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Activity Number:
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401
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Type:
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Invited
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Date/Time:
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Wednesday, August 1, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #307986 |
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Title:
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Understanding Large-Scale Structure in Massive Remote-Sensing Datasets
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Author(s):
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Amy Braverman*+
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Companies:
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Jet Propulsion Laboratory
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Address:
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California Institute of Technology, Mail Stop 126-347, Pasadena, CA, 91106,
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Keywords:
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remote sensing ; massive data sets ; data compression ; hypothesis testing ; atmospheric science
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Abstract:
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NASA's Atmospheric Infrared Sounder (AIRS) mission has been collecting remote-sensing data about the vertical structure of Earth's atmosphere since AIRS was launched in mid 2002. The AIRS team has implemented the Level 3 Quantization data product to provide users with monthly summaries of the joint distributions of measurements at 11 altitudes of atmospheric temperature, water vapor content, and cloud fraction. In each month, each five-degree spatial grid cell contains a multivariate distribution estimate. In this talk we discuss hypothesis testing procedures for characterizing trends, identifying outliers, and distinguishing between atmospheric regimes based on distributional comparisons.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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