气候变化领域集成服务门户(CCPortal): Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data

CCPortal

DOI	10.1016/j.apenergy.2020.115178
	Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data
	Jiang, Hou; Lu, Ning; Huang, Guanghui; Yao, Ling; Qin, Jun; Liu, Hengzi
通讯作者	Lu, N (通讯作者)
发表日期	2020
ISSN	0306-2619
EISSN	1872-9118
卷号	270
英文摘要	The presence of nonhomogeneous clouds and their induced radiation interactions result in significant horizontal photon transport and spatially adjacent effects on surface solar radiation (SSR), making spatial estimation scale-dependent. Overlooking scale effects during SSR retrieval from satellite data is responsible for variations in retrieval accuracy and deviations in associated applications. In this paper, the spatial scale effects on SSR retrieval accuracy are investigated using multivariate linear regression and artificial neural network and convolutional neural network models. Scale effects are quantified through changes in retrieval accuracy under varying satellite data input size and compared among different models to reveal the merits and defects of classic linear, ordinary nonlinear, and spatially nonlinear models. The results show that scale effects have considerable impacts on retrieval accuracy in each of the three models for both site-specific and general conditions. The maximum improvement in terms of the root mean square error can reach up to 9% after involving scale information. The performance of site-specific models is continually enhanced with the expansion of spatial scale, while that of general models will drop to some extent beyond a particular threshold. Approximate distances of 20 km and 40 km from the central location are identified as the optimal scale for artificial neural and convolutional neural networks, respectively. This study also concludes that the robustness of general models is relevant to various atmospheric factors, providing perspectives for further improvements including the fusion of time series images, integration with physical modules, and the combination of multi-resolution data.
关键词	SUNSHINE DURATION ENERGY-PRODUCTION QUALITY-CONTROL AIR-POLLUTION IRRADIANCE NETWORK MODELS PARAMETERIZATION IMPACT
英文关键词	Scale effect; Surface solar radiation; Convolutional neural network; Artificial neural network; Multivariate linear regression
语种	英语
WOS研究方向	Energy & Fuels ; Engineering
WOS类目	Energy & Fuels ; Engineering, Chemical
WOS记录号	WOS:000540433000031
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/259877
推荐引用方式 GB/T 7714	Jiang, Hou,Lu, Ning,Huang, Guanghui,et al. Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data[J]. 中国科学院青藏高原研究所,2020,270.
APA	Jiang, Hou,Lu, Ning,Huang, Guanghui,Yao, Ling,Qin, Jun,&Liu, Hengzi.(2020).Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data.APPLIED ENERGY,270.
MLA	Jiang, Hou,et al."Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data".APPLIED ENERGY 270(2020).