Assessing the forecast skill of Arctic sea ice extent in the GloSea4 seasonal prediction system

Abstract

An assessment of the ability of the Met Office seasonal prediction system, GloSea4, to accurately forecast Arctic sea ice concentration and extent over seasonal time scales is presented. GloSea4 was upgraded in November 2010 to include the initialization of the observed sea ice concentration from satellite measurements. GloSea4 is one of only a few operational seasonal prediction systems to include both the initialization of observed sea ice followed by its prognostic determination in a coupled dynamical model of sea ice. For the forecast of the September monthly mean ice extent the best skill in GloSea4, as judged from the historical forecast period of 1996–2009, is when the system is initialized in late March and early April near to the sea ice maxima with correlation skills in the range of 0.6. In contrast, correlation skills using May initialization dates are much lower due to thinning of the sea ice at the start of the melt season which allows ice to melt too rapidly. This is likely to be due both to a systematic bias in the ice-ocean forced model as well as biases in the ice analysis system. Detailing the forecast correlation skill throughout the whole year shows that for our system, the correlation skill for ice extent at five to six months lead time is highest leading up to the September minimum (from March/April start dates) and leading up to the March maximum (from October/November start dates). Conversely, little skill is found for the shoulder seasons of November and May at any lead time.

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Notes

  1. 1.

    This data has since been reprocessed though 2009.

  2. 2.

    The GloSea4 analysis and NSIDC trends are closer together if one considers only the 1996–2007 period where GloSea4 has a consistent set of sea ice observations.

  3. 3.

    In the sense that these forecasts were performed prior to September 2011 and 2012.

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Acknowledgments

This work was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and the UK Public Weather Service research program. The authors would like to thank two anonymous reviewers for their comments leading to an improved manuscript.

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Correspondence to K. Andrew Peterson.

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Peterson, K.A., Arribas, A., Hewitt, H.T. et al. Assessing the forecast skill of Arctic sea ice extent in the GloSea4 seasonal prediction system. Clim Dyn 44, 147–162 (2015). https://doi.org/10.1007/s00382-014-2190-9

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Keywords

  • Arctic sea ice
  • Seasonal forecasting
  • Ocean and sea ice analysis
  • Data assimilation
  • Ice concentration