气候变化领域集成服务门户(CCPortal): Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products

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DOI	10.1016/j.apenergy.2011.01.018
	Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products
	Qin, Jun; Chen, Zhuoqi; Yang, Kun; Liang, Shunlin; Tang, Wenjun
通讯作者	Qin, J (通讯作者)
发表日期	2011
ISSN	0306-2619
EISSN	1872-9118
起始页码	2480
结束页码	2489
卷号	88 期号:7
英文摘要	Global solar radiation (GSR) is required in a large number of fields. Many parameterization schemes are developed to estimate it using routinely measured meteorological variables, since GSR is directly measured at a limited number of stations. Even so, meteorological stations are sparse, especially, in remote areas. Satellite signals (radiance at the top of atmosphere in most cases) can be used to estimate continuous GSR in space. However, many existing remote sensing products have a relatively coarse spatial resolution and these inversion algorithms are too complicated to be mastered by experts in other research fields. In this study, the artificial neural network (ANN) is utilized to build the mathematical relationship between measured monthly-mean daily GSR and several high-level remote sensing products available for the public, including Moderate Resolution Imaging Spectroradiometer (MODIS) monthly averaged land surface temperature (LST), the number of days in which the LST retrieval is performed in 1 month, MODIS enhanced vegetation index, Tropical Rainfall Measuring Mission satellite (TRMM) monthly precipitation. After training, GSR estimates from this ANN are verified against ground measurements at 12 radiation stations. Then, comparisons are performed among three GSR estimates, including the one presented in this study, a surface data-based estimate, and a remote sensing product by Japan Aerospace Exploration Agency (JAXA). Validation results indicate that the ANN-based method presented in this study can estimate monthly-mean daily GSR at a spatial resolution of about 5 km with high accuracy. (C) 2011 Elsevier Ltd All rights reserved.
关键词	ARTIFICIAL NEURAL-NETWORKS MODELS TEMPERATURE CHINA PRECIPITATION SIMULATION ALGORITHM GROWTH TURKEY
英文关键词	Global solar radiation; Artificial neural network; Remote sensing; MODIS; TRMM
语种	英语
WOS研究方向	Energy & Fuels ; Engineering
WOS类目	Energy & Fuels ; Engineering, Chemical
WOS记录号	WOS:000289497400021
来源期刊	APPLIED ENERGY
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/257915
推荐引用方式 GB/T 7714	Qin, Jun,Chen, Zhuoqi,Yang, Kun,et al. Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products[J]. 中国科学院青藏高原研究所,2011,88(7).
APA	Qin, Jun,Chen, Zhuoqi,Yang, Kun,Liang, Shunlin,&Tang, Wenjun.(2011).Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products.APPLIED ENERGY,88(7).
MLA	Qin, Jun,et al."Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products".APPLIED ENERGY 88.7(2011).