Frontiers in Big Data
Frontiers Research Foundation
NSF, Division of Atmospheric and Geospace Sciences (AGS) 1903721
NSF, Division of Atmospheric and Geospace Sciences (AGS)
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This work is licensed under a Creative Commons Attribution 4.0 License.
Anomalously cold winters with extreme storms strain natural gas (NG) markets due to heightened demand for heating and electricity generation. While extended weather forecasting has become an indicator for NG management, seasonal (2–3 month) prediction could mitigate the impact of extreme winters on the NG market for consumers and industry. Interrelated climate patterns of ocean and atmospheric circulation anomalies exhibit characteristics useful for developing effective seasonal outlooks of NG storage and consumption due to their influence on the persistence and intensity of extreme winter weather in North America. This study explores the connection between the Pacific-North American climate systems and the NG market in the U.S., connecting macro-scale oceanic and atmospheric processes to regional NG storage and consumption. Western Pacific sea surface temperatures and atmospheric pressure patterns describe significant variation in seasonal NG storage and consumption. Prediction of these coupled climate processes is useful for estimating NG storage and consumption; this could facilitate economic adaptation toward extreme winter weather conditions. Understanding the implicated impact of climate variability on NG is a crucial step toward economic adaptation to climate change.
Stuivenvolt-Allen J and Wang SS-Y (2019) Data Mining Climate Variability as an Indicator of U.S. Natural Gas. Front. Big Data 2:20. doi: 10.3389/fdata.2019.00020