John K. Williams

NCAR Research Applications Laboratory P.O. Box 3000  Boulder, CO 80307-3000

Phone: 303-497-2822  Fax: 303-497-8401  Email:

Professional Preparation

2000Ph.D.Mathematics, University of Colorado (Dissertation: On the Convergence of Model-free Policy Iteration Algorithms for Reinforcement Learning: Stochastic Approximation under Discontinuous Mean Dynamics)

1998M.S.Applied Mathematics, University of Colorado

1996M.A.Mathematics, University of Colorado

1990B.A.Physics major, Mathematics and Philosophy minors (with Honors), Swarthmore College

1988Attended University of Tübingen, Germany

1987Attended Colorado College Program at Hochschule Lüneburg, Germany

Appointments and Employment

2014 - presentOptimization and Data Science Consultant for a New York internet company

2008 - presentProject Scientist II, National Center for Atmospheric Research (NCAR) Research Applications Laboratory (RAL), Boulder, CO

2004 - 2005Mathematical Consultant, Kestrel Labs, Inc., Boulder, CO

2000 - 2008Project Scientist I, NCAR RAL, Boulder, CO

1997 - 2000Graduate Research Assistant, NCARRAL, Boulder, CO

1993 - 1996Mathematics Teaching Assistant and Instructor, University of Colorado, Boulder, CO

1991 - 1993High School Physics, Math, and Computer Teacher, St. Stephen’s School, Rome, Italy

1990 - 1991High School Math and Computer Teacher, Fountain Valley School, Colorado Springs, CO

1989 - 1990Research Assistant, Physics Department, Swarthmore College, Swarthmore, PA

1988 - 1989Co-manager, Swarthmore College Computer Store, Swarthmore, PA

1988Commercial Product Programmer, Krause Biagosch GmbH., Bielefeld, Germany

1987Instructor, Computer Instructional Services, Inc., Denver, CO

1986 -1987Seminar Instructor and Salesperson, dma Connecting Point, Colorado Springs, CO

1985 - 1987Research Programmer, Swarthmore College Biology Department, Swarthmore, PA

1984 - 1986In-service Course Instructor, School District 11, Colorado Springs, CO

1985Programmer, dma Connecting Point, Colorado Springs, CO

1984Computer Camp Instructor, Academy Computers, Colorado Springs, CO

1983Programmer, School District 11, Colorado Springs, CO

1981 - 1985Educational Software Developer, Disk Depot, Colorado Springs, CO

Selected Honors, Awards and Certificates

2012University Corporation for Atmospheric Research (UCAR) Certificate of Completion, Supervisor Certificate Program

2010UCAR Certificate of Completion,Leadership Academy

2010NCAR nomination of Turbulence Team (R. Sharman, lead) for Colorado Federal Research Labs 2010 Governor’s Award for High Impact Research: Making Your Flight Safer and More Comfortable by Avoiding Turbulence:The Next Generation Air Transportation System approach to observations, nowcasting, and forecasting for tactical and strategic avoidance of turbulence by commercial and general aviation

2008First place (tie), American Meteorological Society Artificial Intelligence Contest sponsored by Weather Decision Technologies, Inc.

2004NASA Langley Research Center Certificate of Appreciation “for exceptional contributions developing technologies that have significant potential for reducing turbulence-induced injuries aboard commercial transports”

2004NASA Aviation Safety and Security Program Certificate of Appreciation “for outstanding contributions to aviation weather safety research and development”

2003NASA Turning Goals into Reality Award “for outstanding contributions to Aviation Safety Turbulence Prediction and Warning Systems (TPAWS) team”

1994Academic Fellowship, University of Colorado

1986Newton E. Tarble Scholarship, Swarthmore College

1985Valedictorian, William J. Palmer High School, Colorado Springs, CO

Selected Grants and Contracts

2014Principal Investigator, Federal Aviation Administration Weather Technology in the Cockpit Program contract, “Tactical Turbulence Information in the Cockpit.”

2013 – presentAdvanced Load Forecasts Task Lead, Xcel Energy Variable Renewable Energy Forecasting System, Phase III contract.

2013 Co-Investigator, NASA SBIR Phase 1 grant, “Convective Induced Turbulence (CIT) Detection via Total Lightning Sensing” (Jimmy Krozel, Innovation Laboratory, PI; Wiebke Deierling, NCAR PI).

