A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin.
Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements. In this paper, a satellite-based method to estimate sunshine duration is introduced and applied over the Heihe River Basin. This method is based on hourly cloud classification product data from the FY-2D geostationary meteorological satellite (FY-2D). A new index-FY-2D cloud type sunshine factor-is proposed, and the Shuffled Complex Evolution Algorithm (SCE-UA) was used to calibrate sunshine factors from different coverage types based on ground measurement data from the Heihe River Basin in 2007. The estimated sunshine duration from the proposed new algorithm was validated with ground observation data for 12 months in 2008, and the spatial distribution was compared with the results of an interpolation method over the Heihe River Basin. The study demonstrates that geostationary satellite data can be used to successfully estimate sunshine duration. Potential applications include climate research, energy balance studies, and global estimations of evapotranspiration.
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China. wubf@radi.ac.cn.
Bingfang
B
Wu
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China. liushf_263@163.com.
Shufu
S
Liu
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China. zhuww@radi.ac.cn.
Weiwei
W
Zhu
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China. Yumz@radi.ac.cn.
Mingzhao
M
Yu
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China. yannn@radi.ac.cn.
Nana
N
Yan
Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, China. xingqiang@radi.ac.cn.
Qiang
Q
Xing
FY-2D; Heihe River Basin; cloud classification; sunshine duration