Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria

Downward longwave radiation flux is an important variable for estimating net radiation, in order to investigate the surface energy budget and carry out climatic studies. The flux is usually estimated using empirical models based on the information of meteorological parameters such as relative humidi...

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Autor: Soneye-Arogundade, Olanrewaju Olukemi
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:México
Institución:UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO
Repositorio:Atmósfera
Idioma:inglés
OAI Identifier:oai:ojs.pkp.sfu.ca:article/52843
Acceso en línea:https://www.revistascca.unam.mx/atm/index.php/atm/article/view/52843
Access Level:acceso abierto
Palabra clave:surface energy budget
downward longwave radiation
cloudless sky
calibration coefficient
statistical errors
meteorological parameters
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spelling Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, NigeriaSoneye-Arogundade, Olanrewaju Olukemisurface energy budgetdownward longwave radiationcloudless skycalibration coefficientstatistical errorsmeteorological parametersDownward longwave radiation flux is an important variable for estimating net radiation, in order to investigate the surface energy budget and carry out climatic studies. The flux is usually estimated using empirical models based on the information of meteorological parameters such as relative humidity, surface and air temperature, and water vapor pressure. This paper presents the assessment of 11 widely used empirical models for estimating downward longwave radiation using a ground-based dataset acquired from January 2016 to December 2017 at Ile-Ife, a tropical city in Nigeria. The original Idso and Niemela et al. models performed better than other models with errors less than 5.0% when compared to measured values. The performances of all the models improved greatly after calibration. The Guest model, which gave low errors (MBE = 0.65 Wm–2, RMBE = 0.15%, RMSE = 9.38 Wm–2, RRMSE = 2.14%, MAE = 7.84 Wm–2, RMAE = 1.79%), performed best followed by the Dilley and O’Brien, Idso, Prata, Brutsaert, Garratt, Niemela et al., and Ångström models. The calibrated models presented in this study can be used to estimate the flux under cloudless sky conditions at Ile-Ife and at other places with similar meteorological conditions, where this flux is not measured due to technological problems and the high cost of purchasing and maintaining the needed sensors. The proposed model for estimating the flux showed better performance with lower statistical errors than all the existing empirical models tested, and conform greatly (R2 = 0.88) to the measured data.Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México2020-08-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttps://www.revistascca.unam.mx/atm/index.php/atm/article/view/5284310.20937/ATM.52843Atmósfera; Vol. 34 Núm. 4 (2021); 417-432Atmósfera; Vol. 34 No. 4 (2021); 417-4322395-88120187-6236reponame:Atmósferainstname:UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICOinstacron:UNAMenghttps://www.revistascca.unam.mx/atm/index.php/atm/article/view/52843/46731https://www.revistascca.unam.mx/atm/index.php/atm/article/view/52843/46863Copyright (c) 2020 Atmósferahttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessoai:ojs.pkp.sfu.ca:article/528432024-08-16T16:52:41Z
dc.title.none.fl_str_mv Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria
title Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria
spellingShingle Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria
Soneye-Arogundade, Olanrewaju Olukemi
surface energy budget
downward longwave radiation
cloudless sky
calibration coefficient
statistical errors
meteorological parameters
title_short Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria
title_full Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria
title_fullStr Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria
title_full_unstemmed Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria
title_sort Evaluation and calibration of downward longwave radiation models under cloudless sky at Ile-Ife, Nigeria
dc.creator.none.fl_str_mv Soneye-Arogundade, Olanrewaju Olukemi
author Soneye-Arogundade, Olanrewaju Olukemi
author_facet Soneye-Arogundade, Olanrewaju Olukemi
author_role author
dc.subject.none.fl_str_mv surface energy budget
downward longwave radiation
cloudless sky
calibration coefficient
statistical errors
meteorological parameters
topic surface energy budget
downward longwave radiation
cloudless sky
calibration coefficient
statistical errors
meteorological parameters
description Downward longwave radiation flux is an important variable for estimating net radiation, in order to investigate the surface energy budget and carry out climatic studies. The flux is usually estimated using empirical models based on the information of meteorological parameters such as relative humidity, surface and air temperature, and water vapor pressure. This paper presents the assessment of 11 widely used empirical models for estimating downward longwave radiation using a ground-based dataset acquired from January 2016 to December 2017 at Ile-Ife, a tropical city in Nigeria. The original Idso and Niemela et al. models performed better than other models with errors less than 5.0% when compared to measured values. The performances of all the models improved greatly after calibration. The Guest model, which gave low errors (MBE = 0.65 Wm–2, RMBE = 0.15%, RMSE = 9.38 Wm–2, RRMSE = 2.14%, MAE = 7.84 Wm–2, RMAE = 1.79%), performed best followed by the Dilley and O’Brien, Idso, Prata, Brutsaert, Garratt, Niemela et al., and Ångström models. The calibrated models presented in this study can be used to estimate the flux under cloudless sky conditions at Ile-Ife and at other places with similar meteorological conditions, where this flux is not measured due to technological problems and the high cost of purchasing and maintaining the needed sensors. The proposed model for estimating the flux showed better performance with lower statistical errors than all the existing empirical models tested, and conform greatly (R2 = 0.88) to the measured data.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://www.revistascca.unam.mx/atm/index.php/atm/article/view/52843
10.20937/ATM.52843
url https://www.revistascca.unam.mx/atm/index.php/atm/article/view/52843
identifier_str_mv 10.20937/ATM.52843
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistascca.unam.mx/atm/index.php/atm/article/view/52843/46731
https://www.revistascca.unam.mx/atm/index.php/atm/article/view/52843/46863
dc.rights.none.fl_str_mv Copyright (c) 2020 Atmósfera
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Atmósfera
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
dc.publisher.none.fl_str_mv Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México
publisher.none.fl_str_mv Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México
dc.source.none.fl_str_mv Atmósfera; Vol. 34 Núm. 4 (2021); 417-432
Atmósfera; Vol. 34 No. 4 (2021); 417-432
2395-8812
0187-6236
reponame:Atmósfera
instname:UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO
instacron:UNAM
instname_str UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO
instacron_str UNAM
institution UNAM
reponame_str Atmósfera
collection Atmósfera
repository.name.fl_str_mv
repository.mail.fl_str_mv
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