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Instruments and Science Data Systems: Contact 
Amy  Braverman's Picture
Jet Propulsion Laboratory
M/S 306-463
4800 Oak Grove Drive
Pasadena, CA 91109


Amy Braverman
Senior Member of the Technical Staff

Professional Activities
  • Associate Editor, Journal on Uncertainty Quantification, 2012-present
  • Program Leader, Program on Uncertainty Quantification of the Statistical and Applied Mathematical Sciences Institute, 2011-2012
  • Organizing Committee, Frontiers in the Detection and Attribution of Climate Change, Banff International Research Station, May 27, 2012-June 1, 2012
  • Adjunct Associate Professor of Statistics, UCLA, 2008-present
  • Member, American Statistical Association Committee on Climate Change Policy, August 2008-present
  • Program Committee Chair, National Research Council Workshop on Uncertainty Management in the Use of Remote Sensing Data for Climate Studies, December 2008
  • Editorial Board, Earth Science Informatics, 2007- present

  • Ph.D. in Statistics, 1999; UCLA
  • M.A. in Mathematics, 1992; UCLA
  • B.A. in Economics, 1982; Swarthmore College

Research Interests
  • Information theory, data compression and statistics
  • Massive dataset analysis
  • Statistical methods for service oriented architectures
  • Statistical methods for climate model diagnosis
  • Aerosol science data analysis
  • Geostatistical modeling and data fusion


Atmospheric Infrared Sounder (AIRS)
The Atmospheric Infrared Sounder, AIRS, is an instrument whose goal is to support climate research and improved weather forecasting.

Multi-Angle Imaging Spectro-Radiometer (MISR)
The Multi-angle Imaging SpectroRadiometer (MISR) instrument provides a unique opportunity for studying the ecology and climate of Earth through the acquisition of global multiangle imagery on the daylit side of Earth.

Orbiting Carbon Observatory (OCO-2)
OCO-2 is designed to provide space-based global measurements of atmospheric carbon dioxide (CO2) with the precision and resolution needed to identify and characterize the processes that regulate this important greenhouse gas.

Professional Experience
  • Jet Propulsion Laboratory, Pasadena, California
    • Principal Investigator, Multivariate Data Fusion and Uncertainty Quantification for Remote Sensing (2012-2015)
    • Principal Investigator, Likelihood-based Quantification of Agreement between Climate Model Output and NASA Data Records (2011-2015)
    • Principal Investigator, Geostatistical Data Fusion for Remote Sensing Applications (2008-2012)
    • Senior member, Science Data Understanding Group
    • Member, AIRS Science Integration Team
    • Co-investigator, Multi-angle Imaging SpectroRadiometer mission
    • Scientist, Earth and Space Sciences Division (2001-2004)
    • Caltech Post-doctoral Scholar at the Jet Propulsion Laboratory (1999-2001)
  • Micronomics Inc., Los Angeles, CA
    • Research Director (1987-1990)
  • National Economic Research Associates, Los Angeles, CA
    • Senior Analyst (1983-1987)

Selected Publications
  1. Braverman, A.J., Fetzer, E.J., Kahn, B.H., Manning, E.R., Oliphant, R.B., and Teixeira, J.A. (2012). Massive Data Set Analysis for NASA's Atmospheric Infrared Sounder, Technometrics, in press.
  2. Braverman, A., Cressie, N., and Teixeira, J. (2011). A Likelihood-based Comparison of Temporal Models for Physical Processes, Statistical Analysis and Data Mining, Volume 4, Number 3, pp. 247-258, doi: 10.1002/sam.10113.
  3. Nguyen, H., Katzfuss, M., Cressie, N., and Braverman, A. (2011). Spatio-Temporal Data fusion for Very Large Remote Sensing Datasets, Technometrics, submitted.
  4. Braverman, A. (2008). Understanding Large-scale Structure in Massive Data Sets, in Encyclopedia of Quantitative Risk Analysis Assessment, Everitt, B. and Melnick, E. (eds). John Wiley and Sons Limted, Chichester, UK.
  5. Shi, Tao, Yu Bin, Clothiaux, Eugene, and Braverman, Amy (2007). Daytime Arctic Cloud Detection based on Multi-angle Satellite Data with Case Studies, Journal of the American Statistical Association, Volume 103, Number 482, pp. 584-593.
  6. Braverman, A., Fetzer, E., Eldering, A., Nittel, S. and Leung K. (2003). Semi-streaming Quantization for Remote Sensing Data, Journal of Computational and Graphical Statistics, Volume 12, Number 4, pages 759-780.
  7. Braverman, A. (2002) Compressing Massive Data Sets Using Quantization, Journal of Computational and Graphical Statistics, Volume 11, Number 1, pp. 33-62.

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