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Improving and Developing the Fog Stability Index for Predicting Fog at Borg El-Arab Airport, Egypt Using WRF Model
Pure and Applied Geophysics ( IF 1.9 ) Pub Date : 2021-06-18 , DOI: 10.1007/s00024-021-02785-0
Tarek Sayad , Mostafa Morsy , Mostafa A. Mohamed , Abdallah Abdeldym

This study aims to improve and develop local fog stability index (DFSI) as logarithm of horizontal visibility over Borg El-Arab airport, Egypt during the most frequent months of the phenomenon. The results showed that autumn and winter seasons has maximum hourly fog frequency with long duration during the period 1990–2009, so the DFSI regression equations were developed and validated for these seasons. The hourly predictors were obtained from the Weather Research and Forecasting (WRF) model as nest domain with 3 km horizontal resolution along all days of 15 different cases from October to March during the period 1990–2009. Two regression equations were developed for months from October to January (DFSIO-J) and from February March (DFSIF-M). It is found that the developed two regression equations more accurate in training phase than validation phase for fog events. Where, the success percentage for DFSIO-J for fog events reaches to its maximum 100% in January 1997 (training phase) and 91% in November 1996 (validation phase). Whereas, the success percentage for DFSIF-M in February and March are 100% in both two phases except March 89% in the validation phase for fog events. For non-fog events during the two phases, the success percentage for DFSIO-J ranges from 60 to 78%, while it ranges between 64 and 90% for DFSIF-M. Moreover, the general accuracy of DFSIO-J (DFSIF-M) ranges between 61.3 and 77.76% (67.25% and 90.31%) in the training phase and between 63.58 and 78.41% (64.53% and 83.23%) in the validation phase.



中文翻译:

使用 WRF 模型改进和开发用于预测埃及 Borg El-Arab 机场雾的雾稳定性指数

本研究旨在改进和发展局部雾稳定性指数 (DFSI),作为该现象最频繁月份期间埃及博格阿拉伯机场水平能见度的对数。结果表明,1990-2009 年秋冬季的每小时雾频最大且持续时间长,因此开发并验证了这些季节的 DFSI 回归方程。每小时预测变量是从天气研究和预测 (WRF) 模型中获得的,作为巢域,在 1990-2009 年期间从 10 月到 3 月的 15 个不同案例的所有日子中,水平分辨率为 3 公里。从 10 月到 1 月 (DFSI O-J ) 和从 3 月 (DFSI F-M)。发现所开发的两个回归方程在训练阶段比雾事件的验证阶段更准确。其中,DFSI O-J对雾事件的成功率在 1997 年 1 月(训练阶段)达到最高 100%,在 1996 年 11 月(验证阶段)达到 91%。而 DFSI F-M在 2 月和 3 月的成功百分比在两个阶段都是 100%,除了 3 月在雾事件的验证阶段为 89%。对于两个阶段的非雾事件,DFSI O-J的成功百分比在 60% 到 78% 之间,而 DFSI F-M的成功百分比在 64% 到 90% 之间。此外,DFSI O-J (DFSI F-M) 在训练阶段介于 61.3% 和 77.76% (67.25% 和 90.31%) 之间,在验证阶段介于 63.58% 和 78.41% (64.53% 和 83.23%) 之间。

更新日期:2021-06-18
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