2010 - 2012Statistical Analysis Task Lead, Subcontract to ITT Exelis under Federal Aviation Administration SE2020 grant, “Upper Tropopause Lower Stratosphere (UTLS) Research Program.”

2010 – 2013Co-Principal Investigator and NCAR PI, NASA ROSES 2009 Grant No. NNX10AO07G, “Improved Convective Initiation Forecasting in the Gulf of Mexico Region” (John Mecikalski, PI).

2009 – 2011Co-Principal Investigator, NASA ROSES 2008 Grant No. NNX09AP61G, “Improved Contrail and Contrail Cirrus Formation and Dissipation Forecasts for Climate Change Mitigation” (David Johnson, PI).

2008 – 2012Principal Investigator, NASA ROSES 2007 Grant No. NNX08AL89G, “Global Atmospheric Turbulence Decision Support System for Aviation.”

2004 – presentTask Lead for Federal Aviation Administration Aviation Weather Research Program Turbulence Product Development Program research areas, “Turbulence Remote Sensing” and “Diagnosis of Convectively-Induced Turbulence.”

2003 – 2004Task Lead, “Development and Implementation of Automated Scoring Algorithm,” Subcontract to Georgia Tech Research Institute under NASA Contract NAS1-02056.

Selected Community Service

2014Scientific Mentor for SOARS student Sarah Al-Momar

2013 – 2014Reviewer and Session Chair, AMS 12th Conference on Artificial and Computational Intelligence and its Applications to the Environmental Sciences, February 2014 in Atlanta, GA

2013Member, Program Committee, Third International Workshop on Climate Informatics, September, 2013, in Boulder, Colorado

2013Scientific Mentor for SOARS student Sarah Al-Momar

2013Judge, Student Paper Contest, AMS 11th Conference on Artificial and Computational Intelligence Applications to Environmental Science

2012 – 2013Program Co-Chair and Session Chair, 11th Conference on Artificial and Computational Intelligence and its Applications to the Environmental Sciences, January 2013 in Austin, TX

2012 – 2013Member, NSF Earth Cube Data Discovery, Mining and Access Community Group (Earth Cube is sponsored by the NSF Directorate of Geosciencies and Office of Cyberinfrastructure)

2012 – 2013UCAR Leadership AcademyMentor to colleague Elizabeth Page

2012 M.S. co-advisor for University of Oklahoma student Scott Hellman

2012Instructor for Forecaster Turbulence Training at the NWS Aviation Weather Center, Kansas City,KS, February7-10, 2012

2012Lead judge, AMS Tenth Conference on Artificial Intelligence Applications to Environmental Science student paper contest

2011 – 2012Program Co-Chair and Session Chair, AMS 10th Conference on Artificial Intelligence Applications to Environmental Science, January 2012 in New Orleans, LA

2011 – 2012Member, Organizing Committee for the AMS Fifth Artificial Intelligence Forecasting Contest on Wind Power

2011 – 2012Member, Organizing Committee and Earth and Environmental Systems Area Chair, 2012 Conference on Intelligent Data Understanding, October 2012 in Boulder, CO

2011Program Committee Member, Knowledge Discovery, Modeling and Simulation (KDMS) workshop at the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-11), August 2011 in San Diego, CA

2011SOARS writing mentor to student Aaron Piña

2011Lead judge, AMS Ninth Conference on Artificial Intelligence Applications to Environmental Science student paper contest

2011Judge, AMS 15th Conference on Aviation, Range and Aerospace Meteorology student paper contents

2010 – 2011Program Chair and Session Chair, AMS Ninth Conference on Artificial Intelligence Applications to Environmental Science, January 2011 in Seattle, WA

2010 – 2011Member, Organizing Committee for the 91st AMS Annual Meeting, January 2011 in Seattle, WA

2010 – 2011Organizer, Educational Forum on Computational Intelligence Techniques for Data Analysis and Knowledge Discovery at the 91st AMS Annual Meeting

2010 – 2011Member, Organizing Committee for the AMS Fourth Artifical Intelligence Forecasting Contest on Atmospheric Pollution

2010 – 2011Co-Mentor, University of Oklahoma NSF REU students Tim Sliwinski and Jon Trueblood, including sponsoring their summer visit to NCAR

2009 – 2012Member, American Meteorological Society (AMS) Scientific and Technical Activities Commission

2009 - 2012 Chair, AMS Committee on Artificial Intelligence Applications to Environmental Science

2009 – 2010Member, Organizing Committee for the 90thAMS Annual Meeting, January2010 in Atlanta, GA

2009 – 2010Program Chair and Session Chair, AMS Eighth Conference on AI Applications to Environmental Science, January 2010 in Atlanta, GA

2009 – 2010Member, Organizing Committee for the AMS Third Artificial Intelligence Forecasting Contest on Convectively-Induced Turbulence

2009– 2010Co-Mentor, University of Oklahoma NSF REU students David John Gagne and Tim Supinie, includingsponsoringTim’ssummer visit to NCAR.

