The rapid decrease in Arctic sea ice cover and thickness not only has a linkage with extreme weather in the mid-latitudes but also brings more opportunities for Arctic shipping routes and polar resource exploration, both of which motivate us to further understand causes of sea-ice variations and to obtain more accurate estimates of sea-ice cover in the future. Here, a novel data-driven method, the causal effect networks algorithm, is applied to identify the direct precursors of September sea-ice extent covering the Northern Sea Route and Transpolar Sea Route at different lead times so that statistical models can be constructed for sea-ice prediction. The whole study area was also divided into two parts: the northern region covered by multiyear ice and the southern region covered by seasonal ice. The forecast models of September sea-ice extent in the whole study area (TSIE) and southern region (SSIE) at lead times of 1–4 months can explain over 65% and 79% of the variances, respectively, but the forecast skill of sea-ice extent in the northern region (NSIE) is limited at a lead time of 1 month. At lead times of 1–4 months, local sea-ice concentration and sea-ice thickness have a larger influence on September TSIE and SSIE than other teleconnection factors. When the lead time is more than 4 months, the surface meridional wind anomaly from northern Europe in the preceding autumn or early winter is dominant for September TSIE variations but is comparable to thermodynamic factors for NSIE and SSIE. We suggest that this study provides a complementary approach for predicting regional sea ice and is helpful in evaluating and improving climate models.

中文翻译：

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使用熟练的统计模型来预测9月海冰覆盖北极的运输路线

北极海冰覆盖率和厚度的迅速减少，不仅与中纬度地区的极端天气有关，而且为北极航运路线和极地资源勘探带来了更多机会，这两者都促使我们进一步了解海冰的成因变化，并在将来获得更准确的海冰覆盖率估算。在这里，一种新颖的数据驱动方法，即因果效应网络算法，被用于识别覆盖不同交货时间的9月海冰范围的直接前兆，涵盖北海路线和跨极海路线，从而可以构建海上统计模型冰预测。整个研究区域也分为两个部分：北部地区被多年冰覆盖，南部地区被季节性冰覆盖。整个研究区（TSIE）和南部地区（SSIE）9月海冰范围的预报模型在交货期为1-4个月时可以分别解释超过65％和79％的差异，但是北部地区的海冰范围（NSIE）的提前期为1个月。在1-4个月的交付周期中，本地海冰浓度和海冰厚度对9月TSIE和SSIE的影响大于其他遥相关因素。当交货期超过4个月时，9月TSIE的变化主要来自于前秋或初冬的北欧地表子午风异常，但与NSIE和SSIE的热力学因子相当。