September Arctic Sea Ice minimum prediction – a new skillful statistical approach
September Arctic Sea Ice minimum prediction – a new skillful statistical approach
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九月北极海冰最小值预测——一种新的熟练统计方法
DOI：
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Gerrit Lohmann
中科院分区：
文献类型：
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作者：
M. Ionita;K. Grosfeld;P. Scholz;R. Treffeisen;Gerrit Lohmann
抽象的。两极地区的海冰是表达全球气候变化及其极地放大的重要指标。因此，人们对海冰覆盖范围、变化性和长期变化产生了广泛的兴趣。然而，其可预测性很复杂，并且取决于各种大气和海洋参数。为了深入了解海冰演化的每月/季节性信号的潜在发展，我们开发了一个基于海洋和不同大气变量的稳健统计模型，以计算每月时间尺度上的九月海冰范围（SSIE）的估计值。尽管之前的月度/季节性 SSIE 预测统计尝试显示技能相对较低，但当去除趋势后，我们在此显示，根据前几个月的大气和海洋条件，9 月海冰范围具有较高的预测技能，最多可提前 4 个月。我们的统计模型巧妙地捕捉了SSIE的年际变化，并可以提供一个有价值的工具来识别相关区域和大气参数，这些区域和大气参数对于北极海冰的发展非常重要，并可以在全球耦合气候模型中检测敏感和关键区域，重点关注海冰的形成。
Abstract. Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice coverage, variability and long term change. However, its predictability is complex and it depends on various atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on oceanic and different atmospheric variables to calculate an estimate of the September sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' atmospheric and oceanic conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.
影响因子：
6.7
作者：
Day, J. J.;Hargreaves, J. C.;Abe-Ouchi, A.
通讯作者：
Abe-Ouchi, A.
利用被动微波海冰观测对九月北极海冰范围进行熟练的春季预报
DOI：
10.1002/2016ef000495
发表时间：
2017
期刊：
Earth's Future
影响因子：
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作者：
Petty A
通讯作者：
Petty A