Skip to main content
Have a personal or library account? Click to login
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: a twin experiment Cover

Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: a twin experiment

Open Access
|Jan 2020

References

  1. Aagaard, K. and Carmack, E. C. 1989. The role of sea ice and other fresh water in the Arctic circulation. J. Geophys. Res. 94, 1448514498. doi:10.1029/JC094iC10p14485
  2. Bentsen, M., Evensen, G., Drange, H. and Jenkins, A. D. 1999. Coordinate transformation on a sphere using conformal mapping. Mon. Weather Rev. 127, 27332740. doi:10.1175/1520-0493(1999)127<;2733:CTOASU>2.0.CO;2
  3. Bleck, R. 2002. An oceanic general circulation model framed in hybrid isopycnic-cartesian coordinates. Ocean Model. 4, 5588. doi:10.1016/S1463-5003(01)00012-9
  4. Borup, M., Grum, M., Madsen, H. and Mikkelsen, P. S. 2015. A partial ensemble Kalman filtering approach to enable use of range limited observations. Stoch. Environ. Res. Risk Assess. 29, 119129. Online at: doi:10.1007/s00477-014-0908-1
  5. Bouillon, S., Fichefet, T., Legat, V. and Madec, G. 2013. The elastic–viscous–plastic method revisited. Ocean Model. 71, 212. Part of special issue: Arctic Ocean. doi:10.1016/j.ocemod.2013.05.013
  6. Burgers, G., Jan van Leeuwen, P. and Evensen, G. 1998. Analysis scheme in the ensemble Kalman filter. Mon. Weather Rev. 126, 17191724. doi:10.1175/1520-0493(1998)126<;1719:ASITEK>2.0.CO;2
  7. Chassignet, E. P., Smith, L. T., Halliwell, G. R. and Bleck, R. 2003. North Atlantic simulations with the hybrid coordinate ocean model (HYCOM): Impact of the vertical coordinate choice, reference pressure, and thermobaricity. J. Phys. Oceanogr. 33, 25042526. doi:10.1175/1520-0485(2003)033<;2504:NASWTH>2.0.CO;2
  8. Collow, T. W., Wang, W., Kumar, A. and Zhang, J. 2015. Improving Arctic sea ice prediction using PIOMAS initial sea ice thickness in a coupled ocean-atmosphere model. Mon. Weather Rev. 143, 46184630. doi:10.1175/MWR-D-15-0097.1
  9. Connor, L. N., Laxon, S. W., Ridout, A. L., Krabill, W. B. and McAdoo, D. C. 2009. Comparison of Envisat radar and airborne laser altimeter measurements over Arctic sea ice. Remote Sens. Environ. 113, 563570. doi:10.1016/j.rse.2008.10.015
  10. Day, J. J., Hawkins, E. and Tietsche, S. 2014. Will Arctic sea ice thickness initialization improve seasonal forecast skill? Geophys. Res. Lett. 41, 75667575. doi:10.1002/2014GL061694
  11. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P. and co-authors. 2011. The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553597. doi:10.1002/qj.828
  12. Drange, H. and Simonsen, K. 1996. Formulation of Air-Sea Fluxes in the ESOP2 Version of MICOM. Technical Report 125, Nansen Environmental and Remote Sensing Center, Bergen.
  13. Evensen, G. 2003. The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dyn. 53, 343367. doi:10.1007/s10236-003-0036-9
  14. Evensen, G. 2004. Sampling strategies and square root analysis schemes for the EnKF. Ocean Dyn. 54, 539560. doi:10.1007/s10236-004-0099-2
  15. Forsberg, R. and Skourup, H. 2005. Arctic Ocean gravity, geoid and sea-ice freeboard heights from ICESat and GRACE. Geophys. Res. Lett. 32, L21502. doi:10.1029/2005GL023711
  16. Fritzner, S., Graversen, R., Christensen, K. H., Rostosky, P. and Wang, K. 2019. Impact of assimilating sea ice concentration, sea ice thickness and snow depth in a coupled ocean-sea ice modelling system. Cryosphere 13, 491509. doi:10.5194/tc-13-491-2019
  17. Guemas, V., Blanchard-Wrigglesworth, E., Chevallier, M., Day, J. J., Déqué, M. and co-authors. 2016. A review on Arctic sea-ice predictability and prediction on seasonal to decadal time-scales. Q. J. R. Meteorol. Soc. 142, 546561. doi:10.1002/qj.2401
  18. Houtekamer, P. L. and Mitchell, H. L. 1998. Data assimilation using an ensemble Kalman filter technique. Mon. Weather Rev. 126, 796811. doi:10.1175/1520-0493(1998)126<;0796:DAUAEK>2.0.CO;2
  19. Hunke, E. C. and Dukowicz, J. K. 1997. An elastic–viscous–plastic model for sea ice dynamics. J. Phys. Oceanogr. 27, 18491867. doi:10.1175/1520-0485(1997)027<;1849:AEVPMF>2.0.CO;2
