Seasonal variation of surface currents in the southwestern Taiwan Strait observed with HF radar

2008 ◽  
Vol 53 (15) ◽  
pp. 2385-2391 ◽  
Author(s):  
DaYong Zhu ◽  
Li Li ◽  
Yan Li ◽  
XiaoGang Guo
Keyword(s):  
Seasonal Variation ◽  
Taiwan Strait ◽  
Hf Radar ◽  
Surface Currents ◽  
Southwestern Taiwan

Backtracking drifting objects using surface currents from high-frequency (HF) radar technology

2012 ◽  
Vol 62 (7) ◽  
pp. 1073-1089 ◽  
Author(s):  
Ana Julia Abascal ◽  
Sonia Castanedo ◽  
Vicente Fernández ◽  
Raúl Medina
Keyword(s):  
High Frequency ◽  
Hf Radar ◽  
Surface Currents

scholarly journals Assimilation of HF radar surface currents to optimize forcing in the northwestern Mediterranean Sea

2014 ◽  
Vol 21 (3) ◽  
pp. 659-675 ◽  
Author(s):  
J. Marmain ◽  
A. Molcard ◽  
P. Forget ◽  
A. Barth ◽  
Y. Ourmières
Keyword(s):  
Surface Wind ◽  
Circulation Model ◽  
Radar Data ◽  
Hf Radar ◽  
Open Boundary ◽  
Coastal Current ◽  
Surface Currents ◽  
Data Set ◽  
Radar Measurements ◽  
Northwestern Mediterranean

Abstract. HF radar measurements are used to optimize surface wind forcing and baroclinic open boundary condition forcing in order to constrain model coastal surface currents. This method is applied to a northwestern Mediterranean (NWM) regional primitive equation model configuration. A new radar data set, provided by two radars deployed in the Toulon area (France), is used. To our knowledge, this is the first time that radar measurements of the NWM Sea are assimilated into a circulation model. Special attention has been paid to the improvement of the model coastal current in terms of speed and position. The data assimilation method uses an ensemble Kalman smoother to optimize forcing in order to improve the model trajectory. Twin experiments are initially performed to evaluate the method skills. Real measurements are then fed into the circulation model and significant improvements to the modeled surface currents, when compared to observations, are obtained.

scholarly journals Comparison of HF radar measurements with Eulerian and Lagrangian surface currents

2015 ◽  
Vol 65 (5) ◽  
pp. 679-690 ◽  
Author(s):  
Johannes Röhrs ◽  
Ann Kristin Sperrevik ◽  
Kai Håkon Christensen ◽  
Göran Broström ◽  
Øyvind Breivik
Keyword(s):  
Hf Radar ◽  
Surface Currents ◽  
Lagrangian Surface ◽  
Radar Measurements

scholarly journals On the nature of tidal asymmetry in the Gulf of Khambhat, Arabian Sea using HF radar surface currents

2020 ◽  
Vol 232 ◽  
pp. 106481 ◽  
Author(s):  
Samiran Mandal ◽  
Sourav Sil ◽  
Avijit Gangopadhyay ◽  
Basanta Kumar Jena ◽  
Ramasamy Venkatesan
Keyword(s):  
Arabian Sea ◽  
Hf Radar ◽  
Tidal Asymmetry ◽  
Surface Currents

scholarly journals Forecasting of Surface Currents via Correcting Wind Stress with Assimilation of High-Frequency Radar Data in a Three-Dimensional Model

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Lei Ren ◽  
Stephen Nash ◽  
Michael Hartnett
Keyword(s):  
Data Assimilation ◽  
High Frequency ◽  
Three Dimensional ◽  
Hf Radar ◽  
Surface Velocity ◽  
Shear Stresses ◽  
Surface Currents ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
The Impact

This paper details work in assessing the capability of a hydrodynamic model to forecast surface currents and in applying data assimilation techniques to improve model forecasts. A three-dimensional model Environment Fluid Dynamics Code (EFDC) was forced with tidal boundary data and onshore wind data, and so forth. Surface current data from a high-frequency (HF) radar system in Galway Bay were used for model intercomparisons and as a source for data assimilation. The impact of bottom roughness was also investigated. Having developed a “good” water circulation model the authors sought to improve its forecasting ability through correcting wind shear stress boundary conditions. The differences in surface velocity components between HF radar measurements and model output were calculated and used to correct surface shear stresses. Moreover, data assimilation cycle lengths were examined to extend the improvements of surface current’s patterns during forecasting period, especially for north-south velocity component. The influence of data assimilation in model forecasting was assessed using a Data Assimilation Skill Score (DASS). Positive magnitude of DASS indicated that both velocity components were considerably improved during forecasting period. Additionally, the improvements of RMSE for vector direction over domain were significant compared with the “free run.”

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