Predicting September Arctic Sea Ice: A Multi-Model Seasonal Skill Comparison ...

This study quantifies the state-of-the-art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multi-model dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 1...

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Bibliographic Details
Main Authors: Bushuk, Mitchell, Ali, Sahara, Bailey, David A., Bao, Qing, Batté, Lauriane, Bhatt, Uma S., Blanchard-Wrigglesworth, Edward, Blockley, Ed, Cawley, Gavin, Chi, Junhwa, Counillon, François, Coulombe, Philippe Goulet, Cullather, Richard I., Diebold, Francis X., Dirkson, Arlan, Exarchou, Eleftheria, Göbel, Maximilian, Gregory, William, Guemas, Virginie, Hamilton, Lawrence, He, Bian, Horvath, Sean, Ionita, Monica, Kay, Jennifer E., Kim, Eliot, Kimura, Noriaki, Kondrashov, Dmitri, Labe, Zachary M., Lee, WooSung, Lee, Younjoo J., Li, Cuihua, Li, Xuewei, Lin, Yongcheng, Liu, Yanyun, Maslowski, Wieslaw, Massonnet, François, Meier, Walter N., Merryfield, William J., Myint, Hannah, Navarro, Juan C. Acosta, Petty, Alek, Qiao, Fangli, Schröder, David, Schweiger, Axel, Shu, Qi, Sigmond, Michael, Steele, Michael, Stroeve, Julienne, Sun, Nico, Tietsche, Steffen
Format: Text
Language:English
Published: AMS 2024
Subjects:
Arctic
Sea ice
Online Access:https://dx.doi.org/10.13016/m2ga6t-urwo
https://mdsoar.org/handle/11603/33927
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Summary:This study quantifies the state-of-the-art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multi-model 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 2001–2020 for predictions of Pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on June 1, July 1, August 1, and September 1. This diverse set of statistical and dynamical models can individually predict linearly detrended Pan-Arctic SIE anomalies with skill, and a multi-model 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 ...

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