An integrated framework for investigating extreme rainfall events over the eastern mediterranean region : Focusing on Egypt and Cyprus / Doaa Mohamed Fathy Aboelyazeed ; Supervised Ahmad Wagdy Abdeldayem , Johannes Lelieveld
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- إطار متكامل لدراسة العواصف المطرية الحادة على منطقة شرق البحر المتوسط : مع التركيز على مصر وقبرص [Added title page title]
- Issued also as CD
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قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.05.M.Sc.2021.Do.I (Browse shelf(Opens below)) | Not for loan | 01010110084810000 | ||
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مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.13.05.M.Sc.2021.Do.I (Browse shelf(Opens below)) | 84810.CD | Not for loan | 01020110084810000 |
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Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Civil Engineering
Extreme rainfall events are one of the devastating natural hazards that have a great impact on different facets of life.This study is initiated to shed light on extreme rainfall events over the eastern Mediterranean region, especially over both Egypt and Cyprus. Investigating research into such events can help mitigate their risks and increase society resilience. An integratedframework is then suggested through this study to analyze those events from different aspects. First, the evolution of extreme rainfall events over the study area during the last few decades is inspected using trend analysis tests such as Mann Kendal trend test and Cox-Stuart test. Second, two heavy rainfall events that affected both Egypt and Cyprus in October 2019 and March 2020 are chosen as case studies, where the anomaly of the rainfall amounts above normal conditions is reviewed during both events. Third, the Weather Research and Forecasting (WRF) model is used as a numerical weather prediction model to reproduce both targeted events. The best combination of parameterization schemes is utilized for revisiting the synoptic conditions accompanying both events and is further validated with a third severe event to examine the potentiality to use the model in future forecasts
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