%0 Journal Article %1 Hantson2016Status %A Hantson, S. %A Arneth, A. %A Harrison, S. P. %A Kelley, D. I. %A Prentice, I. C. %A Rabin, S. S. %A Archibald, S. %A Mouillot, F. %A Arnold, S. R. %A Artaxo, P. %A Bachelet, D. %A Ciais, P. %A Forrest, M. %A Friedlingstein, P. %A Hickler, T. %A Kaplan, J. O. %A Kloster, S. %A Knorr, W. %A Lasslop, G. %A Li, F. %A Mangeon, S. %A Melton, J. R. %A Meyn, A. %A Sitch, S. %A Spessa, A. %A van der Werf, G. R. %A Voulgarakis, A. %A Yue, C. %D 2016 %J Biogeosciences Discussions %K review climatechange model fire impacts %P 1--30 %R 10.5194/bg-2016-17 %T The status and challenge of global fire modelling %U http://dx.doi.org/10.5194/bg-2016-17 %X Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project – FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.

@article{Hantson2016Status, abstract = {Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project – FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Hantson, S. and Arneth, A. and Harrison, S. P. and Kelley, D. I. and Prentice, I. C. and Rabin, S. S. and Archibald, S. and Mouillot, F. and Arnold, S. R. and Artaxo, P. and Bachelet, D. and Ciais, P. and Forrest, M. and Friedlingstein, P. and Hickler, T. and Kaplan, J. O. and Kloster, S. and Knorr, W. and Lasslop, G. and Li, F. and Mangeon, S. and Melton, J. R. and Meyn, A. and Sitch, S. and Spessa, A. and van der Werf, G. R. and Voulgarakis, A. and Yue, C.}, biburl = {https://www.bibsonomy.org/bibtex/23182516eeb45079e8acc27fbb3eeadfb/pbett}, citeulike-article-id = {13920895}, citeulike-linkout-0 = {http://dx.doi.org/10.5194/bg-2016-17}, day = 25, doi = {10.5194/bg-2016-17}, interhash = {a1fbef7a26b3db315bb930ba70235b57}, intrahash = {3182516eeb45079e8acc27fbb3eeadfb}, issn = {1810-6285}, journal = {Biogeosciences Discussions}, keywords = {review climatechange model fire impacts}, month = jan, pages = {1--30}, posted-at = {2016-01-28 09:55:32}, priority = {2}, timestamp = {2018-06-22T18:36:02.000+0200}, title = {The status and challenge of global fire modelling}, url = {http://dx.doi.org/10.5194/bg-2016-17}, year = 2016 }