Articles | Volume 12, issue 12
https://doi.org/10.5194/gmd-12-5029-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-12-5029-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
03 Dec 2019
Development and technical paper |
| 03 Dec 2019
| 03 Dec 2019
Improving the LPJmL4-SPITFIRE vegetation–fire model for South America using satellite data
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03,
14412 Potsdam, Germany
Humboldt Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
Matthias Forkel
Technische Universität Wien, Department of Geodesy and Geoinformation, Gusshausstr. 27–29, 1040 Vienna, Austria
Werner von Bloh
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03,
14412 Potsdam, Germany
Boris Sakschewski
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03,
14412 Potsdam, Germany
Manoel Cardoso
Instituto Nacional de Pesquisas Espaciais, Av. dos Astronautas, 1.758 – Jardim da Granja, 12227-010, São José dos Campos, São Paulo, Brazil
Mercedes Bustamante
Instituto de Ciências Biologicas, Universidade de Brasília, Campus Universitário Darcy Ribeiro – Asa Norte, 70910-900, Brasília, Brazil
Jürgen Kurths
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03,
14412 Potsdam, Germany
Humboldt Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
Kirsten Thonicke
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03,
14412 Potsdam, Germany
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Cited
15 citations as recorded by crossref.
- Fires in the South American Chaco, from dry forests to wetlands: response to climate depends on land cover R. San Martín et al. 10.1186/s42408-023-00212-4
- CM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model M. Drüke et al. 10.5194/gmd-14-4117-2021
- Exploration of the Contribution of Fire Carbon Emissions to PM2.5 and Their Influencing Factors in Laotian Tropical Rainforests Z. Su et al. 10.3390/rs14164052
- Global and Regional Trends and Drivers of Fire Under Climate Change M. Jones et al. 10.1029/2020RG000726
- Tree crown damage and its effects on forest carbon cycling in a tropical forest J. Needham et al. 10.1111/gcb.16318
- Assessing wildfire activity and forest loss in protected areas of the Amazon basin E. Da Ponte et al. 10.1016/j.apgeog.2023.102970
- Earth Observation for agricultural drought monitoring in the Pannonian Basin (southeastern Europe): current state and future directions L. Crocetti et al. 10.1007/s10113-020-01710-w
- Mapping South America’s Drylands through Remote Sensing—A Review of the Methodological Trends and Current Challenges K. Ganem et al. 10.3390/rs14030736
- Climate-induced hysteresis of the tropical forest in a fire-enabled Earth system model M. Drüke et al. 10.1140/epjs/s11734-021-00157-2
- Physically constrained generative adversarial networks for improving precipitation fields from Earth system models P. Hess et al. 10.1038/s42256-022-00540-1
- Earth beyond six of nine planetary boundaries K. Richardson et al. 10.1126/sciadv.adh2458
- Fire may prevent future Amazon forest recovery after large-scale deforestation M. Drüke et al. 10.1038/s43247-023-00911-5
- Terrestrial carbon dynamics in an era of increasing wildfire T. Hudiburg et al. 10.1038/s41558-023-01881-4
- Integration of a Deep‐Learning‐Based Fire Model Into a Global Land Surface Model R. Son et al. 10.1029/2023MS003710
- Responses of Plant Biomass in the Brazilian Savanna to Frequent Fires L. Gomes et al. 10.3389/ffgc.2020.507710
14 citations as recorded by crossref.
- Fires in the South American Chaco, from dry forests to wetlands: response to climate depends on land cover R. San Martín et al. 10.1186/s42408-023-00212-4
- CM2Mc-LPJmL v1.0: biophysical coupling of a process-based dynamic vegetation model with managed land to a general circulation model M. Drüke et al. 10.5194/gmd-14-4117-2021
- Exploration of the Contribution of Fire Carbon Emissions to PM2.5 and Their Influencing Factors in Laotian Tropical Rainforests Z. Su et al. 10.3390/rs14164052
- Global and Regional Trends and Drivers of Fire Under Climate Change M. Jones et al. 10.1029/2020RG000726
- Tree crown damage and its effects on forest carbon cycling in a tropical forest J. Needham et al. 10.1111/gcb.16318
- Assessing wildfire activity and forest loss in protected areas of the Amazon basin E. Da Ponte et al. 10.1016/j.apgeog.2023.102970
- Earth Observation for agricultural drought monitoring in the Pannonian Basin (southeastern Europe): current state and future directions L. Crocetti et al. 10.1007/s10113-020-01710-w
- Mapping South America’s Drylands through Remote Sensing—A Review of the Methodological Trends and Current Challenges K. Ganem et al. 10.3390/rs14030736
- Climate-induced hysteresis of the tropical forest in a fire-enabled Earth system model M. Drüke et al. 10.1140/epjs/s11734-021-00157-2
- Physically constrained generative adversarial networks for improving precipitation fields from Earth system models P. Hess et al. 10.1038/s42256-022-00540-1
- Earth beyond six of nine planetary boundaries K. Richardson et al. 10.1126/sciadv.adh2458
- Fire may prevent future Amazon forest recovery after large-scale deforestation M. Drüke et al. 10.1038/s43247-023-00911-5
- Terrestrial carbon dynamics in an era of increasing wildfire T. Hudiburg et al. 10.1038/s41558-023-01881-4
- Integration of a Deep‐Learning‐Based Fire Model Into a Global Land Surface Model R. Son et al. 10.1029/2023MS003710
1 citations as recorded by crossref.
Latest update: 15 Apr 2024
Short summary
This work shows the successful application of a systematic model–data integration setup, as well as the implementation of a new fire danger formulation, in order to optimize a process-based fire-enabled dynamic global vegetation model. We have demonstrated a major improvement in the fire representation within LPJmL4-SPITFIRE in terms of the spatial pattern and the interannual variability of burned area in South America as well as in the modelling of biomass and the distribution of plant types.
This work shows the successful application of a systematic model–data integration setup, as...
Special issue