Fire parameterization on a global scale

[1] We present a convenient physically based global-scale fire parameterization algorithm for global climate models. We indicate environmental conditions favorable for fire occurrence based on calculation of the vapor pressure deficit as a function of location and time. Two ignition models are used. One assumes ubiquitous ignition, the other incorporates natural and anthropogenic sources, as well as anthropogenic fire suppression. Evaluation of the method using Global Precipitation Climatology Project precipitation, National Centers for Environmental Prediction/National Center for Atmospheric Research temperature and relative humidity, and Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index as a proxy for global vegetation density gives results in remarkable correspondence with global fire patterns observed from the MODIS and Visible and Infrared Scanner satellite instruments. The parameterized fires successfully reproduce the spatial distribution of global fires as well as the seasonal variability. The interannual variability of global fire activity derived from the 20-year advanced very high resolution radiometer record are well reproduced using Goddard Institute for Space Studies general circulation models climate simulations, as is the response to the climate changes following the eruptions of El Chichon and Mount Pinatubo. In conjunction with climate models and data sets on vegetation changes with time, the suggested fire parameterization offers the possibility to estimate relative variations of global fire activity for past and future climates.

[1]  Navin Ramankutty,et al.  Our share of the planetary pie , 2007, Proceedings of the National Academy of Sciences.

[2]  Emilio Chuvieco,et al.  Estimation of Risk Factors of Human Ignition of Fires in Spain by Means of Logistic Regression 1 , 2004 .

[3]  P. Pérez,et al.  Analysis of methods for estimating vapor pressure deficits and relative humidity , 1996 .

[4]  David Rind,et al.  The Impact of a 2 × CO2 Climate on Lightning-Caused Fires , 1994 .

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

[6]  R. Guyette,et al.  Dynamics of an Anthropogenic Fire Regime , 2003, Ecosystems.

[7]  Q. Schiermeier.  Climate change: That sinking feeling , 2005, Nature.

[8]  J. Randerson,et al.  Carbon emissions from fires in tropical and subtropical ecosystems , 2003 .

[9]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[10]  C. Tucker,et al.  Expansion and Contraction of the Sahara Desert from 1980 to 1990 , 1991, Science.

[11]  S. Ustin,et al.  Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA‐NASA Pathfinder , 2007 .

[12]  B. M. Wotton,et al.  Climate Change and People-Caused Forest Fire Occurrence in Ontario , 2003 .

[13]  A. Granier,et al.  Transpiration of a boreal pine forest measured by branch bag, sap flow and micrometeorological methods. , 1997, Tree physiology.

[14]  Y. Knyazikhin,et al.  Validation and intercomparison of global Leaf Area Index products derived from remote sensing data , 2008 .

[15]  Leslie Dienes.  Observations on the Problematic Potential of Russian Oil and the Complexities of Siberia , 2004 .

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

[17]  Donald B. Anderson.  Relative Humidity or Vapor Pressure Deficit , 1936 .

[18]  C. Justice,et al.  Global characterization of fire activity: toward defining fire regimes from Earth observation data , 2008 .

[19]  Pierre Defourny,et al.  L3JRC - A global, multi-year (2000-2007) burnt area product (1 km resolution and daily time steps) , 2007 .

[20]  Ian R. Noble,et al.  McArthur's fire-danger meters expressed as equations , 1980 .

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

[22]  Paul W. Stackhouse,et al.  Climate-induced boreal forest change: Predictions versus current observations , 2007 .

[23]  Suhung Shen,et al.  EDITORIAL: NASA NEESPI Data and Services Center for Satellite Remote Sensing Information , 2007 .

[24]  J. Randerson,et al.  Interannual variability in global biomass burning emissions from 1997 to 2004 , 2006 .

[25]  M. Flannigan,et al.  Forest Fires and Climate Change in the 21ST Century , 2006 .

[26]  M. Flannigan,et al.  Future Area Burned in Canada , 2005 .

[27]  P. Whitfield,et al.  Potential forest fire danger over Northern Eurasia: Changes during the 20th century , 2005 .

[28]  D. Streets,et al.  Climate simulations for 1880–2003 with GISS modelE , 2006, physics/0610109.

[29]  F. Achard,et al.  Ecology: Human role in Russian wild fires , 2006, Nature.

[30]  David L. Martell,et al.  Modelling seasonal variation in daily people-caused forest fire occurrence , 1989 .

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

[32]  S. A. Prentice,et al.  The Ratio of Cloud to Cloud-Ground Lightning Flashes in Thunderstorms , 1977 .

[33]  C. E. Van Wagner,et al.  Development and structure of the Canadian Forest Fire Weather Index System , 1987 .

[34]  A. Lugo,et al.  Climate Change and Forest Disturbances , 2001 .

[35]  J. Kendall,et al.  A multi-year active fire dataset for the tropics derived from the TRMM VIRS , 2003 .

[36]  J. Randerson,et al.  The use of ATSR active fire counts for estimating relative patterns of biomass burning – a study from the boreal forest region , 2003 .

[37]  J. Janowiak,et al.  The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present) , 2003 .

[38]  G. M. Byram,et al.  A Drought Index for Forest Fire Control , 1968 .