A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model

This paper presents a technique to map monthly average hourly global illuminance from satellite data. A semi-empirical model relating monthly average global illuminance to cloud index, precipitable water, total ozone column (TOC), aerosol optical depth (AOD) and air mass was developed. Data for the...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Renewable energy 2015-02, Vol.74, p.170-175
Hauptverfasser: Pattarapanitchai, S., Janjai, S., Tohsing, K., Prathumsit, J.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 175
container_issue
container_start_page 170
container_title Renewable energy
container_volume 74
creator Pattarapanitchai, S.
Janjai, S.
Tohsing, K.
Prathumsit, J.
description This paper presents a technique to map monthly average hourly global illuminance from satellite data. A semi-empirical model relating monthly average global illuminance to cloud index, precipitable water, total ozone column (TOC), aerosol optical depth (AOD) and air mass was developed. Data for the cloud index, AOD and TOC were obtained from the visible imagery data of MTSAT-1R, MODIS/Terra and OMI/Aura satellites respectively, while precipitable water was extracted from NCEP/NCAR reanalysis database. The model was formulated using global illuminance measured at four stations in Thailand for a four-year period and validated with an independent one-year data set. Values of monthly average hourly global illuminance calculated from the model and those obtained from the measurements were in good agreement, with a root mean square difference (RMSD) and mean bias difference (MBD) of 8.1% and −0.8%, respectively. The model was used to calculate monthly average hourly global illuminance over Thailand and the results were displayed as illuminance maps. The maps reveal diurnal and seasonal effects mainly in response to solar zenith angle changes and cloud cover related to the southwest and northeast monsoons. •A technique to map monthly average global illuminance from satellite data in the tropics was proposed.•The illuminance was estimated using a simple semi-empirical model.•Values of measured and estimated illuminance are in good agreement.•Monthly average illuminance maps over Thailand were produced.
doi_str_mv 10.1016/j.renene.2014.08.005
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1660096468</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0960148114004637</els_id><sourcerecordid>1660096468</sourcerecordid><originalsourceid>FETCH-LOGICAL-c372t-b734cb317ac01563550b59e441e349ffdd2af37cc33321ce4bb05e389b09c8923</originalsourceid><addsrcrecordid>eNqNUU1r3DAUFKWFbtP-gx50zMXukyVb8qUQQpIGArm0ZyHLz7taJMuVtIFAfnwUNudS3uFdZob5IOQ7g5YBG34c24RrvbYDJlpQLUD_geyYkmMDg-o-kh2MAzRMKPaZfMn5CMB6JcWOvFzRgvawur8npCXSYDYa4loO_pmaJ0xmj3Tv42Q8dd6fglvNapEuKQaaTUHvXUE6m2KoW2k5VJEUN2czPWW37qmh2YXNI80YXINhc8nZKhbijP4r-bQYn_Hb-78gf25vfl__ah4e7-6vrx4ay2VXmklyYSfOpLHV9sD7HqZ-RCEYcjEuyzx3ZuHSWs55xyyKaYIeuRonGK0aO35BLs-6W4o1Zy46uGyrd7NiPGXNhgFqQWJQ_wEVEkCMUlaoOENtijknXPSWXDDpWTPQb7vooz7vot920aB03aXSfp5pWBM_OUw6W4e11NkltEXP0f1b4BVfp5mi</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1647004977</pqid></control><display><type>article</type><title>A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model</title><source>ScienceDirect Journals (5 years ago - present)</source><creator>Pattarapanitchai, S. ; Janjai, S. ; Tohsing, K. ; Prathumsit, J.</creator><creatorcontrib>Pattarapanitchai, S. ; Janjai, S. ; Tohsing, K. ; Prathumsit, J.</creatorcontrib><description>This paper presents a technique to map monthly average hourly global illuminance from satellite data. A semi-empirical model relating monthly average global illuminance to cloud index, precipitable water, total ozone column (TOC), aerosol optical depth (AOD) and air mass was developed. Data for the cloud index, AOD and TOC were obtained from the visible imagery data of MTSAT-1R, MODIS/Terra and OMI/Aura satellites respectively, while precipitable water was extracted from NCEP/NCAR reanalysis database. The model was formulated using global illuminance measured at four stations in Thailand for a four-year period and validated with an independent one-year data set. Values of monthly average hourly global illuminance calculated from the model and those obtained from the measurements were in good agreement, with a root mean square difference (RMSD) and mean bias difference (MBD) of 8.1% and −0.8%, respectively. The model was used to calculate monthly average hourly global illuminance over Thailand and the results were displayed as illuminance maps. The maps reveal diurnal and seasonal effects mainly in response to solar zenith angle changes and cloud cover related to the southwest and northeast monsoons. •A technique to map monthly average global illuminance from satellite data in the tropics was proposed.