Assessment of Arctic and Antarctic sea ice predictability in CMIP5 decadal hindcasts
Assessment of Arctic and Antarctic sea ice predictability in CMIP5 decadal hindcasts
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CMIP5 十年后报中北极和南极海冰可预测性评估
DOI：
10.5194/tc-10-2429-2016
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发表时间：
2016-10
期刊：
影响因子：
5.2
通讯作者：
Cheng Xiao
中科院分区：
文献类型：
--
作者：
Yang Chao-Yuan;Liu Jiping;Hu Yongyun;Horton Radley M.;Chen Liqi;Cheng Xiao
本文探讨了耦合全球气候模式预测北极和南极海冰年代际变化的能力。我们分析了11个耦合模式比较项目第5阶段（CMIP5）模式的年代际预测。年代际预测在模拟的海冰范围内表现出较大的多模式分布，随着预测的海冰范围迅速偏离初始约束，一些模式与观测值偏差很大。年代际预测与观测海冰之间的异常相关性分析表明，在北极，对于大多数模式来说，具有显著预测能力的区域与提前时间的增加相关的范围越来越广。这种面积的扩大很大程度上是因为几乎所有的模式都能够预测观测到的北极海冰覆盖面积的减少。北太平洋海冰范围的预测能力优于北大西洋（特别是超前3 ~ 7年），但北大西洋超前6 ~ 8年的预测能力再次出现。与北极相比，南极海冰的年代际预测在任何时间尺度上都没有显示出广泛的预测能力，并且在显著预测能力的面积范围与提前时间的增加之间没有明显的改善。这可能是因为几乎所有的模型都预测了南极海冰覆盖的消退，这与观测结果相反。就北极而言，多模式综合平均值的预测能力优于大多数模式和更长时间尺度上的持续性预测，而南极的情况并非如此。总的来说，与未初始化的模拟相比，初始化的北极年代际预测显示出更高的预测能力，尽管这种改进在南极没有出现。
This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea ice. We analyze decadal hindcasts/predictions of 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Decadal hindcasts exhibit a large multi-model spread in the simulated sea ice extent, with some models deviating significantly from the observations as the predicted ice extent quickly drifts away from the initial constraint. The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Sea ice extent in the North Pacific has better predictive skill than that in the North Atlantic (particularly at a lead time of 3–7 years), but there is a re-emerging predictive skill in the North Atlantic at a lead time of 6–8 years. In contrast to the Arctic, Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales, and there is no obvious improvement linking the areal extent of significant predictive skill to lead time increase. This might be because nearly all the models predict a retreating Antarctic sea ice cover, opposite to the observations. For the Arctic, the predictive skill of the multi-model ensemble mean outperforms most models and the persistence prediction at longer timescales, which is not the case for the Antarctic. Overall, for the Arctic, initialized decadal hindcasts show improved predictive skill compared to uninitialized simulations, although this improvement is not present in the Antarctic.
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影响因子：
4.6
作者：
Goddard, L.;Kumar, A.;Delworth, T.
通讯作者：
Delworth, T.
影响因子：
3.5
作者：
Kwok, Ronald;Untersteiner, Norbert
通讯作者：
Untersteiner, Norbert
DOI：
10.1073/pnas.1422296112
发表时间：
2015-03
期刊：
Proceedings of the National Academy of Sciences
影响因子：
--
作者：
Rong‐Hua Zhang
通讯作者：
Rong‐Hua Zhang
影响因子：
5.2
作者：
Jinting Zhang;Rong‐Hua Zhang
通讯作者：
Jinting Zhang;Rong‐Hua Zhang
影响因子：
6.7
作者：
Day, J. J.;Hargreaves, J. C.;Abe-Ouchi, A.
通讯作者：
Abe-Ouchi, A.