  20. Huntemann, M., Heygster, G., Kaleschke, L., Krumpen, T., Mäkynen, M. and co-authors. 2014. Empirical sea ice thickness retrieval during the freeze-up period from SMOS high incident angle observations. Cryosphere 8, 439451. doi:10.5194/tc-8-439-2014
  21. Kaleschke, L., Maaß, N., Haas, C., Hendricks, S., Heygster, G. and co-authors. 2010. A sea-ice thickness retrieval model for 1.4 GHz radiometry and application to airborne measurements over low salinity sea-ice. Cryosphere 4, 583592. doi:10.5194/tc-4-583-2010
  22. Kaleschke, L., Tian-Kunze, X., Maas, N., Ricker, R., Hendricks, S. and Drusch, M.2015. Improved retrieval of sea ice thickness from SMOS and CryoSat-2. 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, 2015, pp 52325235. doi:10.1109/IGARSS.2015.7327014
  23. Kimmritz, M., Counillon, F., Bitz, C., Massonnet, F., Bethke, I. and co-authors. 2018. Optimising assimilation of sea ice concentration in an Earth system model with a multicategory sea ice model. Tellus A: Dynamic Meteorology and Oceanography 70, 123. doi:10.1080/16000870.2018.1435945
  24. Laxon, S. W., Giles, K. A., Ridout, A. L., Wingham, D. J., Willatt, R. and co-authors. 2013. CryoSat-2 estimates of Arctic sea ice thickness and volume. Geophys. Res. Lett. 40, 732737. doi:10.1002/grl.50193
  25. Mu, L., Losch, M., Yang, Q., Ricker, R., Losa, S. N. and co-authors. 2018. Arctic-wide sea ice thickness estimates from combining satellite remote sensing data and a dynamic ice-ocean model with data assimilation during the CryoSat-2 period. J. Geophys. Res. Oceans 123, 77637780. doi:10.1029/2018JC014316
  26. Ricker, R., Hendricks, S., Helm, V., Skourup, H. and Davidson, M. 2014. Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation. The Cryosphere 8, 16071622. doi:10.5194/tc-8-1607-2014
  27. Ricker, R., Hendricks, S., Kaleschke, L., Tian-Kunze, X., King, J. and co-authors. 2017. A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data. The Cryosphere 11, 16071623. doi:10.5194/tc-11-1607-2017
  28. Sakov, P., Counillon, F., Bertino, L., Lisaeter, K., Oke, P. and co-authors. 2012. TOPAZ4: An ocean-sea ice data assimilation system for the north Atlantic and Arctic. Ocean Sci. 8, 633. doi:10.5194/os-8-633-2012
  29. Screen, J. and Simmonds, I. 2010. The central role of diminishing sea ice in recent Arctic temperature amplification. Nature 464, 13341337. doi:10.1038/nature09051
  30. Shah, A., Gharamti, M. E. and Bertino, L. 2018. Assimilation of semi-qualitative observations with a stochastic ensemble kalman filter. Q. J. R. Meteorol. Soc.144, 1882–1894. doi:10.1002/qj.3381
  31. Tian-Kunze, X., Kaleschke, L., Maaß, N., Mäkynen, M., Serra, N. and co-authors. 2014. SMOS-derived thin sea ice thickness: Algorithm baseline, product specifications and initial verification. Cryosphere 8, 9971018. doi:10.5194/tc-8-997-2014
  32. Tilling, R. L., Ridout, A. and Shepherd, A. 2016. Near-real-time Arctic sea ice thickness and volume from CryoSat-2. Cryosphere 10, 20032012. doi:10.5194/tc-10-2003-2016
  33. Wang, X., Key, J., Kwok, R. and Zhang, J. 2016. Comparison of Arctic sea ice thickness from satellites, aircraft, and PIOMAS data. Remote Sens. 8, 713. doi:10.3390/rs8090713
  34. Xie, J., Bertino, L., Counillon, F., Lisaeter, K. A. and Sakov, P. 2017. Quality assessment of the TOPAZ4 reanalysis in the Arctic over the period 1991–2013. Ocean Sci. 13, 123144. doi:10.5194/os-13-123-2017
  35. Xie, J., Counillon, F. and Bertino, L. 2018. Impact of assimilating a merged sea-ice thickness from cryosat-2 and smos in the arctic reanalysis. Cryosphere 12, 36713691. doi:10.5194/tc-12-3671-2018
  36. Xie, J., Counillon, F., Bertino, L., Tian-Kunze, X. and Kaleschke, L. 2016. Benefits of assimilating thin sea ice thickness from SMOS into the TOPAZ system. Cryosphere 10, 27452761. doi:10.5194/tc-10-2745-2016
  37. Yang, Q., Losa, S. N., Losch, M., Tian-Kunze, X., Nerger, L. and co-authors. 2014. Assimilating SMOS sea ice thickness into a coupled ice-ocean model using a local SEIK filter. J. Geophys. Res. Oceans 119, 66806692. doi:10.1002/2014JC009963
Language: English
Page range: 1697166 - 1697166
Published on: Jan 1, 2020
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2020 Abhishek Shah, Laurent Bertino, François Counillon, Mohamad El Gharamti, Jiping Xie, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.