Typhoon storm surge ensemble forecast based on GPU technique

被引:0
|
作者
Qiuxing Liu [1 ,2 ]
Jinrong Jiang [3 ]
Fujiang Yu [2 ]
Changkuan Zhang [1 ]
Jianxi Dong [2 ]
Xiaojiang Song [2 ]
Yuzhu Wang [4 ]
机构
[1] College of Harbor, Coastal and Offshore Engineering, Hohai University
[2] National Marine Environmental Forecasting Center
[3] Computer Network Information Center, Chinese Academy of Sciences
[4] School of Information Engineering, China University of Geosciences
关键词
typhoon; storm surge; ensemble forecast; probability forecast; CUDA Fortran;
D O I
暂无
中图分类号
P732.3 [海洋热带气象]; P731.23 [潮汐];
学科分类号
0706 ; 070601 ; 0707 ;
摘要
The accuracy of typhoon forecasts plays an important role in the prediction of storm surges. The uncertainty of a typhoon’s intensity and track means it is necessary to use an ensemble model to predict typhoon storm surges. A hydrodynamic model, which is operational at the National Marine Environmental Forecasting Center, is applied to conduct surge simulations for South China coastal areas using the best track data with parametric wind and pressure models. The results agree well with tidal gauge observations. To improve the calculation efficiency, the hydrodynamic model is modified using CUDA Fortran. The calculation results are almost the same as those from the original model, but the calculation time is reduced by more than 99%. A total of 150 typhoon cases are generated by combining 50 typhoon tracks from the European Centre for Medium-Range Weather Forecasts with three possible typhoon intensity forecasts. The surge ensembles are computed by the improved hydrodynamic model. Based on the simulated storm surges for the different typhoon cases, ensemble and probability forecast products can be provided. The mean ensemble results and probability forecast products are shown to agree well with the observed storm surge caused by Typhoon Mangkhut. The improved model is highly suitable for ensemble numerical forecasts, providing better forecast products for decision-making, and can be easily implemented to run on regular workstations.
引用
收藏
页码:77 / 86
页数:10
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