TY - JOUR
T1 - Sensitivities of modelling storm surge to bottom friction, wind drag coefficient, and meteorological product in the East China Sea
AU - Chu, Dongdong
AU - Zhang, Jicai
AU - Wu, Yongsheng
AU - Jiao, Xiaohui
AU - Qian, Suhui
N1 - Publisher Copyright:
© 2019
PY - 2019/12/31
Y1 - 2019/12/31
N2 - In this study, effects of meteorological product, wind drag coefficient, and the bottom drag coefficient on the modelling storm surge in the East China Sea were investigated by using a high-resolution model based on FVCOM (Finite Volume Community Ocean Model). The model was first evaluated against the observational storm surge caused by Typhoon Winnie; the sensitivities of modelling surge variations to different factors were then examined, including four different meteorological products (ERA-Interim, ERA5, CCMP, NCEP-CFSR), seven formulae of wind drag coefficient (Peng & Li, Large & Pond, Garratt, Wu, Large & Yeager, Edson, and Zijlema), and six cases of bottom drag coefficient. The results indicated that all the experiments could capture temporal variations of the surge elevations. However, NCEP-CFSR wind field performs the best among the four wind field products. The wind drag coefficient formulae of Large & Yeager produce better results than the other formulae. The formulae of Edson, Wu, and Garratt produce higher surge elevations than those of the Large & Pond and Zijlema at the time of peak surge. Decreasing the bottom friction has a greater impact on surge elevations and current velocities than increasing the bottom friction. The non-linear interaction between tides and surge was studied as well, and the results showed that the non-linear effect contributed by 37% to the peak surge. The best combination of wind field and parameters derived from the sensitivity studies was used for the other three different storms (Chan-Hom, Herb and Mireille), and the simulations indicated that the best combination of forcing and drag coefficient obtained in this study in general can improve the performance of storm surge models.
AB - In this study, effects of meteorological product, wind drag coefficient, and the bottom drag coefficient on the modelling storm surge in the East China Sea were investigated by using a high-resolution model based on FVCOM (Finite Volume Community Ocean Model). The model was first evaluated against the observational storm surge caused by Typhoon Winnie; the sensitivities of modelling surge variations to different factors were then examined, including four different meteorological products (ERA-Interim, ERA5, CCMP, NCEP-CFSR), seven formulae of wind drag coefficient (Peng & Li, Large & Pond, Garratt, Wu, Large & Yeager, Edson, and Zijlema), and six cases of bottom drag coefficient. The results indicated that all the experiments could capture temporal variations of the surge elevations. However, NCEP-CFSR wind field performs the best among the four wind field products. The wind drag coefficient formulae of Large & Yeager produce better results than the other formulae. The formulae of Edson, Wu, and Garratt produce higher surge elevations than those of the Large & Pond and Zijlema at the time of peak surge. Decreasing the bottom friction has a greater impact on surge elevations and current velocities than increasing the bottom friction. The non-linear interaction between tides and surge was studied as well, and the results showed that the non-linear effect contributed by 37% to the peak surge. The best combination of wind field and parameters derived from the sensitivity studies was used for the other three different storms (Chan-Hom, Herb and Mireille), and the simulations indicated that the best combination of forcing and drag coefficient obtained in this study in general can improve the performance of storm surge models.
KW - Bottom friction
KW - FVCOM
KW - Storm surge
KW - Wind drag coefficient bulk formulae
KW - Wind fields
UR - https://www.scopus.com/pages/publications/85074869003
U2 - 10.1016/j.ecss.2019.106460
DO - 10.1016/j.ecss.2019.106460
M3 - 文章
AN - SCOPUS:85074869003
SN - 0272-7714
VL - 231
JO - Estuarine, Coastal and Shelf Science
JF - Estuarine, Coastal and Shelf Science
M1 - 106460
ER -