Recent Advances and Future Directions in Data-Model Integration: Approaches for Improving Predictive Understanding in the Biogeosciences

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Session ID#: 29270

Session Description:
Terrestrial biogeochemical studies have increasingly focused on making quantitative forecasts, taking advantage of substantial increases in data availability, surges in computational capability and advances in terrestrial biosphere models. However, major uncertainties remain in current and future projections associated with these models. Data-model integration can lead to more realistic model projections, as data can be used to improve model boundary conditions, structures and parameterization, and models provide experimentalists with thorough and timely information for assessing and adjusting potential experimental designs. This session aims to include presentations on efforts to better understand terrestrial biogeochemical, water and energy cycles, especially in response to global change, through data-model integration. We therefore invite contributions from both experimentalists and modelers who share interests in diagnosing and reducing model uncertainty and improving our predictive understanding of responses of biogeochemical, water and energy cycles to global change using a wide range of data and novel, multidisciplinary approaches.
Primary Convener:  Natasha MacBean, University of Arizona, School of Natural Resources and the Environment, Tucson, AZ, United States
Conveners:  Lifen Jiang, University of Oklahoma Norman Campus, Norman, OK, United States, Istem Fer, Boston University, Earth and Environment, Boston, MA, United States and Margaret S Torn, Lawrence Berkeley National Laboratory, Berkeley, CA, United States

  • A - Atmospheric Sciences
  • GC - Global Environmental Change
  • H - Hydrology

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