This paper describes the construction and application of a terrestrial carbon cycle assimilation/... more This paper describes the construction and application of a terrestrial carbon cycle assimilation/prediction scheme. In the assimilation step, we constrain the parameters in a terrestrial biosphere model subject to observations. We demonstrate the technique using atmospheric CO2 concentration observations and satellite estimates of greenness. The method returns not only the values of the parameters but an estimate of their uncertainties. In the prediction step we can use these parameters and their uncertainties to either predict the future behaviour of the terrestrial biosphere or to test the model against data not used in the assimilation. The method relies heavily on the automatic generation of tangent linear and adjoint models for the optimization and uncertainty propagation steps. 1.
Currently available global and regional inventories of biomass burning emissions of gases and par... more Currently available global and regional inventories of biomass burning emissions of gases and particles were compared over the 20th century until the year 2014. Considered datasets were created based on different approaches to emission estimation, such as historical reconstruction of burnt area, use of satellite products for burnt area, active fire data, fire radiative power, fixed or dynamical land cover and associated parameters as well as fire emission models in combination with land surface model. We compare annual totals and seasonal variation of emissions of total carbon in 14 geographical regions from the following data sets: ACCMIP, AMMABB, FINN, GFAS, GFED, GICC, MACCity, QFED and RETRO. This comparison study informs about differences among the datasets and serves as a basis for the community effort in harmonizing and creating a consistent inventory spanning through the studied period. For most of the 20th century the inventory will need to rely on the fire emission models ...
We develop a simple, globally uniform model of CO; exchange between the atmosphere and the terres... more We develop a simple, globally uniform model of CO; exchange between the atmosphere and the terrestrial biosphere by coupling the model with a threedimensional atmospheric tracer transport model using observed winds, and checking results against observed concentrations of C02 at various monitoring sites. C02 fluxes are derived from observed greenness using satellite-derived Global Vegetation Index data, combined with observations of temperature, radiation. and precipitation. We explore a range of C02 flux formulations together with some modifications of the modelled atmospheric transport. It appears that the seasonality of net C02 fluxes in the tropics, which would be expected to be driven by water availability, is remarkably small, because C02 uptake and release are reduced simultaneously during the dry season. Consequently, tropical vegetation contributes only very little to the seaonal cycle of atmospheric C102, which is dominated by northern temperate and boreal vegetation, where...
Climatic fire danger will likely increase because more droughts and heat-waves are caused by clim... more Climatic fire danger will likely increase because more droughts and heat-waves are caused by climate change. Climate change can shift fires from occurring only rarely to regularly in ecosystems not until now adapted to fire. We applied dynamic vegetation-fire models to investigate these future responses. The future of fire in Mediterranean-type ecosystems depends strongly on changes in vegetation productivity, thus fuel availability, if burned area increases as much as fire danger. Temperate ecosystems might be exposed to Mediterranean-like fire regimes. In high altitudes, Mediterranean trees might migrate up-hill and cause feedbacks between diversity and fire under climate change.
ABSTRACT Various indirect methods suggest that much of the year-year variability in the growth-ra... more ABSTRACT Various indirect methods suggest that much of the year-year variability in the growth-rate of atmospheric CO2 over the last two decades is attributable to variability in the net terrestrial flux. It is much less clear which processes are responsible for this terrestrial variability. In this talk we present results from a carbon cycle data assimilation system (CCDAS) in which the controlling parameters in a terrestrial carbon cycle model are inferred by nonlinear optimization based on the model's adjoint. Uncertainties in the parameters are inferred from observational and model uncertainties via the model's Hessian and then mapped forward on predicted quantities such as net CO2 fluxes to the atmosphere via the model's Jacobian. The adjoint, Hessian, and Jacobian are generated by automatic differentiation of the model's source code. The dataset is the set of extended CO2 concentration records from 41 observing sites. The model is able to fit the observations moderately well although it slightly overpredicts the long-term growth rate. This occurs despite the increase in terrestrial uptake through the 1990s over the 1980s. The increase, in turn, occurs despite a reduction in net primary productivity and is hence caused by a larger decrease in soil respiration. It appears that the requirement to fit both the seasonal cycle and interannual dynamics in the CO2 record is a strong constraint on model formulation. We will demonstrate this by describing some of the problems with the description of respiration which are highlighted by this approach.
