Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 4443-4476, 2017
https://doi.org/10.5194/gmd-10-4443-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model description paper
06 Dec 2017
A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)
Matthias Forkel et al.
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Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
SC1: 'Executive Editor Comment on "Identifying required model structures to predict global fire activity from satellite and climate data"', Astrid Kerkweg, 03 Jan 2017 Printer-friendly Version 
AC1: 'Reply to the Short Comment by A. Kerkweg', Matthias Forkel, 04 Jan 2017 Printer-friendly Version 
SC2: 'Reply to reply with respect to Executive Editor comment', Astrid Kerkweg, 09 Jan 2017 Printer-friendly Version 
 
RC1: 'Reviewer comments', Anonymous Referee #1, 13 Jul 2017 Printer-friendly Version 
AC2: 'Response to Anonymous Referee #1', Matthias Forkel, 13 Jul 2017 Printer-friendly Version 
RC2: 'Include that Figure 2 (parameter ranking for random forest) in the final MS', Anonymous Referee #1, 13 Jul 2017 Printer-friendly Version 
 
RC3: 'Review on Forkel et al.', Anonymous Referee #2, 31 Aug 2017 Printer-friendly Version 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Matthias Forkel on behalf of the Authors (27 Sep 2017)  Author's response  Manuscript
ED: Referee Nomination & Report Request started (06 Oct 2017) by Gerd A. Folberth
RR by Gerd A. Folberth (20 Oct 2017)  
ED: Publish subject to technical corrections (20 Oct 2017) by Gerd A. Folberth  
CC BY 4.0
Publications Copernicus
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Short summary
Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how fires should be accurately represented in global vegetation models. We introduce here a new flexible data-driven fire modelling approach that allows us to explore sensitivities of burned areas to satellite and climate datasets. Our results suggest combining observations with data-driven and process-oriented fire models to better understand the role of fires in the Earth system.
Wildfires affect infrastructures, vegetation, and the atmosphere. However, it is unclear how...
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