Session 3 |
| | Forecasting Contest |
| | Chair: Michael B. Richman, Univ. of Oklahoma, Norman, OK
|
| 3:30 PM | 3.1 | Polarimetric Radar and validation data for the 2008 artificial intelligence competition  
Kimberly L. Elmore, CIMMS/Univ. of Oklahoma and NOAA/NSSL, Norman, OK; and M. B. Richman |
| 3:45 PM | 3.2 | Probabilistic hedging of the True Skill Statistic
Neil Gordon, Meteorological Service of New Zealand, Kelburn, Wellington, New Zealand; and D. Kilminster and A. Ziegler |
| 4:00 PM | 3.3 | Application of Neural Net Models to Classify and to Forecast the Observed Precipitation Type at the Ground using the Artificial Intelligence Competition Data Set
Armando Pelliccioni, ISPESL, Monteporzio Catone, Italy; and R. Cotroneo and F. Pungi |
| 4:15 PM | 3.4 | Regime Dependent Precipitation Type Forecasting
Tyler C. McCandless, Penn State University, University Park, PA |
| 4:30 PM | 3.5 | Employing stratified data mining models
Valliappa Lakshmanan, CIMMS/Univ. of Oklahoma, NOAA/NSSL, Norman, OK |
| 4:45 PM | 3.6 | The effects of data issues and skill scores in creating predictive models
Matthew J. Pocernich, NCAR, Boulder, CO |
| 5:00 PM | 3.7 | Ensemble classifier for winter storm precipitation in polarimetric radar data
Emmanuel Goossaert, University of Oklahoma, Norman, OK; and R. Alam |
| 5:15 PM | 3.8 | Comparison of support vector machines and minimax probability machines for precipitation prediction
Stephen Sullivan, UCAR, Boulder, CO |