[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122164-en":3,"doc-seo-122164-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122164,7971461740886,"Theodore","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","ENHANCEMENT OF RAINFALL PREDICTION AND SATELLITE PRECIPITATION ESTIMATES: A MACHINE LEARNING APPROACH FOR UNITED ARAB EMIRATES - Doctorate Dissertation","Accurate rainfall estimation in arid regions is difficult due to sparse ground observations and complex atmospheric dynamics. This dissertation studies rainfall estimation and prediction in the United Arab Emirates using Satellite Precipitation Products (SPPs) and Machine Learning (ML), organized into four articles covering cross-comparison with rain gauges, evaluation of PERSIANN family products, ML-enhanced monthly prediction, and a bias-correction framework to improve SPP usefulness for hydrological applications. Validation applies multiple statistical and categorical metrics and extreme indices.","United Arab Emirates University  \nScholarworks@UAEU  \n\n| Dissertations | Electronic Theses and Dissertations |\n| --- | --- |\n\n4-2024  \nENHANCEMENT OF RAINFALL PREDICTION AND SATELLITE PRECIPITATION ESTIMATES: A MACHINE LEARNING APPROACH FOR UNITED ARAB EMIRATES  \nFaisal Baig  \nFollow this and additional works at: [https://scholarworks.uaeu.ac.ae/all_dissertations](https://scholarworks.uaeu.ac.ae/all_dissertations)  \n Part of the Civil and Environmental Engineering Commons  \nDOCTORATE DISSERTATION NO. 2024: 10  \nCollege of Engineering  \nENHANCEMENT OF RAINFALL PREDICTION AND SATELLITE PRECIPITATION ESTIMATES: A MACHINE LEARNING APPROACH FOR UNITED ARAB EMIRATES  \nFaisal Baig  \nApril 2024  \nUnited Arab Emirates University  \nCollege of Engineering  \nENHANCEMENT OF RAINFALL PREDICTION AND SATELLITE PRECIPITATION ESTIMATES: A MACHINE LEARNING APPROACH FOR UNITED ARAB EMIRATES  \nFaisal Baig  \nThis dissertation is submitted in partial fulfilment of the requirements for the degree of  \nDoctor of Philosophy in Civil Engineering  \nApril 2024  \nUnited Arab Emirates University Doctorate Dissertation  \n2024: 10  \nCover: Satellite constellation measuring precipitation around the globe and focus on the UAE (study area)  \n(Photo: By Faisal Baig)  \n(UAE map with rain gauges sourced from NCM UAE)  \n© 2024, Faisal Baig Al Ain, UAE All Rights Reserved  \nPrint: University Print Service, UAEU 2024  \nDeclaration of Original Work  \nI, Faisal Baig, the undersigned, a graduate student at the United Arab Emirates University (UAEU), and the author of this dissertation entitled “Enhancement of Rainfall Prediction and Satellite Precipitation Estimates: A Machine Learning Approach for United Arab Emirates”, hereby, solemnly declare this is the original research work done by me under the supervision of Dr. Mohsen Sherif, in the College of Engineering at UAEU. This work has not previously formed the basis for the award of any academic degree, diploma or a similar title at this or any other university. Any materials borrowed from other sources (whether published or unpublished) and relied upon or included in my dissertation have been properly cited and acknowledged in accordance with appropriate academic conventions. I further declare that there is no potential conflict of interest with respect to the research, data collection, authorship, presentation and/or publication of this dissertation.  \nStudent’s Signature:  \nDate: 07/May/2024  \nAdvisory Committee  \n1) Advisor: Mohsen Sherif Title: Professor  \nDepartment of Civil and Environmental Engineering College of Engineering  \n2) Member: Munjed Maraqa Title: Professor  \nDepartment of Civil and Environmental Engineering College of Engineering  \n3) Member: Tareefa AlSumaiti Title: Associate Professor  \nDepartment of Geography and Urban Sustainability College of Humanities and Social Sciences  \nApproval of the Doctorate Dissertation  \nThis Doctorate Dissertation is approved by the following Examining Committee Members:  \n1) Advisor (Committee Chair): Mohsen Sherif Title: Professor  \nDepartment of Civil and Environmental Engineering  \nCollege of Engineering  \nSignature  Date 08 May 2024  \n2) Member: Naeema Al Hosni Title: Professor  \nDepartment of Geography and Urban Studies  \nCollege of Humanities and Social Sciences  \nSignature  Date 09 May 2024  \n3) Member: Mohamed Hamouda Title: Associate Professor  \nDepartment of Civil and Environmental Engineering  \nCollege of Engineering  \nSignature Mohamed Hamouda Date 09 May 2024  \n4) Member (External Examiner): Soroosh Sorooshian Title: Professor  \nDepartment of Civil and Environmental Engineering  \nInstitution: University of California, Irvine, USA  \nSignature  \nDate 09 May 2024  \nMay 21, 2024  \n22/05/2024  \nAbstract  \nThe accurate estimation of rainfall in arid regions presents a significant challenge due to sparse ground observations and complex atmospheric dynamics. This dissertation investigates various aspects of rainfall estimation and prediction in the United Arab ","cbCaij1oUTFudbln","https://ap.wps.com/l/cbCaij1oUTFudbln","pdf",3039247,1,70,"English","en",105,"# Abstract\n## Research scope and four-article structure\n## Evaluation methods and validation metrics\n## Extreme indices and hydrological applications","[{\"question\":\"Why is rainfall estimation challenging in the UAE’s arid environment?\",\"answer\":\"Sparse ground observations and complex atmospheric dynamics make rainfall difficult to measure accurately in arid regions, motivating the use of satellite products and predictive modeling.\"},{\"question\":\"How does the dissertation compare satellite precipitation products with rain gauges?\",\"answer\":\"It evaluates rainfall variability, consistency, and concentration in the UAE by contrasting satellite precipitation products against rain gauge observations to highlight discrepancies between data sources.\"},{\"question\":\"What role does machine learning play in improving rainfall estimates?\",\"answer\":\"Machine learning is used to enhance monthly rainfall prediction and to build a bias correction framework that removes systematic biases from satellite precipitation products for better hydrological utility.\"}]","ENHANCEMENT OF RAINFALL PREDICTION AND SATELLITE PRECIPITATION ESTIMATES: A MACHINE LEARNING APPROACH FOR UNITED ARAB EMIRATES - Doctorate Dissertation | PDF",1785809142,176,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"enhancement-of-rainfall-prediction-and-satellite-precipitation-estimates-a-machine-learning-approach-for-united-arab-emirates-doctorate-dissertation","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/enhancement-of-rainfall-prediction-and-satellite-precipitation-estimates-a-machine-learning-approach-for-united-arab-emirates-doctorate-dissertation/122164/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is rainfall estimation challenging in the UAE’s arid environment?","Question",{"text":75,"@type":76},"Sparse ground observations and complex atmospheric dynamics make rainfall difficult to measure accurately in arid regions, motivating the use of satellite products and predictive modeling.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the dissertation compare satellite precipitation products with rain gauges?",{"text":80,"@type":76},"It evaluates rainfall variability, consistency, and concentration in the UAE by contrasting satellite precipitation products against rain gauge observations to highlight discrepancies between data sources.",{"name":82,"@type":73,"acceptedAnswer":83},"What role does machine learning play in improving rainfall estimates?",{"text":84,"@type":76},"Machine learning is used to enhance monthly rainfall prediction and to build a bias correction framework that removes systematic biases from satellite precipitation products for better hydrological utility.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,104,109,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":21,"slug":103},"Exam","exam",{"id":105,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":105,"slug":137},19,"General","general"]