## 2 Literature Review
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Study** & **Year** & **Clear Sky Model** & **rMBE (\%)** & **rRMSE (\%)** & **R\({}^{2}\)** \\ \hline [PERSON] et al. [11] & \multicolumn{3}{c}{[PERSON]} & 0.6\% & 2.2\% & 0.96 \\ \cline{2-6}  & 2021 & [PERSON] (day ahead) & 0.8\% & 3.3\% & 0.99 \\ \hline [PERSON] et al. [57] & 2013 & 54 models & - & 7–14\%, & - \\ \hline [PERSON] et al. [46] & 2016 & Various models & - & less than 30\% & - \\ \hline [PERSON] et al. [47] & 2019 & European Solar Radiation Atlas (ESRA) & - & 6.26\% & - \\ \cline{2-6}  & \multicolumn{3}{c}{[PERSON]–Perez} & - & 3.84\% & - \\ \hline [PERSON] et al. [50] & 2019 & \multicolumn{3}{c}{75 GHI clear sky irradiance models} & - & - \\ \cline{2-6}  & 2016 & \multicolumn{3}{c}{ASHRAE [61; 62], Campbell,} & - & - & - \\ \cline{2-6}  & 2017 & \multicolumn{3}{c}{[63] and [PERSON] [64]} & - & - & - \\ \hline Laguarda and Abal [51] & 2017 & \multicolumn{3}{c}{ESRA, Simplified Solis, and Kasten} & Negative up to \(-5.3\%\) & Range between 4.3\% and 7\% & - \\ \hline Ineichen [7] & 2016 & \multicolumn{3}{c}{Eight high clear sky solar irradiance models} & Negative up to \(-1\%\) & Range between 4\% & - \\ \hline Kwaraikunda and Chiguvare [58] & 2021 & \multicolumn{3}{c}{Berger–Duffie,} & \multirow{3}{*}{-} & Range between 4\% & \multirow{3}{*}{Exceeded 0.98 for all three models} \\  & 2021 & \multicolumn{3}{c}{Adnot–Bourger–Campana–Gicquel and Robledo-Soler} & & \multirow{3}{*}{-} & Range between 4\% & \multirow{3}{*}{Exceeded 0.98 for all three models} \\ \cline{6-6}  & 2017 & \multicolumn{3}{c}{Louche,} & \multirow{3}{*}{-} & 9.9\% to 5.7\% & \multirow{3}{*}{-} \\ \cline{6-6}  & 2017 & \multicolumn{3}{c}{Robledo–Soler, and European} & & 7.8\% to 7.4\%\&8.8\% & \multirow{3}{*}{-} \\ \cline{6-6}  & \multicolumn{3}{c}{Solar Radiation Atlas} & & 5.7\% to 9.9\% & & \\ \hline Alam [67] & 2006 & REST, Yang, and CPCR2 & - & Up to 7\%, 13.4\%, & \multirow{3}{*}{-} \\  & & & and 25.9\% & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Overview of the verification results from the reviewed literature. [PERSON] and [PERSON] [13] investigated six GHI clear sky models using theoretical baseline dependence on transmittance, transmittance after molecular scattering, water vapor transmittance, and ozone transmittance. The study's findings contributed to the development of the [PERSON] clear sky model. [PERSON] [68] investigated the validity and effectiveness of 11 GHI clear sky models in estimating GHI. The representations of atmospheric effects in clear sky models were explored as well as their sensitivity to optical masses, Rayleigh scattering, ozone absorption, mixed gas absorption, water vapor absorption, and aerosol extinction. The models' accuracy was validated by comparing them to data obtained in situ at seven different locations in California, Canada, Belgium, Switzerland, France, and India. The more-physical models are found to be generally of higher accuracy and greater flexibility than empirical models. [PERSON] [69] evaluated 8 GHI clear sky models with 16 distinct databanks of observed GHI covering 20 years and stations, a range of altitudes including 1600 m, and a wide range of climates. Given the models' complexity, the author investigated the impact of atmospheric parameters and indicated that utilizing meteorological databanks rather than locally observed meteorological parameters resulted in underestimation of GHI by the models. According to the author, while accuracy is not heavily reliant on the model, model selection should be based on either the implementation convenience or the availability of input parameters. [PERSON] and [PERSON] [70] analysed four GHI clear sky models at six different locations in the United Kingdom, Spain, and India. The Meteorological Radiation Model (MRM) performed best after being locally calibrated. REST2 [15] was the best performing model among uncalibrated models. [PERSON] [71] used atmospheric data to assess five models capable of forecasting DNI under clear skies.