%0 Journal Article %1 Szopa2007 %A Szopa, S. %A Hauglustaine, D. A. %A Ciais, P. %D 2007 %I American Geophysical Union %J Geophysical Research Letters %K 3399AtmosphericProcesses:Generalormiscellaneous 3319AtmosphericProcesses:Generalcirculation ElNiño biomassburning 0322AtmosphericCompositionandStructure:Constituentsourcesandsinks 0325AtmosphericCompositionandStructure:Evolutionoftheatmosphere 0365AtmosphericCompositionandStructure:Troposphere:compositionandchemistry CO %P L18810 %R 10.1029/2007GL030231 %T Relative contributions of biomass burning emissions and atmospheric transport to carbon monoxide interannual variability %V 34 %X Biomass burning is an important source of greenhouse gases and of ozone precursors such as CO. Recent analyses combining the use of satellite data and of ecosystem models showed that wild fire emissions are subject to a large interannual variability. In this study, NOAA/ESRL CO surface measurements are used in conjunction with the results from the LMDz-INCA global chemistry-transport model and analyzed over the 1997–2001 period in order to quantify the relative contributions of biomass burning emissions and of climate to the CO interannual variability (IAV). Over the considered five year period, the mean CO IAV was found to be about 11% for stations far from regional pollution and 4.5% for Antarctic stations. At both southern and northern high latitude stations, the CO IAV is controlled almost equally by variations in biomass burning emissions and atmospheric meteorology. On the contrary, meteorological variability prevails in the tropics, where it explains 50% to 90% of the CO IAV. Variability in long-range transport and climate is thus the dominant process controlling the CO interannual variability, except during specific episodes, such as the intense fires associated with the 1997–1998 El Niño event.

@article{Szopa2007, abstract = {Biomass burning is an important source of greenhouse gases and of ozone precursors such as CO. Recent analyses combining the use of satellite data and of ecosystem models showed that wild fire emissions are subject to a large interannual variability. In this study, NOAA/ESRL CO surface measurements are used in conjunction with the results from the LMDz-INCA global chemistry-transport model and analyzed over the 1997–2001 period in order to quantify the relative contributions of biomass burning emissions and of climate to the CO interannual variability (IAV). Over the considered five year period, the mean CO IAV was found to be about 11% for stations far from regional pollution and 4.5% for Antarctic stations. At both southern and northern high latitude stations, the CO IAV is controlled almost equally by variations in biomass burning emissions and atmospheric meteorology. On the contrary, meteorological variability prevails in the tropics, where it explains 50% to 90% of the CO IAV. Variability in long-range transport and climate is thus the dominant process controlling the CO interannual variability, except during specific episodes, such as the intense fires associated with the 1997–1998 El Niño event.}, added-at = {2009-06-08T21:16:48.000+0200}, author = {Szopa, S. and Hauglustaine, D. A. and Ciais, P.}, biburl = {https://www.bibsonomy.org/bibtex/282df59b1a52eef47dd1bcb60a537c012/claas}, doi = {10.1029/2007GL030231}, file = {Szopa2007.pdf:Szopa2007.pdf:PDF}, interhash = {09aeebf659e82065b917ab2c6e06a02a}, intrahash = {82df59b1a52eef47dd1bcb60a537c012}, journal = {Geophysical Research Letters}, keywords = {3399AtmosphericProcesses:Generalormiscellaneous 3319AtmosphericProcesses:Generalcirculation ElNiño biomassburning 0322AtmosphericCompositionandStructure:Constituentsourcesandsinks 0325AtmosphericCompositionandStructure:Evolutionoftheatmosphere 0365AtmosphericCompositionandStructure:Troposphere:compositionandchemistry CO}, month = {#sep#}, pages = {L18810}, publisher = {American Geophysical Union}, timestamp = {2009-06-08T21:16:48.000+0200}, title = {Relative contributions of biomass burning emissions and atmospheric transport to carbon monoxide interannual variability}, volume = 34, year = 2007 }