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Document Type |
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Thesis |
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Document Title |
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DEVELOPMENT OF CONVECTIVE CLOUDS PARAMETERIZATION SCHEME IN SAUDI-KAU GLOBAL CLIMATE MODEL FOR ENHANCING CLIMATE PREDICTION OVER ARABIAN PENINSULA " تطوير نمذجة سحب الحمل في نموذج المناخ العالمي لجامعة الملك عبد العزيز-السعودي لتحسين التوقع المناخي على شبه الجزيرة العربية |
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Subject |
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Faculty of Meteorology, Environment and Arid Land Agriculture |
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Document Language |
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Arabic |
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Abstract |
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Global climate models (GCMs) are valuable tools to explore the atmosphere–ocean and land–atmosphere interactions, and to better understand past climate as well as to generate climate scenarios. In GCMs convection is parameterized, because the characteristic scale of this atmospheric process is smaller than the typical global climate model resolution. GCM simulations are strongly influenced by their cumulus convection parameterization schemes (CPSs) and in particular, precipitation simulated by GCMs is strongly dependent on the selected CPS. In this Thesis, the impacts of different CPSs on the climate simulation by the Saudi King Abdulaziz University Global Climate Model (Saudi-KAU GCM) are discussed. In this work, a new CPS namely EMAN is introduced in Saudi-KAU model in addition to the existing CPS called simplified Arakawa Schubert (SAS).
The newly implemented EMAN CPS in Saudi-KAU model improved the climate simulation at global and regional scales. The key areas of improvements include: better simulation of the relative humidity, temperature and precipitation fields in single column model with EMAN. Simulations by Saudi-KAU atmospheric GCM at a moderate resolution (T106L44: 1.125o × 1.125o) showed improved convective precipitation partition with EMAN as compared to SAS. Low (high) outgoing long wave radiation (OLR) values are indicative of enhanced (suppressed) convection and hence more (less) cloud coverage. The root mean square error estimated over tropics for OLR with EMAN is less than that of the SAS. The improvements shown in climatological fields revealed enhancement in the summer season (June-September: JJAS) precipitation predictability over the Arabian Peninsula and northeast Africa, which is one of the important aspects of this research. Results include: the main pattern of JJAS precipitation variability (as measured by the leading empirical orthogonal functions) with EMAN is comparable to the observed pattern, while the maximum variability with SAS occurs in a completely different location. Due to this shift, the El Niño Southern Oscillation (ENSO)-related JJAS precipitation teleconnection simulated with SAS is very weak as compared to observation. In terms of statistical measure of the skill for the simulated precipitation, and that for the upper level circulation patterns, the experiments with EMAN scheme outperforms over the Arabian Peninsula as compared to SAS.
The potential predictability (PP) of the Arabian Peninsula precipitation and surface air temperature is also explored by using reforecast data from the state-of-the-art coupled GCMs of the North American multimodel ensemble (NMME). The PP is estimated by using analysis of variance, perfect model correlation and information-based measures, including relative entropy and mutual information. In general, all models showed a drop in potential predictability with an increase in lead-time. Potential Predictability of the surface air temperature and precipitation during JJAS is higher in the Coupled Forecast System version 2, from the National Centers for Environmental Predictions (CFSV2) as compared to other NMME models. Therefore, in order to improve the Arabian Peninsula climate prediction skill further, developments of model physics as well as the initial conditions are required. |
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Supervisor |
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Prof. Mansour Almazroui |
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Thesis Type |
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Doctorate Thesis |
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Publishing Year |
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1439 AH
2018 AD |
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Co-Supervisor |
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Prof. Abdulrahman A. Alkhalaf |
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Added Date |
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Monday, January 15, 2018 |
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Researchers
| محمد أزهر إحسان | Ehsan, Muhammad Azhar | Researcher | Doctorate | |
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