Integrating archival analysis, observational data, and climate projections to assess extreme event impacts in Alaska

• Published in: Climatic Change
• Main Authors: Kettle, Nathan P., Walsh, John E., Heaney, Lindsey, Thoman, Richard L., Redilla, Kyle, Carroll, Lynneva
• Other Authors: Climate Program Office, USDA, National Institute of Food and Agriculture, Hatch Project
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Science and Business Media LLC 2020
• Subjects: Atmospheric Science; Global and Planetary Change; Arctic; Climate change; Nome; Alaska
• Online Access: http://dx.doi.org/10.1007/s10584-020-02907-y; http://link.springer.com/content/pdf/10.1007/s10584-020-02907-y.pdf; http://link.springer.com/article/10.1007/s10584-020-02907-y/fulltext.html

Abstract 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.