Understanding potential risks, vulnerabilities, and impacts to weather extremes and climate change are key information needs for coastal planners and managers in support of climate adaptation. Assessing historical trends and potential socio-economic impacts is especially difficult in the Arctic given limitations on availability of weather observations and historical impacts. This study utilizes a novel interdisciplinary approach that integrates archival analysis, observational data, and climate model downscaling to synthesize information on historical and projected impacts of extreme weather events in Nome, Alaska. Over 300 impacts (1990–2018) are identified based on analyses of the Nome Nugget newspaper articles and Storm Data entries. Historical impacts centered on transportation, community activities, and utilities. Analysis of observed and ERA5 reanalysis data indicates that impacts are frequently associated with high wind, extreme low temperatures, heavy snowfall events, and winter days above freezing. Downscaled output (2020–2100) from two climate models suggests that there will be changes in the frequency and timing of these extreme weather events. For example, extreme cold temperature is projected to decrease through the 2040s and then rarely occurs afterwards, and extreme wind events show little change before the 2070s. Significantly, our findings also reveal that not all weather-related extremes will change monotonically throughout the twenty-first century, such as extreme snowfall events that will increase through the 2030s before declining in the 2040s. The dynamical nature of projected changes in extreme events has implications for climate adaptation planning.

中文翻译：

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整合档案分析、观测数据和气候预测，以评估阿拉斯加极端事件的影响

了解对极端天气和气候变化的潜在风险、脆弱性和影响是沿海规划者和管理人员支持气候适应的关键信息需求。鉴于天气观测和历史影响的可用性有限，评估北极的历史趋势和潜在的社会经济影响尤其困难。这项研究采用了一种新的跨学科方法，该方法将档案分析、观测数据和气候模型降尺度相结合，以综合有关阿拉斯加诺姆极端天气事件的历史和预测影响的信息。根据对 Nome Nugget 报纸文章和 Storm Data 条目的分析，确定了 300 多种影响（1990-2018 年）。历史影响集中在交通、社区活动和公用事业上。对观测数据和 ERA5 再分析数据的分析表明，影响经常与大风、极端低温、大雪事件和冰点以上的冬季天数有关。两个气候模型的缩减输出（2020-2100）表明这些极端天气事件的频率和时间将会发生变化。例如，预计极端寒冷温度将在 2040 年代降低，之后很少发生，极端风事件在 2070 年代之前几乎没有变化。重要的是，我们的研究结果还表明，并非所有与天气相关的极端事件都会在整个 21 世纪单调变化，例如极端降雪事件将在 2030 年代增加，然后在 2040 年代下降。