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dc.contributor.authorFoyo Moreno, Inmaculada 
dc.contributor.authorLozano, Ismael L.
dc.contributor.authorAlados, Inmaculada
dc.contributor.authorGuerrero Rascado, Juan Luis 
dc.date.accessioned2025-05-12T09:30:44Z
dc.date.available2025-05-12T09:30:44Z
dc.date.issued2025-04-01
dc.identifier.citationI. Foyo-Moreno et al. Atmospheric Research 315 (2025) 107886. https://doi.org/10.1016/j.atmosres.2024.107886es_ES
dc.identifier.urihttps://hdl.handle.net/10481/104058
dc.descriptionThis work was supported by the Spanish Ministry of Economy and Competitiveness through projects CGL2017-90884-REDT, PID2020-120015RB-I00, PID2020-117825GB-C21, PID2020-117825GB-C22 and PID2021-128008OB-I00, by the Andalusia Regional Government, University of Granada and FEDER funds through project C-EXP-363-UGR23. This research was partially supported by the Scientific Units of Excellence Program (grant no. UCE-PP2017-02).es_ES
dc.description.abstractNet surface radiation is a crucial parameter across various fields, as it represents the available energy for the energy exchange between the surface and the atmosphere. This work presents a new model for estimating instantaneous daytime net surface radiation (Rn) under all sky conditions, using solar position via cos ϴz and the clearness index (kt) as predictors. Global solar radiation (G↓) is the primary factor influencing Rn and is exten sively measured at numerous radiometric stations. Consequently, this model takes advantage of using a single input (G↓). The model was validated against other empirical models at various sites with diverse climatological characteristics. Two types of models were evaluated, one including reflected global solar irradiance (G↑) as an additional input variable alongside G↓. The best results were obtained when incorporating G↑. However, this poses a challenge as G↑ is not measured at most radiometric stations. Nevertheless, in both types, the simplest model consistently outperformed the others, revealing no significant improvements with the addition of extra variables. Overall, the proposed model demonstrated good fit with the experimental data, although with some overestimation. The coefficient of determination (R2) is over 0,94, except at sites with extreme surface albedo conditions (α >0,55). Mean bias error values ranged from 4 Wm2 to 44 Wm2, while root mean square error values varied from 25 Wm2 to 62 Wm2. Additional assessments across different seasons and sky conditions revealed improved performance during colder seasons and under cloudy conditions. Finally, the statistical analysis of the proposed model falls within the range of other more sophisticated models that involve additional input variables.es_ES
dc.description.sponsorshipSpanish Ministry of Economy and Competitiveness CGL2017-90884-REDT, PID2020-120015RB-I00, PID2020-117825GB-C21, PID2020-117825GB-C22 and PID2021-128008OB-I00es_ES
dc.description.sponsorshipAndalusia Regional Governmentes_ES
dc.description.sponsorshipUniversity of Granadaes_ES
dc.description.sponsorshipFEDER C-EXP-363-UGR23es_ES
dc.description.sponsorshipScientific Units of Excellence Program (UCE-PP2017-02)es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licenseen_EN
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en_EN
dc.titleA new model to estimate daytime net surface radiation under all sky conditionses_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.atmosres.2024.107886
dc.type.hasVersionVoRes_ES


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