Abstract
In this work, the benefits of high-frequency (HF) radar ocean observation technology for backtracking drifting objects are analysed. The HF radar performance is evaluated by comparison of trajectories between drifter buoys versus numerical simulations using a Lagrangian trajectory model. High-resolution currents measured by a coastal HF radar network combined with atmospheric fields provided by numerical models are used to backtrack the trajectory of two dataset of surface-drifting buoys: group I (with drogue) and group II (without drogue). A methodology based on optimization methods is applied to estimate the uncertainty in the trajectory simulations and to optimize the search area of the backtracked positions. The results show that, to backtrack the trajectory of the buoys in group II, both currents and wind fields were required. However, wind fields could be practically discarded when simulating the trajectories of group I. In this case, the optimal backtracked trajectories were obtained using only HF radar currents as forcing. Based on the radar availability data, two periods ranging between 8 and 10 h were selected to backtrack the buoy trajectories. The root mean squared error (RMSE) was found to be 1.01 km for group I and 0.82 km for group II. Taking into account these values, a search area was calculated using circles of RMSE radii, obtaining 3.2 and 2.11 km2 for groups I and II, respectively. These results show the positive contribution of HF radar currents for backtracking drifting objects and demonstrate that these data combined with atmospheric models are of value to perform backtracking analysis of drifting objects.
Similar content being viewed by others
References
Abascal AJ, Castanedo S, Gutierrez AD, Comerma E, Medina R, Losada IJ (2007) TESEO, an operational system for simulating oil spills trajectories and fate processes. Proceedings ISOPE-2007: The 17th International Offshore Ocean and Polar Engineering Conference. Lisbon, Portugal, The International Society of Offshore Ocean and Polar Engineers (ISOPE) 3:1751–1758
Abascal AJ, Castanedo S, Mendez FJ, Medina R, Losada IJ (2009a) Calibration of a Lagrangian transport model using drifting buoys deployed during the Prestige oil spill. J Coast Res 25(1):80–90
Abascal AJ, Castanedo S, Medina R, Losada IJ, Alvarez-Fanjul E (2009b) Application of HF radar currents to oil spill modelling. Mar Pollut Bull 58:238–248
Allen AA, Plourde JV (1999) Review of Leeway; field experiments and implementation. USCG & R&D Center Technical Report CG-D-08-99
Allen-Perkins S, Montero P, Ayensa G (2010) Testing and application of buoys to follow up spills. Drifter workshop, Vigo (Spain)
Al-Rabeh AH, Lardner RW, Gunay N (2000) Gulfspill Version 2.0: a software package for oil spills in the Arabian Gulf. Environ Model Softw 15:425–442
Ambjörn C (2008) Seatrack Web forecasts and backtracking of oil spills—an efficient tool to find illegal spills using AIS. US/EU-Baltic International Symposium, IEEE/OES
ASCE (1996) State-of-the-art review of modeling transport and fate of oil spills. ASCE Committee on Modeling Oil Spills. Water Resources Engineering Division. J Hydraul Eng 122(11):594–609
Balseiro CF (2008) MeteoGalicia final report. Easy Project
Barrick DE, Evens MW, Weber BL (1977) Ocean surface currents mapped by radar. Science 198:138–144
Beegle-Krause CJ (2001) General NOAA Oil Modeling Environment (GNOME): a new spill trajectory model. International Oil Spill Conference
Breivik Ø, Allen AA (2008) An operational search and rescue model for the Norwegian Sea and the North Sea. J Mar Syst 69(1–2):99–113
