Journal cover Journal topic
Ocean Science An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 2.539 IF 2.539
  • IF 5-year value: 3.129 IF 5-year
    3.129
  • CiteScore value: 2.78 CiteScore
    2.78
  • SNIP value: 1.217 SNIP 1.217
  • IPP value: 2.62 IPP 2.62
  • SJR value: 1.370 SJR 1.370
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 48 Scimago H
    index 48
  • h5-index value: 32 h5-index 32
OS | Articles | Volume 15, issue 2
Ocean Sci., 15, 443–457, 2019
https://doi.org/10.5194/os-15-443-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: The Copernicus Marine Environment Monitoring Service (CMEMS):...

Ocean Sci., 15, 443–457, 2019
https://doi.org/10.5194/os-15-443-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 26 Apr 2019

Research article | 26 Apr 2019

A multiscale ocean data assimilation approach combining spatial and spectral localisation

Ann-Sophie Tissier et al.

Related authors

Assimilation of chlorophyll data into a stochastic ensemble simulation for the North Atlantic ocean
Yeray Santana-Falcón, Pierre Brasseur, Jean Michel Brankart, and Florent Garnier
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-6,https://doi.org/10.5194/os-2020-6, 2020
Preprint under review for OS
Short summary
Physical-biogeochemical regional ocean model uncertainties stemming from stochastic parameterizations and potential impact on data assimilation
Vassilios D. Vervatis, Pierre De Mey-Frémaux, Nadia Ayoub, Sarantis Sofianos, Charles-Emmanuel Testut, Marios Kailas, John Karagiorgos, and Malek Ghantous
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-31,https://doi.org/10.5194/gmd-2019-31, 2019
Revised manuscript not accepted
Short summary
An ensemble probabilisitic approach to reconstruct the biogeochemical state of the North Atlantic Ocean using ocean colour images
Florent Garnier, Pierre Brasseur, Jean-Michel Brankart, Yeray Santana-Falcon, and Emmanuel Cosme
Ocean Sci. Discuss., https://doi.org/10.5194/os-2018-153,https://doi.org/10.5194/os-2018-153, 2019
Publication in OS not foreseen
Assimilation of passive microwave AMSR-2 satellite observations in a snowpack evolution model over northeastern Canada
Fanny Larue, Alain Royer, Danielle De Sève, Alexandre Roy, and Emmanuel Cosme
Hydrol. Earth Syst. Sci., 22, 5711–5734, https://doi.org/10.5194/hess-22-5711-2018,https://doi.org/10.5194/hess-22-5711-2018, 2018
Short summary
Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time 1∕12° high-resolution system
Jean-Michel Lellouche, Eric Greiner, Olivier Le Galloudec, Gilles Garric, Charly Regnier, Marie Drevillon, Mounir Benkiran, Charles-Emmanuel Testut, Romain Bourdalle-Badie, Florent Gasparin, Olga Hernandez, Bruno Levier, Yann Drillet, Elisabeth Remy, and Pierre-Yves Le Traon
Ocean Sci., 14, 1093–1126, https://doi.org/10.5194/os-14-1093-2018,https://doi.org/10.5194/os-14-1093-2018, 2018
Short summary

Cited articles

Anderson, J. L.: A Method for Producing and Evaluating Probabilistic Forecasts from Ensemble Model Integrations, J. Climate, 9, 1518–1530, https://doi.org/10.1175/1520-0442(1996)009<1518:AMFPAE>2.0.CO;2, 1996. a, b
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive Sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical Aspects, Mon. Weather Rev., 129, 420–436, https://doi.org/10.1175/1520-0493(2001)129<0420:ASWTET>2.0.CO;2, 2001. a, b
Brankart, J.-M.: Impact of uncertainties in the horizontal density gradient upon low resolution global ocean modelling, Ocean Model., 66, 64–76, https://doi.org/10.1016/j.ocemod.2013.02.004, 2013. a
Brankart, J.-M., Cosme, E., Testut, C.-E., Brasseur, P., and Verron, J.: Efficient Local Error Parameterizations for Square Root or Ensemble Kalman Filters: Application to a Basin-Scale Ocean Turbulent Flow, Mon. Weather Rev., 139, 474–493, https://doi.org/10.1175/2010MWR3310.1, 2011. a, b
Brankart, J.-M., Candille, G., Garnier, F., Calone, C., Melet, A., Bouttier, P.-A., Brasseur, P., and Verron, J.: A generic approach to explicit simulation of uncertainty in the NEMO ocean model, Geosci. Model Dev., 8, 1285–1297, https://doi.org/10.5194/gmd-8-1285-2015, 2015. a
Publications Copernicus
Download
Short summary
To better exploit the observational information available for all scales in data assimilation systems, we investigate a new method to introduce scale separation in the algorithm. It consists in carrying out the analysis with spectral localisation for the large scales and spatial localisation for the residual scales. The performance is then checked explicitly and separately for all scales. Results show that accuracy can be improved for the large scales while preserving reliability at all scales.
To better exploit the observational information available for all scales in data assimilation...
Citation