NSSL/CIMMS researcher Kim Elmore received second place in the American Meteorological Society Artificial Intelligence Competition.  This is the third year of the contest.
To compete, participants are given a data set, then tasked with defining or detecting some weather-related phenomena based the provided data.  The entrants are also requested to present a paper on the method used.

This year’s task was to make probability forecasts of moderate or greater turbulence for airline flights using over 100,000 observations and 130 variables. Elmore, along with co-participant University of Oklahoma School of Meteorology Professor Mike Richman, used an ensemble tree regression method to solve the problem, and were awarded second place.

Elmore and Richman co-chaired last year’s competition, and was invited to compete in the 2009 event.  As a result of Elmore’s efforts, he has been invited to become a member of the AMS Committee on Artificial Intelligence.