•The illuminance was estimated using a simple semi-empirical model.•Values of measured and estimated illuminance are in good agreement.•Monthly average illuminance maps over Thailand were produced.</description><identifier>ISSN: 0960-1481</identifier><identifier>EISSN: 1879-0682</identifier><identifier>DOI: 10.1016/j.renene.2014.08.005</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Argon oxygen decarburizing ; Clouds ; Global illuminance ; Illuminance ; Mathematical models ; Satellite data ; Satellite imagery ; Satellites ; Thailand ; Tropics</subject><ispartof>Renewable energy, 2015-02, Vol.74, p.170-175</ispartof><rights>2014 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c372t-b734cb317ac01563550b59e441e349ffdd2af37cc33321ce4bb05e389b09c8923</citedby><cites>FETCH-LOGICAL-c372t-b734cb317ac01563550b59e441e349ffdd2af37cc33321ce4bb05e389b09c8923</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.renene.2014.08.005$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids></links><search><creatorcontrib>Pattarapanitchai, S.</creatorcontrib><creatorcontrib>Janjai, S.</creatorcontrib><creatorcontrib>Tohsing, K.</creatorcontrib><creatorcontrib>Prathumsit, J.</creatorcontrib><title>A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model</title><title>Renewable energy</title><description>This paper presents a technique to map monthly average hourly global illuminance from satellite data. A semi-empirical model relating monthly average global illuminance to cloud index, precipitable water, total ozone column (TOC), aerosol optical depth (AOD) and air mass was developed. Data for the cloud index, AOD and TOC were obtained from the visible imagery data of MTSAT-1R, MODIS/Terra and OMI/Aura satellites respectively, while precipitable water was extracted from NCEP/NCAR reanalysis database. The model was formulated using global illuminance measured at four stations in Thailand for a four-year period and validated with an independent one-year data set. Values of monthly average hourly global illuminance calculated from the model and those obtained from the measurements were in good agreement, with a root mean square difference (RMSD) and mean bias difference (MBD) of 8.1% and −0.8%, respectively. The model was used to calculate monthly average hourly global illuminance over Thailand and the results were displayed as illuminance maps. The maps reveal diurnal and seasonal effects mainly in response to solar zenith angle changes and cloud cover related to the southwest and northeast monsoons. •A technique to map monthly average global illuminance from satellite data in the tropics was proposed.•The illuminance was estimated using a simple semi-empirical model.•Values of measured and estimated illuminance are in good agreement.•Monthly average illuminance maps over Thailand were produced.</description><subject>Argon oxygen decarburizing</subject><subject>Clouds</subject><subject>Global illuminance</subject><subject>Illuminance</subject><subject>Mathematical models</subject><subject>Satellite data</subject><subject>Satellite imagery</subject><subject>Satellites</subject><subject>Thailand</subject><subject>Tropics</subject><issn>0960-1481</issn><issn>1879-0682</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNUU1r3DAUFKWFbtP-gx50zMXukyVb8qUQQpIGArm0ZyHLz7taJMuVtIFAfnwUNudS3uFdZob5IOQ7g5YBG34c24RrvbYDJlpQLUD_geyYkmMDg-o-kh2MAzRMKPaZfMn5CMB6JcWOvFzRgvawur8npCXSYDYa4loO_pmaJ0xmj3Tv42Q8dd6fglvNapEuKQaaTUHvXUE6m2KoW2k5VJEUN2czPWW37qmh2YXNI80YXINhc8nZKhbijP4r-bQYn_Hb-78gf25vfl__ah4e7-6vrx4ay2VXmklyYSfOpLHV9sD7HqZ-RCEYcjEuyzx3ZuHSWs55xyyKaYIeuRonGK0aO35BLs-6W4o1Zy46uGyrd7NiPGXNhgFqQWJQ_wEVEkCMUlaoOENtijknXPSWXDDpWTPQb7vooz7vot920aB03aXSfp5pWBM_OUw6W4e11NkltEXP0f1b4BVfp5mi</recordid><startdate>20150201</startdate><enddate>20150201</enddate><creator>Pattarapanitchai, S.