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GMD | Articles | Volume 12, issue 1
Geosci. Model Dev., 12, 89-110, 2019
https://doi.org/10.5194/gmd-12-89-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 12, 89-110, 2019
https://doi.org/10.5194/gmd-12-89-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 04 Jan 2019

Model description paper | 04 Jan 2019

Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations

Sergey Venevsky et al.
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Cited articles  
Albini, F. A.: Estimating wildfire behavior and effects, General Technical Report, INT-GTR-30,USDA Forest Service, Intermountain Forest and Range Experiment Station, Ogden Utah, 92 pp., available at: http://www.treesearch.fs.fed.us/pubs/29574 (last access: 26 December 2018), 1976. 
Allen, D. J. and Pickering, K. E.: Evaluation of lightning flash rate parameterizations for use in a global chemical transport model, J. Geophys. Res.-Atmos., 107, ACH 15-11–ACH 15-21, https://doi.org/10.1029/2002jd002066, 2002. 
Andela, N., Morton, D. C., Giglio, L., Paugam, R., Chen, Y., Hantson, S., van der Werf, G. R., and Randerson, J. T.: The Global Fire Atlas of individual fire size, duration, speed, and direction, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-89, in review, 2018. 
Anderson, K.: A model to predict lightning-caused fire occurrences, Int. J. Wildland Fire, 11, 163–172, https://doi.org/10.1071/WF02001, 2002. 
Andreae, M. O. and Merlet, P.: Emission of trace gases and aerosols from biomass burning, Global Biogeochem. Cy., 15, 955–966, https://doi.org/10.1029/2000GB001382, 2001. 
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We present SEVER-FIRE (v1.0), incorporated into the SEVER DGVM. One of the major focuses of SEVER-FIRE is an implementation of the pyrogenic behavior of humans (timing of their activities and their willingness and necessity to ignite or suppress fire), related to socioeconomic and demographic conditions in a geographical domain of the model application. Unlike other DGVM- and ESM-based global fire models, we do not use any satellite-derived assumptions in equations of fire model development.
We present SEVER-FIRE (v1.0), incorporated into the SEVER DGVM. One of the major focuses of...
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