(3) Abstract. Each manuscript must have an abstract that clearly describes the paper and is no mo... more (3) Abstract. Each manuscript must have an abstract that clearly describes the paper and is no more than 150 words long. (4) Index Terms. At least one and up to five numerical index terms must be provided when submitting the article. See http://publications.agu.org/ author-resource-center/author-guide/index-terms/ for current index terms.
Photosynthetic capacity is one of the most sensitive parameters of terrestrial biosphere models w... more Photosynthetic capacity is one of the most sensitive parameters of terrestrial biosphere models whose representation in global scale simulations has been severely hampered by a lack of systematic analyses using a sufficiently broad database. Due to its coupling to stomatal conductance changes in the parameterisation of photosynthetic capacity may potentially influence transpiration rates and vegetation surface temperature. Here, we provide
The current and future strength of the terrestrial carbon sink has a crucial influence on the exp... more The current and future strength of the terrestrial carbon sink has a crucial influence on the expected degree of climate warming humanity is going to face. Usually, Earth Observation (EO) by its very nature focuses on diagnosing the current state of the planet. However, it is possible to use EO products in data assimilation systems to improve not only the diagnostics of the current state, but also the accuracy of future predictions. This contribution reports from an on-going ESA funded study (see http://rs.ccdas.org) in which the MERIS FAPAR product is assimilated into a terrestrial biosphere model within the global Carbon Cycle Data Assimilation System (see http://CCDAS.org). Using methods of variational data assimilation, CCDAS relies on first and second derivatives of the underlying model for estimating process parameters with uncertainty ranges. In a subsequent step these parameter uncertainties are mapped forward onto uncertainty ranges for predicted carbon fluxes. In this cont...
This contribution gives an overview of the Medium Resolution Imaging Spectrometer (MERIS) global ... more This contribution gives an overview of the Medium Resolution Imaging Spectrometer (MERIS) global land product corresponding to the biophysical variable of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). This product can be used in large- scale biosphere modeling for better estimating the carbon fluxes since they directly represent the amount of solar energy which serves as a 'battery' during the photosynthetic process. The daily FAPAR value is operationally estimated from MERIS data 1 and the (demonstration) global products, recently produced at European Space Research Institute (ESRIN) by the grid on demand system 2 , are first compared against the Joint Research Centre (JRC) SeaWiFS global datasets which is
<p>The Paris Agreement foresees to establish a tran... more <p>The Paris Agreement foresees to establish a transparency framework that builds upon inventory-based national greenhouse gas emission reports, complemented by independent emission estimates derived from atmospheric measurements through inverse modelling. The capability of such a Monitoring and Verification Support (MVS) capacity to constrain fossil fuel emissions to a sufficient extent has not yet been assessed. The CO2 Monitoring Mission (CO2M), planned as a constellation of satellites measuring column-integrated atmospheric CO2 concentration (XCO2), is expected to become a key component of an MVS capacity. </p><p>Here we present a CCFFDAS that operates at the resolution of the CO2M sensor, i.e. 2km by 2km, over a 200 km by 200 km region around Berlin. It combines models of sectorial fossil fuel CO2 emissions and biospheric fluxes with the Community Multiscale Air Quality model (coupled to a model of the plume rise from large power plants) as observation operator for XCO2 and tropospheric column NO2 measurements. Inflow from the domain boundaries is treated as extra unknown to be solved for by the CCFFDAS, which also includes prior information on the process model parameters. We discuss the sensitivities (Jacobian matrix) of simulated XCO2 and NO2 troposheric columns with respect to a) emissions from power plants, b) emissions from the surface and c) the lateral inflow and quantify the respective contributions to the observed signal. The Jacobian representation of the complete modelling chain allows us to evaluate data sets of simulated random and systematic CO2M errors in terms of posterior uncertainties in sectorial fossil fuel emissions. We provide assessments of XCO2 alone and in combination with NO2 on the posterior uncertainty in sectorial fossil fuel emissions for two 1-day study periods, one in winter and one in summer. We quantify the added value of the observations for emissions at a single point, at the 2km by 2km scale, at the scale of Berlin districts, and for  Berlin and further cities in our domain. This means the assessments include temporal and spatial scales typically not covered by inventories. Further, we quantify the effect of better information of atmospheric aerosol, provided by a multi-angular polarimeter (MAP) onboard CO2M, on the posterior uncertainties.</p><p>The assessments differentiate the fossil fuel CO2 emissions into two sectors, an energy generation sector (power plants) and the complement, which we call “other sector”. We find that XCO2 measurements alone provide a powerful constraint on emissions from larger power plants and a constraint on emissions from the other sector that increases when aggregated to larger spatial scales. The MAP improves the impact of the CO2M measurements for all power plants and for the other sector on all spatial scales. Over our study domain, the impact of the MAP is particularly high in winter. NO2 measurements provide a powerful additional constraint on the emissions from power plants and from the other sector.</p>
Wildfire damage is expected to increase under climate warming. Research now suggests that increas... more Wildfire damage is expected to increase under climate warming. Research now suggests that increased human exposure to wildfires will be driven primarily by population growth in areas with frequent wildfires, rather than by a general increase in fire area.
