17 Jan 2024
 | 17 Jan 2024
Status: this preprint is currently under review for the journal AMT.

Regional validation of the solar irradiance tool SolaRes in clear-sky conditions, with a focus on the aerosol module

Thierry Elias, Nicolas Ferlay, Gabriel Chesnoiu, Isabelle Chiapello, and Mustapha Moulana

Abstract. The objective of the paper is to validate SolaRes (Solar Resource estimate) in clear-sky conditions, and to examine the aerosol influence on the differences between observation and estimate. SolaRes has the ambition to fulfil both research and industrial applications exploiting downwelling solar radiation at surface level. Consistently with solar resource applications, we show the capacity of SolaRes to reproduce the angular behaviour of the angular field, by validating not only global horizontal irradiance (GHI), but also direct normal irradiance (DNI), diffuse horizontal irradiance (DifHI), global and diffuse irradiance in tilted plane (GTI, DifTI), and even the circumsolar contributions.

Computations are made with the SMART-G radiative transfer code, taking spectral aerosol optical thickness (AOT) data sets as input, which are delivered by the Aerosol Robotic network (AERONET) and the Copernicus Atmospheric Monitoring Service (CAMS). A mixture of two aerosol models is required to compute aerosol optical properties. Measurements for validation are made at two sites in Northern France. Clear-sky is identified by two methods to show its influence: 1) a method reproducing the AOT variability conditions, and 2) a stricter method eliminating some residual cloud influence but also conditions with largest AOT.

SolaRes is validated according to comparison scores found in the literature, with the (relative) root mean square difference (RMSD) in GHI as low as 1 %, and the mean bias difference (MBD) which could be 0 %. Angular behaviour is reproduced with satisfying scores. The circumsolar contribution improves MBD in DNI and DifHI, by 1 % and 4 % respectively, as well as RMSD by ~0.5 %. MBD in DNI is around -1 % and RMSD around 2 %, and MBD in DifHI is 2 % and RMSD around 9 %. RMSD and MBD in both DNI and DifHI are larger than in GHI because they are more sensitive to the aerosol and surface properties. DifTI measured in a vertical plane facing South is reproduced with a RMSD of 8 %, similar to DifHI. It is suggested a strong influence of reflection by not only ground surface but also surrounding buildings, increasing the albedo from 0.13 to 0.35.

The sensitivity study on the aerosol parameterisation shows that the spectral AOT contains enough information for best quality in DNI retrieval. The choice of aerosol models in the parameterisation has an influence in RMSD smaller than 0.7 %. Complementary information on angular scattering and aerosol absorption has a significant influence in GHI by reducing RMSD by ~0.5 %, and MBD by ~0.8 %. The uncertainty on the data source has a significant influence. The CAMS data set increases the RMSD in DNI by 5 %, but has has less influence in GHI, by increasing RMSD by ~1 % and MBD by ~0.4 %. RMSD in GHI still remains slightly smaller than state-of-the-art methods.

Thierry Elias, Nicolas Ferlay, Gabriel Chesnoiu, Isabelle Chiapello, and Mustapha Moulana

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-236', Anonymous Referee #1, 07 Feb 2024
  • RC2: 'Comment on amt-2023-236', Anonymous Referee #2, 19 Feb 2024
  • RC3: 'Comment on amt-2023-236', Anonymous Referee #3, 20 Feb 2024
Thierry Elias, Nicolas Ferlay, Gabriel Chesnoiu, Isabelle Chiapello, and Mustapha Moulana
Thierry Elias, Nicolas Ferlay, Gabriel Chesnoiu, Isabelle Chiapello, and Mustapha Moulana


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Short summary
In the solar energy application field, it is important to simulate solar resource anywhere on the globe. We conceived the SolaRes tool to provide precise and accurate estimates of solar resource estimates for any solar plant technology. The paper presents the validation of SolaRes, by comparing estimates with measurements made on two ground-based platforms. Little differences are found, validating SolaRes. Validation is performed in clear-sky conditions when aerosols are main factors.