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A multi-model consensus forecast technique for tropical cyclone intensity based on model output calibration (in Chinese)

modify : 2016-11-08 10:44:07 hits: 812

Abstract: Forecast errors of tropical cyclone (TC) intensity are analyzed for seven operational numerical weather prediction models during 2010-2012 in the western North Pacific region. It is found that the intensity forecast error is significantly related not only to initial error, but also to initial TC intensity, size, and translation speed. Other factors highly related to the forecast error include the environment pressure, vertical wind shear and maximum potential intensity. Stepwise regression technique is applied to set up model forecast error estimation equations, which can be used to calibrate the model outputs. Independent experiments exhibit that the calibrated model forecasts have significant skill over the original model outputs. A multi-model consensus forecast technique for TC intensity is then developed based on the calibrated model outputs and it shows a 28% (15-20%) skill at 12h (24-72h) over the climatology and persistency technique for TC intensity. Such a consensus technique is much more skillful than the consensus based on the original model outputs and has the potential to be applied in real time operation.

 

Yu H., Chen G.M., Wan R.J.. 2015. A multi-model consensus forecast technique for tropical cyclone intensity based on model output calibration. Acta Meteorologica Sinica, 73(4):667-678, doi:10.11676/qxxb2015.043 (in Chinese)

 

 
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