Abstract We present two novel earth observation products derived from the BESD and EMMA XCO2 prod... more Abstract We present two novel earth observation products derived from the BESD and EMMA XCO2 products which were respectively retrieved from SCIAMACHY and GOSAT observations within the GreenHouse Gas project of ESA's Climate Change Initiative (GHG-CCI). These products are inferred by a Carbon Cycle Data Assimilation System (CCDAS) and consist of net and gross biosphere-atmosphere fluxes of carbon dioxide on a global 0.5° grid. As a further dataset provided by the CCI, the burnt area product developed by its Fire忌i project was used in the CCDAS to prescribe the emission component from biomass burning. The new flux products are provided with per-pixel uncertainty ranges. Fluxes with uncertainty ranges can also be provided aggregated in space and time, e.g. over given regions or as annual means. For both, posterior flux fields inferred from BESD and EMMA products, transport model simulations show reasonable agreement with the atmospheric carbon dioxide concentration observed at flask sampling stations. This means that the information provided by the terrestrial and transport models, the respective GHG ECV product, the burnt area ECV product, a product of the Fraction of Absorbed Photosynthetically Active Radiation used to drive the model, and the atmospheric flask samples is largely consistent. The most prominent feature in the posterior net flux is the tropical source of CO2 inferred from both products. But for the EMMA product this release, especially over South America, is with 300 gC/m2/year much more pronounced than for BESD. This confirms findings by a recent intercomparison of transport inversions using GOSAT data by Houweling et al. (2015) . The reason for the larger net flux is increased heterotrophic respiration. For both products the posterior 2010 sink over Europe (without Russia) is in the range of a recent compilation of European flux estimates by Reuter et al. (2016b) . The posterior 2010 uptake of Australia (including Oceania) inferred from the EMMA product is 1.3 ± 0.2 PgC/year and appears to confirm the high sink also derived from GOSAT by Detmers et al. (2015) over a slightly different period and area. While for some regions (USA, Canada, Europe, Russia, Asia) the one standard deviation uncertainty ranges derived from BESD and EMMA do overlap, for some other regions (Brazil, Africa, Australia) this is not the case. It is not clear yet whether this is due to the uncertainty specifications in the respective products or the handling of uncertainty in the assimilation chain. Assumptions on correlation of observational uncertainty in space and time have a considerable impact on the inferred flux fields (≈ 60 gC/m2/year). The effect of adding an uncertainty that approximates the error in the retrieval system is of similar size.
Wildfires are by far the largest contributor to global biomass burning and constitute a large glo... more Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO<sub>2</sub> fertilisation of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.</p><p class="p"&g...
Wildfires are by far the largest contributor to global biomass burning and constitute a large glo... more Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO<sub>2</sub> fertilization of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.…
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and c... more Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project…
This paper describes the construction and application of a terrestrial carbon cycle assimilation/... more This paper describes the construction and application of a terrestrial carbon cycle assimilation/prediction scheme. In the assimilation step, we constrain the parameters in a terrestrial biosphere model subject to observations. We demonstrate the technique using atmospheric CO2 concentration observations and satellite estimates of greenness. The method returns not only the values of the parameters but an estimate of their uncertainties. In the prediction step we can use these parameters and their uncertainties to either predict the future behaviour of the terrestrial biosphere or to test the model against data not used in the assimilation. The method relies heavily on the automatic generation of tangent linear and adjoint models for the optimization and uncertainty propagation steps. 1.
