This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 522
Type: Contributed
Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract - #309294
Title: Post-Processing of Spatio-Temporal Physical Model Output
Author(s): Hongfei Li*+ and Fei Liu and Yasuo Amemiya
Companies: IBM T.J. Watson Research Center and IBM T.J. Watson Research Center and IBM T.J. Watson Research Center
Address: 1101 Kitchawan Rd, Yorktown Heights, NY, 10598,
Keywords: spatio-temporal model ; post processing ; physical model outputs
Abstract:

An important application of physical model prediction is to use its results to improve decision making. A major obstacle, however, is the mismatch between the output from the physical model and the information required by decision model. We developed a post-processing model which links the model outputs with real observations and forecast the variable required by decision making. We illustrate the application in the context of a weather model. The wind gust speed is needed by the decision model, but is not directly predicted by the weather model. We propose a Bayesian hierarchical modeling approach to forecast gust speed. This model post-processes the sustained wind forecast on regular grids based on the gust observations at sparsely located weather stations over time. In particular, our attention is given to calibration of physical model outputs using spatially limited real observation.


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