Evaluation of different wind fields for storm surge modeling in the Persian gulf

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Author(s)
Afshar-Kaveh, Naghmeh
Ghaheri, Abbas
Chegini, Vahid
Etemad-Shahidi, Amir
Nazarali, Mostafa
Griffith University Author(s)
Year published
2017
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With the increasing demand for accurate storm-surge predictions in coastal regions, there is an urgent need to select the most accurate wind field product to use in hydrodynamic prediction models. In this study, the responses of a coastal and ocean circulation model to four wind products, QuikSCAT, European Center of Middle-Range Weather Forecasting (ECMWF) ERA-Interim, Global Forecast System (GFS), and Cross-Calibrated Multi-Platform (CCMP), were evaluated. Simulation of water-level fluctuation with the mentioned wind forcings were compared with tide-gauge observations in the northern part of the Persian Gulf. The results ...
View more >With the increasing demand for accurate storm-surge predictions in coastal regions, there is an urgent need to select the most accurate wind field product to use in hydrodynamic prediction models. In this study, the responses of a coastal and ocean circulation model to four wind products, QuikSCAT, European Center of Middle-Range Weather Forecasting (ECMWF) ERA-Interim, Global Forecast System (GFS), and Cross-Calibrated Multi-Platform (CCMP), were evaluated. Simulation of water-level fluctuation with the mentioned wind forcings were compared with tide-gauge observations in the northern part of the Persian Gulf. The results show that using the GFS wind field, which is a global numerical weather prediction model, produces better results compared with using other wind datasets. Although the result shows competitive improvement of the storm-surge prediction between the GFS and the CCMP forced model, the former exceeds the results almost in all stations. The correlation coefficient of the GFS-forced model for Kangan tide-gauge station is 0.80 compared with those of QuikSCAT, ECMWF, and CCMP, which are 0.64, 0.73, and 0.79, respectively.
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View more >With the increasing demand for accurate storm-surge predictions in coastal regions, there is an urgent need to select the most accurate wind field product to use in hydrodynamic prediction models. In this study, the responses of a coastal and ocean circulation model to four wind products, QuikSCAT, European Center of Middle-Range Weather Forecasting (ECMWF) ERA-Interim, Global Forecast System (GFS), and Cross-Calibrated Multi-Platform (CCMP), were evaluated. Simulation of water-level fluctuation with the mentioned wind forcings were compared with tide-gauge observations in the northern part of the Persian Gulf. The results show that using the GFS wind field, which is a global numerical weather prediction model, produces better results compared with using other wind datasets. Although the result shows competitive improvement of the storm-surge prediction between the GFS and the CCMP forced model, the former exceeds the results almost in all stations. The correlation coefficient of the GFS-forced model for Kangan tide-gauge station is 0.80 compared with those of QuikSCAT, ECMWF, and CCMP, which are 0.64, 0.73, and 0.79, respectively.
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Journal Title
Journal of Coastal Research
Volume
33
Issue
3
Copyright Statement
© 2017 CASANZ. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
Subject
Earth sciences
Engineering
Other engineering not elsewhere classified