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 m...

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Main Authors: Bingfang Wu, Shufu Liu, Weiwei Zhu, Mingzhao Yu, Nana Yan, Qiang Xing
Format: Article
Language:English
Published: MDPI AG 2016-11-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/16/11/1859
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author Bingfang Wu
Shufu Liu
Weiwei Zhu
Mingzhao Yu
Nana Yan
Qiang Xing
author_facet Bingfang Wu
Shufu Liu
Weiwei Zhu
Mingzhao Yu
Nana Yan
Qiang Xing
author_sort Bingfang Wu
collection DOAJ
description 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.
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spelling doaj.art-f732f6a4eb5a49558fb17ae4a4ea3ae92022-12-22T02:59:01ZengMDPI AGSensors1424-82202016-11-011611185910.3390/s16111859s16111859A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River BasinBingfang Wu0Shufu Liu1Weiwei Zhu2Mingzhao Yu3Nana Yan4Qiang Xing5Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, ChinaInstitute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, ChinaInstitute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, ChinaInstitute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, ChinaInstitute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, ChinaInstitute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences, Beijing 100094, ChinaSunshine 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.http://www.mdpi.com/1424-8220/16/11/1859sunshine durationcloud classificationFY-2DHeihe River Basin
spellingShingle Bingfang Wu
Shufu Liu
Weiwei Zhu
Mingzhao Yu
Nana Yan
Qiang Xing
A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin
Sensors
sunshine duration
cloud classification
FY-2D
Heihe River Basin
title A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin
title_full A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin
title_fullStr A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin
title_full_unstemmed A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin
title_short A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin
title_sort method to estimate sunshine duration using cloud classification data from a geostationary meteorological satellite fy 2d over the heihe river basin
topic sunshine duration
cloud classification
FY-2D
Heihe River Basin
url http://www.mdpi.com/1424-8220/16/11/1859
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