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How well can the observed Arctic sea ice summer retreat and winter advance be represented in the NCEP Climate Forecast System version 2?

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Abstract

The capability of a numerical model to simulate the statistical characteristics of the summer sea ice date of retreat (DOR) and the winter date of advance (DOA) is investigated using sea ice concentration output from the Climate Forecast System Version 2 model (CFSv2). Two model configurations are tested, the operational setting (CFSv2CFSR) which uses initial data from the Climate Forecast System Reanalysis, and a modified version (CFSv2PIOMp) which ingests sea ice thickness initialization data from the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) and includes physics modifications for a more realistic representation of heat fluxes at the sea ice top and bottom. First, a method to define DOR and DOA is presented. Then, DOR and DOA are determined from the model simulations and observational sea ice concentration from the National Aeronautics and Space Administration (NASA). Means, trends, and detrended standard deviations of DOR and DOA are compared, along with DOR/DOA rates in the Arctic Ocean. It is found that the statistics are generally similar between the model and observations, although some regional biases exist. In addition, regions of new ice retreat in recent years are represented well in CFSv2PIOMp over the Arctic Ocean, in terms of both spatial extent and timing. Overall, CFSv2PIOMp shows a reduction in error throughout the Arctic. Based on results, it is concluded that the model produces a reasonable representation of the climatology and variability statistics of DOR and DOA in most regions. This assessment serves as a prerequisite for future predictability experiments.

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References

  • Barnhart K, Miller CR, Overeem I, Kay JE (2016) Mapping the future expansion of Arctic open water. Nat Clim Change 6:280–285. doi:10.1038/nclimate2848

    Google Scholar 

  • Belchansky GI, Douglas DC, Platonov NG (2004) Duration of the Arctic sea ice melt season: regional and interannual variability, 1979-2001. J Clim 17:67–80. doi:10.1075/1520-0442(2004)017<0067:DOTASI>2.0.CO;2

    Article  Google Scholar 

  • Cavalieri DJ, Parkinson CL, Gloersen P., and Zwally H (1996) updated yearly: sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS passive microwave data. NASA National Snow and Ice Data Center Distributed Active Archive Center [1980–2015]. Boulder, Colorado USA

  • Chevallier M, Salas-Melia D, Voldoire A, Deque M (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

    Article  Google Scholar 

  • Collow TW, Wang W, Kumar A, Zhang J (2015) Improving Arctic sea ice prediction using PIOMAS initial sea ice thickness in a coupled ocean-atmosphere model. Mon Weather Rev 143:4618–4630. doi:10.1175/MWR-D-15-0097.1

    Article  Google Scholar 

  • Comiso JC (2000) updated yearly: bootstrap sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS.Version 2. NASA National Snow and Ice Data Center Distributed Active Archive Center [1980–2014]. Boulder, Colorado USA

  • Day JJ, Hawkins E, Tietsche S (2014) Will Arctic sea ice thickness initialization improve seasonal forecast skill? Geophys Res Lett 41:7566–7575. doi:10.1002/2014GL061694

    Article  Google Scholar 

  • Howell SEL, Duguay CR, Markus T (2009) Sea ice conditions and melt season duration variability within the Canadian Arctic archipelago: 1979–2008. Geophys Res Lett 36:L10502. doi:10.1029/2009GL037681

    Article  Google Scholar 

  • Kwok R, Cunningham GF, Nghiem SV (2003) A study of the onset of melt over the Arctic Ocean in RADARSAT synthetic aperture radar data. J Geophys Res Oceans 108:3363. doi:10.1029/2002JC001363

    Article  Google Scholar 

  • Markus T, Stroeve JC, Miller J (2009) Recent changes in Arctic sea ice melt onset, freezeup, and melt season length. J Geophys Res Oceans 114:C12024. doi:10.1029/2009JC005436

    Article  Google Scholar 

  • Maslanik J, Stroeve J, Fowler C, Emery W (2011) Distribution and trends in Arctic sea ice age through spring 2011. Geophys Res Lett 38:L13502. doi:10.1029/2011GL047735

    Article  Google Scholar 

  • Msadek RG, Vecchi GA, Winton M, Gudgel RG (2014) Importance of initial conditions in seasonal predictions of Arctic sea ice extent. Geophys Res Lett 41:5208–5215. doi:10.1002/2014GL060799

    Article  Google Scholar 

  • Notz D (2014) Sea-ice extent and its trend provide limited metrics of model performance. The Cryosphere 8:229–243. doi:10.5194/tc-8-229-2014

    Article  Google Scholar 

  • Perovich DK, Nghiem SV, Markus T, Schweiger A (2007) Seasonal evolution and interannual variability of the local solar energy absorbed by the Arctic sea ice-ocean system. J Geophys Res Oceans 112:C03005. doi:10.1029/2006JC003558

    Article  Google Scholar 

  • Peterson AK, Arribas A, Hewitt HT, Keen AB, Lea DJ, McLaren AJ (2015) Assessing the forecast skill of Arctic sea ice extent in the GloSea4 seasonal prediction system. Clim Dyn 44:147–162. doi:10.1007/s00382-014-2190-9

