Articles | Volume 12, issue 5
https://doi.org/10.5194/gmd-12-2033-2019
https://doi.org/10.5194/gmd-12-2033-2019
Development and technical paper
 | 
24 May 2019
Development and technical paper |  | 24 May 2019

Calculating the turbulent fluxes in the atmospheric surface layer with neural networks

Lukas Hubert Leufen and Gerd Schädler

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Gerd Schädler on behalf of the Authors (31 Jan 2019)  Manuscript 
ED: Reconsider after major revisions (13 Feb 2019) by Chiel van Heerwaarden
AR by Gerd Schädler on behalf of the Authors (15 Feb 2019)  Manuscript 
ED: Referee Nomination & Report Request started (15 Feb 2019) by Chiel van Heerwaarden
RR by Anonymous Referee #1 (04 Mar 2019)
ED: Publish subject to minor revisions (review by editor) (18 Mar 2019) by Chiel van Heerwaarden
AR by Gerd Schädler on behalf of the Authors (21 Mar 2019)  Manuscript 
ED: Publish as is (17 Apr 2019) by Chiel van Heerwaarden
AR by Gerd Schädler on behalf of the Authors (30 Apr 2019)  Manuscript 
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Short summary
An artificial neural network was used to calculate the scaling quantities u* and T*. To train and test the network, a large set of worldwide observations was used. Extensive sensitivity studies showed that a relatively small 6–3–2 network with six input parameters and one hidden layer yields satisfying results. An implementation of this network in a stand-alone land surface model showed that the neural network gives results equivalent to and sometimes better than the standard implementation.