Articles | Volume 17, issue 23
https://doi.org/10.5194/acp-17-14457-2017
https://doi.org/10.5194/acp-17-14457-2017
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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Cited articles

Al Bitar, A., Mialon, A., Kerr, Y. H., Cabot, F., Richaume, P., Jacquette, E., Quesney, A., Mahmoodi, A., Tarot, S., Parrens, M., Al-Yaari, A., Pellarin, T., Rodriguez-Fernandez, N., and Wigneron, J.-P.: The global SMOS Level 3 daily soil moisture and brightness temperature maps, Earth Syst. Sci. Data, 9, 293–315, https://doi.org/10.5194/essd-9-293-2017, 2017.
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Anderson, G. B. and Bell, M. L.: Heat waves in the United States: mortality risk during heat waves and effect modification by heat wave characteristics in 43 US communities, Environ. Health Persp., 119, 210–218, 2011.
Bentley, M. L. and Stallins, J. A.: Synoptic evolution of Midwestern US extreme dew point events, Int. J. Climatol., 28, 1213–1225, 2008.
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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.
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