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Climatological Teleconnections with Wind Energy in a Midcontinental Region

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  • 1 Department of Geography, Environment and Society, University of Minnesota, Minneapolis, Minnesota
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Abstract

Variations in wind resources affect the reliability and feasibility of wind energy. At longer time scales, modes within the climate system and externally forced variability become important as the decadelong lifetimes of wind installations and upfront investment costs are considered. Understanding the influence of teleconnections may yield important insights for skillful seasonal predictions. In this study, several modes of variability, including the Arctic Oscillation (AO), El Niño–Southern Oscillation (ENSO), and the global surface solar flux, are assessed for their influence on wind energy anomalies in the upper Midwest (40°–52°N, 87°–105°W). Monthly wind energy is calculated using extrapolated 80-m wind fields from reanalysis data for the period 1980–2018. A multiple linear regression analysis is conducted for the monthly turbine energy output anomalies (TEOA) against the effects of synoptic patterns and pressure gradients, as well as the teleconnection indices, for each grid cell and season, yielding information on the spatial and temporal variations in influence throughout the region. The regression model indicated that each of the factors had significant influences on wind energy, although the effects varied spatially and by season. Periods of extremely low production are often embedded in prolonged declines over several months that were the result of a combination of synoptic variability and significant phases of the teleconnections such as large El Niño events, negative AO episodes, and volcanically induced reductions in surface solar flux. Monthly TEOA are found to vary by up to 37%, amounting to ±130 MW h and tens of thousands of dollars per turbine.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JAMC-D-20-0203.s1.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jacob Coburn, cobur018@umn.edu

Abstract

Variations in wind resources affect the reliability and feasibility of wind energy. At longer time scales, modes within the climate system and externally forced variability become important as the decadelong lifetimes of wind installations and upfront investment costs are considered. Understanding the influence of teleconnections may yield important insights for skillful seasonal predictions. In this study, several modes of variability, including the Arctic Oscillation (AO), El Niño–Southern Oscillation (ENSO), and the global surface solar flux, are assessed for their influence on wind energy anomalies in the upper Midwest (40°–52°N, 87°–105°W). Monthly wind energy is calculated using extrapolated 80-m wind fields from reanalysis data for the period 1980–2018. A multiple linear regression analysis is conducted for the monthly turbine energy output anomalies (TEOA) against the effects of synoptic patterns and pressure gradients, as well as the teleconnection indices, for each grid cell and season, yielding information on the spatial and temporal variations in influence throughout the region. The regression model indicated that each of the factors had significant influences on wind energy, although the effects varied spatially and by season. Periods of extremely low production are often embedded in prolonged declines over several months that were the result of a combination of synoptic variability and significant phases of the teleconnections such as large El Niño events, negative AO episodes, and volcanically induced reductions in surface solar flux. Monthly TEOA are found to vary by up to 37%, amounting to ±130 MW h and tens of thousands of dollars per turbine.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JAMC-D-20-0203.s1.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Jacob Coburn, cobur018@umn.edu

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