World Library  

Add to Book Shelf
Flag as Inappropriate
Email this Book

On the Assimilation of Ice Velocity and Concentration Data Into Large-scale Sea Ice Models : Volume 3, Issue 2 (08/06/2007)

By Dulière, V.

Click here to view

Book Id: WPLBN0004020329
Format Type: PDF Article :
File Size: Pages 15
Reproduction Date: 2015

Title: On the Assimilation of Ice Velocity and Concentration Data Into Large-scale Sea Ice Models : Volume 3, Issue 2 (08/06/2007)  
Author: Dulière, V.
Volume: Vol. 3, Issue 2
Language: English
Subject: Science, Ocean, Science
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

Fichefet, T., & Dulière, V. (2007). On the Assimilation of Ice Velocity and Concentration Data Into Large-scale Sea Ice Models : Volume 3, Issue 2 (08/06/2007). Retrieved from

Description: Université Catholique de Louvain, Institut d'Astronomie et de Géophysique Georges LemaÎtre, Louvain-la-Neuve, Belgium. Data assimilation into sea ice models designed for climate studies has started about 15 years ago. In most of the studies conducted so far, it is assumed that the improvement brought by the assimilation is straightforward. However, some studies suggest this might not be true. In order to elucidate this question and to find an appropriate way to further assimilate sea ice concentration and velocity observations into a global sea ice-ocean model, we analyze here results from a number of twin experiments (i.e. experiments in which the assimilated data are model outputs) carried out with a simplified model of the Arctic sea ice pack. Our objective is to determine to what degree the assimilation of ice velocity and/or concentration data improves the global performance of the model and, more specifically, reduces the error in the computed ice thickness. A simple optimal interpolation scheme is used, and outputs from a control run and from perturbed experiments without and with data assimilation are thoroughly compared. Our results indicate that, under certain conditions depending on the assimilation weights and the type of model error, the assimilation of ice velocity data enhances the model performance. The assimilation of ice concentration data can also help in improving the model behavior, but it has to be handled with care because of the strong connection between ice concentration and ice thickness. This study is first step towards real data assimilation into NEMO-LIM, a global sea ice-ocean model.

On the assimilation of ice velocity and concentration data into large-scale sea ice models

Cavalieri, D., Parkinson, C., and Vinnikov, K.: 30-Year satellite record reveals contrasting Arctic and Antarctic decadal sea ice variability, Geophys. Res. Lett., 30, 18, doi:10.1029/2003GL018031, 2003.; Comiso, J.: A rapidly declining perennial sea ice cover in the Arctic, Geophys. Res. Lett., 20, 1956, doi:10.1029/2002GL015650, 2002.; Comiso, J. and Steffen, J.: Studies of Antarctic sea ice concentrations from satellite data and their applications, J. Geophys. Res., 106, 31 361–31 385, 2001.; Meier, W. and Maslanik, J.: Improved sea ice parcel trajectories in the Arctic via data assimilation, Mar. Pollut. Bull., 42, 506–512, 2001b.; Arbetter, T., Lynch, A., Maslanik, J., and Meier, W.: Effects of data assimilation of ice motion in a basin-scale sea ice model, Ice in the Environment: Proceedings of the 16th IAHR International Symposium on Ice, Dunedin, New Zealand, 2–6 December 2002, International Association of Hydraulic Engineering and Research, edited by: Squire, V. and Langhore, P., 3, 186–193, 2002.; Bj\orgo, E., Johannessen, O., and Miles, M.: Analysis of merged SMMR/SSMI time series of Arctic and Antarctic sea ice parameters, Geophys. Res. Lett., 24, 413–416, 1997.; Bourke, R. and Garrett, R.: Sea ice thickness distribution in the Arctic Ocean, Cold Reg. Sci. Technol., 13, 259–280, 1987.; Cavalieri, D., Gloersen, P., Parkinson, J., Comiso, J., and Zwally, H.: Observed hemispheric asymmetry in global sea ice changes, Science, 278, 1104–1106, 1997.; Comiso, J.: Bootstrap sea ice concentrations for NIMBUS-7 SMMR and DMSP SSM/I, National Snow and Ice Data Center, Boulder, CO, USA, digital media, 1999.; Dai, M., Arbetter, T., and Meier, W.: Data assimilation of sea-ice motion vectors: Sensitivity to the parameterization of sea-ice strength, Ann. Glaciol., 44, 357–360, 2006.; Emery, W., Fowler, C., and Maslanik, J.: Satellite-derived maps of Arctic and Antarctic sea ice motion: 1988 to 1994, Geophys. Res. Lett., 24, 897–900, 1997.; Fichefet, T., Tartinville, B., and Goosse, H.: Antarctic sea ice variability during 1958–1999 : A simulation with a global ice-ocean model, J. Geophys. Res., 108(C3), 3102, doi:10.1029/2001JC001148-12, 2003.; Fowler, C. and Emery, W. and Maslanik, J.: Satellite-derived evolution of Arctic sea ice ages: October 1978 to March 2003, IEEE Geoscience and Remote Sensor Letters, 1, 2, 71–74,2004.; Fox, A., Haines, K., de~Cuevas, B., and Webb, D.: Altimeter assimilation in the OCCAM global model, Part I : A twin experiment, J. Mar. Syst., 26, 303–320., 2000.; Ghil, M. and Malanotte-Rizzoli, P.: Data assimilation in meteorology and oceanography, Adv. Geophys., 33, 141–266, 1991.; Goosse, H.: Modelling the large-scale behaviour of the coupled ocean-sea ice system, Ph.D. thesis, Université Catholique de Louvain, Louvain-la-Neuve, Belgium, 1997.; Hibler: A dynamic thermodynamic sea ice model, J. Phys. Oceanogr., 9, 815–846, 1979.; Holloway, G. and Sou, T.: Has Arctic sea ice rapidly thinned?, J. Climate, 15, 1691–1701, 2002.; Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, B. Am. Meteor. Soc., 77(3), 437–471, 1996.; Köberle, C. and Gerdes, R.: Mechanisms determining the variability of the Arctic sea ice conditions and export, J. Climate, 16, 2843–2858, 2003.; Kreyscher, M., Harder, M., Lemke, P., and Flato, G.: Results of the Sea Ice Model Intercomparison Project : Evaluation of sea ice rheology schemes for use in climate simulations, J. Geophys. Res., 105, 11 299–11 320, 2000.; Kwok, R., Zwally, H., and Yi, D.: ICEsat observations of Arctic sea ice: a first look


Click To View

Additional Books

  • Mediterranean Forecasting System: Foreca... (by )
  • Exceptional Dense Water Formation on the... (by )
  • A 20-year Reanalysis Experiment in the B... (by )
  • The Assessment of Temperature and Salini... (by )
  • A Parameter Model of Gas Exchange for th... (by )
  • Interannual Correlations Between Sea Sur... (by )
  • A New Parameterisation of Salinity Advec... (by )
  • About Uncertainties in Practical Salinit... (by )
  • Friction and Mixing Effects on Potential... (by )
  • Detecting Marine Hazardous Substances an... (by )
  • Assimilation of Sla Along Track Observat... (by )
  • Sensors for Physical Fluxes at the Sea S... (by )
Scroll Left
Scroll Right


Copyright © World Library Foundation. All rights reserved. eBooks from World Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.