Yu, R., Ruddell, B. L., Kang, M., Kim, J., & Childers, D. (2019). Anticipating global terrestrial ecosystem state change using FLUXNET. Global change biology. https://doi.org/10.1111/gcb.14602 Ecosystems can be characterized as complex systems that traverse a variety of functional and structural states in response to changing bioclimatic forcings. A central challenge of global change biology is the […]
Summer School on Information Theory in the Earth Sciences (3rd-8th June 2019) For more information and to register Information theory provides a powerful conceptual framework for learning, model building, and prediction in the Earth sciences. It extends probability theory in certain important ways that make it particularly applicable to questions related to value and uncertainty […]
Postdoctoral Scholar in Watershed Hydrology/Hydroinformatics The Environmental Systems Dynamics Laboratory (http://esdlberkeley.com) at UC Berkeley seeks a postdoctoral scholar with expertise in data science and hydrology. The position is funded jointly through the Gordon and Betty Moore Foundation Data-Driven Discovery Program and a U.S. Geological Survey Powell Center for Synthesis grant. The position will be focused […]
Prof. Paul Dirmeyer’s GEWEX & GLASS project has posted a list of land-atmosphere coupling metrics, a “cheat sheet”, which includes some information theory metrics. The community may find this useful. http://cola.gmu.edu/dirmeyer/Coupling_metrics.html
Alexia María, IHCantabria Allison Goodwell, University of Colorado at Denver Anneli Guthke, University of Stuttgart Ben Ruddell, Northern Arizona University Benedikt, ETH Zurich Cristina Prieto, IHCantabria Dino Bellugi, University of California at Berkeley Grey Nearing, University of Alabama Hoshin Gupta, University of Arizona Ilias Pechlivanidis, Swedish Meteorological and Hydrological Institute Inmaculada Pulido, Huelva University Jara […]
AGU Session Title: H053. Better Informed than Uncertain: Applications of Information Theory in the Earth Sciences Information Theory (IT) quantifies the information content, or uncertainty and changes in uncertainty, within any form of structured content, including data relevant to earth systems. IT has a broad and growing applicability within the geosciences in the contexts of […]
