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Atmospheric Sciences Seminar

November 8, 3:30pm - 4:30pm
Mānoa Campus, Marine Sciences Building, MSB 100

Calibrating Nino 3.4 SST Forecast Ensembles using Bayesian Model Averaging

Hanpei Zhang
Atmospheric Sciences M.S. Candidate
Department of Atmospheric Sciences, SOEST
University of Hawaii at Manoa

Seminar Date: Wednesday, November 8, 2017
Refreshments: 3:00pm at MSB lanai
Free Cookies, Coffee & Tea Provided (Please Bring Your Own Cup)
Seminar Time: 3:30pm
Location: Marine Sciences Building, MSB 100

Abstract:
Individual models have strengths and weaknesses which lead model evaluation studies to conclude that “no single model can be considered the ‘best’ and it is important to utilize the results from a range of different models.” Bayesian model averaging (BMA) is an effective tool not only for describing uncertainties associated with each model simulation but also for providing forecast performance evaluation of different models. The BMA method in this study was developed for multi-model ensemble forecasts of seasonal sea surface temperatures (SST) in the Niño 3.4 region. We aim to use the BMA method to weight the different SST forecast models in such a way that the weighted estimate is a better predictor of SST than any of the individual models of the ensemble.


Event Sponsor
SOEST Atmospheric Sciences, Mānoa Campus

More Information
(808) 956-8775, SEE FLYER (PDF)

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