2008 – 2009 Session Chair, AMS Seventh Conference on AI Applications to Environmental Science, January 2009 in Phoenix, AZ

2008Member, Program Committee, SPIE Optics and Photonics Conference on Remote Sensing Applications for Aviation Weather Hazard Detection and Decision Support, August 2008, in San Diego, CA (SPIE is the International Society for Optical Engineering)

2007 – 2008Session Chair, AMS Sixth Conference on AI Applications to Environmental Science, January, 2008

2005 - 2012 Member, AMS Committee on Artificial Intelligence Applications to Environmental Science

2004 – presentReviewer for Journal of Atmospheric and Oceanic Technology, Atmospheric Chemistry and Physics, Weather and Forecasting, Monthly Weather Review and Meteorology and Atmospheric Physics

2001 - presentMember and Chair (2003-2006 and 2008-2010), Board of Directors, United Ministries in Higher Education at the University of Colorado-Boulder

2001 – 2003Member, Board of Directors, and Fundraising Committee Chair, Boulder Chorale, Boulder, CO

Peer-ReviewedPublications

  1. Haupt, S. E., V. Lakshmanan, C. Marzban, A. Pasini and J. K.Williams, 2009: “Environmental Science Models and Artificial Intelligence” (Chapter 1)in S. E. Haupt, C. Marzban and A. Pasini, Eds., Artificial Intelligence Methods in the Environmental Sciences, Springer, New York, 424 pp.
  2. Lane, T. P., R. D. Sharman, S. B. Trier, R. G. Fovell and J. K. Williams, 2012: Recent advances in the understanding of near-cloud turbulence.Bull. Amer. Meteor. Soc., 93, 499-515.
  3. McGovern, A., N. Troutman, R. A. Brown, J. K. Williams, and J. Abernethy, 2013: Enhanced Spatiotemporal Relational Probability Trees and Forests.Data Mining and Knowledge Discovery, 26, 398–433.
  4. McGovern, A., R. A. Brown, D. J. Gagne, J. K. Williams and J. B. Basara, 2014: Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning. Machine Learning, 95(1), 27-50. DOI10.1007/s10994-013-5343-x
  5. McGovern, A., D. J. Gagne II, N. Troutman, R. A. Brown, J. Basara and J. K. Williams, 2011: Using Spatiotemporal Relational Random Forests to improve our understanding of severe weather processes.Statistical Analysis and Data Mining, 4, 407-429.
  6. McGovern, A., T. Supinie, D. J. Gagne II, N. Troutman, M. Collier, R. A. Brown, J. Basara, and J. Williams, 2010: Understanding severe weather processes through Spatiotemporal Relational Random Forests. Proc. 2010 Conference on Intelligent Data Understanding, NASA, 213-227. [peer-reviewed conference paper]
  7. Mecikalski, J. R., J. K. Williams, C. P. Jewett, D. Ahijevych, A. LeRoy, J. R. Walker, 2014: Improving Probabilistic 0–1 hour Convective Initiation Nowcasts by Combining Geostationary Satellite Observations and Numerical Weather Prediction Model Data. Submitted to Journal of Applied Meteorology and Climatology. (under review)
  8. Supinie, T. A., A. McGovern, J. Williams and J. Abernethy, 2009: Spatiotemporal Relational Random Forests.Proceedings of the 2009 IEEE International Conference on Data Mining (ICDM) workshop on Spatiotemporal Data Mining, 630-635. [peer-reviewed conference paper]
  9. Williams, J. K.. 2014: Using random forests to diagnose aviation turbulence. Machine Learning, 95(1),51-70. DOI: 10.1007/s10994-013-5346-7
  10. Williams, J. K., 2009: “Introduction to Fuzzy Logic” (Chapter 6) in S. E. Haupt, C. Marzban and A. Pasini, Eds., Artificial Intelligence Methods in the Environmental Sciences, Springer, New York, 424 pp.
  11. Williams, J. K., 2009: “Reinforcement Learning of Optimal Controls” (Chapter 15)in S. E. Haupt, C. Marzban and A. Pasini, Eds., Artificial Intelligence Methods in the Environmental Sciences, Springer, New York, 424 pp.
  12. Williams, J. K., C. Kessinger, J. Abernethy and S. Ellis, 2009:“Fuzzy Logic Applications” (Chapter 17)in S. E. Haupt, C. Marzban and A. Pasini, Eds., Artificial Intelligence Methods in the Environmental Sciences, Springer, New York, 424 pp.
  13. Williams, J. K. and J. Vivekanandan, 2007: Sources of error in dual-wavelength radar remote sensing of cloud liquid water content.Journal of Atmospheric and Oceanic Technology, 24, 1317-1336.
  14. Williams, J. K., 2000: On the Convergence of Model-free Policy Iteration Algorithms for Reinforcement Learning: Stochastic Approximation under Discontinuous Mean Dynamics. Doctoral Dissertation, University of Colorado.
  15. Williams, J. K. and S. Singh, 1999: Experimental results on learning stochastic memoryless policies for partially observable Markov decision processes.In M. S. Kearns, S. A. Solla and D. A. Cohn, editors, Advances in Neural Information Processing Systems 11, MIT Press, 1073–1079. [peer-reviewed conference]

