• NSF Expeditions in Computing on Climate Change
• Climate Assessments for the Quadrennial Defense Review
• Uncertainty Characterization - Regional Integrated Assessments Modeling
• Data Mining - Carbon Sequestration in Terrestrial Ecosystems
• US DOD Langley AFB and Sea Level Rise
• Climate Data Mining
• Climate Change Wargaming
• Climate Change & National Security
• US DOD Arctic TTX
• Climate Change in the Dominican Republic

Peer-Reviewed Journal

1. Steinhaeuser, K., Ganguly, A.R., and N. Chawla(2011): Multivariate and multiscale dependence in the global climate system revealed through complex networks , Climate Dynamics DOI: 10.1007/s00382-011-1135-9. .
2. Kao, S.C., A.R. Ganguly (2011): Intensity, duration, and frequency of precipitation extremes under 21st-century warming scenarios , Journal of Geophysical Research DOI: 10.1029/2010JD015529 .
3. Kodra, E., K. Steinhaeuser, A.R. Ganguly (2011): Persisting cold extremes under 21st-century warming scenarios , Geophysical Research Letters DOI: 10.1029/2011GL047116 .
4. Steinhaeuser, K., N. Chawla, A.R. Ganguly (2010): Complex networks as a unified framework for descriptive analysis and predictive modeling in climate science , Statistics and Data Mining DOI: 10.1002/sam.10100.
5. Kodra, E.A., S. Chatterjee, A. R. Ganguly (2010): Exploring Granger causality between global average observed time series of carbon dioxide and temperature, Theoretical and Applied Climatology DOI 10.1007/s00704-010-0342-3.
6. Ganguly, A.R., K. Steinhaeuser, D.J. Erickson III, M. Branstetter, E.S. Parish, N. Singh, J.B. Drake, L. Buja (2009): Higher trends but larger uncertainty and geographic variability in 21st century temperature and heat waves, Proceedings of the National Academy of Sciences of the United States of America 106(37): 15555-15559
7. Khan, S., S. Bandyopadhyay, A.R. Ganguly, S. Saigal, D.J. Erickson III, V. Protopopescu, G. Ostrouchov (2007): Relative performance of mutual information estimation methods for quantifying the dependence among short and noisy data. Physical Review E, 026209.
8. Kuhn, G., S. Khan, A.R. Ganguly, M. Branstetter (2007): Geospatial-temporal dependence among weekly precipitation extremes with applications to observations and climate model simulations in South America. Advances in Water Resources, 30(12), 2401-2423.
9. Khan, S., G. Kuhn, A.R. Ganguly, D.J. Erickson III, G. Ostrouchov (2007): Spatio-temporal variability of daily and weekly precipitation extremes in South America. Water Resources Research, 43, W11424.
10. Khan, S., A.R. Ganguly, S. Bandyopadhyay, S. Saigal, D.J. Erickson III, V. Protopopescu, G. Ostrouchov (2006): Nonlinear statistics reveals stronger ties between ENSO and the tropical hydrological cycle. Geophysical Research Letters, 33, L24402, doi:10.1029/2006GL027941.
11. Khan, S., A.R. Ganguly, S. Saigal (2005): Detection and predictive modeling of chaos in finite hydrological time series. Nonlinear Processes in Geophysics, 12, 41-53.
12. Ganguly, A.R., R.L. Bras (2003): Distributed quantitative precipitation forecasting combining information from radar and numerical weather prediction model outputs. Journal of Hydrometeorology, 4(6), 1168-1180.

Peer-Reviewed Conference

1. Steinhaeuser, K., N.V. Chawla, A.R. Ganguly (2009): An Exploration of Climate Data Using Complex Networks. ACM SIGKDD Conference on Knowledge Discovery and Data Mining - Workshops (SensorKDD).
2. Ganguly, A.R., K. Steinhaeuser (2008): Data Mining for Climate Change and Impacts. IEEE International Conference on Data Mining - Workshops (SSTDM).
3. Fang, Y., A.R. Ganguly, N. Singh, V. Vijayaraj, N. Feierabend, D.T. Potere (2006): Online change detection: Monitoring land cover from remotely sensed data. IEEE International Conference on Data Mining - Workshops (ICDMW).

Books and Book Chapters

1. Ganguly, A.R., J. Gama, O.A. Omitaomu, M.M. Gaber, R.R. Vatsavai (2009): Knowledge Discovery from Sensor Data. CRC Press, Taylor & Francis Group (2009).
2. Ganguly, A.R., O.A. Omitaomu, Y. Fang, S. Khan, B.L. Bhaduri (2007): Knowledge discovery from sensor data for scientific applications. In Gaber, M.M., J. Gama (eds.), Learning from Data Streams - Processing Techniques in Sensor Networks, Springer-Verlag, 205-229.

