风暴潮预报系统升级及应用
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摘要
我国是遭受台风暴潮最频繁和最严重的国家之一,特别是东南沿海,人口密集,经济发达,又经常受到台风暴潮的袭击。因此,进行风暴潮预报的研究对于保护人民生命财产安全有着非常重要的现实意义。
首先,本文对长江口及其邻近海域风暴潮可视化预报系统进行了以下三方面的改进：1)引入SWAN并行计算模式；2)优化流场模式代码；3)重新设计软件界面。通过五次台风暴潮的计算对比,表明新系统预报精度良好,大幅缩短了系统整体计算时间。在本文所使用的PC平台上,不考虑波浪的风暴潮计算可节约计算时间60%以上,而考虑波浪的风暴潮计算可节约近70%,进行3天风暴潮预报的计算时间可在45分钟以内。风暴潮预报系统的优化与升级解决了原风暴潮可视化预报系统中虽包含波—流相互作用,但由于计算波浪耗时较多而在风暴潮快速预报中一般不考虑波浪因素的问题。
其次,鉴于浙闽沿海是我国风暴潮灾害高发区,本文还将优化升级后的风暴潮可视化预报系统初步应用于浙闽海域。在对预报模式进行了天文潮和波浪模式率定、验证的基础上,后报计算了近几年影响浙闽区域较为严重的六次台风暴潮过程,并使用实测风速水位资料进行验证分析。后报结果显示在浙闽海域台风订正系数c1,c2应小于长江口杭州湾区域的经验取值,在本文的实验中,c1取0.6-0.7,c2取0.7更为合理；沿海站点的水位验证结果精度较好。本文工作为下一步建立浙闽海域精细化风暴潮可视化预报系统打下了坚实的基础。
China is one of the countries suffering from typhoons with high-frequency impacts and severe disasters. Storm-induced disaster ranks first in marine disasters in China. Southeast China coasts with large population and increasing economics are frequently attacked by tropical and sub-tropical cyclones during summertime, which caused severe damages. Therefore, the studies of the numerical storm-surge forecasting are of great importance for the security and economy.
This thesis focuses on the major upgrading of an integrated storm surge forecasting system for the Changjiang Estuary and adjacent waters with the improvement of the forecasting efficiency. The main three improvements are listed as follows:1) invoking SWAN under OpenMP-supported parallel framework; 2) optimizing the source code for hydrodynamic model; 3) designing a new software interface. The comparison between the original and upgraded version is given with five storm-surge hind-castings, with an aim to show the system improvement on forecasting efficiency and precision. It indicates the model precision of upgraded version is guaranteed. The efficiency is quantitatively increased by 70% and 60% with consideration and neglecting of wave effect, respectively. Total forecasting time with consideration of wave effect could be limited less than 45 minutes. Thus it solves the original problem that wave effect was not considered in fast storm surge forecasting due to its poor efficiency, although the original storm surge forecasting system had included the wave interaction module.
A 2-D storm surge forecasting model system is preliminary set up for the Zhejiang and Fujian provinces which significantly suffer from the storm-induced disasters. The verification of astronomical tide and wave processes shows this model system is robust to reveal the major oceanic and coastal dynamics structures. Six storm surges in recent years were simulated and analyzed with the hind-casting precision guaranteed. The results show that the revised coefficient of Typhoon in Zhejiang and Fujian should be significantly smaller than the empirical values in Changjiang Estuary and Hangzhou Bay. In the cases of this thesis, cl ranges 0.6～0.7 and c2 equals 0.7. These parameter configurations have best modeling performance around the Zhejiang and Fujian coasts. The hind-casting results agree well with observational data.
The works in this thesis laid a solid ground for future research and forecasting of the storm impacts at the Zhejiang and Fujian regions.
首先,本文对长江口及其邻近海域风暴潮可视化预报系统进行了以下三方面的改进：1)引入SWAN并行计算模式；2)优化流场模式代码；3)重新设计软件界面。通过五次台风暴潮的计算对比,表明新系统预报精度良好,大幅缩短了系统整体计算时间。在本文所使用的PC平台上,不考虑波浪的风暴潮计算可节约计算时间60%以上,而考虑波浪的风暴潮计算可节约近70%,进行3天风暴潮预报的计算时间可在45分钟以内。风暴潮预报系统的优化与升级解决了原风暴潮可视化预报系统中虽包含波—流相互作用,但由于计算波浪耗时较多而在风暴潮快速预报中一般不考虑波浪因素的问题。
其次,鉴于浙闽沿海是我国风暴潮灾害高发区,本文还将优化升级后的风暴潮可视化预报系统初步应用于浙闽海域。在对预报模式进行了天文潮和波浪模式率定、验证的基础上,后报计算了近几年影响浙闽区域较为严重的六次台风暴潮过程,并使用实测风速水位资料进行验证分析。后报结果显示在浙闽海域台风订正系数c1,c2应小于长江口杭州湾区域的经验取值,在本文的实验中,c1取0.6-0.7,c2取0.7更为合理；沿海站点的水位验证结果精度较好。本文工作为下一步建立浙闽海域精细化风暴潮可视化预报系统打下了坚实的基础。
China is one of the countries suffering from typhoons with high-frequency impacts and severe disasters. Storm-induced disaster ranks first in marine disasters in China. Southeast China coasts with large population and increasing economics are frequently attacked by tropical and sub-tropical cyclones during summertime, which caused severe damages. Therefore, the studies of the numerical storm-surge forecasting are of great importance for the security and economy.
This thesis focuses on the major upgrading of an integrated storm surge forecasting system for the Changjiang Estuary and adjacent waters with the improvement of the forecasting efficiency. The main three improvements are listed as follows:1) invoking SWAN under OpenMP-supported parallel framework; 2) optimizing the source code for hydrodynamic model; 3) designing a new software interface. The comparison between the original and upgraded version is given with five storm-surge hind-castings, with an aim to show the system improvement on forecasting efficiency and precision. It indicates the model precision of upgraded version is guaranteed. The efficiency is quantitatively increased by 70% and 60% with consideration and neglecting of wave effect, respectively. Total forecasting time with consideration of wave effect could be limited less than 45 minutes. Thus it solves the original problem that wave effect was not considered in fast storm surge forecasting due to its poor efficiency, although the original storm surge forecasting system had included the wave interaction module.
A 2-D storm surge forecasting model system is preliminary set up for the Zhejiang and Fujian provinces which significantly suffer from the storm-induced disasters. The verification of astronomical tide and wave processes shows this model system is robust to reveal the major oceanic and coastal dynamics structures. Six storm surges in recent years were simulated and analyzed with the hind-casting precision guaranteed. The results show that the revised coefficient of Typhoon in Zhejiang and Fujian should be significantly smaller than the empirical values in Changjiang Estuary and Hangzhou Bay. In the cases of this thesis, cl ranges 0.6～0.7 and c2 equals 0.7. These parameter configurations have best modeling performance around the Zhejiang and Fujian coasts. The hind-casting results agree well with observational data.
The works in this thesis laid a solid ground for future research and forecasting of the storm impacts at the Zhejiang and Fujian regions.
引文
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