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Estimation of atmospheric turbidity coefficient β over Zhengzhou, China during 1961–2013 using an improved hybrid model

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  • Lin, Aiwen
  • Zou, Ling
  • Wang, Lunche
  • Gong, Wei
  • Zhu, Hongji
  • Salazar, Germán Ariel

Abstract

Accurate measurement and determination of the atmospheric turbidity is of great importance for solar radiation modeling and climate change studies. Daily values of global, direct and diffuse solar irradiation and meteorological variables (air temperature, relative humidity, sunshine duration and wind speed) during 1960–2013 are used to investigate the monthly variations of Ångström turbidity coefficient (β) at Zhengzhou, China. An improved method (IYHM-ZZ) is proposed by combining the format of the Yang hybrid model (YHM) with corrected spectral terms. The β value is obtained by adjusting the estimated direct radiation until it matches the measured values. Statistical indicators (RMSE, MBE and t-test) are used to evaluate the performance of YHM and IYHM-ZZ models, and the IYHM-ZZ model produces more accurate estimates than the YHM model. The results indicate that the β values are generally higher in winter and spring, lower in summer and autumn. An increasing trend of β is observed during 1960–2010 at Zhengzhou, and the annual mean β are 0.07, 0.09, 0.11, 0.12, 0.12 and 0.13 for 1960s, 1970s, 1980s, 1990s, 2000s and 2010-, respectively.

Suggested Citation

  • Lin, Aiwen & Zou, Ling & Wang, Lunche & Gong, Wei & Zhu, Hongji & Salazar, Germán Ariel, 2016. "Estimation of atmospheric turbidity coefficient β over Zhengzhou, China during 1961–2013 using an improved hybrid model," Renewable Energy, Elsevier, vol. 86(C), pages 1134-1144.
    • Handle: RePEc:eee:renene:v:86:y:2016:i:c:p:1134-1144
    DOI: 10.1016/j.renene.2015.09.043
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    References listed on IDEAS

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    1. Wang, Lunche & Salazar, Germán Ariel & Gong, Wei & Peng, Simao & Zou, Ling & Lin, Aiwen, 2015. "An improved method for estimating the Ångström turbidity coefficient β in Central China during 1961–2010," Energy, Elsevier, vol. 81(C), pages 67-73.
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    1. Zou, Ling & Wang, Lunche & Xia, Li & Lin, Aiwen & Hu, Bo & Zhu, Hongji, 2017. "Prediction and comparison of solar radiation using improved empirical models and Adaptive Neuro-Fuzzy Inference Systems," Renewable Energy, Elsevier, vol. 106(C), pages 343-353.

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