Global mapping of maximum emission heights and resulting vertical profiles of wildfire emissions

Abstract. The problem of characteristic vertical profile of smoke released from wildland fires is considered. A methodology for bottom-up evaluation of this profile is suggested and a corresponding global dataset is calculated. The profile estimation is based on: (i) a semi-empirical formula for plume-top height recently suggested by the authors, (ii) satellite observations of active wildland fires, and (iii) meteorological conditions evaluated for each fire using output of the numerical weather prediction model. Injection profiles of the plumes from all fires recorded globally from March 2000 till November 2012 are estimated with a time step of 1 h. The resulting 4-dimensional dataset is split into daytime and nighttime subsets. The subsets are projected onto a global grid with a resolution of 1° × 1° × 500 m, aggregated to a monthly level, and normalised by total emissions in each vertical column. Evaluation of the obtained dataset was performed in several ways. Firstly, the quality of the semi-empirical formula for plume-top computations was evaluated using updated MISR fire Plume Height Project data. Secondly, the upper percentiles of the profiles are compared with an independent dataset of space lidar CALIOP. Thirdly, the results are compared with the distribution suggested for AEROCOM modelling community. Finally, the inter-annual variations of the calculated profiles are estimated.

[1]  Owen B. Toon,et al.  Simulations of microphysical, radiative, and dynamical processes in a continental-scale forest fire smoke plume , 1991 .

[2]  David J. Diner,et al.  Wildfire smoke injection heights: Two perspectives from space , 2008 .

[3]  D. Sullivan,et al.  An Evaluation of Modeled Plume Injection Height with Satellite-Derived Observed Plume Height , 2012 .

[4]  R. Colvile,et al.  Estimating the direct radiative forcing due to haze from the 1997 forest fires in Indonesia , 2004 .

[5]  R. Draxler,et al.  Verification of the NOAA Smoke Forecasting System: Model Sensitivity to the Injection Height , 2009 .

[6]  M. Sofieva,et al.  A dispersion modelling system SILAM and its evaluation against ETEX data , 2005 .

[7]  David J. Diner,et al.  A data-mining approach to associating MISR smoke plume heights with MODIS fire measurements , 2007 .

[8]  D. Winker,et al.  The CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm , 2009 .

[9]  G. Roberts,et al.  Annual and diurnal african biomass burning temporal dynamics , 2008 .

[10]  Gareth Roberts,et al.  An approach to estimate global biomass burning emissions of organic and black carbon from MODIS fire radiative power , 2009 .

[11]  Numerical simulation of tropospheric injection of biomass burning products by pyro-thermal plumes , 2009 .

[12]  J. Morcrette,et al.  SEVIRI Fire Radiative Power and the MACC Atmospheric Services , 2009 .

[13]  Mikhail Sofiev,et al.  Evaluation of the smoke-injection height from wild-land fires using remote-sensing data , 2011 .

[14]  J. Penner,et al.  A global three‐dimensional model study of carbonaceous aerosols , 1996 .

[15]  J. Goldammer,et al.  Modeling of carbonaceous particles emitted by boreal and temperate wildfires at northern latitudes , 2000 .

[16]  David J. Diner,et al.  Dynamics of fire plumes and smoke clouds associated with peat and deforestation fires in Indonesia , 2011 .

[17]  Duane A. Haugen,et al.  Lectures on Air Pollution and Environmental Impact Analyses , 1982 .

[18]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[19]  B. Grisogono,et al.  Atmospheric Boundary Layers , 2007 .

[20]  C. Justice,et al.  Potential global fire monitoring from EOS‐MODIS , 1998 .

[21]  Charles Ichoku,et al.  Relationships between energy release, fuel mass loss, and trace gas and aerosol emissions during laboratory biomass fires , 2008 .

[22]  S. Freitas,et al.  Including the plume rise of vegetation fires , 2006 .

[23]  Ulla Wandinger,et al.  Transport of boreal forest fire emissions from Canada , 2001 .

[24]  Tami C. Bond,et al.  Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom , 2006 .

[25]  M. Razinger,et al.  Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power , 2011 .

[26]  Gareth Roberts,et al.  Fire Detection and Fire Characterization Over Africa Using Meteosat SEVIRI , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[27]  L. Remer,et al.  Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy , 2008 .

[28]  Sundar A. Christopher,et al.  Mesoscale modeling of Central American smoke transport to the United States: 1. “Top‐down” assessment of emission strength and diurnal variation impacts , 2006 .

[29]  C. O. Justicea,et al.  The MODIS fire products , 2002 .

[30]  J. D. Laat,et al.  An aerosol boomerang: Rapid around-the-world transport of smoke from the December 2006 Australian forest fires observed from space , 2009 .

[31]  L. Giglio Characterization of the tropical diurnal fire cycle using VIRS and MODIS observations , 2007 .

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

[33]  Eric P. Shettle,et al.  Observations of boreal forest fire smoke in the stratosphere by POAM III, SAGE II, and lidar in 1998 , 2000 .

[34]  Gunnar Luderer,et al.  Modeling of biomass smoke injection into the lower stratosphere by a large forest fire (Part II): sensitivity studies , 2006 .

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

[36]  Y. Kaufman,et al.  Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release , 2005 .

[37]  D. L. Nelson,et al.  Smoke injection heights from fires in North America: analysis of 5 years of satellite observations , 2009 .

[38]  J. Kauffman,et al.  Biomass dynamics associated with deforestation, fire, and, conversion to cattle pasture in a Mexican tropical dry forest , 2003 .

[39]  G. Briggs,et al.  Plume Rise Predictions , 1982 .

[40]  F. Bréon,et al.  Injection height of biomass burning aerosols as seen from a spaceborne lidar , 2007 .

[41]  L. Pirjola,et al.  African biomass burning plumes over the Atlantic: aircraft based measurements and implications for H2SO4 and HNO3 mediated smoke particle activation , 2011 .

[42]  David M. Winker,et al.  Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements , 2009 .

[43]  Jaakko Kukkonen,et al.  An operational system for the assimilation of the satellite information on wild-land fires for the needs of air quality modelling and forecasting , 2009 .