Publication Abstracts
Bushuk et al. 2024
Bushuk, M., S. Ali, D.A. Bailey, Q. Bao, L. Batté, U.S. Bhatt, E. Blanchard-Wrigglesworth, E. Blockley, G. Cawley, J. Chi, F. Counillon, P.G. Coulombe, R.I. Cullather, F.X. Diebold, A. Dirkson, E. Exarchou, M. Göbel, W. Gregory, V. Guemas, L. Hamilton, B. He, S. Horvath, M. Ionita, J.E. Kay, E. Kim, N. Kimura, D. Kondrashov, Z.M. Labe, W. Lee, Y.J. Lee, C. Li, X. Li, Y. Lin, Y. Liu, W. Maslowski, F. Massonnet, W.N. Meier, W.J. Merryfield, H. Myint, J.C.A. Navarro, A. Petty, F. Qiao, D. Schröder, A. Schweiger, Q. Shu, M. Sigmond, M. Steele, J. Stroeve, N. Sun, S. Tietsche, M. Tsamados, K. Wang, J. Wang, W. Wang, Y. Wang, Y. Wang, , Q. Yang, X. Yuan, J. Zhang, and Y. Zhang, 2024: Predicting September Arctic sea ice: A multimodel seasonal skill comparison. Bull. Amer. Meteorol. Soc., 105, no. 7, E1170-E1203, doi:10.1175/BAMS-D-23-0163.1.
This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001-20 for predictions of pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on 1 June, 1 July, 1 August, and 1 September. This diverse set of statistical and dynamical models can individually predict linearly detrended pan-Arctic SIE anomalies with skill, and a multimodel median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and central Arctic sectors. The skill of dynamical and statistical models is generally comparable for pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least 3 months in advance.
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BibTeX Citation
@article{bu03200x,
author={Bushuk, M. and Ali, S. and Bailey, D. A. and Bao, Q. and Batté, L. and Bhatt, U. S. and Blanchard-Wrigglesworth, E. and Blockley, E. and Cawley, G. and Chi, J. and Counillon, F. and Coulombe, P. G. and Cullather, R. I. and Diebold, F. X. and Dirkson, A. and Exarchou, E. and Göbel, M. and Gregory, W. and Guemas, V. and Hamilton, L. and He, B. and Horvath, S. and Ionita, M. and Kay, J. E. and Kim, E. and Kimura, N. and Kondrashov, D. and Labe, Z. M. and Lee, W. and Lee, Y. J. and Li, C. and Li, X. and Lin, Y. and Liu, Y. and Maslowski, W. and Massonnet, F. and Meier, W. N. and Merryfield, W. J. and Myint, H. and Navarro, J. C. A. and Petty, A. and Qiao, F. and Schröder, D. and Schweiger, A. and Shu, Q. and Sigmond, M. and Steele, M. and Stroeve, J. and Sun, N. and Tietsche, S. and Tsamados, M. and Wang, K. and Wang, J. and Wang, W. and Wang, Y. and Wang, Y. and Williams, J. and Yang, Q. and Yuan, X. and Zhang, J. and Zhang, Y.},
title={Predicting September Arctic sea ice: A multimodel seasonal skill comparison},
year={2024},
journal={Bulletin of the American Meteorological Society},
volume={105},
number={7},
pages={E1170--E1203},
doi={10.1175/BAMS-D-23-0163.1},
}
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RIS Citation
TY - JOUR ID - bu03200x AU - Bushuk, M. AU - Ali, S. AU - Bailey, D. A. AU - Bao, Q. AU - Batté, L. AU - Bhatt, U. S. AU - Blanchard-Wrigglesworth, E. AU - Blockley, E. AU - Cawley, G. AU - Chi, J. AU - Counillon, F. AU - Coulombe, P. G. AU - Cullather, R. I. AU - Diebold, F. X. AU - Dirkson, A. AU - Exarchou, E. AU - Göbel, M. AU - Gregory, W. AU - Guemas, V. AU - Hamilton, L. AU - He, B. AU - Horvath, S. AU - Ionita, M. AU - Kay, J. E. AU - Kim, E. AU - Kimura, N. AU - Kondrashov, D. AU - Labe, Z. M. AU - Lee, W. AU - Lee, Y. J. AU - Li, C. AU - Li, X. AU - Lin, Y. AU - Liu, Y. AU - Maslowski, W. AU - Massonnet, F. AU - Meier, W. N. AU - Merryfield, W. J. AU - Myint, H. AU - Navarro, J. C. A. AU - Petty, A. AU - Qiao, F. AU - Schröder, D. AU - Schweiger, A. AU - Shu, Q. AU - Sigmond, M. AU - Steele, M. AU - Stroeve, J. AU - Sun, N. AU - Tietsche, S. AU - Tsamados, M. AU - Wang, K. AU - Wang, J. AU - Wang, W. AU - Wang, Y. AU - Wang, Y. AU - Williams, J. AU - Yang, Q. AU - Yuan, X. AU - Zhang, J. AU - Zhang, Y. PY - 2024 TI - Predicting September Arctic sea ice: A multimodel seasonal skill comparison JA - Bull. Amer. Meteorol. Soc. JO - Bulletin of the American Meteorological Society VL - 105 IS - 7 SP - E1170 EP - E1203 DO - 10.1175/BAMS-D-23-0163.1 ER -
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