Will Arctic sea ice thickness initialization improve seasonal forecast skill?

Geophysical Research Letters

Volumn 41, Issue 21, 2014, Pages 7566-7575

  Day, J J ^a   Hawkins, E ^a   Tietsche, S ^a  

^a UNIVERSITY OF READING   (United Kingdom)

Author keywords

Arctic; polar; predictability; prediction; sea ice

Indexed keywords

ATMOSPHERIC TEMPERATURE; CLIMATE MODELS; EXPERIMENTS; FORECASTING;

ARCTIC; GLOBAL CLIMATE MODEL; POLAR; PREDICTABILITY; SEA ICE CONCENTRATION; SEA-ICE THICKNESS; SEASONAL FORECASTS; SURFACE TEMPERATURES;

SEA ICE;

CLIMATE MODELING; CLIMATE PREDICTION; CONCENTRATION (COMPOSITION); GLOBAL CLIMATE; ICE THICKNESS; SEA ICE; SEASONAL VARIATION;

ARCTIC OCEAN;

EID: 84912060614     PISSN: 00948276     EISSN: 19448007     Source Type: Journal    
DOI: 10.1002/2014GL061694     Document Type: Article

References (38)

1. Bitz, C. M., M. M. Holland, E. C. Hunke, and, R. E. Moritz, (2005), Maintenance of the sea-ice edge, J. Clim., 18 (15), 2903-2921.
2. Blanchard-Wrigglesworth, E., and, C. M. Bitz, (2014), Characteristics of Arctic sea-ice thickness variability in GCMs, J. Clim., 27, 8244-8258, doi: 10.1175/JCLI-D-14-00345.1.
3. Blanchard-Wrigglesworth, E., C. M. Bitz, and, M. M. Holland, (2011a), Influence of initial conditions and climate forcing on predicting Arctic sea ice, Geophys. Res. Lett., 38, L18503, doi: 10.1029/2011GL048807.
4. Blanchard-Wrigglesworth, E., K. C. Armour, C. M. Bitz, and, E. DeWeaver, (2011b), Persistence and inherent predictability of Arctic sea ice in a GCM ensemble and observations, J. Clim., 24, 231-250, doi: 10.1175/2010JCLI3775.1.
5. Chevallier, M., and, D. Salas-Mélia, (2012), The role of sea ice thickness distribution in the Arctic sea ice potential predictability: A diagnostic approach with a coupled GCM, J. Clim., 25 (8), 3025-3038, doi: 10.1175/JCLI-D-11-00209.1.
6. Chevallier, M., D. Salas Y Mélia, A. Voldoire, M. Déqué, and, G. Garric, (2013), Seasonal forecasts of the pan-Arctic sea ice extent using a GCM-based seasonal prediction system, J. Clim., 26, 6092-6104, doi: 10.1175/JCLI-D-12-00612.1.
7. Collins, M., (2002), Climate predictability on interannual to decadal time scales: The initial value problem, Clim. Dyn., 19, 671-692, doi: 10.1007/s00382-002-0254-8.
8. Day, J. J., S. Tietsche, and, E. Hawkins, (2014), Pan-Arctic and regional sea ice predictability: Initialization month dependence, J. Clim., 27, 4371-4390, doi: 10.1175/JCLI-D-13-00614.1.
9. Doblas-Reyes, F. J., J. Garca-Serrano, F. Lienert, A. P. Biescas, and, L. R. L. Rodrigues, (2013), Seasonal climate predictability and forecasting: Status and prospects, Wiley Interdiscip. Rev. Clim. Change, 4 (4), 245-268, doi: 10.1002/wcc.217.
10. Dunstone, N. J., D. M. Smith, and, R. Eade, (2011), Multi-year predictability of the tropical Atlantic atmosphere driven by the high latitude North Atlantic Ocean, Geophys. Res. Lett., 38, L14701, doi: 10.1029/2011GL047949.
11. Eicken, H., (2013), Ocean science: Arctic sea ice needs better forecasts, Nature, 497 (7450), 431-433, doi: 10.1038/497431a.
12. Guemas, V., et al. (2014a), A review on Arctic sea ice predictability and prediction on seasonal-to-decadal timescales, Q. J. R. Meteorol. Soc., doi: 10.1002/qj.2401.
13. Guemas, V., F. J. Doblas-Reyes, K. Mogensen, S. Keeley, and, Y. Tang, (2014b), Ensemble of sea ice initial conditions for interannual climate predictions, Clim. Dyn., 43 (9-10), 2813-2829, doi: 10.1007/s00382-014-2095-7.
14. Holland, M. M., D. A. Bailey, and, S. Vavrus, (2010), Inherent sea ice predictability in the rapidly changing arctic environment of the community climate system model, version 3, Clim. Dyn., 36 (7), 1239-1253.
15. Hunke, E. C., and, W. H. Lipscomb, (2004), CICE: The Los Alamos Sea Ice Model, Documentation and Software, Version 3.1, Tech. Rep. LA-CC-98-16, Los Alamos Natl. Lab., Los Alamos, N. M.
16. Johns, T., et al. (2006), The new Hadley Centre Climate Model (HadGEM1): Evaluation of coupled simulations, J. Clim., 19 (7), 1327-1353.
17. Jung, T., M. A. Kasper, T. Semmler, and, S. Serrar, (2014), Arctic influence on subseasonal midlatitude prediction, Geophys. Res. Lett., 41, 3676-3680, doi: 10.1002/2014GL059961.
18. Kaleschke, L., X. Tian-Kunze, N. Maaß, M. Mäkynen, and, M. Drusch, (2012), Sea ice thickness retrieval from SMOS brightness temperatures during the Arctic freeze-up period, Geophys. Res. Lett., 39, L05501, doi: 10.1029/2012GL050916.
