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Evaluation of sunshine duration from cloud data in Egypt

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  • Robaa, S.M.

Abstract

In this study, three empirical formulae have been deduced to estimate relative sunshine duration, n/N, using readily available observed data of cloud amount, C, in Egypt. The monthly mean values of n/N and C recorded at 34 stations during the period (1990–2005) have been used in the present study. The three deduced formulae have been verified for any locality in Egypt which lies above (zone 1) and below latitude 30° (zone 2) and for the whole country of Egypt. The agreement between measured and estimated values of the three deduced formulae were remarkable. It was found that the maximum possible error of estimated values, e (%), of the three deduced empirical formulae have not exceeded ±7.27% with mean percentage error (MPE) values range from −0.62% to +0.81%; meanwhile the values of statistical tests of main bias error (MBE) and root mean square error (RMSE) are very close to zero. It has been concluded that Egypt's deduced formula gives precise estimations for n/N and was recommended for use at any location in Egypt. The sunshine distribution and its percentage frequency over Egypt were also studied. The results revealed that latitudinal dependent of n/N. Egypt has minimum value of n/N (0.48) during January at the northern part of the country and maximum value (0.92) during June at the southern part.

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  • Robaa, S.M., 2008. "Evaluation of sunshine duration from cloud data in Egypt," Energy, Elsevier, vol. 33(5), pages 785-795.
    • Handle: RePEc:eee:energy:v:33:y:2008:i:5:p:785-795
    DOI: 10.1016/j.energy.2007.12.001
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    1. Ertekin, Can & Yaldız, Osman, 1999. "Estimation of monthly average daily global radiation on horizontal surface for Antalya (Turkey)," Renewable Energy, Elsevier, vol. 17(1), pages 95-102.
    2. Aksoy, Bülent, 1997. "Estimated monthly average global radiation for Turkey and its comparison with observations," Renewable Energy, Elsevier, vol. 10(4), pages 625-633.
    3. Ododo, J.C. & Sulaiman, A.T. & Aidan, J. & Yuguda, M.M. & Ogbu, F.A., 1995. "The importance of maximum air temperature in the parameterisation of solar radiation in Nigeria," Renewable Energy, Elsevier, vol. 6(7), pages 751-763.
    4. Tadros, M.T.Y., 2000. "Uses of sunshine duration to estimate the global solar radiation over eight meteorological stations in Egypt," Renewable Energy, Elsevier, vol. 21(2), pages 231-246.
    5. Raja, I.A. & Twidell, J.W., 1994. "Statistical analysis of measured global insolation data for Pakistan," Renewable Energy, Elsevier, vol. 4(2), pages 199-216.
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    2. Martínez-Chico, M. & Batlles, F.J. & Bosch, J.L., 2011. "Cloud classification in a mediterranean location using radiation data and sky images," Energy, Elsevier, vol. 36(7), pages 4055-4062.
    3. Hassan, Gasser E. & Youssef, M. Elsayed & Mohamed, Zahraa E. & Ali, Mohamed A. & Hanafy, Ahmed A., 2016. "New Temperature-based Models for Predicting Global Solar Radiation," Applied Energy, Elsevier, vol. 179(C), pages 437-450.
    4. Muzathik, A.M. & Ibrahim, M.Z. & Samo, K.B. & Wan Nik, W.B., 2011. "Estimation of global solar irradiation on horizontal and inclined surfaces based on the horizontal measurements," Energy, Elsevier, vol. 36(2), pages 812-818.
    5. Khalil, Samy A. & Shaffie, A.M., 2013. "A comparative study of total, direct and diffuse solar irradiance by using different models on horizontal and inclined surfaces for Cairo, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 853-863.
    6. Dong, Zibo & Yang, Dazhi & Reindl, Thomas & Walsh, Wilfred M., 2015. "A novel hybrid approach based on self-organizing maps, support vector regression and particle swarm optimization to forecast solar irradiance," Energy, Elsevier, vol. 82(C), pages 570-577.
    7. Khalil, Samy A. & Shaffie, A.M., 2016. "Evaluation of transposition models of solar irradiance over Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 105-119.
    8. El Ouderni, Ahmed Ridha & Maatallah, Taher & El Alimi, Souheil & Ben Nassrallah, Sassi, 2013. "Experimental assessment of the solar energy potential in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 155-168.
    9. Ghada Elshafei & Silvia Vilcekova & Martina Zelenakova & Abdelazim M. Negm, 2021. "Towards an Adaptation of Efficient Passive Design for Thermal Comfort Buildings," Sustainability, MDPI, vol. 13(17), pages 1-23, August.
    10. Alonso-Montesinos, J. & Martínez-Durbán, M. & del Sagrado, J. & del Águila, I.M. & Batlles, F.J., 2016. "The application of Bayesian network classifiers to cloud classification in satellite images," Renewable Energy, Elsevier, vol. 97(C), pages 155-161.
    11. Escrig, H. & Batlles, F.J. & Alonso, J. & Baena, F.M. & Bosch, J.L. & Salbidegoitia, I.B. & Burgaleta, J.I., 2013. "Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast," Energy, Elsevier, vol. 55(C), pages 853-859.

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