Currently available global and regional inventories of biomass burning emissions of gases and par... more Currently available global and regional inventories of biomass burning emissions of gases and particles were compared over the 20th century until the year 2014. Considered datasets were created based on different approaches to emission estimation, such as historical reconstruction of burnt area, use of satellite products for burnt area, active fire data, fire radiative power, fixed or dynamical land cover and associated parameters as well as fire emission models in combination with land surface model. We compare annual totals and seasonal variation of emissions of total carbon in 14 geographical regions from the following data sets: ACCMIP, AMMABB, FINN, GFAS, GFED, GICC, MACCity, QFED and RETRO. This comparison study informs about differences among the datasets and serves as a basis for the community effort in harmonizing and creating a consistent inventory spanning through the studied period. For most of the 20th century the inventory will need to rely on the fire emission models ...
We develop a simple, globally uniform model of CO; exchange between the atmosphere and the terres... more We develop a simple, globally uniform model of CO; exchange between the atmosphere and the terrestrial biosphere by coupling the model with a threedimensional atmospheric tracer transport model using observed winds, and checking results against observed concentrations of C02 at various monitoring sites. C02 fluxes are derived from observed greenness using satellite-derived Global Vegetation Index data, combined with observations of temperature, radiation. and precipitation. We explore a range of C02 flux formulations together with some modifications of the modelled atmospheric transport. It appears that the seasonality of net C02 fluxes in the tropics, which would be expected to be driven by water availability, is remarkably small, because C02 uptake and release are reduced simultaneously during the dry season. Consequently, tropical vegetation contributes only very little to the seaonal cycle of atmospheric C102, which is dominated by northern temperate and boreal vegetation, where...
Climatic fire danger will likely increase because more droughts and heat-waves are caused by clim... more Climatic fire danger will likely increase because more droughts and heat-waves are caused by climate change. Climate change can shift fires from occurring only rarely to regularly in ecosystems not until now adapted to fire. We applied dynamic vegetation-fire models to investigate these future responses. The future of fire in Mediterranean-type ecosystems depends strongly on changes in vegetation productivity, thus fuel availability, if burned area increases as much as fire danger. Temperate ecosystems might be exposed to Mediterranean-like fire regimes. In high altitudes, Mediterranean trees might migrate up-hill and cause feedbacks between diversity and fire under climate change.
ABSTRACT Various indirect methods suggest that much of the year-year variability in the growth-ra... more ABSTRACT Various indirect methods suggest that much of the year-year variability in the growth-rate of atmospheric CO2 over the last two decades is attributable to variability in the net terrestrial flux. It is much less clear which processes are responsible for this terrestrial variability. In this talk we present results from a carbon cycle data assimilation system (CCDAS) in which the controlling parameters in a terrestrial carbon cycle model are inferred by nonlinear optimization based on the model&#39;s adjoint. Uncertainties in the parameters are inferred from observational and model uncertainties via the model&#39;s Hessian and then mapped forward on predicted quantities such as net CO2 fluxes to the atmosphere via the model&#39;s Jacobian. The adjoint, Hessian, and Jacobian are generated by automatic differentiation of the model&#39;s source code. The dataset is the set of extended CO2 concentration records from 41 observing sites. The model is able to fit the observations moderately well although it slightly overpredicts the long-term growth rate. This occurs despite the increase in terrestrial uptake through the 1990s over the 1980s. The increase, in turn, occurs despite a reduction in net primary productivity and is hence caused by a larger decrease in soil respiration. It appears that the requirement to fit both the seasonal cycle and interannual dynamics in the CO2 record is a strong constraint on model formulation. We will demonstrate this by describing some of the problems with the description of respiration which are highlighted by this approach.
(3) Abstract. Each manuscript must have an abstract that clearly describes the paper and is no mo... more (3) Abstract. Each manuscript must have an abstract that clearly describes the paper and is no more than 150 words long. (4) Index Terms. At least one and up to five numerical index terms must be provided when submitting the article. See http://publications.agu.org/ author-resource-center/author-guide/index-terms/ for current index terms.
