Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE – Part 1: simulating historical global burned area and fire regimes

Abstract. Fire is an important global ecological process that influences the distribution of biomes, with consequences for carbon, water, and energy budgets. Therefore it is impossible to appropriately model the history and future of the terrestrial ecosystems and the climate system without including fire. This study incorporates the process-based prognostic fire module SPITFIRE into the global vegetation model ORCHIDEE, which was then used to simulate burned area over the 20th century. Special attention was paid to the evaluation of other fire regime indicators such as seasonality, fire size and fire length, next to burned area. For 2001–2006, the simulated global spatial extent of fire agrees well with that given by satellite-derived burned area data sets (L3JRC, GLOBCARBON, GFED3.1), and 76–92% of the global burned area is simulated as collocated between the model and observation, depending on which data set is used for comparison. The simulated global mean annual burned area is 346 Mha yr−1, which falls within the range of 287–384 Mha yr−1 as given by the three observation data sets; and is close to the 344 Mha yr−1 by the GFED3.1 data when crop fires are excluded. The simulated long-term trend and variation of burned area agree best with the observation data in regions where fire is mainly driven by climate variation, such as boreal Russia (1930–2009), along with Canada and US Alaska (1950–2009). At the global scale, the simulated decadal fire variation over the 20th century is only in moderate agreement with the historical reconstruction, possibly because of the uncertainties of past estimates, and because land-use change fires and fire suppression are not explicitly included in the model. Over the globe, the size of large fires (the 95th quantile fire size) is underestimated by the model for the regions of high fire frequency, compared with fire patch data as reconstructed from MODIS 500 m burned area data. Two case studies of fire size distribution in Canada and US Alaska, and southern Africa indicate that both number and size of large fires are underestimated, which could be related with short fire patch length and low daily fire size. Future efforts should be directed towards building consistent spatial observation data sets for key parameters of the model in order to constrain the model error at each key step of the fire modelling.

[1]  F. Siegert,et al.  Biomass burning fuel consumption rates: a field measurement database , 2014 .

[2]  Kirsten Thonicke,et al.  SPITFIRE within the MPI Earth system model: Model development and evaluation , 2014 .

[3]  G. Hurtt,et al.  HESFIRE: an explicit fire model for projections in the coupled Human–Earth System , 2014 .

[4]  H. Tian,et al.  Spatial and temporal patterns of global burned area in response to anthropogenic and environmental factors: Reconstructing global fire history for the 20th and early 21st centuries , 2014 .

[5]  Richard J. Blakeslee,et al.  Gridded lightning climatology from TRMM-LIS and OTD: Dataset description , 2014 .

[6]  P. Ciais,et al.  Modelling global burned area and fire regime , 2014 .

[7]  Tim R. McVicar,et al.  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 , 2013 .

[8]  A. Arneth,et al.  Impact of human population density on fire frequency at the global scale , 2013 .

[9]  J. Randerson,et al.  Global impact of smoke aerosols from landscape fires on climate and the Hadley circulation , 2013 .

[10]  J. Kaplan,et al.  A model for global biomass burning in preindustrial time: LPJ-LMfire (v1.0) , 2013 .

[11]  E. Chuvieco,et al.  Strengths and weaknesses of MODIS hotspots to characterize global fire occurrence , 2013 .

[12]  R. Bradstock,et al.  Defining pyromes and global syndromes of fire regimes , 2013, Proceedings of the National Academy of Sciences.

[13]  Philippe Martinez,et al.  Orbital-scale climate forcing of grassland burning in southern Africa , 2013, Proceedings of the National Academy of Sciences.

[14]  J. Randerson,et al.  El Niño and health risks from landscape fire emissions in Southeast Asia , 2012, Nature climate change.

[15]  J. Randerson,et al.  Global burned area and biomass burning emissions from small fires , 2012 .

[16]  D. S. Ward,et al.  Quantifying the role of fire in the Earth system – Part 1: Improved global fire modeling in the Community Earth System Model (CESM1) , 2012 .

[17]  J. Randerson,et al.  The changing radiative forcing of fires: global model estimates for past, present and future , 2012 .

[18]  J. Randerson,et al.  High-latitude cooling associated with landscape changes from North American boreal forest fires , 2012 .

[19]  Elena Shevliakova,et al.  Separating agricultural and non-agricultural fire seasonality at regional scales , 2012 .

[20]  S. Levis,et al.  A process-based fire parameterization of intermediate complexity in a Dynamic Global Vegetation Model , 2012 .

[21]  Christopher C. Schmidt,et al.  Near-Real-Time Global Biomass Burning Emissions Product from Geostationary Satellite Constellation , 2012 .

[22]  S. Gotsch,et al.  Ecological thresholds at the savanna-forest boundary: how plant traits, resources and fire govern the distribution of tropical biomes. , 2012, Ecology letters.

[23]  E. Kasischke,et al.  Controls on carbon consumption during Alaskan wildland fires , 2012 .

[24]  F. Li,et al.  Quantifying the role of fire in the Earth system – Part 1 : Improved global fire modeling in the Community Earth System Model ( CESM 1 ) , 2012 .

[25]  John B. Loomis,et al.  The hidden cost of wildfires: Economic valuation of health effects of wildfire smoke exposure in Southern California , 2012 .

[26]  J. Randerson,et al.  Daily and 3‐hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide , 2011 .

[27]  Niklaus E. Zimmermann,et al.  Plant functional type mapping for earth system models , 2011 .

