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SPARTA: Solar parameterization for the radiative transfer of the cloudless atmosphere

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  • Ruiz-Arias, José A.

Abstract

The high-performance SPARTA broadband clear-sky solar irradiance model is presented. It evaluates global (GHI), diffuse (DIF) and direct normal (DNI) irradiances from atmospheric transmittance functions developed using an advanced 2-band hybrid spectral integration scheme, calculates aerosol extinction using a universal and highly accurate aerosol transmittance scheme, and incorporates a versatile parameterization of the aerosol circumsolar solar irradiance. The model's performance is assessed against 1-min quality-assured measurements at three research-class radiometric ground stations spanning 15 years of data combined, and it is benchmarked against three high-performance radiative transfer models. The performance assessment proved that SPARTA was superior to the reference models for GHI, DIF and DNI at the three observational sites combined. SPARTA produced unbiased estimates of the three solar irradiance components (remarkably, it was the only model producing unbiased estimates of DIF) and yielded the smallest standard deviations of the model−observation differences (≈2 %, ≈10 % and ≈2 % for GHI, DIF and DNI, respectively). SPARTA was the only model capable of improving the estimation of DIF when using observed inputs of the aerosol scattering optical properties instead of modelled values. The results of the performance assessment proved that, provided accurate inputs to the model, SPARTA produces predictions with similar uncertainty than ground observations, especially if the ground sensors are not optimaly maintained or they are not A or B ISO-9060 class.

Suggested Citation

  • Ruiz-Arias, José A., 2023. "SPARTA: Solar parameterization for the radiative transfer of the cloudless atmosphere," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
  • Handle: RePEc:eee:rensus:v:188:y:2023:i:c:s1364032123006901
    DOI: 10.1016/j.rser.2023.113833
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    References listed on IDEAS

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    1. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    2. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2019. "Worldwide performance assessment of 75 global clear-sky irradiance models using Principal Component Analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 550-570.
    3. Sengupta, Manajit & Xie, Yu & Lopez, Anthony & Habte, Aron & Maclaurin, Galen & Shelby, James, 2018. "The National Solar Radiation Data Base (NSRDB)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 51-60.
    4. Sun, Xixi & Bright, Jamie M. & Gueymard, Christian A. & Bai, Xinyu & Acord, Brendan & Wang, Peng, 2021. "Worldwide performance assessment of 95 direct and diffuse clear-sky irradiance models using principal component analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. Gueymard, Christian A. & Bright, Jamie M. & Lingfors, David & Habte, Aron & Sengupta, Manajit, 2019. "A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 412-427.
    6. Yang, Dazhi, 2022. "Estimating 1-min beam and diffuse irradiance from the global irradiance: A review and an extensive worldwide comparison of latest separation models at 126 stations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    7. Ruiz-Arias, José A., 2021. "Aerosol transmittance for clear-sky solar irradiance models: Review and validation of an accurate universal parameterization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    8. Antonanzas-Torres, F. & Urraca, R. & Polo, J. & Perpiñán-Lamigueiro, O. & Escobar, R., 2019. "Clear sky solar irradiance models: A review of seventy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 374-387.
    9. Ruiz-Arias, José A., 2022. "Spectral integration of clear-sky atmospheric transmittance: Review and worldwide performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    10. Paulescu, Eugenia & Paulescu, Marius, 2021. "A new clear sky solar irradiance model," Renewable Energy, Elsevier, vol. 179(C), pages 2094-2103.
    11. Gueymard, Christian A. & Ruiz-Arias, José Antonio, 2015. "Validation of direct normal irradiance predictions under arid conditions: A review of radiative models and their turbidity-dependent performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 379-396.
    12. Bright, Jamie M. & Sun, Xixi & Gueymard, Christian A. & Acord, Brendan & Wang, Peng & Engerer, Nicholas A., 2020. "Bright-Sun: A globally applicable 1-min irradiance clear-sky detection model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
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