Photosynthetic capacity is one of the most sensitive parameters of terrestrial biosphere models w... more Photosynthetic capacity is one of the most sensitive parameters of terrestrial biosphere models whose representation in global scale simulations has been severely hampered by a lack of systematic analyses using a sufficiently broad database. Due to its coupling to stomatal conductance changes in the parameterisation of photosynthetic capacity may potentially influence transpiration rates and vegetation surface temperature. Here, we provide
The current and future strength of the terrestrial carbon sink has a crucial influence on the exp... more The current and future strength of the terrestrial carbon sink has a crucial influence on the expected degree of climate warming humanity is going to face. Usually, Earth Observation (EO) by its very nature focuses on diagnosing the current state of the planet. However, it is possible to use EO products in data assimilation systems to improve not only the diagnostics of the current state, but also the accuracy of future predictions. This contribution reports from an on-going ESA funded study (see http://rs.ccdas.org) in which the MERIS FAPAR product is assimilated into a terrestrial biosphere model within the global Carbon Cycle Data Assimilation System (see http://CCDAS.org). Using methods of variational data assimilation, CCDAS relies on first and second derivatives of the underlying model for estimating process parameters with uncertainty ranges. In a subsequent step these parameter uncertainties are mapped forward onto uncertainty ranges for predicted carbon fluxes. In this cont...
This contribution gives an overview of the Medium Resolution Imaging Spectrometer (MERIS) global ... more This contribution gives an overview of the Medium Resolution Imaging Spectrometer (MERIS) global land product corresponding to the biophysical variable of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). This product can be used in large- scale biosphere modeling for better estimating the carbon fluxes since they directly represent the amount of solar energy which serves as a 'battery' during the photosynthetic process. The daily FAPAR value is operationally estimated from MERIS data 1 and the (demonstration) global products, recently produced at European Space Research Institute (ESRIN) by the grid on demand system 2 , are first compared against the Joint Research Centre (JRC) SeaWiFS global datasets which is
&amp;amp;amp;amp;lt;p&amp;amp;amp;amp;gt;The Paris Agreement foresees to establish a tran... more &amp;amp;amp;amp;lt;p&amp;amp;amp;amp;gt;The Paris Agreement foresees to establish a transparency framework that builds upon inventory-based national greenhouse gas emission reports, complemented by independent emission estimates derived from atmospheric measurements through inverse modelling. The capability of such a Monitoring and Verification Support (MVS) capacity to constrain fossil fuel emissions to a sufficient extent has not yet been assessed. The CO2 Monitoring Mission (CO2M), planned as a constellation of satellites measuring column-integrated atmospheric CO2 concentration (XCO2), is expected to become a key component of an MVS capacity.&amp;amp;amp;amp;amp;#160;&amp;amp;amp;amp;lt;/p&amp;amp;amp;amp;gt;&amp;amp;amp;amp;lt;p&amp;amp;amp;amp;gt;Here we present a CCFFDAS that operates at the resolution of the CO2M sensor, i.e. 2km by 2km, over a 200 km by 200 km region around Berlin. It combines models of sectorial fossil fuel CO2 emissions and biospheric fluxes with the Community Multiscale Air Quality model (coupled to a model of the plume rise from large power plants) as observation operator for XCO2 and tropospheric column NO2 measurements. Inflow from the domain boundaries is treated as extra unknown to be solved for by the CCFFDAS, which also includes prior information on the process model parameters. We discuss the sensitivities (Jacobian matrix) of simulated XCO2 and NO2 troposheric columns with respect to a) emissions from power plants, b) emissions from the surface and c) the lateral inflow and quantify the respective contributions to the observed signal. The Jacobian representation of the complete modelling chain allows us to evaluate data sets of simulated random and systematic CO2M errors in terms of posterior uncertainties in sectorial fossil fuel emissions. We provide assessments of XCO2 alone and in combination with NO2 on the posterior uncertainty in sectorial fossil fuel emissions for two 1-day study periods, one in winter and one in summer. We quantify the added value of the observations for emissions at a single point, at the 2km by 2km scale, at the scale of Berlin districts, and for &amp;amp;amp;amp;amp;#160;Berlin and further cities in our domain. This means the assessments include temporal and spatial scales typically not covered by inventories. Further, we quantify the effect of better information of atmospheric aerosol, provided by a multi-angular polarimeter (MAP) onboard CO2M, on the posterior uncertainties.