Skillful seasonal forecasts of Arctic sea ice retreat and advance dates in a dynamical forecast system
Skillful seasonal forecasts of Arctic sea ice retreat and advance dates in a dynamical forecast system
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在动态预报系统中对北极海冰退缩和提前日期进行熟练的季节性预报
DOI：
10.1002/2016gl071396
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发表时间：
2016
影响因子：
5.2
通讯作者：
A. Tivy
中科院分区：
文献类型：
--
作者：
M. Sigmond;M. C. Reader;G. Flato;W. Merryfield;A. Tivy
对北极海冰进行熟练的季节性预报的需求正在迅速增加。利用大气-海洋-海冰耦合系统进行此类预测的技术最近才出现，之前的技能评估主要限于区域综合量。在这里，我们基于大量回顾性集合模型预测表明，动态预测系统可以对当地海冰消退和提前日期进行熟练的季节性预测，这些变量是广泛的最终用户非常感兴趣的。通常可以在比撤退日期（平均约 3 个月）更长的提前时间（平均约 5 个月）内巧妙地预测提前日期。退缩日期预报的技巧主要源于初始海冰异常的持续存在，而提前日期预报则受益于更长的时间尺度和更可预测的海洋温度变化。这些结果表明，进一步投资动态季节性预报系统的开发可能会带来显着的社会经济效益。
The need for skillful seasonal forecasts of Arctic sea ice is rapidly increasing. Technology to perform such forecasts with coupled atmosphere‐ocean‐sea ice systems has only recently become available, with previous skill evaluations mainly limited to area‐integrated quantities. Here we show, based on a large set of retrospective ensemble model forecasts, that a dynamical forecast system produces skillful seasonal forecasts of local sea ice retreat and advance dates—variables that are of great interest to a wide range of end users. Advance dates can generally be skillfully predicted at longer lead times (~5 months on average) than retreat dates (~3 months). The skill of retreat date forecasts mainly stems from persistence of initial sea ice anomalies, whereas advance date forecasts benefit from longer time scale and more predictable variability in ocean temperatures. These results suggest that further investments in the development of dynamical seasonal forecast systems may result in significant socioeconomic benefits.