Selected Conference Publications

  1. Abernethy, J. and J. K. Williams, 2008: A storm-type classifier using support vector machines and fuzzy logic.American Meteorological Society (AMS) 6th Conference on Artificial Intelligence Applications to Environmental Science, paper 2.5.
  2. Ahijevych, D., J. K. Williams, C. P. Jewett, J. R. Mecikalski, and J. R. Walker, 2012:Using a random forest to predict convective initiation. In K. Das, N. V. Chawla, A. N. Srivastava (Eds.), Proc. 2012 Conf. on Intelligent Data Understanding, 158-159. [refereed conference]
  3. Ahijevych, D., J. Williams, S. Dettling, H. Cai, and M. Steiner, 2010: Evaluation of a probabilistic convective nowcast for CoSPA.AMS 20th Conference on Probability and Statistics in the Atmospheric Sciences, 14th Conference on Aviation, Range, and Aerospace Meteorology, and 8th Conference on Artificial Intelligence Applications to Environmental Science Joint Session, paper J10.4.
  4. Cai, H., C. Kessinger, D. Ahijevych, J. Williams, N. Rehak, D. Megenhardt, R. Bankert, J. Hawkins, M. Donovan, and E. R. Williams, 2009: Nowcasting oceanic convection using random forest classification.AMS 16th Conference on Satellite Meteorology and Oceanography and Fifth Annual Symposium on Future Operational Environmental Satellite Systems - NPOESS and GOES-R, paper J8.4.
  5. Cornman, L., J. Williams, G. Meymaris, and B. Chorbajian, 2003: Verification of an airborne Doppler radar turbulence detection algorithm.Preprints, 6th International Conference on Tropospheric Profiling: Needs and Technologies, 9-12.
  6. Cornman, L., J. Williams, G. Meymaris, and B. Chorbajian, 2003:Verification of an Airborne Radar Turbulence Detection Algorithm, Preprints, AMS 31st Conference on Radar Meteorology, Seattle, WA, paper 5A.3.
  7. Cornman, L. B., S. Gerding, G. Meymaris, and J. Williams, 2002: Evaluation of an airborne radar turbulence detection algorithm.Preprints, 10th Conference on Aviation, Range, and Aerospace Meteorology, 237-240.
  8. Cornman, L. B., J. K. Williams and R. K. Goodrich, 2000. The detection of convective turbulence using airborne Doppler radars.Proc. Ninth Conference on Aviation, Range, and Aerospace Meteorology, paper 8.16.
  9. Cotter, A., J. K. Williams, R. K. Goodrich, and J. A. Craig, 2007: A random-forest turbulence prediction algorithm.AMS Fifth Conference on Artificial Intelligence Applications to Environmental Science, San Antonio, TX, paper 1.3.
  10. Craig, J. A., J. K. Williams, G. Blackburn, S. Linden and R. Stone, 2008: Remote detection and real-time alerting for in-cloud turbulence.AMS 13th Conference on Aviation, Range and Aerospace Meteorology, paper 10.5.
  11. Dupree, W. J., D. Morse, M. Chan, X. Tao, M. Wolfson, J. O. Pinto, J. K. Williams, D. Albo, S. Dettling, M. Steiner, S. G. Benjamin, and S. S. Weygandt, 2009: The 2008 CoSPA Demonstration.AMS Aviation, Range and Aerospace Meteorology Special Symposium on Weather-Air Traffic Management Integration, paper P1.1.
  12. Fang, M., J. Zhang, J. K. Williams and J. A. Craig, 2008: Three-dimensional mosaic of the eddy dissipation rate field from WSR-88Ds.AMS 13th Conference on Aviation, Range and Aerospace Meteorology, paper P4.5.
  13. Hannon, S. M., R. Frehlich, L. B. Cornman, R. Goodrich, D. Norris, and J. Williams, 1999: Juneau airport Doppler lidar deployment: extraction of accurate turbulent wind statistics. Tenth Biennial Coherent Laser Radar Technology and Applications Conference, 24-27.
