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Journal of Geophysical Research: Atmospheres

Over the last two decades satellite observations have revealed the importance of fire in many ecosystems around the world, but only more recently have quantitative analyses of burned area and emissions been available. We present results from our improved Global Fire Emissions Database (GFED) version 3 based on satellite derived burned area and a biogeochemical model. Model results provide an overview of the role of fires in the global carbon cycle over 1996-2008, and, for the first time, we partition total fire emissions into contributions from deforestation, agriculture, savanna, and forest fires. This allowed us to assess the fraction of total fire emissions that contributed to the build-up of atmospheric CO2 over the last decade because only deforestation fire emissions or emissions from regions where fire frequency increases are net emissions. However, global scale modeling approaches cannot easily incorporate all key regional fire processes. We will therefore focus on the Indonesia region where complicated fuel composition and uncertain burned area estimates have so far prevented reliable emissions estimates so far. By combining emissions from our fire database with atmospheric modeling and measured carbon monoxide mixing ratios from the MOPITT sensor we were able to provide constrained emissions and assess the performance of our database in this region. We found that fire emissions were roughly equal to regional fossil fuel emissions but that emissions showed large interannual variability due to the dependence of fires on drought conditions. This drought-fire link was found to be highly non-linear, revealing the vulnerability of the region to climate change if future droughts become more frequent or more intense. One of the factors contributing to the non-linearity was the climate sensitivity of forest loss. Our findings imply that land manager responses to expected shifts in tropical precipitation may critically determine the strength of climate-carbon cycle feedbacks during the 21st century.

Most of our understanding of the sources and sinks of atmospheric CO2 has come from inverse studies of atmospheric CO2 concentration measurements. However, the number of currently available observation stations and our ability to simulate the diurnal planetary boundary layer evolution over continental regions essentially limit the number of regions that can be reliably inverted globally, especially over continental areas. In order to overcome these restrictions, a nested inverse modeling system was developed based on the Bayesian principle for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Inverse modeling was conducted in monthly steps using CO2 concentration measurements of 5 years (2000 - 2005) with the following two models: (a) An atmospheric transport model (TM5) is used to generate the transport matrix where the diurnal variation n of atmospheric CO2 concentration is considered to enhance the use of the afternoon-hour average CO2 concentration measurements over the continental sites. (b) A process-based terrestrial ecosystem model (BEPS) is used to produce hourly step carbon fluxes, which could minimize the limitation due to our inability to solve the inverse problem in a high resolution, as the background of our inversion. We will present our recent results achieved through a combination of the bottom-up modeling with BEPS and the top-down modeling based on TM5 driven by offline meteorological fields generated by the European Centre for Medium Range Weather Forecast (ECMFW).

Over the last two decades satellite observations have revealed the importance of fire in many ecosystems around the world, but only more recently have quantitative analyses of burned area and emissions been available. We present results from our improved Global Fire Emissions Database (GFED) version 3 based on satellite derived burned area and a biogeochemical model. Model results provide an overview of the role of fires in the global carbon cycle over 1996-2008, and, for the first time, we partition total fire emissions into contributions from deforestation, agriculture, savanna, and forest fires. This allowed us to assess the fraction of total fire emissions that contributed to the build-up of atmospheric CO2 over the last decade because only deforestation fire emissions or emissions from regions where fire frequency increases are net emissions. However, global scale modeling approaches cannot easily incorporate all key regional fire processes. We will therefore focus on the Indonesia region where complicated fuel composition and uncertain burned area estimates have so far prevented reliable emissions estimates so far. By combining emissions from our fire database with atmospheric modeling and measured carbon monoxide mixing ratios from the MOPITT sensor we were able to provide constrained emissions and assess the performance of our database in this region. We found that fire emissions were roughly equal to regional fossil fuel emissions but that emissions showed large interannual variability due to the dependence of fires on drought conditions. This drought-fire link was found to be highly non-linear, revealing the vulnerability of the region to climate change if future droughts become more frequent or more intense. One of the factors contributing to the non-linearity was the climate sensitivity of forest loss. Our findings imply that land manager responses to expected shifts in tropical precipitation may critically determine the strength of climate-carbon cycle feedbacks during the 21st century.

