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International Journal of Coastal and Offshore Engineering، جلد ۱۰، شماره ۳، صفحات ۱۰-۱۷
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عنوان انگلیسی Analysis of the Normal and Extreme Wind Patterns in the North Central Persian Gulf Using Two Wind Data Sources
چکیده انگلیسی مقاله This study examines wind data from the North Central Persian Gulf, focusing on both normal and extreme wind patterns. The region’s wind climate is influenced by dominant systems like the Shamal and Kaus winds, which significantly affect marine and offshore operations. To assess these wind conditions, two widely used reanalysis datasets including ERA5 and CFSR were analyzed for the period 1979-2023 at three locations in the Persian Gulf.

A performance evaluation of ERA5 and CFSR data was conducted using Advanced Scatterometer (ASCAT) observations. Results revealed that while both datasets accurately represent general wind patterns, CFSR tends to better capture extreme wind speeds, though it exhibits greater scatter than ERA5. ERA5, on the other hand, underestimates high wind speeds, particularly at extreme values.

Wind roses were generated to analyze the prevailing wind directions, highlighting the predominance of northwesterly and westerly winds across all stations. These findings align with the region's exposure to the Shamal wind system. A frequency analysis showed that most winds occur at lower speeds (<6 m/s), with stronger winds (>9 m/s) more frequent in the northwest and west directions.

For extreme value analysis (EVA), the Peaks-Over-Threshold (POT) method was employed, using the 95th percentile to capture extreme events. Various probabilistic distribution models were fitted, with the Weibull distribution providing the best fit for both datasets. The results indicate that CFSR predicts consistently higher extreme wind speeds across all return periods compared to ERA5, which has implications for the design and safety of offshore structures in the Persian Gulf.
کلیدواژه‌های انگلیسی مقاله CFSR,Extreme Value Analysis,ERA5,statistical analysis,Peak Over Threshold
نویسندگان مقاله Mohammad Hossein Kazeminezhad |
INIOAS

نشانی اینترنتی https://www.ijcoe.org/article_232475_f44b8e1d710ce0b6a066b402648a4961.pdf
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