Advertisement

Ocean Dynamics

, Volume 67, Issue 1, pp 117–135 | Cite as

Correction of inertial oscillations by assimilation of HF radar data in a model of the Ligurian Sea

  • Luc VandenbulckeEmail author
  • Jean-Marie Beckers
  • Alexander Barth
Article
Part of the following topical collections:
  1. Topical Collection on the 47th International Liège Colloquium on Ocean Dynamics, Liège, Belgium, 4-8 May 2015

Abstract

This article aims at analyzing if high-frequency radar observations of surface currents allow to improve model forecasts in the Ligurian Sea, where inertial oscillations are a dominant feature. An ensemble of ROMS models covering the Ligurian Sea, and nested in the Mediterranean Forecasting System, is coupled with two WERA high-frequency radars. A sensitivity study allows to determine optimal parameters for the ensemble filter. By assimilating observations in a single point, the obtained correction shows that the forecast error covariance matrix represents the inertial oscillations, as well as large- and meso-scale processes. Furthermore, it is shown that the velocity observations can correct the phase and amplitude of the inertial oscillations. Observations are shown to have a strong effect during approximately half a day, which confirms the importance of using a high temporal observation frequency. In general, data assimilation of HF radar observations leads to a skill score of about 30% for the forecasts of surface velocity.

Keywords

Data assimilation High-frequency radar Ligurian sea Inertial oscillation 

Notes

Acknowledgments

This work has been funded by the EU FP7-SPACE-2011 project SANGOMA (grant 283580). CMRE and WERA are acknowledged for the HF radar data and Jacopo Chiggiato and Michel Rixen for their help with the ROMS setup. This publication is MARE publication 341.

