This project has received funding from the European Community's Seventh Framework Program (FP7/2007-2013) under grant agreement nº265178

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Carbon scenario_______________________________

The Carbon cycle scenario is based on the following user story: in the process of updating the emission thresholds and mitigation strategies for the Kyoto protocol, the generation of carbon cycle products (in particular carbon flux products) provides scientific data for decision makers. We have imagined a period in which negotiations on emission thresholds and international agreements are discussed, searching the establishment of mitigation strategies and emission trading rules.

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In the Carbon flux and budgets estimation there is a high diversity of data sources (space agencies, in situ laboratories, statistical agencies, meteorological institutes, green house gases metrology institutes). From sources compilation and collocation, direct terrestrial and oceanic carbon models are derived encapsulating natural and human induced processes through which land ecosystems absorb and emit CO2. For producing global CO2 flux maps, a terrestrial carbon model generally needs soils and vegetation maps, and climate drivers on a global grid, leading to prior fluxes estimation.

Next, statistical methods are used to combine available information (prior fluxes, observations of atmospheric trace gas concentrations, chemistry and transport model) to estimate fluxes by an inverse procedure, resulting in optimized carbon fluxes estimation. Using the information contained in observed concentration fields from ground based networks and from upcoming satellite observations in order to constrain the geographic distribution of surface fluxes is an inverse problem, which consists in finding a set of fluxes which optimally matches the available observations. The application of inverse methods enables the quantification of the distribution of the sources and sinks of CO2 at the surface of the Earth based upon global measurements of atmospheric concentration and three-dimensional models of the atmospheric transport. Top-down atmospheric inversion methods in terms of numerical transport modeling and atmospheric observation networks, and detail some of the currently important issues in prescribing errors are described in the Carbon cycle (Ciais et al. 2008). Model discrepancy and uncertainties assessment and integration contribute to an iterative parameterization of the prior fluxes, resulting in optimized posterior fluxes estimation (i.e., improved correlation to observations).

Flux models can be compared and analysed, detecting trends, anomalies and calculating statistics related to the quality and performance of the models. This process allows for model choice. When several models are selected, model ensembling is attempted. In this manner, carbon products are generated, including models, estimation of fluxes and budgets, maps and uncertainty assessment, which can be exported in different levels of details and complexity.

Input from the scientific side enables quality aware visualization, which is available in the Carbon Atlas portal (that could be an improved version of the actual Carboscope website). Besides, products are registered in GEOSS. Inside GEOSS, the development of quality aware tools is implied, suchlike a model comparison tool that enables the quality model compliance (extensively the GEO Label specifications) and enhanced geosearch capabilities (e.g. cataloguing services, broker, search filters). A technical commitee in charge of the research tasks finds the Carbon Atlas web and sufficient material to provide both technical reports and dissemination material for the media, general public and, most importantly, the national policy maker who in the end can contribute to the final version of the emission market rules agreement and can decide on an actionable scientific base on the best strategy for his country in particular, with a global understanding of the carbon fluxes, the associated uncertainties, and the regional budget knowledge in this country.

 

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