School of Earth Sciences - Research Publications
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ItemUncertainty in temperature projections reduced using carbon cycle and climate observations(Nature Research, 2013-08-01)The future behaviour of the carbon cycle is a major contributor to uncertainty in temperature projections for the twenty-first century1,2. Using a simplified climate model3, we show that, for a given emission scenario, it is the second most important contributor to this uncertainty after climate sensitivity, followed by aerosol impacts. Historical measurements of carbon dioxide concentrations4 have been used along with global temperature observations5 to help reduce this uncertainty. This results in an increased probability of exceeding a 2 °C global–mean temperature increase by 2100 while reducing the probability of surpassing a 6 °C threshold for non-mitigation scenarios such as the Special Report on Emissions Scenarios A1B and A1FI scenarios6, as compared with projections from the Fourth Assessment Report7 of the Intergovernmental Panel on Climate Change. Climate sensitivity, the response of the carbon cycle and aerosol effects remain highly uncertain but historical observations of temperature and carbon dioxide imply a trade–off between them so that temperature projections are more certain than they would be considering each factor in isolation. As well as pointing out the promise from the formal use of observational constraints in climate projection, this also highlights the need for an holistic view of uncertainty.
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ItemEstimating CO<sub>2</sub> emissions from point sources: a case study of an isolated power station(Copernicus Publications, 2014-12-15)Abstract. A methodology to estimate CO2 emissions from an isolated power plant is presented and illustrated for the Northern Power Station at Port Augusta, South Australia. The method involves measurement of in-situ and column-averaged CO2 at a site near the power plant, forward modelling (using WRF-Chem) of the observed signals and inverse modelling to obtain an estimate of the fluxes from the power plant. By subtracting the simulated background CO2 (obtained from Monitoring Atmospheric Composition and Climate CO2 fields) from the observed and simulated signals, we are able to account for fluxes from the power plant that are mainly responsible for the variations in the CO2 concentrations. Although the enhancements of the surface concentration of CO2 are a factor of 10 larger than the enhancements in the column-averaged concentration, the forward transport model has difficulty predicting the in-situ data, which is complicated by sea breeze effects and influence from other local sources. Better simulation is obtained for the column-averaged data leading to better estimates of fluxes. The ratio of our estimated emissions to the reported values is 1.06 ± 0.54. Modelling local biospheric fluxes makes little difference either to the estimated emissions or quality of the fit to the data. Variations in the large-scale concentration field have a larger impact highlighting the importance of good boundary conditions even in the relatively homogeneous Southern Hemisphere. The estimates are insensitive to details of the calculation such as stack height or modelling of plume injection. We conclude that column-integrated measurements offer a reasonable trade-off between sensitivity and model capability for estimating point sources.
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ItemConstraining regional greenhouse gas emissions using geostationary concentration measurements: a theoretical study(COPERNICUS GESELLSCHAFT MBH, 2014)Abstract. We investigate the ability of column-integrated trace gas measurements from a geostationary satellite to constrain surface fluxes at regional scale. The proposed GEOCARB instrument measures CO2, CO and CH4 at a maximum resolution of 3 km east–west × 2.7 km north–south. Precisions are 3 ppm for CO2, 10 ppb for CO and 18 ppb for CH4. Sampling frequency is flexible. Here we sample a region at the location of Shanghai every 2 daylight hours for 6 days in June. We test the observing system by calculating the posterior uncertainty covariance of fluxes. We are able to constrain urban emissions at 3 km resolution including an isolated power plant. The CO measurement plays the strongest role; without it our effective resolution falls to 5 km. Methane fluxes are similarly well estimated at 5 km resolution. Estimating the errors for a full year suggests such an instrument would be a useful tool for both science and policy applications.
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ItemSensitivity of simulated CO2 concentration to regridding of global fossil fuel CO2 emissions(COPERNICUS GESELLSCHAFT MBH, 2014)Abstract. Errors in the specification or utilization of fossil fuel CO2 emissions within carbon budget or atmospheric CO2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO2 emissions (FFCO2) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO2 concentration driven by two different approaches to regridding fossil fuel CO2 emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell−1 yr−1 (−3.39 kgC m−2 yr−1) to +30.0 TgC grid cell−1 yr−1 (+2.6 kgC m−2 yr−1) along coastal margins. Maximum simulated annual mean CO2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO2 concentration, such as atmospheric CO2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.
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ItemGreenhouse gas network design using backward Lagrangian particle dispersion modelling - Part 1: Methodology and Australian test case(COPERNICUS GESELLSCHAFT MBH, 2014)Abstract. This paper describes the generation of optimal atmospheric measurement networks for determining carbon dioxide fluxes over Australia using inverse methods. A Lagrangian particle dispersion model is used in reverse mode together with a Bayesian inverse modelling framework to calculate the relationship between weekly surface fluxes, comprising contributions from the biosphere and fossil fuel combustion, and hourly concentration observations for the Australian continent. Meteorological driving fields are provided by the regional version of the Australian Community Climate and Earth System Simulator (ACCESS) at 12 km resolution at an hourly timescale. Prior uncertainties are derived on a weekly timescale for biosphere fluxes and fossil fuel emissions from high-resolution model runs using the Community Atmosphere Biosphere Land Exchange (CABLE) model and the Fossil Fuel Data Assimilation System (FFDAS) respectively. The influence from outside the modelled domain is investigated, but proves to be negligible for the network design. Existing ground-based measurement stations in Australia are assessed in terms of their ability to constrain local flux estimates from the land. We find that the six stations that are currently operational are already able to reduce the uncertainties on surface flux estimates by about 30%. A candidate list of 59 stations is generated based on logistic constraints and an incremental optimisation scheme is used to extend the network of existing stations. In order to achieve an uncertainty reduction of about 50%, we need to double the number of measurement stations in Australia. Assuming equal data uncertainties for all sites, new stations would be mainly located in the northern and eastern part of the continent.
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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.