19. Koenigk, T., and, U. Mikolajewicz, (2009), Seasonal to interannual climate predictability in mid and high northern latitudes in a global coupled model, Clim. Dyn., 32 (6), 783-798, doi: 10.1007/s00382-008-0419-1.
20. Koenigk, T., A. Devasthale, and, K. G. Karlsson, (2014), Summer Arctic sea ice albedo in CMIP5 models, Atmos. Chem. Phys., 14 (4), 1987-1998, doi: 10.5194/acp-14-1987-2014.
21. Latif, M., M. Collins, H. Pohlmann, and, N. Keenlyside, (2006), A review of predictability studies of Atlantic sector climate on decadal time scales, J. Clim., 19 (23), 5971-5987, doi: 10.1175/JCLI3945.1.
22. Laxon, S. W., et al. (2013), CryoSat-2 estimates of arctic sea ice thickness and volume, Geophys. Res. Lett., 40, 732-737, doi: 10.1002/grl.50193.
23. Lindsay, R., C. Haas, S. Hendricks, P. Hunkeler, N. Kurtz, J. Paden, B. Panzer, J. Sonntag, J. Yungel, and, J. Zhang, (2012), Seasonal forecasts of arctic sea ice initialized with observations of ice thickness, Geophys. Res. Lett., 39, L21502, doi: 10.1029/2012GL053576.
24. Massonnet, F., T. Fichefet, H. Goosse, C. M. Bitz, G. Philippon-Berthier, M. M. Holland, and, P. -Y. Barriat, (2012), Constraining projections of summer arctic sea ice, The Cryosphere, 6 (6), 1383-1394, doi: 10.5194/tc-6-1383-2012.
25. Mathiot, P., C. König Beatty, T. Fichefet, H. Goosse, F. Massonnet, and, M. Vancoppenolle, (2012), Better constraints on the sea-ice state using global sea-ice data assimilation, Geosci. Model Dev., 5 (6), 1501-1515, doi: 10.5194/gmd-5-1501-2012.
26. McLaren, A. J., et al. (2006), Evaluation of the sea ice simulation in a new coupled atmosphere-ocean climate model (HadGEM1), J. Geophys. Res., 111, C12014, doi: 10.1029/2005JC003033.
27. Persson, P. O. G., C. W. Fairall, E. L. Andreas, P. S. Guest, and, D. K. Perovich, (2002), Measurements near the atmospheric surface flux group tower at SHEBA: Near-surface conditions and surface energy budget, J. Geophys. Res., 107 (C10), 8045, doi: 10.1029/2000JC000705.
28. Pohlmann, H., M. Botzet, M. Latif, A. Roesch, M. Wild, and, P. Tschuck, (2004), Estimating the decadal predictability of a coupled AOGCM, J. Clim., 17 (22), 4463-4472.
29. Schröder, D., D. L. Feltham, D. Flocco, and, M. Tsamados, (2014), September arctic sea-ice minimum predicted by spring melt-pond fraction, Nat. Clim. Change, 4, 353-357, doi: 10.1038/nclimate2203.
30. Serreze, M. C., and, R. G. Barry, (2009), The Arctic Climate System, Cambridge University Press, Cambridge, U. K.
31. Shaffrey, L. C., et al. (2009), U. K. HiGEM: The new U.K. high-resolution global environment Model-Model description and basic evaluation, J. Clim., 22 (8), 1861-1896, doi: 10.1175/2008JCLI2508.1.
32. Sigmond, M., J. C. Fyfe, G. M. Flato, V. V. Kharin, and, W. J. Merryfield, (2013), Seasonal forecast skill of Arctic sea ice area in a dynamical forecast system, Geophys. Res. Lett., 40, 529-534, doi: 10.1002/grl.50129.
33. Stephenson, S. R., L. C. Smith, and, J. A. Agnew, (2011), Divergent long-term trajectories of human access to the arctic, Nat. Clim. Change, 1 (3), 156-160, doi: 10.1038/nclimate1120.
34. Stroeve, J., L. C. Hamilton, C. M. Bitz, and, E. Blanchard-Wrigglesworth, (2014), Predicting September sea ice ensemble skill of the search sea ice outlook 2008-2013, Geophys. Res. Lett., 41, 2411-2418, doi: 10.1002/2014GL059388.
35. Tietsche, S., D. Notz, J. H. Jungclaus, and, J. Marotzke, (2013), Assimilation of sea-ice concentration in a global climate model physical and statistical aspects, Ocean Sci., 9 (1), 19-36, doi: 10.5194/os-9-19-2013.
36. Tietsche, S., J. J. Day, V. Guemas, W. J. Hurlin, S. P. E. Keeley, D. Matei, R. Msadek, M. Collins, and, E. Hawkins, (2014), Seasonal to interannual arctic sea ice predictability in current global climate models, Geophys. Res. Lett., 41, 1035-1043, doi: 10.1002/2013GL058755.
37. Wang, W., M. Chen, and, A. Kumar, (2013), Seasonal prediction of arctic sea ice extent from a coupled dynamical forecast system, Mon. Weather Rev., 141 (4), 1375-1394, doi: 10.1175/MWR-D-12-00057.1.
38. Yang, Q., S. N. Losa, M. Losch, X. Tian-Kunze, L. Nerger, J. Liu, L. Kaleschke, and, Z. Zhang, (2014), Assimilating SMOS sea ice thickness into a coupled ice-ocean model, using a local SEIK filter, J. Geophys. Res. Oceans, 119, doi: 10.1002/2014JC009963.