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This is the preliminary program for the 2007 Joint Statistical Meetings in Salt Lake City, Utah.

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Activity Number: 185
Type: Invited
Date/Time: Monday, July 30, 2007 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract - #309154
Title: EAKF-CMAQ: Introduction and Evaluation of a Data Assimilation for CMAQ Based on the Ensemble Adjustment Kalman Filter
Author(s): Li Chen*+ and Michael Stein
Companies: The University of Chicago and The University of Chicago
Address: The Center for Integrating Statistical and Environmental Science, Chicago, IL, 60637,
Keywords: data exploration ; space-time dependency
Abstract:

The typical data sets from geophysical and environmental sciences are rich in time and space. In order to model this kind of data statistically, the exploration of the space-time data is needed first. In this poster, we present some data exploration methods to study not only the trend surface but also the structure of space-time dependency. An application to air pollution data is described in depth.

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Revised September, 2007