Articles | Volume 17, issue 23
https://doi.org/10.5194/acp-17-14457-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks
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- Final revised paper (published on 06 Dec 2017)
- Preprint (discussion started on 13 Jul 2017)
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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- RC1: 'Referee 1 comments', Anonymous Referee #2, 30 Jul 2017
- RC2: 'Review for the manuscript “Modeling the contribution of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks” by Pryor et al.', Anonymous Referee #3, 23 Oct 2017
Peer-review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Sara C. Pryor on behalf of the Authors (01 Nov 2017)
Author's response
Manuscript
ED: Publish as is (04 Nov 2017) by Qiang Fu
AR by Sara C. Pryor on behalf of the Authors (05 Nov 2017)