B43I:
Advances and Opportunities in Forecasting and Data-Model Integration: Approaches for Reducing Complexity and Improving Predictive Understanding in Biogeochemical Models of the Earth System I

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Session ID#: 35461

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 modeling. Process understanding has improved via theoretical and empirical analyses; so too have the methods for incorporating complex biological processes into models. However, major uncertainties remain in current and future projections of feedbacks between the terrestrial biosphere and climate. Many conceptual and technical challenges must be overcome to improve our ability to make predictions, such as the need for improvements in theories and models, data assimilation, targeted reductions in data deficiencies, and the quantification, propagation, and analysis of uncertainties. This session aims to highlight cutting-edge research in terrestrial biosphere modeling and model-data integration, both for reducing model uncertainty and complexity, and for improving our predictive understanding of terrestrial biogeochemical processes in response to global change.
Primary Convener:  Natasha MacBean, Western University, Department of Geography & Environment and Department of Biology, London, Canada
Conveners:  Michael Dietze, Boston University, Boston, MA, United States, Lifen Jiang, Northern Arizona University, Flagstaff, AZ, United States and Istem Fer, Boston University, Earth and Environment, Boston, MA, United States
Chairs:  Istem Fer, Boston University, Earth and Environment, Boston, MA, United States, Lifen Jiang, Northern Arizona University, Flagstaff, AZ, United States, Natasha MacBean, Western University, Department of Geography & Environment and Department of Biology, London, Canada and Margaret S Torn, Berkeley Lab/UC Berkeley, Berkeley, United States
OSPA Liaison:  Istem Fer, Boston University, Earth and Environment, Boston, MA, United States

Cross-Listed:
  • A - Atmospheric Sciences
  • GC - Global Environmental Change
Index Terms:

0414 Biogeochemical cycles, processes, and modeling [BIOGEOSCIENCES]
0430 Computational methods and data processing [BIOGEOSCIENCES]
0439 Ecosystems, structure and dynamics [BIOGEOSCIENCES]
1910 Data assimilation, integration and fusion [INFORMATICS]

Abstracts Submitted to this Session:

EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model (Invited) (284366)
Shuang Ma1, Yuanyuan Huang2,3, Mark Stacy4, Jiang Jiang5,6, Nilutpal Sundi7, Daniel M Ricciuto8, Paul J Hanson9, Yiqi Luo6,10 and Volodymyr Saruta6, (1)Northern Arizona University, Flagstaff, United States, (2)LSCE Laboratoire des Sciences du Climat et de l'Environnement, Gif-Sur-Yvette Cedex, France, (3)Northern Arizona University, The Center for Ecosystem Science and Society at NAU, Flagstaff, United States, (4)University of Oklahoma Information Technology, Norman, United States, (5)Nanjing Forestry University, Department of Soil and Water Conservation, Nanjing, China, (6)Northern Arizona University, The Center for Ecosystem Science and Society at NAU, Flagstaff, AZ, United States, (7)University of Oklahoma Norman Campus, Department of Computer Science, Norman, OK, United States, (8)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (9)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, United States, (10)Tsinghua University, Department of Earth System Science, Beijing, China
Ten years of multiple data stream assimilation with the ORCHIDEE land surface model to improve regional to global simulated carbon budgets: synthesis and perspectives on directions for the future (230174)
Philippe P Peylin, CNRS, Paris Cedex 16, France, Cédric Bacour, Noveltis, Labège, France, Natasha MacBean, Western University, Department of Geography & Environment and Department of Biology, London, Canada, Fabienne Maignan, CEA Saclay DSM / LSCE, Gif sur Yvette, France, Vladislav Bastrikov, LSCE Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France and Frederic Chevallier, LSCE Laboratoire des Sciences du Climat et de l'Environnement, Gif-Sur-Yvette Cedex, France
Initializing carbon cycle predictions from the Community Land Model by assimilating global biomass observations (Invited) (208037)
Andrew M Fox, NASA Goddard Space Flight Center, Greenbelt, United States, Timothy J Hoar, NCAR, Boulder, CO, United States, William Kolby Smith, University of Arizona, Tucson, AZ, United States and David JP Moore, University of Arizona, School of Natural Resources and the Environment, Tucson, AZ, United States
A multi-model assessment of terrestrial biosphere model data needs (289754)
Anthony Gardella1, Elizabeth (Betsy) Cowdery1, Martin Gerard De Kauwe2, Ankur R Desai3, Matthew Duveneck4, Istem Fer5, Rosie Fisher6, Ryan G Knox7, Rob Kooper8, David LeBauer9, Tess McCabe1, Francesco Minunno10, Ann Raiho11, Dr. Shawn Serbin, BA, MS, PhD12, Alexey N Shiklomanov1, Anne Thomas13, Anthony Walker14, Michael Dietze1 and PEcAn Team, (1)Boston University, Boston, MA, United States, (2)University of Bristol, School of Biological Sciences, Bristol, United Kingdom, (3)University of Wisconsin Madison, Atmospheric and Oceanic Sciences, Madison, WI, United States, (4)Harvard University, Harvard Forest, Petersham, MA, United States, (5)Boston University, Earth and Environment, Boston, MA, United States, (6)National Center for Atmospheric Research, Boulder, CO, United States, (7)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (8)National Center for Super Computing Applications, Urbana, United States, (9)Energy Biosciences Institute, Urbana, IL, United States, (10)University of Helsinki, Helsinki, Finland, (11)Funga PBC, Austin, United States, (12)Brookhaven National Laboratory, Environmental Science and Technologies Department, Upton, United States, (13)Brigham Young University, Provo, UT, United States, (14)Oak Ridge National Laboratory, Oak Ridge, TN, United States
Multi-Hypothesis Modelling Capabilities for Robust Data-Model Integration (Invited) (244648)
Anthony P Walker1, Martin Gerard De Kauwe2, Dan Lu1, Belinda Medlyn3, Richard J. Norby4, Daniel M Ricciuto5, Alistair Rogers6, Dr. Shawn Serbin, BA, MS, PhD7, David J Weston1, Ming Ye8 and Sönke Zaehle9, (1)Oak Ridge National Laboratory, Oak Ridge, TN, United States, (2)University of Bristol, School of Biological Sciences, Bristol, United Kingdom, (3)Western Sydney University, Hawkesbury Institute for the Environment, Penrith, NSW, Australia, (4)Oak Ridge National Lab, Oak Ridge, TN, United States, (5)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, TN, United States, (6)Brookhaven National Laboratory, Environmental and Climate Sciences Department, Upton, United States, (7)Brookhaven National Laboratory, Environmental Science and Technologies Department, Upton, United States, (8)Florida State University, Earth, Ocean, and Atmospheric Science, Tallahassee, United States, (9)Max Planck Institute for Biogeochemistry, Jena, Germany
Getting beyond hand-waving about microsites with numerical representations of trace gas production and consumption (268090)
Debjani Sihi, University of Maryland Center for Environmental Science Appalachian Laboratory, Frostburg, MD, United States, Eric A Davidson, University of Maryland Center (UMCES) for Environmental Science, Frostburg, United States, Kathleen E Savage, Woodwell Climate Research Center, Falmouth, United States and Dong Liang, College of Urban and Environmental Sciences, Northwest University, Xi'an, China
The role of ecosystem memory in predicting inter-annual variations of the tropical carbon balance. (Invited) (287183)
A. Anthony Bloom1, Junjie Liu2, Kevin W Bowman3, Alexandra G Konings4, Sassan Saatchi3, John R Worden5, Helen Marie Worden6, Zhe Jiang7, Nicholas Parazoo8, Mathew Williams9 and David Schimel2, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, (3)NASA Jet Propulsion Laboratory, Pasadena, United States, (4)Stanford University, Earth System Science, Stanford, CA, United States, (5)Jet Propulsion Laboratory, Pasadena, CA, United States, (6)NSF National Center for Atmospheric Research (NSF NCAR), Atmospheric Chemistry Observations & Modeling Laboratory (ACOM), Boulder, CO, United States, (7)University Corporation for Atmospheric Research, Boulder, CO, United States, (8)Colorado State University, Fort Collins, CO, United States, (9)University of Edinburgh, School of GeoSciences, Edinburgh, United Kingdom
Improving Estimates and Forecasts of Lake Carbon Pools and Fluxes Using Data Assimilation (218389)
Jacob A Zwart, USGS Wisconsin Water Science Center, Middleton, WI, United States, Oleksandra Hararuk, Natural Resources Canada - Canadian Forest Service, Victoria, BC, Canada, Yves Prairie, Groupe de Recherche Interuniversitaire en Limnologie, Montréal, QC, Canada, Chris Solomon, Cary Institute of Ecosystem Studies, Millbrook, NY, United States and Stuart Jones, University of Notre Dame, Biological Sciences, Notre Dame, United States

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