Paper Deadline Extension: July 29th

Plus optional Hackathon: Wednesday, September 20, 2017

Where: Mesa Lab, National Center for Atmospheric Research (NCAR) in Boulder, CO

Website: https://www2.cisl.ucar.edu/events/workshops/climate-informatics/2017/climate-informatics-workshop   

Workshop Overview:

Climate informatics broadly refers to any research combining climate science with approaches from statistics, machine learning and data mining. The Climate Informatics workshop series, now in its seventh year, seeks to bring together researchers from all of these areas. We aim to stimulate the discussion of new ideas, foster new collaborations, grow the climate informatics community, and thus accelerate discovery across disciplinary boundaries. The format of the workshop seeks to overcome cross disciplinary language barriers and to emphasize communication between participants by featuring a hackathon, invited talks, panel discussions, posters and breakout sessions.

Short Papers:

Submission Deadline: July 29th, 2017

We encourage conference paper submissions up to four pages on topics anywhere at the interface of climate science and machine learning, statistics, data mining, or related fields. Reviews, position papers, and works in progress, are also encouraged.

Topics include but are not limited to:

• Machine learning, statistics, or data mining, applied to climate science

• Management and processing of large climate datasets

• Long and short term climate prediction

• Ensemble characterization of climate model projections

• Paleoclimate reconstruction

• Uncertainty quantification

• Spatiotemporal methods applied to climate data

• Time series methods applied to climate data

• Methods for modeling, detecting and predicting climate extremes

• Climate change attribution

• Dependence and causality among climate variables

• Detection and characterization of climate teleconnections

• Data assimilation

• Climate model parameterizations

• Hybrid methods

• Other data science approaches at the nexus of climate and earth system sciences

Keynote Speakers:

Alexis Hannart - Franco-Argentine Institute on Climate Studies and their Impacts (IFAECI) and the French National Center for Scientific Research (CNRS)

Dr. Hannart is a researcher at the Franco-Argentine Institute for Climate Studies and Impacts (IFAECI), an international laboratory of the CNRS based in Buenos Aires. Its main research topic concerns the detection and attribution of climate change, the purpose of which is to highlight possible causal links between the observed climatic responses (long-term trends or punctual events) and external (natural forcings or anthropogenic) for which it develops statistical methods.

Robert Lund - Clemson University

Dr. Lund received his Ph.D. degree in Statistics from The University of North Carolina in 1993.  He is currently a Professor in the Department of Mathematical Sciences at Clemson University.  He is a Fellow of the American Statistical Association and was the 2005-2007 Editor of the Journal of the American Statistical Association, Reviews Section.  He has published over 70 refereed papers and has graduated 15 doctoral students. His interests are in time series, applied probability, statistical climatology, and veterinary disease mapping.

Elisabeth Moyer - University of Chicago

Dr. Moyer’s research interests fall in two main threads. The first includes the use of the isotopic composition of atmospheric water vapor as a tracer of convective processes, cirrus formation, and stratosphere-troposphere exchange; and the design of spectroscopic techniques for in-situ trace gas measurements. The second includes climate (and human) response to greenhouse-gas forcing; development of tools for impacts assessment; statistical emulation of climate model output; and climate and energy policy evaluation.

Prabhat - National Energy Research Computing Center, Lawrence Berkeley National Laboratory

Prabhat leads the Data and Analytics Services team at NERSC. His current research interests include scientific data management, parallel I/O, high performance computing and scientific visualization. He is also interested in applied statistics, machine learning, computer graphics and computer vision. Prabhat received an ScM in Computer Science from Brown University (2001) and a B.Tech in Computer Science and Engineering from IIT-Delhi (1999). He is currently pursuing a PhD in the Earth and Planetary Sciences Department at U.C. Berkeley.

Sai Ravela - Massachusetts Institute of Technology (MIT)

Within the broader arena of estimation, control and information theories, and topics in statistical pattern recognition and statistical inference and learning, Dr. Ravela's focus is on the design of numerical methods for succinctly representing stochastic signals and systems. Research in his group develops new algorithms to overcome the "curses" of nonlinearity, dimensionality and uncertainty inference problems, such as estimation, planning and control and key characteristics of data-driven applications and cyber-physical systems with applications including tracking, autonomous sampling and mapping, data assimilation and uncertainty quantification.

Organizing Committee:

Workshop Co-Chairs:

Andy Rhines, University of Washington

Slava Lyubchich, University of Maryland Center for Environmental Science

Program Committee Co-Chairs:

Nikunj C. Oza, NASA

Eniko Szekely, New York University

Publicity and Publications Chair:

Erich Seamon, University of Idaho

Travel and Budget Chair:

Mohammad Gorji, Syntelli Solutions Inc.

Steering Committee:

Imme Ebert-Uphoff, Colorado State University


Claire Monteleoni, George Washington University


Doug Nychka, National Center for Atmospheric Research

Local Administrative Support:

Michelle Patton, NCAR

Cecilia Banner, NCAR