"Data Assimilation in Carbon Cycle Science"; Edinburgh, 9-11 May 2006.
Presentations
Martin Heimann, MPI. Carbon data assimilation, a challenge of integrating heterogeneous data streams;
Peter Rayner, LSCE, Paris. The Anatomy of a carbon-cycle data assimilation system;
Marko Scholze, QUEST, Bristol. Results from the Carbon Cycle Data Assimilation System (CCDAS) ;
Sarah Dance, University of Reading. Data Assimilation Theory and Practice: Lessons learned from the Atmosphere ;
Keith Haines, University of Reading. Budgets and Bias in the context of data assimilation problems ;
Ed Rastetter, MBL, Woods Hole. Developing and testing mechanistic models of terrestrial carbon cycling using time-series data;.
Mathew Williams, CTCD, University of Edinburgh. What can model-data fusion really tell us about the terrestrial C cycle? ;
Mike Raupach, CSIRO, Canberra. Data assimilation into terrestrial biosphere models: exploiting mutual constraints among the carbon, water and energy cycles;
Shaun Quegan, CTCD, University of Sheffield. Assimilating satellite observations of land surface properties into carbon models;
Nadine Gobron, JRC, Italy. A global validated dataset of EO surface radiation fluxes for applications in climate/carbon modelling;
Markus Reichstein, MPI, Jena. On the assimilation of eddy covariance and optical remote sensing data for biogeochemical modelling;
Richard Engelen & Tony Hollingsworth, ECMWF Global Earth-system Modelling using Space and in-situ data (GEMS): progress so far and review of satellite data provision;
Bill Emanuel and Steve Pawson, NASA Overview of NASA Research in Carbon Data Fusion and Data assimilation"
Phillipe Ciais & Shilong Piao, LSCE Interannual and decadal changes in the seasonal activity of CO2 fluxes : The critical role of Autumn temperatures;.
David Crisp, JPL. "The Orbiting Carbon Observatory: Sampling Approach and Anticipated Data Products;
Chris Barnet, NOAA/NESDIS. The challenges in using atmospheric trace gas products from operational thermal sounders;
Shamil Maksyutov, NIES, Japan .Plans for operational GOSAT data analysis at NIES;
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