Paper Info
Title
A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin.
Abstract
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.
Year
DOI
Venue
2016
10.3390/s16111859
SENSORS
Keywords
Field
DocType
sunshine duration,cloud classification,FY-2D,Heihe River Basin
Meteorology,Satellite,Drainage basin,Interpolation,Sunshine duration,Atmospheric electricity,Energy balance,Engineering,Evapotranspiration,Geostationary orbit
Journal
Volume
Issue
ISSN
16
11.0
1424-8220
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Wu Bingfang116539.66
Shufu Liu231.12
Weiwei Zhu321.12
Mingzhao Yu400.68
Nana Yan531.51
Qiang Xing6133.07