Examining the Climatology of Shortwave Radiation in the Northeastern United States

Examining the Climatology of Shortwave Radiation in the Northeastern United States AbstractAs demand for renewable energy grows, so does the need for an improved understanding of renewable energy sources. Paradoxically, the climate change mitigation strategy of fossil fuel divestment is in itself subject to shifts in weather patterns resulting from climate change. This is particularly true with solar power which depends on local cloud cover. However, because observed shortwave radiation data usually span a decade or less, persistent long-term trends may not be identified. A simple linear regression model is created here using diurnal temperature range (DTR) during 2002 – 2015 as a predictor variable to estimate long-term shortwave radiation (SR) values in the Northeastern U.S. Using an extended DTR dataset, SR values are computed for 1956 – 2015. Statistically significant decreases in shortwave radiation are identified which are dominated by changes during the summer months. Because this coincides with the season of greatest insolation and the highest potential for energy production, financial implications may be large for the solar energy industry if such trends persist into the future. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Meteorology and Climatology American Meteorological Society

Examining the Climatology of Shortwave Radiation in the Northeastern United States

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1558-8432
D.O.I.
10.1175/JAMC-D-16-0420.1
Publisher site
See Article on Publisher Site

Abstract

AbstractAs demand for renewable energy grows, so does the need for an improved understanding of renewable energy sources. Paradoxically, the climate change mitigation strategy of fossil fuel divestment is in itself subject to shifts in weather patterns resulting from climate change. This is particularly true with solar power which depends on local cloud cover. However, because observed shortwave radiation data usually span a decade or less, persistent long-term trends may not be identified. A simple linear regression model is created here using diurnal temperature range (DTR) during 2002 – 2015 as a predictor variable to estimate long-term shortwave radiation (SR) values in the Northeastern U.S. Using an extended DTR dataset, SR values are computed for 1956 – 2015. Statistically significant decreases in shortwave radiation are identified which are dominated by changes during the summer months. Because this coincides with the season of greatest insolation and the highest potential for energy production, financial implications may be large for the solar energy industry if such trends persist into the future.

Journal

Journal of Applied Meteorology and ClimatologyAmerican Meteorological Society

Published: Aug 23, 2017

References

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