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Predictability of Arctic sea ice on weather time scales

机译:北极海冰在天气时间尺度上的可预测性

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摘要

The field of Arctic sea ice prediction on “weather time scales” is still in its infancy with little existing understanding of the limits of predictability. This is especially true for sea ice deformation along so-called Linear Kinematic Features (LKFs) including leads that are relevant for marine operations. Here the potential predictability of the sea ice pack in the wintertime Arctic up to ten days ahead is determined, exploiting the fact that sea ice-ocean models start to show skill at representing sea ice deformation at high spatial resolutions. Results are based on ensemble simulations with a high-resolution sea ice-ocean model driven by atmospheric ensemble forecasts. The predictability of LKFs as measured by different metrics drops quickly, with predictability being almost completely lost after 4–8 days. In contrast, quantities such as sea ice concentration or the location of the ice edge retain high levels of predictability throughout the full 10-day forecast period. It is argued that the rapid error growth for LKFs is mainly due to the chaotic behaviour of the atmosphere associated with the low predictability of near surface wind divergence and vorticity; initial condition uncertainty for ice thickness is found to be of minor importance as long as LKFs are initialized at the right locations.
机译:北极海冰在“天气时间尺度”上的预测领域仍处于起步阶段,对可预测性限制的现有了解很少。对于海冰沿所谓的线性运动学特征(LKF)变形尤其如此,其中包括与海洋作业相关的导线。在此,利用海冰-海洋模型开始显示出以高空间分辨率表示海冰变形的技能的事实,确定了北极冬季最多10天之前海冰袋的潜在可预测性。结果是基于大气模拟的高分辨率海冰海洋模型的整体模拟得出的。用不同的指标测量的LKFs的可预测性迅速下降,在4–8天后几乎完全丧失了可预测性。相反,在整个10天的预测期内,诸如海冰浓度或冰缘位置之类的数量仍保持较高的可预测性。有人认为,LKFs的快速误差增长主要是由于大气的混沌行为与近地表风的发散性和涡度的低可预测性有关。只要将LKFs初始化在正确的位置,冰厚度的初始条件不确定性就显得次要。

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