    Article  Google Scholar 

  • Saha S, Moorthi S, Pan H et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteorol Soc 91:1015–1067. doi:10.1175/2010BAMS3001.1

    Article  Google Scholar 

  • Saha S, Moorthi S, Wu X et al (2014) The NCEP climate forecast system version 2. J Clim 27:2185–2208. doi:10.1175/JCLI-D-12-00823.1

    Article  Google Scholar 

  • Serreze MC, Barry RG (2011) Processes and impacts of Arctic amplification: a research synthesis. Global Planet Change 77:85–96. doi:10.1016/j.gloplacha.2011.03.004

    Article  Google Scholar 

  • Sigmond M, Fyfe JC, Flato GM, Kharin VV, Merryfield WJ (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

    Article  Google Scholar 

  • Smith DM (1998a) Observation of perennial Arctic sea ice melt and freeze-up using passive microwave data. J Geophys Res Oceans 103:27753–27769. doi:10.1029/98JC02416

    Article  Google Scholar 

  • Smith DM (1998b) Recent increase in the length of the melt season of perennial Arctic sea ice. Geophys Res Lett 25:655–658. doi:10.1029/98GL00251

    Article  Google Scholar 

  • Smith LC, Stephenson SR (2013) New trans-Arctic shipping routes navigable by midcentury. Proc Natl Acad Sci USA 110:E1191–E1195. doi:10.1073/pnas.1214212110

    Article  Google Scholar 

  • Steele M, Dickinson S, Zhang J, Lindsay RL (2015) Seasonal ice loss in the Beaufort Sea: toward synchrony and prediction. J Geophys Res Oceans 120:1118–1132. doi:10.1002/2014JC010247

    Article  Google Scholar 

  • Stroeve JC, Serreze MC, Holland MM, Kay JE, Malanik J, Barrett AP (2012) The Arctic’s rapidly shrinking sea ice cover: a research synthesis. Clim Change 110:1005–1027. doi:10.1007/s10584-011-0101-1

    Article  Google Scholar 

  • Stroeve JC, Markus T, Boisvert L, Miller J, Barrett A (2014) Changes in Arctic melt season and implications for sea ice loss. Geophys Res Lett 41:1216–1225. doi:10.1002/2013GL058951

    Article  Google Scholar 

  • Vaughan DG, Comiso JC, Allison I et al (2013), Observations: Cryosphere. In: Stocker TF, Qin D, Plattner G et al (eds) Climate Change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 317–382

  • Wang W, Chen M, Kumar A (2013) Seasonal prediction of Arctic sea ice extent from a coupled dynamical forecast system. Mon Weather Rev 141:1375–1394. doi:10.1175/MWR-D-12-00057

    Article  Google Scholar 

  • Wang L, Yuan X, Ting M, Li C (2015) Predicting summer Arctic sea ice concentration intraseasonal variability using a vector autoregressive model. J Clim 29:1529–1543. doi:10.1175/JCLI-D-15-0313.1

    Article  Google Scholar 

  • Woodgate RA, Aagaard K, Weingartner TJ (2006) Interannual changes in the Bering Strait fluxes of volume, heat and freshwater between 1991 and 2004. Geophys Res Lett 33:L15609. doi:10.1029/2006GL026931

    Article  Google Scholar 

  • Zhang J, Rothrock DA (2003) Modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates. Mon Weather Rev 131:845–861

    Article  Google Scholar 

  • Zhang J, Woodgate R, Moritz R (2010) Sea ice response to atmospheric and oceanic forcing in the Bering Sea. J Phys Oceanogr 40:1729–1747. doi:10.1175/2010JPO4323.1

    Article  Google Scholar 

  • Zhang J, Lindsay R, Schweiger A, Steele M (2013) The impact of an intense summer cyclone on 2012 Arctic sea ice retreat. Geophys Res Lett 40:720–726. doi:10.1002/grl.50190

    Article  Google Scholar 

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Acknowledgements

Support for WW and JZ was provided by the NOAA Climate Program Office (Grant NA15OAR4310170). JZ was also supported by NOAA/OAR under the auspices of the National Earth System Prediction Capability. PIOMAS data used in this study are available at ftp://psc.apl.washington.edu/zhang/IDAO/data_piomas.html, NASA Team sea ice concentrations can be downloaded at ftp://sidads.colorado.edu/pub/DATASETS. The authors thank Peitao Peng and Michael Halpert for review of this manuscript. The authors are grateful to two anonymous reviewers for their helpful suggestions and comments.

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Collow, T.W., Wang, W., Kumar, A. et al. How well can the observed Arctic sea ice summer retreat and winter advance be represented in the NCEP Climate Forecast System version 2?. Clim Dyn 49, 1651–1663 (2017). https://doi.org/10.1007/s00382-016-3417-8

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  • DOI: https://doi.org/10.1007/s00382-016-3417-8

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