
Vol 713 ◽  
pp. 136634 ◽  
Author(s):  
Zhiwei Zhang ◽  
Hui Wu ◽  
Guyu Peng ◽  
Pei Xu ◽  
Daoji Li
Keyword(s):  
Coastal Ocean ◽  
Open Ocean ◽  
Ocean Dynamics

scholarly journals Impact of HF radar current gap-filling methodologies on the Lagrangian assessment of coastal dynamics

Ocean Science ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 827-847 ◽  
Author(s):  
Ismael Hernández-Carrasco ◽  
Lohitzune Solabarrieta ◽  
Anna Rubio ◽  
Ganix Esnaola ◽  
Emma Reyes ◽  
...  
Keyword(s):  
Transport Properties ◽  
Coastal Ocean ◽  
Transport Processes ◽  
Empirical Orthogonal Functions ◽  
Ocean Dynamics ◽  
Hf Radar ◽  
Open Boundary ◽  
Small Scale ◽  
Gap Filling ◽  
Spatial Coverage

Abstract. High-frequency radar, HFR, is a cost-effective monitoring technique that allows us to obtain high-resolution continuous surface currents, providing new insights for understanding small-scale transport processes in the coastal ocean. In the last years, the use of Lagrangian metrics to study mixing and transport properties has been growing in importance. A common condition among all the Lagrangian techniques is that complete spatial and temporal velocity data are required to compute trajectories of virtual particles in the flow. However, hardware or software failures in the HFR system can compromise the availability of data, resulting in incomplete spatial coverage fields or periods without data. In this regard, several methods have been widely used to fill spatiotemporal gaps in HFR measurements. Despite the growing relevance of these systems there are still many open questions concerning the reliability of gap-filling methods for the Lagrangian assessment of coastal ocean dynamics. In this paper, we first develop a new methodology to reconstruct HFR velocity fields based on self-organizing maps (SOMs). Then, a comparative analysis of this method with other available gap-filling techniques is performed, i.e., open-boundary modal analysis (OMA) and data interpolating empirical orthogonal functions (DINEOFs). The performance of each approach is quantified in the Lagrangian frame through the computation of finite-size Lyapunov exponents, Lagrangian coherent structures and residence times. We determine the limit of applicability of each method regarding four experiments based on the typical temporal and spatial gap distributions observed in HFR systems unveiled by a K-means clustering analysis. Our results show that even when a large number of data are missing, the Lagrangian diagnoses still give an accurate description of oceanic transport properties.

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