Over the last two decades satellite observations have revealed the importance of fire in many ecosystems around the world, but only more recently have quantitative analyses of burned area and emissions been available. We present results from our improved Global Fire Emissions Database (GFED) version 3 based on satellite derived burned area and a biogeochemical model. Model results provide an overview of the role of fires in the global carbon cycle over 1996-2008, and, for the first time, we partition total fire emissions into contributions from deforestation, agriculture, savanna, and forest fires. This allowed us to assess the fraction of total fire emissions that contributed to the build-up of atmospheric CO2 over the last decade because only deforestation fire emissions or emissions from regions where fire frequency increases are net emissions. However, global scale modeling approaches cannot easily incorporate all key regional fire processes. We will therefore focus on the Indonesia region where complicated fuel composition and uncertain burned area estimates have so far prevented reliable emissions estimates so far. By combining emissions from our fire database with atmospheric modeling and measured carbon monoxide mixing ratios from the MOPITT sensor we were able to provide constrained emissions and assess the performance of our database in this region. We found that fire emissions were roughly equal to regional fossil fuel emissions but that emissions showed large interannual variability due to the dependence of fires on drought conditions. This drought-fire link was found to be highly non-linear, revealing the vulnerability of the region to climate change if future droughts become more frequent or more intense. One of the factors contributing to the non-linearity was the climate sensitivity of forest loss. Our findings imply that land manager responses to expected shifts in tropical precipitation may critically determine the strength of climate-carbon cycle feedbacks during the 21st century.

Most of our understanding of the sources and sinks of atmospheric CO2 has come from inverse studies of atmospheric CO2 concentration measurements. However, the number of currently available observation stations and our ability to simulate the diurnal planetary boundary layer evolution over continental regions essentially limit the number of regions that can be reliably inverted globally, especially over continental areas. In order to overcome these restrictions, a nested inverse modeling system was developed based on the Bayesian principle for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Inverse modeling was conducted in monthly steps using CO2 concentration measurements of 5 years (2000 - 2005) with the following two models: (a) An atmospheric transport model (TM5) is used to generate the transport matrix where the diurnal variation n of atmospheric CO2 concentration is considered to enhance the use of the afternoon-hour average CO2 concentration measurements over the continental sites. (b) A process-based terrestrial ecosystem model (BEPS) is used to produce hourly step carbon fluxes, which could minimize the limitation due to our inability to solve the inverse problem in a high resolution, as the background of our inversion. We will present our recent results achieved through a combination of the bottom-up modeling with BEPS and the top-down modeling based on TM5 driven by offline meteorological fields generated by the European Centre for Medium Range Weather Forecast (ECMFW).

Most of our understanding of the sources and sinks of atmospheric CO2 has come from inverse studies of atmospheric CO2 concentration measurements. However, the number of currently available observation stations and our ability to simulate the diurnal planetary boundary layer evolution over continental regions essentially limit the number of regions that can be reliably inverted globally, especially over continental areas. In order to overcome these restrictions, a nested inverse modeling system was developed based on the Bayesian principle for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Inverse modeling was conducted in monthly steps using CO2 concentration measurements of 5 years (2000 - 2005) with the following two models: (a) An atmospheric transport model (TM5) is used to generate the transport matrix where the diurnal variation n of atmospheric CO2 concentration is considered to enhance the use of the afternoon-hour average CO2 concentration measurements over the continental sites. (b) A process-based terrestrial ecosystem model (BEPS) is used to produce hourly step carbon fluxes, which could minimize the limitation due to our inability to solve the inverse problem in a high resolution, as the background of our inversion. We will present our recent results achieved through a combination of the bottom-up modeling with BEPS and the top-down modeling based on TM5 driven by offline meteorological fields generated by the European Centre for Medium Range Weather Forecast (ECMFW).