Articles | Volume 11, issue 2
https://doi.org/10.5194/gmd-11-815-2018
https://doi.org/10.5194/gmd-11-815-2018
Model description paper
 | 
02 Mar 2018
Model description paper |  | 02 Mar 2018

A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1

Sam S. Rabin, Daniel S. Ward, Sergey L. Malyshev, Brian I. Magi, Elena Shevliakova, and Stephen W. Pacala

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Cited articles

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.
Archibald, S., Roy, D. P., van Wilgen, B. W., and Scholes, R.: What limits fire? An examination of drivers of burnt area in Southern Africa, Glob. Change Biol., 15, 613–630, https://doi.org/10.1111/j.1365-2486.2008.01754.x, 2009.
Archibald, S., Lehmann, C. E. R., Gomez-Dans, J. L., and Bradstock, R. A.: Defining pyromes and global syndromes of fire regimes, P. Natl. Acad. Sci. USA, 110, 6442–6447, https://doi.org/10.1073/pnas.1211466110, 2013.
Arora, V. K. and Boer, G. J.: Fire as an interactive component of dynamic vegetation models, J. Geophys. Res., 110, G02008, https://doi.org/10.1029/2005JG000042, 2005.
Balch, J. K., Nepstad, D. C., Brando, P. M., Curran, L. M., Portela, O., de Carvalho, O., and Lefebvre, P.: Negative fire feedback in a transitional forest of southeastern Amazonia, Glob. Change Biol., 14, 2276–2287, https://doi.org/10.1111/j.1365-2486.2008.01655.x, 2008.
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Short summary
This paper describes a new fire model that for the first time simulates how fire is used on cropland and pasture in the modern day, as imposed using a recently developed dataset. A non-agricultural fire module is fit algorithmically against non-agricultural burned area. Fitting improves performance and the general global pattern of fire is represented, but some gaps remain. The novel separation of agricultural burning from other fire may necessitate new design thinking in the future.