Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.154 IF 5.154
  • IF 5-year value: 5.697 IF 5-year
    5.697
  • CiteScore value: 5.56 CiteScore
    5.56
  • SNIP value: 1.761 SNIP 1.761
  • IPP value: 5.30 IPP 5.30
  • SJR value: 3.164 SJR 3.164
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 59 Scimago H
    index 59
  • h5-index value: 49 h5-index 49
Volume 10, issue 12
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.
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

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.
Related authors  
Improving the LPJmL4-SPITFIRE vegetation-fire model for South America using satellite data
Markus Drüke, Matthias Forkel, Werner von Bloh, Boris Sakschewski, Manoel Cardoso, Mercedes Bustamante, Jürgen Kurths, and Kirsten Thonicke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-92,https://doi.org/10.5194/gmd-2019-92, 2019
Revised manuscript accepted for GMD
Short summary
The Global Long-term Microwave Vegetation Optical Depth Climate Archive VODCA
Leander Moesinger, Wouter Dorigo, Richard de Jeu, Robin van der Schalie, Tracy Scanlon, Irene Teubner, and Matthias Forkel
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-42,https://doi.org/10.5194/essd-2019-42, 2019
Revised manuscript under review for ESSD
Short summary
Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models
Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
Biogeosciences, 16, 57–76, https://doi.org/10.5194/bg-16-57-2019,https://doi.org/10.5194/bg-16-57-2019, 2019
Short summary
LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description
Sibyll Schaphoff, Werner von Bloh, Anja Rammig, Kirsten Thonicke, Hester Biemans, Matthias Forkel, Dieter Gerten, Jens Heinke, Jonas Jägermeyr, Jürgen Knauer, Fanny Langerwisch, Wolfgang Lucht, Christoph Müller, Susanne Rolinski, and Katharina Waha
Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018,https://doi.org/10.5194/gmd-11-1343-2018, 2018
Short summary
LPJmL4 – a dynamic global vegetation model with managed land – Part 2: Model evaluation
Sibyll Schaphoff, Matthias Forkel, Christoph Müller, Jürgen Knauer, Werner von Bloh, Dieter Gerten, Jonas Jägermeyr, Wolfgang Lucht, Anja Rammig, Kirsten Thonicke, and Katharina Waha
Geosci. Model Dev., 11, 1377–1403, https://doi.org/10.5194/gmd-11-1377-2018,https://doi.org/10.5194/gmd-11-1377-2018, 2018
Short summary
Related subject area  
Biogeosciences
Evaluation of leaf-level optical properties employed in land surface models
Titta Majasalmi and Ryan M. Bright
Geosci. Model Dev., 12, 3923–3938, https://doi.org/10.5194/gmd-12-3923-2019,https://doi.org/10.5194/gmd-12-3923-2019, 2019
Short summary
ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions – Part 1: Rationale, model description, and simulation protocol
Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 12, 3503–3521, https://doi.org/10.5194/gmd-12-3503-2019,https://doi.org/10.5194/gmd-12-3503-2019, 2019
Short summary
Modelling northern peatland area and carbon dynamics since the Holocene with the ORCHIDEE-PEAT land surface model (SVN r5488)
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Shushi Peng, Gerhard Krinner, Ardalan Tootchi, Agnès Ducharne, and Adam Hastie
Geosci. Model Dev., 12, 2961–2982, https://doi.org/10.5194/gmd-12-2961-2019,https://doi.org/10.5194/gmd-12-2961-2019, 2019
Short summary
Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage)
Femke Lutz, Tobias Herzfeld, Jens Heinke, Susanne Rolinski, Sibyll Schaphoff, Werner von Bloh, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 12, 2419–2440, https://doi.org/10.5194/gmd-12-2419-2019,https://doi.org/10.5194/gmd-12-2419-2019, 2019
Short summary
Description and validation of an intermediate complexity model for ecosystem photosynthesis and evapotranspiration: ACM-GPP-ETv1
Thomas Luke Smallman and Mathew Williams
Geosci. Model Dev., 12, 2227–2253, https://doi.org/10.5194/gmd-12-2227-2019,https://doi.org/10.5194/gmd-12-2227-2019, 2019
Short summary
Cited articles  
Albergel, C., Dorigo, W., Balsamo, G., Muñoz-Sabater, J., de Rosnay, P., Isaksen, L., Brocca, L., de Jeu, R., and Wagner, W.: Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses, Remote Sens. Environ., 138, 77–89, https://doi.org/10.1016/j.rse.2013.07.009, 2013.
Aldersley, A., Murray, S. J., and Cornell, S. E.: Global and regional analysis of climate and human drivers of wildfire, Sci. Total Environ., 409, 3472–3481, https://doi.org/10.1016/j.scitotenv.2011.05.032, 2011.
Alonso-Canas, I. and Chuvieco, E.: Global burned area mapping from ENVISAT-MERIS and MODIS active fire data, Remote Sens. Environ., 163, 140–152, https://doi.org/10.1016/j.rse.2015.03.011, 2015.
Andela, N. and van der Werf, G. R.: Recent trends in African fires driven by cropland expansion and El Nino to La Nina transition, Nat. Clim. Change, 4, 791–795, https://doi.org/10.1038/nclimate2313, 2014.
Andela, N., Liu, Y. Y., van Dijk, A. I. J. M., de Jeu, R. A. M., and McVicar, T. R.: Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data, Biogeosciences, 10, 6657–6676, https://doi.org/10.5194/bg-10-6657-2013, 2013.
Publications Copernicus
Download
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...
Citation