</creator><creator>Janjai, S.</creator><creator>Tohsing, K.</creator><creator>Prathumsit, J.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7U6</scope><scope>C1K</scope><scope>SOI</scope><scope>7SU</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20150201</creationdate><title>A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model</title><author>Pattarapanitchai, S. ; Janjai, S. ; Tohsing, K. ; Prathumsit, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c372t-b734cb317ac01563550b59e441e349ffdd2af37cc33321ce4bb05e389b09c8923</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Argon oxygen decarburizing</topic><topic>Clouds</topic><topic>Global illuminance</topic><topic>Illuminance</topic><topic>Mathematical models</topic><topic>Satellite data</topic><topic>Satellite imagery</topic><topic>Satellites</topic><topic>Thailand</topic><topic>Tropics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pattarapanitchai, S.</creatorcontrib><creatorcontrib>Janjai, S.</creatorcontrib><creatorcontrib>Tohsing, K.</creatorcontrib><creatorcontrib>Prathumsit, J.</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Renewable energy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pattarapanitchai, S.</au><au>Janjai, S.</au><au>Tohsing, K.</au><au>Prathumsit, J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model</atitle><jtitle>Renewable energy</jtitle><date>2015-02-01</date><risdate>2015</risdate><volume>74</volume><spage>170</spage><epage>175</epage><pages>170-175</pages><issn>0960-1481</issn><eissn>1879-0682</eissn><abstract>This paper presents a technique to map monthly average hourly global illuminance from satellite data. A semi-empirical model relating monthly average global illuminance to cloud index, precipitable water, total ozone column (TOC), aerosol optical depth (AOD) and air mass was developed. Data for the cloud index, AOD and TOC were obtained from the visible imagery data of MTSAT-1R, MODIS/Terra and OMI/Aura satellites respectively, while precipitable water was extracted from NCEP/NCAR reanalysis database. The model was formulated using global illuminance measured at four stations in Thailand for a four-year period and validated with an independent one-year data set. Values of monthly average hourly global illuminance calculated from the model and those obtained from the measurements were in good agreement, with a root mean square difference (RMSD) and mean bias difference (MBD) of 8.1% and −0.8%, respectively. The model was used to calculate monthly average hourly global illuminance over Thailand and the results were displayed as illuminance maps. The maps reveal diurnal and seasonal effects mainly in response to solar zenith angle changes and cloud cover related to the southwest and northeast monsoons. •A technique to map monthly average global illuminance from satellite data in the tropics was proposed.•The illuminance was estimated using a simple semi-empirical model.•Values of measured and estimated illuminance are in good agreement.•Monthly average illuminance maps over Thailand were produced.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.renene.2014.08.005</doi><tpages>6</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0960-1481
ispartof Renewable energy, 2015-02, Vol.74, p.170-175
issn 0960-1481
1879-0682
language eng
recordid cdi_proquest_miscellaneous_1660096468
source ScienceDirect Journals (5 years ago - present)
subjects Argon oxygen decarburizing
Clouds
Global illuminance
Illuminance
Mathematical models
Satellite data
Satellite imagery
Satellites
Thailand
Tropics
title A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T12%3A52%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20technique%20to%20map%20monthly%20average%20global%20illuminance%20from%20satellite%20data%20in%20the%20tropics%20using%20a%20simple%20semi-empirical%20model&rft.jtitle=Renewable%20energy&rft.au=Pattarapanitchai,%20S.&rft.date=2015-02-01&rft.volume=74&rft.spage=170&rft.epage=175&rft.pages=170-175&rft.issn=0960-1481&rft.eissn=1879-0682&rft_id=info:doi/10.1016/j.renene.2014.08.005&rft_dat=%3Cproquest_cross%3E1660096468%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1647004977&rft_id=info:pmid/&rft_els_id=S0960148114004637&rfr_iscdi=true