Ding, X. L.; Chen, Y. P.; Pan, Y., and Reeve, D., 2016. Fast Ensemble Forecast of Storm Surge along the Coast of China. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 1077–1081. Coconut Creek (Florida), ISSN 0749-0208.

The uncertainties in typhoon wind field forecasts may introduce significant errors in storm surge forecasts. The common method to tackle this problem is based on ensemble forecasting of a typhoon wind field by using different initial and/or boundary conditions in the adopted weather forecast model. However, this method demands very high computational costs and therefore may not always be acceptable for operational use. In order to improve time efficiency, this paper introduces a new method which mainly relies on the forecast results from different weather forecast centres. With the bias modification, the control typhoon forecast is first generated by the weighted averaging of forecast results from individual forecast centres. The weighted factor for each centre is calculated under a dynamic training scheme. The ensemble typhoon forecasts are then generated by combination of five different typhoon tracks and three different wind speeds around the control forecast. The ensemble storm surge forecasts are conducted by running a well-validated storm surge model driven by the wind fields obtained from the above ensemble typhoon forecasts. Since each storm surge forecast can be calculated independently, the ensemble storm surge forecast can be fast conducted without significant increase in computational time. The above method is applied to the forecasting of storm surge in 2013 along the coast of China. By comparison with the traditional forecast, the control forecast exhibits a higher accuracy, and the ensemble forecasts provide more types of forecast results, such as the occurrence probability of storm surge over a certain surge level, which are useful for the probabilistic decision of protection measures against storm surge.

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