Estimation of monthly-mean global solar radiation using MODIS atmospheric product over China

被引:23
作者
Chen, Ji-Long [1 ,2 ,3 ]
Xiao, Bei-Bei [4 ,5 ,6 ]
Chen, Chun-Di [1 ,2 ]
Wen, Zhao-Fei [1 ,2 ]
Jiang, Yi [1 ,2 ]
Lv, Ming-Quan [1 ,2 ]
Wu, Sheng-Jun [1 ,2 ]
Li, Guo-Sheng [3 ]
机构
[1] Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 401122, Peoples R China
[2] Chinese Acad Sci, Key Lab Water Environm Reservoir Watershed, Chongqing 401122, Peoples R China
[3] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
[4] Chongqing Inst Surveying & Planning Land Resource, Chongqing 400020, Peoples R China
[5] Chongqing Res Ctr, Natl Engn Technol Res Ctr Remote Sensing Applicat, Chongqing 400020, Peoples R China
[6] Chongqing Xinrong Inst Surveying Technol Land & H, Chongqing 400020, Peoples R China
基金
中国科学院西部之光基金;
关键词
Month-mean global solar radiation; Models; MODIS; Atmosphere constituents; SURFACE SHORTWAVE RADIATION; DAILY NET-RADIATION; AIR-TEMPERATURE; MODEL; SATELLITE; IRRADIANCE; SUNSHINE; COVER; PARAMETERIZATION; ALGORITHM;
D O I
10.1016/j.jastp.2014.01.017
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
This paper investigated the potential of MOD08-M3 atmospheric product in estimation of monthly-mean solar radiation. 8 models were developed using cloud fraction (CF), cloud optical thickness (COT), precipitable water vapor (PWV) and aerosol optical thickness (AOT) at 50 stations across China. All the models give reasonable results with average RMSE of 1.247 MJ m(-2) and MAPE of 9.9%. Models have lower RMSE in cool temperature (CT) and warm temperate (WT) zones. In terms of MAPE, models perform better in Qinghai-Tibet plateau climate (QT) zone. Model accuracy can be significantly improved by introducing COT and PWV. The improvements by introducing COT are more pronounced in summer for CT, WT and ST regions. While inclusion of PWV is more effective in summer, autumn, and winter for CT, QT, and ST regions, respectively. However, introducing AOT does not contribute to the improvement in estimation accuracy. The performances of models show seasonal behavior. In terms of MAPE, models perform best in summer for CT and WT regions, and in autumn for ST region. Lowest RMSE are observed in autumn and winter for CT and QT regions, respectively. Models have lower RMSE in both autumn and winter for WT and ST regions. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:63 / 80
页数:18
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