Breivik Ø, Allen AA, Maisondieu C, Roth JC (2011) Wind-induced drift of objects at sea: the leeway field method. Appl Ocean Res 33(2):100–109
Castanedo S, Medina R, Losada IJ, Vidal C, Méndez FJ, Osorio A, Juanes JA, Puente A (2006) The Prestige oil spill in Cantabria (Bay of Biscay). Part I: operational forecasting system for quick response, risk assessment and protection of natural resources. J Coast Res 22(6):1474–1489
Chapman RD, Graber HC (1997) Validation of HF radar measurements. Oceanography 10:76–79
Chapman RD, Shay LK, Graber HC, Edson JB, Karachintsev A, Trump CL, Ross DB (1997) On the accuracy of HF radar surface current measurements: intercomparisons with ship-based sensors. J Geophys Res 102(8):18737–18748
Christiansen BM (2003) 3D oil drift and fate forecast at DMI. Technical report no. 03-36. Danish Meteorological Institute, Denmark
Daniel P, Marty F, Josse P, Skandrani C, Benshila R (2003) Improvement of drift calculation in MOTHY operational oil spill prediction system. Proceedings of the 2003 International Oil Spill Conference. Washington, DC: American Petroleum Institute
Davidson FJM, Allen A, Brassington GB, Breivik Ø, Daniel P, Kamachi M, Sato S, King B, Lefevre F, Sutton M, Kaneko H (2009) Applications of GODAE ocean current forecasts to search and rescue and ship routing. Oceanography 22(3):176–181
Duan Q, Sorooshian S, Gupta V (1992) Effective and efficient global optimization for conceptual rainfall–runoff models. Water Resour Res 28(4):1015–1031
Edwards KP, Werner FE, Blanton BO (2006) Comparison of observed and modeled drifter trajectories in coastal regions: an improvement through adjustments for observed drifter slip and errors in wind fields. J Atmos Ocean Technol 23(11):1614–1620
Fernández V, Ferrer MI, Abascal AJ, Castanedo S, Medina R, Alvarez E (2010) Operational applications of coastal high-frequency (HF) radar technology for oil spill operations. I Encuentro Oceanografía Física Española, Barcelona (Spain)
Griffa A, Piterbarg LI, Ozgokmen T (2004) Predictability of Lagrangian particle trajectories: effects of smoothing of the underlying Eulerian flow. J Mar Res 62:1–35
Hackett B, Breivik Ø, Wettre C (2006) Forecasting the drift of objects and substances in the oceans. In: Chassignet EP, Verron J (eds) Ocean weather forecasting: an integrated view of oceanography. Springer, Dordrecht, pp 507–524
Hodgins DO (1991) New capabilities in real-time oil spill and fate prediction using HF radar remote sensing. Proceedings of the 14th AMOP Technical Seminar, Canada
Hunter JR, Craig PD, Phillips HE (1993) On the use of random walk models with spatially variable diffusivity. J Comp Phys 106:366–376
Kohut JT, Roarty HJ, Glenn SM (2006) Characterizing observed environmental variability with HF Doppler radar surface current mappers and acoustic Doppler current profilers: environmental variability in the coastal ocean. J Ocean Eng 31(4):876–884
Lipa BJ, Barrick DE (1983) Least-squares methods for the extraction of surface currents for CODAR cross/loop data application at ARSLOE. IEEE J Ocean Eng OE-8:226–253
Maier-Reimer E (1982) On tracer methods in computational hydrodynamics. In: Abbott MB, Cunge JA (eds) Engineering application of computational hydraulics, 1 (Chapter 9). Pitman, London
Martinez WL, Martinez AR (2002) Computational statistics handbook (Chapter 8). Chapman and Hall, Boca Raton
Miranda R, Braunschweig F, Leitão P, Neves R, Martins F, Santos A (2000) MOHID 2000, a coastal integrated object oriented model. Hydraulic Engineering Software VII. WIT, Southampton
