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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Feb 2020

14 Feb 2020

Review status
A revised version of this preprint is currently under review for the journal OS.

A new Lagrandian based short term prediction methodology for HF radar currents

Lohitzune Solabarrieta1,2, Ismael Hernandez-Carrasco3, Anna Rubio4, Alejandro Orfila3, Michael Campbell1, Ganix Esnaola5,6, Julien Mader4, and Burt H. Jones1 Lohitzune Solabarrieta et al.
  • 1KAUST, Red Sea Research Center, Integrated Ocean Processes, Saudi Arabia
  • 2Mondragon Unibertsitatea, Faculty of Engineering, Electronics and Computer Science department, Loramendi 4, Mondragon 20500 Gipuzkoa, Spain
  • 3Instituto Mediterráneo de Estudios Avanzados. IMEDEA (CSIC-UIB), 07190 Esporles, Spain
  • 4AZTI Marine Research, Pasaia, Spain
  • 5Nuclear Engineering and Fluid Mechanics Dept., Gipuzkoako Ingeniaritza Eskola, Europa Plaza 1, 20018-Donostia, Spain
  • 6Joint Research Unit BEGIK, Instituto Español de Oceanografía (IEO)-Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), Plentziako Itsas Estazioa, Areatza Pasealekua, 48620-Plentzia, Spain

Abstract. The use of High Frequency Radar (HFR) data is increasing worldwide for operational oceanography and data assimilation, as it provides real-time coastal surface currents at high temporal and spatial resolution. In this work, a Lagrangian based empirical real-time, Short-Term Prediction (L-STP) system is presented in order to provide short term forecasts of up to 48 hours of ocean currents from HFR data. The method is based on the finding of historical gridded analogues of Lagrangian trajectories obtained from HFR surface currents. Then, assuming that the present state will follow the same temporal evolution as did the historical analogue, we obtain a short-term prediction of the surface currents. The method is applied to two HFR systems covering two areas with different dynamical characteristics: the southeast Bay of Biscay and the central Red Sea. The L-STP improves on previous prediction systems implemented for the SE Bay of Biscay and provides good results for the Red Sea study area. A comparison of the L-STP methodology with predictions based on persistence and reference fields has been performed in order to quantify the error introduced by this Lagrangian approach. Furthermore, a temporal sensitivity analysis has been addressed to determine the limit of applicability of the methodology regarding the temporal horizon of Lagrangian prediction. A real-time skill-score has been developed using the results of this analysis which allows to identify periods when the short-term prediction performance is more likely to be low and persistence can be used as a better predictor for the future currents.

Lohitzune Solabarrieta et al.

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Lohitzune Solabarrieta et al.

Lohitzune Solabarrieta et al.


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Latest update: 28 Oct 2020
Publications Copernicus
Short summary
High Frequency Radar technology measures coastal ocean surface currents. The use of this technology is increasing as it provides near-real time information that can be used in oil spill or search and rescue emergencies to forecast the trajectories of the floating objects. In this work, a Short-Term Prediction methodology is presented and it provides surface currents’ forecasts of up to 48 hours. The primary advantage of it, is that it is easily implemented in real time.
High Frequency Radar technology measures coastal ocean surface currents. The use of this...