&amp;amp;amp;amp;lt;/p&amp;amp;amp;amp;gt;&amp;amp;amp;amp;lt;p&amp;amp;amp;amp;gt;The assessments differentiate the fossil fuel CO2 emissions into two sectors, an energy generation sector (power plants) and the complement, which we call &amp;amp;amp;amp;amp;#8220;other sector&amp;amp;amp;amp;amp;#8221;. We find that XCO2 measurements alone provide a powerful constraint on emissions from larger power plants and a constraint on emissions from the other sector that increases when aggregated to larger spatial scales. The MAP improves the impact of the CO2M measurements for all power plants and for the other sector on all spatial scales. Over our study domain, the impact of the MAP is particularly high in winter. NO2 measurements provide a powerful additional constraint on the emissions from power plants and from the other sector.&amp;amp;amp;amp;lt;/p&amp;amp;amp;amp;gt;
Wildfire damage is expected to increase under climate warming. Research now suggests that increas... more Wildfire damage is expected to increase under climate warming. Research now suggests that increased human exposure to wildfires will be driven primarily by population growth in areas with frequent wildfires, rather than by a general increase in fire area.
Abstract We present two novel earth observation products derived from the BESD and EMMA XCO2 prod... more Abstract We present two novel earth observation products derived from the BESD and EMMA XCO2 products which were respectively retrieved from SCIAMACHY and GOSAT observations within the GreenHouse Gas project of ESA's Climate Change Initiative (GHG-CCI). These products are inferred by a Carbon Cycle Data Assimilation System (CCDAS) and consist of net and gross biosphere-atmosphere fluxes of carbon dioxide on a global 0.5° grid. As a further dataset provided by the CCI, the burnt area product developed by its Fire忌i project was used in the CCDAS to prescribe the emission component from biomass burning. The new flux products are provided with per-pixel uncertainty ranges. Fluxes with uncertainty ranges can also be provided aggregated in space and time, e.g. over given regions or as annual means. For both, posterior flux fields inferred from BESD and EMMA products, transport model simulations show reasonable agreement with the atmospheric carbon dioxide concentration observed at flask sampling stations. This means that the information provided by the terrestrial and transport models, the respective GHG ECV product, the burnt area ECV product, a product of the Fraction of Absorbed Photosynthetically Active Radiation used to drive the model, and the atmospheric flask samples is largely consistent. The most prominent feature in the posterior net flux is the tropical source of CO2 inferred from both products. But for the EMMA product this release, especially over South America, is with 300 gC/m2/year much more pronounced than for BESD. This confirms findings by a recent intercomparison of transport inversions using GOSAT data by Houweling et al. (2015) . The reason for the larger net flux is increased heterotrophic respiration. For both products the posterior 2010 sink over Europe (without Russia) is in the range of a recent compilation of European flux estimates by Reuter et al. (2016b) . The posterior 2010 uptake of Australia (including Oceania) inferred from the EMMA product is 1.3 ± 0.2 PgC/year and appears to confirm the high sink also derived from GOSAT by Detmers et al. (2015) over a slightly different period and area. While for some regions (USA, Canada, Europe, Russia, Asia) the one standard deviation uncertainty ranges derived from BESD and EMMA do overlap, for some other regions (Brazil, Africa, Australia) this is not the case. It is not clear yet whether this is due to the uncertainty specifications in the respective products or the handling of uncertainty in the assimilation chain. Assumptions on correlation of observational uncertainty in space and time have a considerable impact on the inferred flux fields (≈ 60 gC/m2/year). The effect of adding an uncertainty that approximates the error in the retrieval system is of similar size.
Wildfires are by far the largest contributor to global biomass burning and constitute a large glo... more Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO<sub>2</sub> fertilisation of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.</p><p class="p"&g...
Wildfires are by far the largest contributor to global biomass burning and constitute a large glo... more Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO<sub>2</sub> fertilization of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.…
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and c... more Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project…
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