[28]  A. McGuire,et al.  Potential shifts in dominant forest cover in interior Alaska driven by variations in fire severity. , 2011, Ecological applications : a publication of the Ecological Society of America.

[29]  James T. Randerson,et al.  The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN , 2011 .

[30]  P. Friedlingstein,et al.  Modeling fire and the terrestrial carbon balance , 2011 .

[31]  M. G. Ryan,et al.  Continued warming could transform Greater Yellowstone fire regimes by mid-21st century , 2011, Proceedings of the National Academy of Sciences.

[32]  J. Randerson,et al.  The impacts and implications of an intensifying fire regime on Alaskan boreal forest composition and albedo , 2011, Global Change Biology.

[33]  M. Moritz,et al.  Constraints on global fire activity vary across a resource gradient. , 2011, Ecology.

[34]  J. Randerson,et al.  Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009) , 2010 .

[35]  D. Roy,et al.  Southern African Fire Regimes as Revealed by Remote Sensing , 2010 .

[36]  A. McGuire,et al.  Alaska's Changing Fire Regime - Implications for the Vulnerability of Its Boreal Forests , 2010 .

[37]  Sandy P. Harrison,et al.  The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model , 2010 .

[38]  F. M. Hoffman,et al.  Fire dynamics during the 20th century simulated by the Community Land Model , 2010 .

[39]  J. Randerson,et al.  Assessing variability and long-term trends in burned area by merging multiple satellite fire products , 2009 .

[40]  Drew T. Shindell,et al.  Fire parameterization on a global scale , 2009 .

[41]  Benjamin M. Jones,et al.  Fire Behavior, Weather, and Burn Severity of the 2007 Anaktuvuk River Tundra Fire, North Slope, Alaska , 2009 .

[42]  J. Keeley,et al.  A Burning Story: The Role of Fire in the History of Life , 2009 .

[43]  Christopher I. Roos,et al.  Fire in the Earth System , 2009, Science.

[44]  B. Duncan,et al.  Vegetation fire emissions and their impact on air pollution and climate , 2009 .

[45]  M. Turner,et al.  Landscape heterogeneity following large fires: insights from Yellowstone National Park, USA , 2008 .

[46]  J. Randerson,et al.  Climate regulation of fire emissions and deforestation in equatorial Asia , 2008, Proceedings of the National Academy of Sciences.

[47]  J. Randerson,et al.  Climate controls on the variability of fires in the tropics and subtropics , 2008 .

[48]  S. Sitch,et al.  The role of fire disturbance for global vegetation dynamics: coupling fire into a Dynamic Global Vegetation Model , 2008 .

[49]  J. Randerson,et al.  Interannual variability of surface energy exchange depends on stand age in a boreal forest fire chronosequence , 2008 .

[50]  J. Grégoire,et al.  A new, global, multi‐annual (2000–2007) burnt area product at 1 km resolution , 2008 .

[51]  Ronald J. Hall,et al.  Large fires as agents of ecological diversity in the North American boreal forest , 2008 .

[52]  A. Gill,et al.  Large fires, fire effects and the fire-regime concept , 2008 .

[53]  Ian McCallum,et al.  An Update on the globcarbon initiative : multi-sensor estimation of global biophysical products for global terrestrial carbon studies , 2007 .

[54]  S. Pueyo.  Self-Organised Criticality and the Response of Wildland Fires to Climate Change , 2007 .

[55]  J. Randerson,et al.  The Impact of Boreal Forest Fire on Climate Warming , 2006, Science.

[56]  T. Swetnam,et al.  Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity , 2006, Science.

[57]  E. Kasischke,et al.  Recent changes in the fire regime across the North American boreal region—Spatial and temporal patterns of burning across Canada and Alaska , 2006 .

[58]  Vivek K. Arora,et al.  Fire as an interactive component of dynamic vegetation models , 2005 .

[59]  A. Smith,et al.  Remote classification of head and backfire types from MODIS fire radiative power and smoke plume observations , 2005 .

[60]  J. Randerson,et al.  Changes in the surface energy budget after fire in boreal ecosystems of interior Alaska: An annual perspective , 2005 .

[61]  B. Malamud,et al.  Characterizing wildfire regimes in the United States. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[62]  C. Field,et al.  Fire history and the global carbon budget: a 1°× 1° fire history reconstruction for the 20th century , 2005 .

[63]  I. C. Prentice,et al.  A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system , 2005 .

[64]  F. Woodward,et al.  The global distribution of ecosystems in a world without fire. , 2004, The New phytologist.

[65]  S. Sitch,et al.  Simulating fire regimes in human‐dominated ecosystems: Iberian Peninsula case study , 2002 .

[66]  K. Hirsch,et al.  Large forest fires in Canada, 1959–1997 , 2002 .

[67]  Keeley,et al.  Reexamining fire suppression impacts on brushland fire regimes , 1999, Science.

[68]  D. Turcotte,et al.  Forest fires: An example of self-organized critical behavior , 1998, Science.

[69]  W. Hargrove,et al.  Effects of fire on landscape heterogeneity in Yellowstone National Park, Wyoming , 1994 .

[70]  Kevin C. Ryan,et al.  Modeling postfire conifer mortality for long-range planning , 1986 .

[71]  R. A. Jr. Wilson.  A reexamination of fire spread in free-burning porous fuel beds [Wildland fuels, forest fire management, model] , 1982 .