The objective of this study was to explore an optimal multiple-model ensemble technique to aid the forecasting of tropical cyclone(TC) intensity. The maximum winds of TCs as forecast by the models of the European Cent...The objective of this study was to explore an optimal multiple-model ensemble technique to aid the forecasting of tropical cyclone(TC) intensity. The maximum winds of TCs as forecast by the models of the European Centre for Medium-Range Weather Forecasts, the Japan Meteorological Agency and the National Centers for Environmental Prediction for the period from July 2010 to October 2011 were studied. Performance of various multiple-model ensemble techniques, including equally weighted ensemble, weighted ensemble based on initial forecast error, weighted ensemble based on 12-hour forecast error, bias-corrected equally weighted ensemble and bias-corrected weighted ensemble based on initial forecast error, was verified against the TC intensities post-analysed by the Hong Kong Observatory. Results showed that the equally weighted ensemble technique generally outperformed the best of the individual models and other multiple-model ensemble techniques. The mean absolute errors of the equally weighted ensemble technique were the lowest at 12, 24 and 36-hour forecasts, and the error spreads were generally the smallest from 12 to 72-hour forecasts.展开更多
文摘The objective of this study was to explore an optimal multiple-model ensemble technique to aid the forecasting of tropical cyclone(TC) intensity. The maximum winds of TCs as forecast by the models of the European Centre for Medium-Range Weather Forecasts, the Japan Meteorological Agency and the National Centers for Environmental Prediction for the period from July 2010 to October 2011 were studied. Performance of various multiple-model ensemble techniques, including equally weighted ensemble, weighted ensemble based on initial forecast error, weighted ensemble based on 12-hour forecast error, bias-corrected equally weighted ensemble and bias-corrected weighted ensemble based on initial forecast error, was verified against the TC intensities post-analysed by the Hong Kong Observatory. Results showed that the equally weighted ensemble technique generally outperformed the best of the individual models and other multiple-model ensemble techniques. The mean absolute errors of the equally weighted ensemble technique were the lowest at 12, 24 and 36-hour forecasts, and the error spreads were generally the smallest from 12 to 72-hour forecasts.