References

  1. Auclair F, Marsaleix P, De Mey P (2003) Space-time structure and dynamics of the forecast error in a coastal circulation model of the Gulf of Lions. Dyn Atmos Oceans 36:309–346CrossRefGoogle Scholar
  2. Ayoub N, Lucas M, De Mey P (2015) Estimating uncertainties on a Gulf Stream mixed-layer heat budget from stochastic modeling. J Mar Syst 150:66–79CrossRefGoogle Scholar
  3. Barrick DE, Evans MW, Weber BL (1977) Ocean surface currents mapped by radar. Science 198:138–144CrossRefGoogle Scholar
  4. Barth A, Alvera-Azcarate A, Weisberg RH (2008) Assimilation of high-frequency radar currents in a nested model of the West Florida shelf. J Geophys Res:113Google Scholar
  5. Barth A, Alvera-Azcarate A, Beckers J-M, Weisberg RH, Vandenbulcke L, Lenartz F, Rixen M (2009) Dynamically constrained ensemble perturbations—application to tides on the West Florida shelf. Ocean Sci 5:259–270CrossRefGoogle Scholar
  6. Barth A, Alvera-Azcarate A, Beckers J-M, Staneva J, Stanev E, Schulz-Stellenfleth J (2011) Correcting surface winds by assimilating high-frequency radar surface currents in the German Bight. Ocean Dyn 61:599–610CrossRefGoogle Scholar
  7. Beckers J-M, Barth A, Alvera-Azcarate A (2006) DINEOF Reconstruction of clouded images including error maps—application to the sea-surface temperature around Corsican Island. Ocean Sci 2:183–199CrossRefGoogle Scholar
  8. Bishop C, Etherton B, Majumdar S (2001) Adaptive sampling with the ensemble transform Kalman filter part I: the theoretical aspects. Mon Weather Rev 129:420–436CrossRefGoogle Scholar
  9. Breivik O, Saetra O (2001) Real time assimilation of HF currents into a coastal ocean model. J Mar Syst 28:161–182CrossRefGoogle Scholar
  10. Burrillo A, Caniaux G, Gavart M, De Mey P, Baraille R (2002) Assessing ocean-model sensitivity to wind forcing uncertainties. Geophys Res Lett:29Google Scholar
  11. Chao Y, Li Z, Farrara J, McWilliams J, Bellingham J, Capet X, Chavez F, Choi J-K, Davis R, Doyle J, Fratantoni D, Li P, Marchesiello P, Moline M, Paduan J, Ramp S (2009) Development, implementation and evaluation of a data-assimilative ocean forecasting system off the central California coast. Deep-Sea Res II(56):100– 126Google Scholar
  12. Counillon F, Sakov P, Bertino L (2009) Application of a hybrid EnKF-OI to ocean forecasting. Ocean Sci 5:389–401CrossRefGoogle Scholar
  13. Evensen G (2003) The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dyn 53:343–367CrossRefGoogle Scholar
  14. Gomez R, Helzel T, Merz CR, Yonggang L, Weisberg RH, Thomas N (2015) Improvements in ocean surface radar applications through real-time data quality-control. In: Current, waves and turbulence measurement (CWTM), 2015 IEEE/OES eleventhGoogle Scholar
  15. Hunt BR, Kalnay E, Kostelich EJ, Ott E, Patil DJ, Sauer T, Szunyogh I, Yorke JA, Zimin AV (2004) Four-dimensional ensemble Kalman filtering. Tellus 56:273–277CrossRefGoogle Scholar
  16. Hunt BR, Kostelich EJ, Szunyogh I (2007) Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter. Physica D: Nonlinear Phenomena 230:112–126CrossRefGoogle Scholar
  17. Jorda G, De Mey P (2010) Characterization of error dynamics in a 3D coastal model of the Catalan sea using stochastic modelling. Cont Shelf Res 30:419–441CrossRefGoogle Scholar
  18. Kaplan D, Lekien F (2007) Spatial interpolation and filtering of surface current data based on open-boundary modal analysis. J Geophys Res Oceans:112Google Scholar
  19. Kurapov A (2014) Improvements in the Oregon coastal ocean forecast system: data assimilation in the presence of the Columbia River plume. In: COSS-TT workshop, Puerto Rico, session 2Google Scholar
  20. Lamouroux J (2006) Erreur de prevision d’un modele oceanique barotrope du Golfe de Gascogne en reponse aux incertitudes sur les forcages atmospheriques: caracterisation et utilisation dans un schema d’assimilation de donnees a ordre reduit. PhD thesis, Universite Paul Sabatier, ToulouseGoogle Scholar
  21. Lang M, Van Leeuwen PJ, Browne P (2016) A systematic method of parameterisation estimation using data assimilation. Tellus A 68:1–10CrossRefGoogle Scholar
  22. Lellouche JM, Le Galloudec O, Drevillon M, Regnier C, Greiner E, Garric G, Ferry N, Desportes C, Testut C-E, Bricaud C, Bourdalle-Badie R, Tranchant B, Benkiran M, Drillet Y, Daudin A, De Nicola C (2013) Evaluation of global monitoring and forecasting systems at Mercator Ocean. Ocean Sci 9:57–81CrossRefGoogle Scholar
  23. Lewis J, Shulman I, Blumberg A (1998) Assimilation of Doppler radar current data into numerical ocean models. Cont Shelf Research 18:541–559CrossRefGoogle Scholar
