Articles | Volume 9, issue 6
https://doi.org/10.5194/gmd-9-2255-2016
https://doi.org/10.5194/gmd-9-2255-2016
Model experiment description paper
 | 
29 Jun 2016
Model experiment description paper |  | 29 Jun 2016

The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1

Jonathan J. Day, Steffen Tietsche, Mat Collins, Helge F. Goessling, Virginie Guemas, Anabelle Guillory, William J. Hurlin, Masayoshi Ishii, Sarah P. E. Keeley, Daniela Matei, Rym Msadek, Michael Sigmond, Hiroaki Tatebe, and Ed Hawkins

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Cited articles

Arzel, O., Fichefet, T., Goosse, H.: Sea ice evolution over the 20th and 21st centuries as simulated by current AOGCMs, Ocean Model., 12, 401–415, https://doi.org/10.1016/j.ocemod.2005.08.002, 2006.
Blanchard-Wrigglesworth, E., Armour, K. C., Bitz, C. M., and DeWeaver, E.: Persistence and Inherent Predictability of Arctic Sea Ice in a GCM Ensemble and Observations, J. Climate, 24, 231–250, https://doi.org/10.1175/2010JCLI3775.1, 2011a.
Blanchard-Wrigglesworth, E., Bitz, C., and Holland, M.: Influence of initial conditions and climate forcing on predicting Arctic sea ice, Geophys. Res. Lett., 38, L18503, https://doi.org/10.1029/2011GL048807, 2011b.
Chevallier, M., Salas y Mélia, D., Voldoire, A., Déqué, M., and Garric, G.: Seasonal Forecasts of the Pan-Arctic Sea Ice Extent Using a GCM-Based Seasonal Prediction System, J. Climate, 26, 6092–6104, https://doi.org/10.1175/JCLI-D-12-00612.1, 2013.
Collins, M.: Climate predictability on interannual to decadal time scales: the initial value problem, Clim. Dynam., 19, 671–692, https://doi.org/10.1007/s00382-002-0254-8, 2002.
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Short summary
Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable.
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