Articles | Volume 17, issue 23
Research article
06 Dec 2017
Research article |  | 06 Dec 2017

Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

Sara C. Pryor, Ryan C. Sullivan, and Justin T. Schoof


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Short summary
The air temperature and water vapor content are increasing globally due to the increased concentration of "heat-trapping" (greenhouse) gases. But not all regions are warming at the same rate. This analysis is designed to improve understanding of the causes of recent trends and year-to-year variability in summertime heat indices over the eastern US and to present a new model that can be used to make projections of future events that may cause loss of life and/or decreased human well-being.
Final-revised paper