  14. Laffea, L. L., J. K. Williams, R. Monson, and R. Han, 2007: Using artificial intelligence to optimize wireless sensor network deployments for sub-alpine biogeochemical process studies.AMS Fifth Conference on Artificial Intelligence Applications to Environmental Science, San Antonio, TX, paper 1.5.
  15. Meymaris, G., J. K. Williams and J. C. Hubbert, 2009: Performance of a Proposed Hybrid Spectrum Width Estimator for the NEXRAD ORDA.AMS 25th Conference on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, paper 11B.1.
  16. Meymaris, G., J. K. Williams, and J. C. Hubbert, 2009: An improved hybrid spectrum width estimator.AMS 34th Conference on Radar Meteorology, paper P5.20.
  17. Meymaris, G. and J. K. Williams, 2007: Spectrum width estimators for the NEXRAD ORDA: evaluation and recommendation.AMS 23rd Conference on Interactive Information Processing Systems, San Antonio, TX, paper 5B.5.
  18. Pinto, J., J. Williams, M. Steiner, D. Albo, S. Dettling, W. Dupree, D. Morse, H. Iskenderian, T. Xiaofeng, M. Wolfson, C. Reiche, S. Weygandt, S. Benjamin, and C. Alexander, 2010: Advances in the Collaborative Storm Prediction for Aviation (CoSPA). Joint session between the AMS 8th Conference on Artificial Intelligence Applications to Environmental Science, 20th Conference on Probability and Statistics in the Atmospheric Sciences, 14th Conference on Aviation, Range, and Aerospace Meteorology, and Presidential Forum, paper J11.2.
  19. Politovich, M. K., G. Zhang, J. Vivekanandan and J. K. Williams, 2003: Characteristics of clouds containing SLD relevant to icing remote sensing.41st Aerospace Annual Meeting and Exhibit, paper AIAA 2003-562. [refereed conference]
  20. Sharman, R., and J. K. Williams, 2009: The complexities of thunderstorm avoidance due to turbulence and implications for traffic flow for management. Aviation, Range and Aerospace Meteorology Special Symposium on Weather-Air Traffic Management Integration. Phoenix, AZ, paper 2.4.
  21. Sharman, R., L. Cornman, J. Williams, S. Koch, and W. Moninger, 2006: The FAA AWRP Turbulence PDT, AMS 12th Conference on Aviation, Range and Aerospace Meteorology, paper 3.3.
  22. Walker, J. R.,C. P. Jewett, J. R. Mecikalski, A. LeRoy, L. Schultz, J. Williams and D. Ahijevych, 2012: Optimizing the use of geostationary satellite data for nowcasting convective initiation.In K. Das, N. V. Chawla, A. N. Srivastava (Eds.), Proc. 2012 Conf. on Intelligent Data Understanding, 146-147. [refereed conference]
  23. Williams, J. K., J. Pearson, S. E. Haupt, and T. McCandless, 2014: Distributed solar and net load forecasts for utilities. Proceedings of the American Solar Energy Society (ASES) 2014 National Solar Conference (SOLAR 2014).
  24. Williams, J. K., G. Blackburn, J. A. Craig and G. Meymaris, 2012: A data mining approach to data fusion for turbulence diagnosis.In K. Das, N. V. Chawla, A. N. Srivastava (Eds.), Proc. 2012 Conf. on Intelligent Data Understanding, 168-169. [refereed conference]
  25. Williams, J. K., D. A. Ahijevych, S. M. Dettling, and M. Steiner, 2009: Data mining for thunderstorm nowcast development.Proc. WMO Symposium on Nowcasting and Very Short Range Forecasting, 30 Aug-4 Sep 2009, Whistler, B.C., Canada, paper 6.12.
  26. Williams, J. K., R. Sharman, C. Kessinger, W. Feltz, A. Wimmers and K. Bedka, 2009: Developing a global turbulence and convection nowcast and forecast system.Proc. 1st AIAA Atmospheric and Space Environments Conference, paper AIAA 2009-3634. [refereed conference]
