Remotely sensed surface currents in Monterey Bay from shore-based HF radar (Coastal Ocean Dynamics Application Radar)

1996 ◽  
Vol 101 (C9) ◽  
pp. 20669-20686 ◽  
Author(s):  
Jeffrey D. Paduan ◽  
Leslie K. Rosenfeld
Keyword(s):  
Remotely Sensed ◽  
Coastal Ocean ◽  
Ocean Dynamics ◽  
Hf Radar ◽  
Monterey Bay ◽  
Surface Currents

Variational assimilation of HF radar surface currents in a coastal ocean model off Oregon

2012 ◽  
Vol 49-50 ◽  
pp. 86-104 ◽  
Author(s):  
Peng Yu ◽  
Alexander L. Kurapov ◽  
Gary D. Egbert ◽  
John S. Allen ◽  
P. Michael Kosro
Keyword(s):  
Coastal Ocean ◽  
Ocean Model ◽  
Hf Radar ◽  
Surface Currents ◽  
Variational Assimilation ◽  
Coastal Ocean Model

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.

scholarly journals Coastal observing and forecasting system for the German Bight – estimates of hydrophysical states

Ocean Science ◽  
2011 ◽  
Vol 7 (5) ◽  
pp. 569-583 ◽  
Author(s):  
E. V. Stanev ◽  
J. Schulz-Stellenfleth ◽  
J. Staneva ◽  
S. Grayek ◽  
J. Seemann ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Assimilation ◽  
German Bight ◽  
Numerical Models ◽  
Coastal Ocean ◽  
Hf Radar ◽  
Optimal Interpolation ◽  
Surface Currents ◽  
Arctic Seas

Abstract. A coastal observing system for Northern and Arctic Seas (COSYNA) aims at construction of a long-term observatory for the German part of the North Sea, elements of which will be deployed as prototype modules in Arctic coastal waters. At present a coastal prediction system deployed in the area of the German Bight integrates near real-time measurements with numerical models in a pre-operational way and provides continuously state estimates and forecasts of coastal ocean state. The measurement suite contributing to the pre-operational set up includes in situ time series from stationary stations, a High-Frequency (HF) radar system measuring surface currents, a FerryBox system and remote sensing data from satellites. The forecasting suite includes nested 3-D hydrodynamic models running in a data-assimilation mode, which are forced with up-to-date meteorological forecast data. This paper reviews the present status of the system and its recent upgrades focusing on developments in the field of coastal data assimilation. Model supported data analysis and state estimates are illustrated using HF radar and FerryBox observations as examples. A new method combining radial surface current measurements from a single HF radar with a priori information from a hydrodynamic model is presented, which optimally relates tidal ellipses parameters of the 2-D current field and the M2 phase and magnitude of the radials. The method presents a robust and helpful first step towards the implementation of a more sophisticated assimilation system and demonstrates that even using only radials from one station can substantially benefit state estimates for surface currents. Assimilation of FerryBox data based on an optimal interpolation approach using a Kalman filter with a stationary background covariance matrix derived from a preliminary model run which was validated against remote sensing and in situ data demonstrated the capabilities of the pre-operational system. Data assimilation significantly improved the performance of the model with respect to both SST and SSS and demonstrated a good skill not only in the vicinity of the Ferry track, but also over larger model areas. The examples provided in this study are considered as initial steps in establishing new coastal ocean products enhanced by the integrated COSYNA-observations and numerical modelling.

scholarly journals HF Radar Performance in a Low-Energy Environment: CODAR SeaSonde Experience on the West Florida Shelf*

2010 ◽  
Vol 27 (10) ◽  
pp. 1689-1710 ◽  
Author(s):  
Yonggang Liu ◽  
Robert H. Weisberg ◽  
Clifford R. Merz ◽  
Sage Lichtenwalner ◽  
Gary J. Kirkpatrick
Keyword(s):  
Coastal Ocean ◽  
Low Energy ◽  
Ocean Dynamics ◽  
Hf Radar ◽  
Limiting Factors ◽  
West Florida Shelf ◽  
The West ◽  
Florida Shelf ◽  
Significant Wave ◽  
Energy Environment

Abstract Three long-range (5 MHz) Coastal Ocean Dynamics Application Radar (CODAR) SeaSonde HF radars overlooking an array of as many as eight moored acoustic Doppler current profilers (ADCPs) have operated on the West Florida Shelf since September 2003 for the purpose of observing the coastal ocean currents. HF radar performance on this low-energy (currents and waves) continental shelf is evaluated with respect to data returns, the rms differences between the HF radar and the ADCP radial currents, bearing offsets, and radial velocity uncertainties. Possible environmental factors affecting the HF radar performance are discussed, with the findings that both the low-energy sea state and the unfavorable surface wave directions are the main limiting factors for these HF radar observations of currents on the WFS. Despite the challenge of achieving continuous backscatter from this low-energy environment, when acquired the data quality is good in comparison with the ADCP measurements. The rms differences range from 6 to 10 cm s−1 for hourly and from 3 to 6 cm s−1 for 36-h low-pass-filtered radial currents, respectively. Bearing offsets are in the range from −15° to +9°. Coherent variations of the HF radar and ADCP radial currents are seen across both tidal and subtidal frequency bands. By examining the HF radar radial velocities at low wave energy, it is found that the data returns decrease rapidly for significant wave heights smaller than 1 m, and that the rms differences between the HF radar and ADCP radials are degraded when the significant wave height is smaller than 0.3 m.

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