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

Liu, Yonggang; Weisberg, Robert H.; Merz, Clifford R.; Lichtenwalner, Sage; Kirkpatrick, Gary J.

doi:10.1175/2010jtecho720.1

Cited by 73 publications

(56 citation statements)

References 106 publications

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“…This can explain the significant scatter found in the literature concerning point to point comparison between HFR and other in situ measurements. When HFR data are compared with surface drifter clusters or ADCPs whose uppermost bins are not deeper than 5 m, RMSDs typical values range between 3 and 12 cm.s −1 (e.g., Ohlmann et al, 2007;Molcard et al, 2009;Liu et al, 2010;Kalampokis et al, 2016). Each row corresponds to one of the ITU frequency bands allocated for oceanographic radar with the lower and upper band limits in frequency.…”

Section: Basic Principles Of Hfr Operation and Data Specificationsmentioning

confidence: 99%

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

et al. 2017

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High Frequency Radar (HFR) is a land-based remote sensing instrument offering a unique insight to coastal ocean variability, by providing synoptic, high frequency and high resolution data at the ocean atmosphere interface. HFRs have become invaluable tools in the field of operational oceanography for measuring surface currents, waves and winds, with direct applications in different sectors and an unprecedented potential for the integrated management of the coastal zone. In Europe, the number of HFR networks has been showing a significant growth over the past 10 years, with over 50 HFRs currently deployed and a number in the planning stage. There is also a growing literature concerning the use of this technology in research and operational oceanography. A big effort is made in Europe toward a coordinated development of coastal HFR technology and its products within the framework of different European and international initiatives. One recent initiative has been to make an up-to-date inventory of the existing HFR operational systems in Europe, describing the characteristics of the systems, their operational products and applications. This paper offers a comprehensive review on the present status of European HFR network, and discusses the next steps toward the integration of HFR platforms as operational components of the European Ocean Observing System, designed to align and integrate Europe's ocean observing capacity for a truly integrated end-to-end observing system for the European coasts.

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Section: Basic Principles Of Hfr Operation and Data Specificationsmentioning

confidence: 99%

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

et al. 2017

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“…Wave signals sent from radar stations in the high frequency band 3~30 MHz can receive feedback from wind-driven gravity waves of surface water when ocean waves' wavelengths are exactly half the wavelength of the broadcast radio [40][41][42]. Radar stations record radial surface currents; a single radar station determines the radial component of the surface currents relative to that station, providing current magnitudes and directions toward or away from that radar station.…”

Section: Hfr Systemmentioning

confidence: 99%

Short-Term Forecasting of Coastal Surface Currents Using High Frequency Radar Data and Artificial Neural Networks

Ren

Hartnett

2018

Remote Sensing

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Accurate and timely information of surface currents is crucial for various operations such as search and rescue, marine renewable energy extraction and oil spill treatment. Conventional approaches to study coastal surface currents are numerical models and observation platforms such as radars and satellites. However, both have limits. To efficiently obtain high accuracy short-term forecasting states of oceanic parameters of interest, a robust soft computing approach-Artificial Neural Networks (ANN)-was applied to predict surface currents in a tide-and wind-dominated coastal area. Hourly observed surface currents from a Coastal Ocean Dynamic Application Radar (CODAR) system, and tide and wind data from forecasting models were used to establish ANN models for Galway Bay area. One of the fastest algorithms, resilient back propagation, was used to adapt all weights and biases. This study focused on investigating the sensitivity of an ANN model to a series of different input datasets. Results indicate that correlation between ANN forecasts and observation was greater than 0.9 for both surface velocity components with one-hour lead time. Strong correlation (≥0.75) was obtained between predicted results and radar data for both surface velocity components with three-hour lead time at best. However, forecasting accuracy deteriorated rapidly with longer lead time. By comparison with previous data assimilation models, in this research, best performance was achieved from ANN model's peak times of the tidally dominant surface velocity component. The forecasts presented in this research show clear improvements over previous attempts at short-term forecasting of wind-and tide-dominated currents using ANN.

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“…In many works the limitations of HF radars with respect of vertical resolution is complemented by ADCP observations (e.g., Paduan and Rosenfeld, 1996;Shay et al, 1998). As demonstrated by Shay et al (2007) and Liu et al (2010) mapping surface currents combined with ADCP data serves as a strong component of monitoring and prediction systems for coastal ocean. This dominating trend in developing coastal observatories is implemented in the framework of the integrated coastal observing system for the German Bight COSYNA.…”

Section: Remote Sensingmentioning

confidence: 99%

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

et al. 2011

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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 preoperational 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 dataassimilation 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 maCorrespondence to: E. V. Stanev (emil.stanev@hzg.de) trix 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.

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

Cited by 73 publications

References 106 publications

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

HF Radar Activity in European Coastal Seas: Next Steps toward a Pan-European HF Radar Network

Short-Term Forecasting of Coastal Surface Currents Using High Frequency Radar Data and Artificial Neural Networks

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

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