Work

A new model to estimate daytime net surface radiation under all sky conditions

Year: 2024

Type: article

Abstract: Net 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 (R n ) under all sky conditions, using solar position via cos ϴ z and the clearness index (k t ) as predictors. Global solar radiation (G ↓ ) is the primary factor influencing R n and is extensively 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 (R 2 ) is over 0,94, except at sites with extreme surface albedo conditions (α > 0,55). Mean bias error values ranged from 4 Wm −2 to 44 Wm −2 , while root mean square error values varied from 25 Wm −2 to 62 Wm −2 . 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. • A new model for net radiation during daytime under all sky conditions is proposed. • Model based only on solar irradiance data, available in many radiometric stations. • Radiometric characterization can be easily extended, increasing global coverage.

Source: Atmospheric Research

DOI: 10.1016/j.atmosres.2024.107886

Authors: Inmaculada Foyo-Moreno, Ismael L. Lozano, Inmaculada Alados, Juan Luis Guerrero-Rascado

Institutions: Universidad de Granada, Instituto Andaluz de Ciencias de la Tierra, University of Helsinki, Universidad de Málaga

Language: English

Topic: Solar Radiation and Photovoltaics

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Climate action

Open Access status: hybrid

Estimated APC paid: $3,210