干旱区生态环境知识资源中心(Arid): Prediction of Solar Irradiance over the Arabian Peninsula: Satellite Data, Radiative Transfer Model, and Machine Learning Integration Approach

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DOI	10.3390/app12020717
	Prediction of Solar Irradiance over the Arabian Peninsula: Satellite Data, Radiative Transfer Model, and Machine Learning Integration Approach
	Alwadei, Sahar; Farahat, Ashraf; Ahmed, Moataz; Kambezidis, Harry D.
通讯作者	Farahat, A (corresponding author)，King Fahd Univ Petr & Minerals, Dept Phys, Coll Gen Studies, Dhahran 31261, Saudi Arabia. ; Farahat, A (corresponding author)，King Fahd Univ Petr & Minerals, Ctr Res Excellence Renewable Energy CORERE, Dhahran 31261, Saudi Arabia.
来源期刊	APPLIED SCIENCES-BASEL
EISSN	2076-3417
出版年	2022
卷号	12 期号:2
英文摘要	Data from a moderate resolution imaging spectroradiometer instrument onboard the Terra satellite along with a radiative transfer model and a machine learning technique were integrated to predict direct solar irradiance on a horizontal surface over the Arabian Peninsula (AP). In preparation for building appropriate residual network (ResNet) prediction models, we conducted some exploratory data analysis (EDA) and came to some conclusions. We noted that aerosols in the atmosphere correlate with solar irradiance in the eastern region of the AP, especially near the coastlines of the Arabian Gulf and the Sea of Oman. We also found low solar irradiance during March 2016 and March 2017 in the central (~20% less) and eastern regions (~15% less) of the AP, which could be attributed to the high frequency of dust events during those months. Compared to other locations in the AP, high solar irradiance was recorded in the Rub Al Khali desert during winter and spring. The effect of major dust outbreaks over the AP during March 2009 and March 2012 was also noted. The EDA indicated a correlation between high aerosol loading and a decrease in solar irradiance. The analysis showed that the Rub Al Khali desert is one of the best locations in the AP to harvest solar radiation. The analysis also showed the ResNet prediction model achieves high test accuracy scores, indicated by a mean absolute error of ~0.02, a mean squared error of ~0.005, and an R-2 of 0.99.
英文关键词	solar radiation atmospheric aerosols dust storms machine learning technique Arabian Peninsula
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000747829100001
WOS关键词	GLOBAL DISTRIBUTION ; AEROSOL PRODUCTS ; SAUDI-ARABIA ; NORTH-AFRICA ; MIDDLE-EAST ; PERFORMANCE ; ULTRAVIOLET ; ALGORITHM ; IMPACT
WOS类目	Chemistry, Multidisciplinary ; Engineering, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied
WOS研究方向	Chemistry ; Engineering ; Materials Science ; Physics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/376741
作者单位	[Alwadei, Sahar; Ahmed, Moataz] King Fahd Univ Petr & Minerals, Dept Informat & Comp Sci, Dhahran 31261, Saudi Arabia; [Alwadei, Sahar] Najran Univ, Dept Comp Sci, Coll Comp Sci & Informat Syst, Najran 66521, Saudi Arabia; [Farahat, Ashraf] King Fahd Univ Petr & Minerals, Dept Phys, Coll Gen Studies, Dhahran 31261, Saudi Arabia; [Farahat, Ashraf] King Fahd Univ Petr & Minerals, Ctr Res Excellence Renewable Energy CORERE, Dhahran 31261, Saudi Arabia; [Ahmed, Moataz] King Fahd Univ Petr & Minerals, Interdisciplinary Res Ctr Intelligent Secure Syst, Dhahran 31261, Saudi Arabia; [Kambezidis, Harry D.] Natl Observ Athens, Inst Environm Res & Sustainable Dev, Atmospher Res Team, GR-11810 Athens, Greece; [Kambezidis, Harry D.] Univ West Attica, Lab Soft Energies & Environm Protect, Dept Mech Engn, GR-12241 Athens, Greece
推荐引用方式 GB/T 7714	Alwadei, Sahar,Farahat, Ashraf,Ahmed, Moataz,et al. Prediction of Solar Irradiance over the Arabian Peninsula: Satellite Data, Radiative Transfer Model, and Machine Learning Integration Approach[J],2022,12(2).
APA	Alwadei, Sahar,Farahat, Ashraf,Ahmed, Moataz,&Kambezidis, Harry D..(2022).Prediction of Solar Irradiance over the Arabian Peninsula: Satellite Data, Radiative Transfer Model, and Machine Learning Integration Approach.APPLIED SCIENCES-BASEL,12(2).
MLA	Alwadei, Sahar,et al."Prediction of Solar Irradiance over the Arabian Peninsula: Satellite Data, Radiative Transfer Model, and Machine Learning Integration Approach".APPLIED SCIENCES-BASEL 12.2(2022).