暴风雪
环境科学
风暴
雪
极端天气
气象学
外推法
气候学
极寒
寒冷的天气
相关系数
气候变化
数值天气预报
地理
数学
统计
地质学
海洋学
作者
Melissa Allen‐Dumas,Sangkeun Lee,Supriya Chinthavali
标识
DOI:10.1109/bigdata55660.2022.10020733
摘要
The significance of the impact of weather on the electric grid has grown as climate change continues to increase the frequency and intensity of extreme weather events. In recent years (2021-2022) in particular, extreme winter weather has affected the grid in locations in the US rarely exposed to extreme low temperatures, snow and icing conditions. Here we analyze the correlation between cold weather meteorological variables and electricity outages during two large winter storm events, Uri (February 2021) and Landon (February 2022) using Random Forest machine learning and Pearson’s correlation coefficient. Our geographical focus across the two storms is the state of Texas. Extrapolation of the method to winter weather impacts over other years and additional locations is proposed.
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