  24. Marmain J, Molcard A, Forget P, Barth A, Ourmieres Y (2014) Assimilation of HF radar surface currents to optimize forcing in the northwestern Mediterranean Sea. Nonlin Processes Geophys 21:659–675CrossRefGoogle Scholar
  25. Mourre B, Ballabrera-Poy J, Garcia-Ladona E, Font J (2008) Surface salinity response to changes in the model parameters and forcings in a climatological simulation of the Eastern North-Atlantic Ocean. Ocean Model 23:21–32CrossRefGoogle Scholar
  26. Nerger L, Janjic T, Schroter J, Hiller W (2012) A regulated localization scheme for ensemble-based Kalman filters. Q J R Meteorol Soc 138:802–812CrossRefGoogle Scholar
  27. Paduan J, Washburn L (2013) Observations of ocean surface currents. Annu Rev Mar Sci:5Google Scholar
  28. Pham D, Verron J, Roubaud M (1998) A singular evolutive extended Kalman filter for data assimilation in oceanography. J Mar Syst 16:323–340CrossRefGoogle Scholar
  29. Quattrocchi G, De Mey P, Ayoub N, Vervatis VD, Testut C-E, Reffray G, Chanut J, Drillet Y (2014) Characterisation of errors of a regional model of the Bay of Biscay in response to wind uncertainties: a first step toward a data assimilation system suitable for coastal sea domains. J Oper Oceanograpy 7:25–34CrossRefGoogle Scholar
  30. Sakov P, Evensen G, Bertino L (2010) Asynchronous data assimilation with the EnKF. Tellus 62A:24–29CrossRefGoogle Scholar
  31. Sakov P, Counillon F, Bertino L, Lisaeter KA, Oke OR, Korablev A (2012) Topaz4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic. Ocean Sci 8:633–656CrossRefGoogle Scholar
  32. Schiller A, Bell M, Brassington G, Brasseur P, Barciela R, De Mey P, Dombrowsky E, Gehlen M, Hernandez F, Kourafalou V, Larnicol G, Le Traon P-Y, Martin M, Oke P, Smith GC, Smith N, Tolman H, Wilmer-Becker K (2015) Synthesis of new scientific challenges for GODAE OceanView. Journal Of Operational Oceanography 8:259–271CrossRefGoogle Scholar
  33. Shchepetkin AF, McWilliams JC (2003) A method for computing horizontal pressure-gradient force in an oceanic model with a nonaligned vertical coordinate. J Geophys Res 108(C3)Google Scholar
  34. Shchepetkin AF, McWilliams JC (2005) The regional ocean modeling system: a split-explicit, free-surface, topography following coordinates ocean model. Ocean Model 9:347–404CrossRefGoogle Scholar
  35. Shchepetkin AF, McWilliams JC (1998) Quasi-monotone advection schemes based on explicit locally adaptive dissipation. Mon Weather Rev 126:1541–1580CrossRefGoogle Scholar
  36. Sperrevik AK, Christensen KH, Rohrs J (2015) Constraining energetic slope currents through assimilation of high-frequency radar observations. Ocean Sci 11:237–249CrossRefGoogle Scholar
  37. Talagrand O (1972) On the damping of high-frequency motions in four-dimensional assimilation of meteorological data/. J Atmos Sci:1571–1547Google Scholar
  38. van Leeuwen PJ (2001) An ensemble smoother with error estimates. Mon Weather Rev 129:709–728CrossRefGoogle Scholar
  39. Vandenbulcke L, Barth A (2015) A stochastic operational forecasting system of the black sea: technique and validation. Ocean Model 93:7–21CrossRefGoogle Scholar
  40. Vandenbulcke L., Barth A., Rixen M., Alvera-Azcárate A., Ben Bouallegue Z., Beckers J.-M. (2006) Study of the combined effects of data assimilation and grid nesting in ocean models. Application to the Gulf of Lions. Ocean Science, vol 2. doi: http://dx.doi.org/10.5194/os-2-213-2006
  41. Vandenbulcke L, Rixen M, Beckers J-M, Alvera-Azcarate A, Barth A (2008) An analysis of the error space of a high-resolution implementation of GHER hydrodynamic model in the Mediterranean Sea. Ocean Model 24:46–64CrossRefGoogle Scholar
  42. Verlaan M (1998) Efficient Kalman filtering algorithms for hydrodynamic models. PhD thesis, TU Delft, The NetherlandsGoogle Scholar
  43. Vervatis V, Testut C-E, De Mey P, Ayoub N, Chanut J, Quattrocchi G (2015) Data assimilative twin-experiment in a high-resolution Bay of Biscay configuration: 4D EnOI based on stochastic modelling of the wind forcing. Ocean ModelGoogle Scholar
  44. Zhang W, Wilkin J, Arango H (2010) Towards an integrated observation and modeling system in the New York Bight using variational methods. Part I: 4DVAR data assimilation. Ocean Model 35:119–133CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Luc Vandenbulcke
    • 1
    Email author
  • Jean-Marie Beckers
    • 1
  • Alexander Barth
    • 1
  1. 1.University of LiègeLiègeBelgium

Personalised recommendations