[ESIP-all] Fall AGU IN14: Uncertainty, Error, and Quality of Observational Data

[Raskin, Rob (388M)]

Please consider submitting an abstract to the following session at the Fall AGU Meeting (San Francisco, Dec 13-17):

IN14:	Uncertainty, Error, and Quality of Observational Data

Earth and space science observational data are characterized by errors and uncertainties that accrue from multiple factors: i) instrument limitations; ii) locational uncertainty; iii) contamination from environmental conditions (rainfall, clouds, etc.); iv) inaccurate conversion from raw measurements to geophysically meaningful quantities; and v) interpolation errors. It is challenging to quantify these errors so that the uncertainty is commensurate within and across observations. We seek informatics and statistical approaches to the estimation, representation, aggregation, propagation, and dissemination of data uncertainty, including solutions that bridge the gap between statisticians and geophysical scientists.

The abstract submission deadline is Sept 2. To submit an abstract, go to:
http://www.agu.org/meetings/fm10/program/abstract_submissions.php


Rob Raskin, Jet Propulsion Laboratory
Amy Braverman, Jet Propulsion Laboratory
Stephan Sain, NCAR Geophysical Statistics Program


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Rob Raskin
Group Supervisor, Science Data Engineering and Archiving
Instrument Software and Science Data Systems Section
Jet Propulsion Laboratory
Pasadena, CA 91109
(818) 354-4228