O’Donnell J, Ullman D, Spaulding M, Howlett E, Fake T, Hall P, Tatsu I, Edwards C, Anderson E, McClay T, Kohut J, Allen A, Lester S, Lewandowski M (2005) Integration of Coastal Ocean Dynamics Application Radar (CODAR) and Short-Term Prediction System (STPS) surface current estimates into the Search and Rescue Optimal Planning System (SAROPS). US Coast Guard Tech. Rep., DTCG39-00-D-R00008/HSCG32-04-J-100052
Price JM, Reed M, Howard MK, Johnson WR, Zhen-Gang J, Marshall CF, Guinasso JRNL, Rainey GB (2006) Preliminary assessment of an oil-spill trajectory model using a satellite-tracked, oil-spill-simulating drifters. Environ Model Softw 21:258–270
Reed M, Turner C, Odulo A (1994) The role of wind and emulsification in modelling oil spill and surface drifter trajectories. Spill Sci Technol Bull 1(2):143–157
Rixen M, Ferreira-Coelho E, Signell R (2008) Surface drift prediction in the Adriatic Sea using hyper-ensemble statistics on atmospheric, ocean and wave models: uncertainties and probability distribution areas. J Mar Syst 69(1–2):86–98
Sebastiao P, Soares CG (2006) Uncertainty in predictions of oil spill trajectories in a coastal zone. J Mar Syst 63:257–269
Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Wang W, Powers JG (2005) A description of the Advanced Research WRF version 2. NCAR technical note NCAR/TN-468+STR, 88 pp
Sotillo MG, Alvarez Fanjul E, Castanedo S, Abascal AJ, Menendez J, Olivella R, García-Ladona E, Ruiz-Villareal M, Conde J, Gómez M, Conde P, Gutierrez AD, Medina R (2008) Towards an operational system for oil spill forecast in the Spanish waters: initial developments and implementation test. Mar Pollut Bull 56(4):686–703
Spaulding ML, Howlett E, Anderson E, Jayko K (1992) OILMAP: a global approach to spill modelling. 15th Annual Arctic and marine Oilspill Program, Technical Seminar, Edmonton
Stewart RH, Joy JW (1974) HF radio measurements of surface currents. Deep-Sea Res 21:1039–1049
Ullman D, O’Donnell J, Edwards C, Fake T, Morschauser D, Sprague M, Allen A, Krenzien B (2003) Use of Coastal Ocean Dynamics Application Radar (CODAR) technology in U. S. Coast Guard search and rescue planning. US Coast Guard Rep., CG-D-09-03. 40 pp
Ullman DS, O’Donnell J, Kohut J, Fake T, Allen A (2006) Trajectory prediction using HF radar surface currents: Monte Carlo simulations of prediction uncertainties. J Geophys Res 111(C12005):1–14
Varela R (2010) Implementación de un sistema radar de alta frecuencia en la Ria de Vigo. Características fundamentales. I Encuentro Oceanografía Física Española, Barcelona (España)
Vrugt JA, Gupta HV, Bouten W, Sorooshian S (2003a) A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters. Water Resour Res 39(8) 1201:1–8 1–16
Vrugt JA, Gupta HV, Bouten W, Sorooshian S (2003b) Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm. Manual, version 1.0. 24 pp
Acknowledgments
This work has been partially funded by the Spanish Ministry for Science and Innovation under the research projects PSE-310000-2009-03 (PSE PROMARES, OCTOPOS subproject) and TRA2011-28900 (PLVMA project). The authors would like to thank the Galician Coast Guard, INTECMAR, the University of Vigo, Puertos del Estado and MeteoGalicia for the collaboration and the data provided for the study.
Author information
Authors and Affiliations
Corresponding author
Additional information
Responsible Editor: Oyvind Breivik
This article is part of the Topical Collection on Advances in Search and Rescue at Sea
Rights and permissions
About this article
Cite this article
Abascal, A.J., Castanedo, S., Fernández, V. et al. Backtracking drifting objects using surface currents from high-frequency (HF) radar technology. Ocean Dynamics 62, 1073–1089 (2012). https://doi.org/10.1007/s10236-012-0546-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10236-012-0546-4