Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks
The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of th...
Main Authors: | S. C. Pryor, R. C. Sullivan, J. T. Schoof |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-12-01
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Series: | Atmospheric Chemistry and Physics |
Online Access: | https://www.atmos-chem-phys.net/17/14457/2017/acp-17-14457-2017.pdf |
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