Computing Accurate Probabilistic Estimates of One-D Entropy from Equiprobable Random Samples (arxiv.org)

There is a GeoInfoTheory Session at EGU 2021; your submissions are welcome! HS3.7, Information theory in the Earth sciences Convener: Cristina Prieto Co-conveners: Grey Nearing, Rui A. P. Perdigão, Benjamin L. Ruddell, Steven Weijs https://meetingorganizer.copernicus.org/EGU21/sessionmodification/39112

28 participants joined the 2020 SITES Virtual Meeting held on August 3–4, 2020 to discuss the recent WRR Debates and explore and plan work at the frontiers of information theory in the geosciences. A major theme of the meeting was the intersection of information theory, machine learning, and AI. Four presentations from the meeting are […]

COVID-19 UPDATE JUNE 12TH 2020: WE ARE POSTPONING THE WORKSHOP UNTIL SUMMER 2021 DUE TO COVID, DATES TBD. THERE WILL BE A SHORT VIRTUAL WORKSHOP HELD ON THE MORNING OF AUGUST 3-4 INSTEAD. PLEASE REACH OUT IF YOU WANT TO BE A PART OF THAT. You are invited to attend the Workshop (and Summer School) […]

Nature Communications 11, Article number: 1415 (2020) Peer Nowack, Jakob Runge, Veronika Eyring & Joanna D. Haigh  Article LINK Abstract Global climate models are central tools for understanding past and future climate change. The assessment of model skill, in turn, can benefit from modern data science approaches. Here we apply causal discovery algorithms to sea level pressure data from a large set of […]

Entropy 2020, 22(3), 360; https://doi.org/10.3390/e22030360 by Peishi Jiang and Praveen Kumar Abstract Complex systems arise as a result of the nonlinear interactions between components. In particular, the evolutionary dynamics of a multivariate system encodes the ways in which different variables interact with each other individually or in groups. One fundamental question that remains unanswered is: How do two non-overlapping […]

Kumar, P., & Gupta, H. V. (2020). Debates—Does Information Theory provide a new paradigm for Earth Science?. Water Resources Research, 56, e2019WR026398. https://doi.org/10.1029/2019WR026398 Abstract The basis for all knowledge is “information” that we compile about the world, expressed through models that support understanding, prediction, and decision making. This overview paper provides a contextual basis for the four papers that make up […]

Nearing, G. S., Ruddell, B. L., Bennett, A. R., Prieto, C., & Gupta, H. V. (2020). Does information theory provide a new paradigm for earth science? Hypothesis testing. Water Resources Research, 56, e2019WR024918. https://doi.org/10.1029/2019WR024918 Abstract Model evaluation and hypothesis testing are fundamental to any field of science. We propose here that by changing slightly the way we […]

Goodwell, A. E., Jiang, P., Ruddell, B. L., & Kumar, P. (2020). Debates—Does information theory provide a new paradigm for Earth science? Causality, interaction, and feedback. Water Resources Research, 56, e2019WR024940. https://doi.org/10.1029/2019WR024940 Abstract The concept of causal interactions between components is an integral part of hydrology and Earth system sciences. Modelers, decision makers, scientists, and other water […]

Perdigão, R. A. P., Ehret, U., Knuth, K. H., & Wang, J. ( 2020). Debates: Does information theory provide a new paradigm for Earth science? Emerging concepts and pathways of information physics. Water Resources Research, 56, e2019WR025270. https://doi.org/10.1029/2019WR025270 Abstract Entropy and Information are key concepts not only in Information Theory but also in Physics: historically in the fields of Thermodynamics, Statistical and Analytical Mechanics, […]

Weijs, S. V., & Ruddell, B. L. (2020). Debates: Does information theory provide a new paradigm for earth science? Sharper predictions using Occam’s digital razor. Water Resources Research, 56, e2019WR026471. https://doi.org/10.1029/2019WR026471 Abstract Occam’s Razor is a bedrock principle of science philosophy, stating that the simplest hypothesis (or model) is preferred, at any given level of model […]

Jiang, Peishi, and Praveen Kumar. “Information transfer from causal history in complex system dynamics.” Physical Review E 99.1 (2019): 12306. https://link.aps.org/doi/10.1103/PhysRevE.99.012306

Bennett, Andrew, et al. “Quantifying process connectivity with transfer entropy in hydrologic models.” Water Resources Research (2019). https://doi.org/10.1029/2018WR024555

Ruddell, Benjamin L., Darren T. Drewry, and Grey S. Nearing. “Information Theory for Model Diagnostics: Structural Error is Indicated by Trade‐Off Between Functional and Predictive Performance.” Water Resources Research. https://doi.org/10.1029/2018WR023692

Gerken, T., B.L. Ruddell, R. Yu, P.C. Stoy, and D.T. Drewry (2019), Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET, NPJ Climate and Atmospheric Science, 2:37, https://www.nature.com/articles/s41612-019-0094-4.

Session HS3.5, “Information Theory in the Geosciences”, will be held at the European Geophysical Union spring 2020 meeting. Submissions are welcomed! Conveners: Cristina Prieto, with Grey Nearing, Rui A. P. Perdigão, Benjamin Ruddell, and Steven Weijs.

The SITES 2019 course will use a Google Drive link. Instructors should use a google account email address to join the Google Group “SITES_2019_Instructors@googlegroups.com” for edit access. Students should use a google account email address to join the Google Group “SITES_2019_Students@googlegroups.com” for read-only access. This link should take you directly to the 2019 Course Content […]

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 […]

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 […]