School of Earth Sciences - Research Publications
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ItemA new global gridded data set of CO2 emissions from fossil fuel combustion: methodology and evaluation(American Geophysical Union, 2010)We describe a system for constraining the spatial distribution of fossil fuel emissions of CO2. The system is based on a modified Kaya identity which expresses emissions as a product of areal population density, per capita economic activity, energy intensity of the economy, and carbon intensity of energy. We apply the methodology of data assimilation to constrain such a model with various observations, notably, the statistics of national emissions and data on the distribution of nightlights and population. We hence produce a global, annual emission field at 0.25° resolution. Our distribution of emissions is smoother than that of the population downscaling traditionally used to describe emissions. Comparison with the Vulcan inventory suggests that the assimilated product performs better than downscaling for distributions of either population or nightlights alone for describing the spatial structure of emissions over the United States. We describe the complex structure of uncertainty that arises from combining pointwise and area-integrated constraints. Uncertainties can be as high as 50% at the pixel level and are not spatially independent. We describe the use of 14CO2 measurements to further constrain national emissions. Their value is greatest over large countries with heterogeneous emissions. Generated fields may be found online (http://ffdas.org/).
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ItemA three-dimensional synthesis inversion of the molecular hydrogen cycle: sources and sinks budget and implications for the soil uptake(American Geophysical Union, 2011)Our understanding of the global budget of atmospheric hydrogen (H2) contains large uncertainties. An atmospheric Bayesian inversion of H2 sources and sinks is presented for the period 1991-2004, based on a two networks of flask measurement stations. The types of fluxes and the spatial scales potentially resolvable by the inversion are first estimated from an analysis of the correlations of errors between the different processes and regions emitting or absorbing H2. Then, the estimated budget of H2 and its uncertainties is presented and discussed, for five groups of fluxes and three groups of large regions, in terms of mean fluxes, seasonal and interannual variations, and long-term trends. One main focus of the study is the improvement of the estimate of H2 soil uptake, which is the largest sink of H2. Various sensitivity tests are performed defining an ensemble of more than 20 inversions. We show that inferring a robust estimate of the H2 soil uptake requires to prescribe the prior magnitude of some other sources and sinks with a small uncertainty. Doing so an estimate of the H2 soil uptake of -62 ± 3 Tg y−1 is inferred for the period 1991-2004 (the uncertainty is the residual error after inversion). The inferred soil H2 sink presents a negative long-term trend that is qualitatively consistent with a bottom-up process-based model.
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ItemAtmospheric CO2 inversion validation using vertical profile measurements: analysis of four independent inversion models(American Geophysical Union, 2011)We present the results of a validation of atmospheric inversions of CO2 fluxes using four transport models. Each inversion uses data primarily from surface stations, combined with an atmospheric transport model, to estimate surface fluxes. The validation (or model evaluation) consists of running these optimized fluxes through the forward model and comparing the simulated concentrations with airborne concentration measurements. We focus on profiles from Cape Grim, Tasmania, and Carr, Colorado, while using other profile sites to test the generality of the comparison. Fits to the profiles are generally worse than to the surface data from the inversions and worse than the expected model-data mismatch. Thus inversion estimates are generally not consistent with the profile measurements. The TM3 model does better by some measures than the other three models. Models perform better over Tasmania than Colorado, and other profile sites bear out a general improvement from north to south and from continental to marine locations. There are also errors in the interannual variability of the fit, consistent in time and common across models. This suggests real variations in sources visible to the profile but not the surface measurements.
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ItemOptimal representation of source-sink fluxes for mesoscale carbon dioxide inversion with synthetic data(American Geophysical Union, 2011)The inversion of CO2 surface fluxes from atmospheric concentration measurements involves discretizing the flux domain in time and space. The resolution choice is usually guided by technical considerations despite its impact on the solution to the inversion problem. In our previous studies, a Bayesian formalism has recently been introduced to describe the discretization of the parameter space over a large dictionary of adaptive multiscale grids. In this paper, we exploit this new framework to construct optimal space-time representations of carbon fluxes for mesoscale inversions. Inversions are performed using synthetic continuous hourly CO2 concentration data in the context of the Ring 2 experiment in support of the North American Carbon Program Mid Continent Intensive (MCI). Compared with the regular grid at finest scale, optimal representations can have similar inversion performance with far fewer grid cells. These optimal representations are obtained by maximizing the number of degrees of freedom for the signal (DFS) that measures the information gain from observations to resolve the unknown fluxes. Consequently information from observations can be better propagated within the domain through these optimal representations. For the Ring 2 network of eight towers, in most cases, the DFS value is relatively small compared to the number of observations d (DFS/d < 20%). In this multiscale setting, scale-dependent aggregation errors are identified and explicitly formulated for more reliable inversions. It is recommended that the aggregation errors should be taken into account, especially when the correlations in the errors of a priori fluxes are physically unrealistic. The optimal multiscale grids allow to adaptively mitigate the aggregation errors.
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ItemA European summertime CO2 biogenic flux inversion at mesoscale from continuous in situ mixing ratio measurements(American Geophysical Union, 2011)A regional variational inverse modeling system for the estimation of European biogenic CO2 fluxes is presented. This system is based on a 50 km horizontal resolution configuration of a mesoscale atmospheric transport model and on the adjoint of its tracer transport code. It exploits hourly CO2 in situ data from 15 CarboEurope-Integrated Project stations. Particular attention in the inversion setup is paid to characterizing the transport model error and to selecting the observations to be assimilated as a function of this error. Comparisons between simulations and data of CO2 and 222Rn concentrations indicate that the model errors should have a standard deviation which is less than 7 ppm when simulating the hourly variability of CO2 at low altitude during the afternoon and evening or at high altitude at night. Synthetic data are used to estimate the uncertainty reduction for the fluxes using this inverse modeling system. The improvement brought by the inversion to the prior estimate of the fluxes for both the mean diurnal cycle and the monthly to synoptic variability in the fluxes and associated mixing ratios are checked against independent atmospheric data and eddy covariance flux measurements. Inverse modeling is conducted for summers 2002 - 2007 which should reduce the uncertainty in the biogenic fluxes by ∼60% during this period. The trend in the mean flux corrections between June and September is to increase the uptake of CO2 by ∼12 gCm−2. Corrections at higher resolution are also diagnosed that reveal some limitations of the underlying prior model of the terrestrial biosphere.