Information Theory & Earth Sciences Workshop Programme

Talks

• Branicki, Michal, School of Mathematics & Maxwell Institute, U. Edinburgh, UK; A. J. Majda, Dept. of Mathematics, Courant Institute, NYU, USA. Interplay between information theory, uncertainty quantification, and improving reduced-order predictions.
• Gong, Wei, Junior Research Scientist, GCESS, Beijing Normal University. On the Information in Models: Quantification of model structure adequacy with information based metrics.
• Gupta, Hoshin V., University of Arizona. Information Theory and the Hydrological Sciences: Models, Data, Uncertainty and Learning.
• Jackson, Bethanna, Ilias Pechlivanidis, Hilary McMillan and Hoshin Gupta. Entropy based metrics to evaluate physical models (and data).
• Knuth, Kevin H., Departments of Physics and Informatics University at Albany (SUNY). The Relationship Between Information and Physics.
• Kumar, Praveen and Allison Goodwell. Civil and Environmental Engineering, UIUC, Information sharing in eco-hydrologic systems: synergy, uniqueness, and redundancy.
• Nearing, Grey, National Center for Atmospheric Research, NASA Goddard Space Flight Center, University of Maryland Baltimore County. Information in Models and Data.
• Ruddell, Benjamin L., Dan Childers, Rong Yu, Minseok Kang, and Joon Kim. Climate sensitivity of global terrestrial ecosystems’ subdaily carbon, water, and energy dynamics (an application of information flow process networks).
• Wang, Jingfeng, School of Civil and Environmental Engineering, Georgia Institute of Technology, USA. Maximum Entropy Production Model of Heat Fluxes – An Application of Information Theory in Modeling Earth System.
• Weijs, Steven , University of British Columbia. Information, complexity, description length, data compression and their application in hydrology.
• Wellmann, J. Florian, RWTH Aachen; Mark Lindsay, Mark Jessell, Jonathan Poh, Klaus Regenauer-Lieb, Miguel de la Varga Hormazabal, Simin Huang, Wang Hui, Philipp Schendt, Johannes Aichele. Information Theory and the Analysis of Uncertainties in a Spatial Geological Context.

Posters

• de la Varga, Miguel and Florian Wellmann, The Aachen Institute for Advanced Study in Computational Engineering Science, RWTH Aachen University. Analysis of information correlation in geological models.
• Ehret, Uwe, Karlsruhe Institute of Technology, Institute for Water and River Basin Management. Structogram: A method to quantify the structuredness and complexity of data sets.
• Gong, Wei, College of Global Change and Earth System Science (GCESS), Beijing Normal University and Qingyun Duan, Joint Center for Global Change Studies, Beijing Normal University. Surrogate-based Multi-Objective Optimization and Uncertainty Quantification Methods for Large, Complex Geophysical Models.
• Goodwell, Allison and Praveen Kumar, Both from the Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign. A network approach to determine ecosystem vulnerability.
• Huang, Shih-Yu, School of Civil and Environmental Engineering; Yi Deng, School of Earth and Atmospheric Science; Jingfeng Wang, School of Civil and Environmental Engineering; all from Georgia Institute of Technology, USA. Revisit of the Global Surface Energy Balance Using the MEP Model of Surface Heat Fluxes and Remote Sensing Observations.
• Larsen, Laurel, Mollie van Gordon, Christopher Tennant, Saalem Adera, Dino Bellugi, Hong-xu Ma, All from the Dept. of Geography, University of California, Berkeley; and Theresa Oehmke, Dept. of Civil and Environmental Engineering, University of California, Berkeley. Space in the Informationscape: Resolution of critical spatial scales and functional connectivity in heterogeneous landscapes.
• Marçais, J., Geosciences Rennes (UMR 6118 CNRS), Université de Rennes 1, Campus de Beaulieu; J.-R. de dreuzy, Geosciences Rennes (UMR 6118 CNRS), Université de Rennes 1, Campus de Beaulieu; T. R. Ginn, University of California-Davis, Department of Civil and Environmental Engineering; P. Rousseau-Gueutin, EHESP Rennes, Sorbonne Université Paris; and S. Leraye, IFP Energie Nouvelles. Inferring Transit Times Distributions from atmospheric tracer data: Assessment of the predictive capacities of Lumped Parameter Models on a 3D cristalline aquifer.
• Nijssen, Bart, Civil and Environmental Engineering, University of Washington, USA; Martyn Clark, Research Applications Laboratory, National Center for Atmospheric Research, USA; Gengxin Ou, Civil and Environmental Engineering, University of Washington, USA; Naoki Mizukami, Research Applications Laboratory, National Center for Atmospheric Research, USA; Andrew Newman, Research Applications Laboratory, National Center for Atmospheric Research, USA; Oriana Chegwidden, Civil and Environmental Engineering, University of Washington, USA. Alternative spatial configurations to reflect landscape structure in a hydrological model: SUMMA applications to the Reynolds Creek Watershed and the Columbia River Basin.
• Pande, Saket, Delft University of Technology, Netherlands. Hydrologic model complexity depends on the magnitude of model parameters.
• Pechlivanidis, Ilias G., Swedish Meteorological and Hydrological Institute, Norrköping, Sweden; Hoshin V. Gupta, Department of Hydrology and Water Resources, University of Arizona, USA; and Thomas Bosshard, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden. Identification of representative hydroclimatic projections based on the MIMR concept.
• Sendrowski, Alicia and Paola Passalacqua, Department of Civil, Architechural, and Environmental Engineering, The University of Texas at Austin, USA. Characterizing Delta-Scale Process Connectivity Using Information Theory.
• Tejedor, Alejandro, Department of Civil, Environmental and Geo-Engineering, University of Minnesota, USA; Anthony Longjas, Department of Civil, Environmental and Geo-Engineering, University of Minnesota, USA; Ilya Zaliapin, Department of Mathematics and Statistics, University of Nevada, USA; and Efi Foufoula-Georgiou, Department of Civil, Environmental and Geo-Engineering, University of Minnesota, USA. A Graph-Theoretic Approach to Delta Channel Networks: Entropic assessment of complexity.
• Tennant, Christopher J. and Laurel G. Larsen, University of California – Berkeley. Can causality be detected in noisy environmental systems?