IRCEB: Biological Control of Terrestrial Carbon Fluxes

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9977066OjimaFrom a global perspective, understanding the role of terrestrial ecosystems in the carbon cycle is crucial to quantifying carbon storage. Great progress has been made in recent years in measurement networks (LTER and AmeriFLUX), in the re-analysis of inventory data, and in modeling relevant to carbon budgets at large spatial scales. In addition, 'inverse' analyses of atmospheric data are beginning to provide information on continental scales. In this IRCEB research project, we will develop an integrated data-model system to analyze consequences of different assumptions about biology and land management on patterns of CO2 in the atmosphere. This is a powerful complement to traditional model testing against site-specific data, but the development of measurement networks and gradient studies greatly improves the power of in situ data-model comparisons. The time is ripe for an ambitious, integrated, analysis of terrestrial ecosystems and the carbon cycle. This project focuses on the conterminous US, an area where data resources and validation information are unparalleled, and an area diverse enough to seriously challenge our understanding while remaining tractable. This project has three integrated components: (1) The implementation of a new framework to analyze processes controlling net carbon exchange based on recent advances of ecosystem models, process studies, and analytical technologies. The project will develop a modular framework linking disturbance and land use to life form distribution and biogeochemistry, in order to provide a comprehensive way to examine and estimate terrestrial net carbon exchanges. This framework will be developed by our team, but with input from colleagues and potential users on a regular basis. The model will be a 'community' model designed to be operated on multiple platforms and remotely. Both the model code and large output data sets from important experiments will be made available, with documentation and metadata. This model will take advantage of lessons learned by the participants and will use science from extant models. However, rather than simply 'linking' extant models, we will integrate key components and processes to evaluate changes in terrestrial carbon fluxes. (2) The development of the data sets needed to operate the model. These will include soils, meteorology and land use histories. The main emphasis in the data activity will be the development of spatial land use histories containing sufficient information to operate the model. This activity will draw on existing efforts and, as a huge task, will be progressively improved over time. (3) The analysis of the US carbon budget. We will begin by evaluating our model system against 'traditional' in situ observations such as NPP, soil carbon/biomass data. We will then integrate the continental model and compare the simulated patterns of atmospheric CO2 against observations. This will require coupling the terrestrial model and estimated spatial/seasonal fossil fuel fluxes to an atmospheric model. We will used a well-tested model (RAMS) operated in a 'data assimilation mode', a mathematical approach where the model is continuously adjusted to observations of key variables widely used in forecast studies. Data assimilation is a mature technology in the atmospheric sciences and will permit the model to produce transport winds, turbulent fluxes, and weather close to observed conditions. This will make both the weather used as input to the ecosystem model and the transport used to compare simulated to observed CO2 consistent and close to reality.