Presentations

2010 AGU: Complex Networks Reveal Persistent Global / Regional Structure and Predictive Information Content in Climate Data
2010 AGU: The possibility of persistent cold extremes under 21st century warming scenarios
2010 AGU: Uncertainty and Extremes Analysis to Evaluate Dynamical Downscaling of Climate Models
2010 AGU: Evaluating Projected Changes in Mean Processes, Extreme
2010 AGU: A Software Prototype For Accessing Large Climate Simulation Data Through Digital Globe Interface
SuperComputing 2009 [SC09] in Portland, OR --- (Larger version of the presentation)
2009 FCF: Projecting Climate Change Impacts on Regional Hydrology and 21st Century Water Resources
2009 FCF: Climate Extremes: The Science, Impacts and Policy Relevance
2009 American Meteorological Society
2008 IEEE ICDM Workshop (SSTDM)
2008 American Geophysical Union - Global Hydrology - SSTA Teleconnections
2008 American Meteorological Society
2008 NASA CIDU

Conference & Workshop Sessions

Geophysics
2010 Fall AGU: Predictive Modeling and Uncertainty Quantification for Systematic Evaluation of Climate Models and Data-Guided Enhancements of Regional Climate Projections
2010 Fall AGU: Characterization, Prediction and Attribution of Weather and Hydrological Extremes with Changing Climate
2008 Fall AGU: Precipitation Extremes and Economic Impacts
2008 Joint AGU: Oral Session on Severe Weather Impacts
2008 Joint AGU: Poster Session on Severe Weather Impacts
2005 Fall AGU: Oral Session on Nonlinear Geophysics
2005 Fall AGU: Poster Session on Nonlinear Geophysics

Computer Science
2009 IEEE ICDM: Climate-KD Workshop
2009 IEEE ICDM: SSTDM Workshop
2009 ACM SIGKDD: Sensor-KDD Workshop
2008 IEEE ICDM: SSTDM Workshop
2008 ACM SIGKDD: Sensor-KDD Workshop
2007 ACM SIGKDD: Sensor-KDD Workshop
2006 IEEE ICDM: IWMESD Workshop

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Our Amazing Planet - "Chilling: Cold Snaps Will Persist in Warming World"
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ORNL Collaborators

Marcia Branstetter
Virginia Dale
John B. Drake
David J. Erickson
Chuck Garten
Robin Graham
Anthony (Tony) King
Evan Kodra
Erin J. Middleton
Aaron Myers
Olufemi A. Omitaomu
George Ostrouchov
Benjamin Preston
Blair Ross
Nagendra Singh
Alexander Sorokine
Stan Wullschleger
Raju Ranga Vatsavai
Thomas J. Wilbanks
The collaborators and contributors are from three divisions at ORNL: Computational Sciences and Engineering Division (GIST Group); Computer Science and Mathematics Division (Computational Earth Sciences Group) and Environmental Sciences Division (multiple groups).

External Collaborators

Massachusetts Institute of Technology / Georgia Tech
Rafael Bras
Jingfeng Wang

DIAL Research Lab, University of Notre Dame
Nitesh Chawla

Department of Computer Science and Engineering, University of Minnesota
Arindam Banerjee
Snigdhansu Chatterjee
Vipin Kumar
Michael Steinbach

National Center for Atmospheric Research (NCAR), Climate Extremes
Lawrence Buja
Rick Katz

Global Change Program, Jadavpur University
Joyashree Roy
Anwesha Chakraborty
Shamik Pal

School of Information Technologies, University of Sydney
Sanjay Chawla
Elizabeth Wu

University of Tennessee, Knoxville
Dayakar Penumadu
Randy Gentry
Glenn Tootle

Indian Institute of Technology, Bombay
Subimal Ghosh (Civil Engineering)
Anand Patwardhan (School of Business)

Computer and Information Sciences, Temple University
Zoran Obradovic
Debasish Das

Trent Lott Geospatial & Visualisation Research Center, Carnegie Mellon University
Yerramilli Anjaneyulu

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For scientific questions or additional information about the technical content of this website, please contact:
Auroop R. Ganguly
Geographic Information Science & Technology Group
Computational Sciences and Engineering Division
Oak Ridge National Laboratory
Oak Ridge, TN 37831
Phone: (865) 241-1305
Fax: (865) 241-6261
E-Mail:gangulyar.ornl.gov

For questions or comments about the website, please contact:
Evan Kodra
E-mail: ekodra@utk.edu

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While US citizens and legal permanent residents are strongly encouraged
to apply, the positions are open for other legal residents in the US as well.

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