  27. Williams, J. K., R. Sharman, J. Craig and G. Blackburn, 2008: Remote Detection and Diagnosis of Thunderstorm Turbulence.In W. Feltz and J. Murray, Eds., Remote Sensing Applications for Aviation Weather Hazard Detection and Decision Support.Proceedings of SPIE, 7088, paper 708804. [refereed conference]
  28. Williams, J. K., D. Ahijevych, S. Dettling and M. Steiner, 2008: Combining observations and model data for short-term storm forecasting.In W. Feltz and J. Murray, Eds., Remote Sensing Applications for Aviation Weather Hazard Detection and Decision Support.Proceedings of SPIE, 7088, paper 708805. [refereed conference]
  29. Williams, J. K., D. A. Ahijevych, C. J. Kessinger, T. R. Saxen, M. Steiner and S. Dettling, 2008:A machine-learning approach to finding weather regimes and skillful predictor combinations for short-term storm forecasting.AMS 13th Conference on Aviation, Range and Aerospace Meteorology and 6th Conference on Artificial Intelligence Applications to Environmental Science, paper J1.4.
  30. Williams, J. K., G. E. Blackburn, J. A. Craig, S. Linden and R. D. Sharman, 2008: Diagnosing hazardous turbulence associated with thunderstorms. AMS 13th Conference on Aviation, Range and Aerospace Meteorology, paper 10.5.
  31. Williams, J. K. and J. Abernethy, 2008: Using random forests and fuzzy logic for automated storm type identification.AMS 6th Conference on Artificial Intelligence Applications to Environmental Science, paper 2.2.
  32. Williams, J. K., J. Craig, A. Cotter, and J. K. Wolff, 2007:A hybrid machine learning and fuzzy logic approach to CIT diagnostic development,” AMS Fifth Conference on Artificial Intelligence Applications to Environmental Science, paper 1.2.
  33. Williams, J. K., L. B. Cornman, J. Yee, S. G. Carson, G. Blackburn, and J. Craig, 2006: NEXRAD detection of hazardous turbulence, AIAA 44th Annual Aerospace Sciences Meeting and Exhibit, paper AIAA 2006-0076.[refereed conference]
  34. Williams, J. K., L. Cornman, S. G. Carson and A. Cotter, 2006: Detection of turbulence with operational weather radar. Preprints, 7th International Symposium on Tropospheric Profiling: Needs and Technologies, Boulder, CO, 7-28–7-29.
  35. Williams, J. K., J. K. Wolff, A. Cotter, and R. D. Sharman, 2006: Evaluating effectiveness of the FAA’s CIT avoidance guidelines, AMS 12th Conference on Aviation, Range and Aerospace Meteorology, paper P1.6.
  36. Williams, J. K., L. Cornman, J. Yee, S. G. Carson and A. Cotter, 2005: Real-time remote detection of convectively-induced turbulence, AMS 32nd Radar Meteorology Conference, paper P12R.1.
  37. Williams, J. K., L. Cornman, D. Gilbert, S. G. Carson, and J. Yee, 2004: Remote detection of turbulence using ground-based Doppler radars. AMS 11th Conference on Aviation, Range, and Aerospace Meteorology, paper 4.5.
  38. Williams, J. K., J. Vivekanandan and G. Zhang, 2003: Enhanced dual-wavelength technique for remote detection of cloud liquid water content.Preprints, AMS 31st Conference on Radar Meteorology, 130-133.
  39. Williams, J. K., J. Vivekanandan, and G. Zhang, 2002: Evaluation of remote icing detection techniques using X-, Ka-, and W-band radar and microwave radiometer observations.Preprints, 10th Conference on Aviation, Range, and Aerospace Meteorology, 224-227.
  40. Yee, J., J. K. Williams, G. Blackburn, S. G. Carson and J. A. Craig, 2006: Turbulence remote sensing operational demonstration system, AMS 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology, paper P1.2.

Selected Presentations at National or International Meetings