Volume 9 Issue 1
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Yi Pan, Yong-ping Chen, Jiang-xia Li, Xue-lin Ding. 2016: Improvement of wind field hindcasts for tropical cyclones. Water Science and Engineering, 9(1): 58-66. doi: 10.1016/j.wse.2016.02.002
Citation: Yi Pan, Yong-ping Chen, Jiang-xia Li, Xue-lin Ding. 2016: Improvement of wind field hindcasts for tropical cyclones. Water Science and Engineering, 9(1): 58-66. doi: 10.1016/j.wse.2016.02.002
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Improvement of wind field hindcasts for tropical cyclones

doi: 10.1016/j.wse.2016.02.002

  • a State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China

  • b College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China

Funds:  This work was supported by the National Natural Science Foundation of China (Grants No. 51309092 and 51379072), the Special Fund for Public Welfare Industry of the Ministry of Water Resources of China (Grant No. 201201045), the Natural Science Fund for Colleges and Universities in Jiangsu Province (Grant No. BK20130833), and the Fundamental Research Funds for the Central Universities (Grants No. 2015B16014 and 2013B03414).
  • Received Date: 2015-08-16
  • Rev Recd Date: 2015-12-10
    Abstract
  • This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the Cross-Calibrated Multi-Platform (CCMP) reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.

     

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