Atmospheric Sciences Seminar
November 8, 3:30pm - 4:30pmMānoa 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 芒鈧搉o single model can be considered the 芒鈧渂est芒鈧劉 and it is important to utilize the results from a range of different models.芒鈧 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 Ni脙卤o 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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