Estimation of Extinction Coefficient of Solar Radiation under Cloudless Sky in the Atmosphere of Thailand
Abstract
This research objective is an estimation of the extinction coefficient of solar radiation in the atmosphere of Thailand. Solar radiation data from measurements and calculations using a theoretical model on cloudless days were used. The data was collected from four meteorological stations which located on Chiang Mai, Ubon Ratchathani, Bangkok, and Songkhla during 2013-2017. It was found that, the extinction coefficient of solar radiation was correlated in the mathematical model with the precipitable water vapor and visibility data. The correlation coefficient was 0.86. The extinction coefficients were calculated from the model are closed to those obtained from solar radiation data. The result indicating that both data are not significantly different at the confidence level 95%. The model was used to calculate the extinction coefficient of solar radiation from 85 meteorological stations throughout the country. The results showed that, the extinction coefficient of solar radiation were high at lower latitudes and also high in February to April.
Keywords : extinction coefficient ; precipitable water vapor ; visibility data ; cloudless sky ; solar radiation
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Belcher, B.N. and DeGaetano, A.T. (2007). A revised empirical model to estimate solar radiation using automated
surface weather observations. Solar Energy, 81(3), 329-345.
Boland, J., McArthur, L.C. and Luther, M. (2001). Modelling the diffuse fraction of global solar radiation on
a horizontal surface. Environmetrics, 12(2), 103-116.
Brine, D.T. and Iqbal, M. (1983). Diffuse and Global solar spectral irradiance under cloudless skies.
Solar Energy, 30(5), 447-456.
Chantraket, P., Tantiplubthong, N. and Chanyatham, T. (2013). Aersol and cloud condensation nuclei distribution
during summer season over Northern region of Thailand. Applied Environmental Research, 35(1),
-102.
Esposito, F., Leone, L., Pavese, G., Resteiri, R. and Serio, C. (2004). Seasonal variation of aerosols properties
in South Italy: a study on aerosol optical depths, Angstrom turbidity parameters and aerosol size
distributions. Atmospheric Environment, 38(11), 1605-1614.
Garrison, J.D. (1992). Estimation of precipitable water over Australia for application to the division of solar
radiation into its direct and diffuse components . Solar Energy, 48(2), 89-96.
Gueymard, C.A. and Garrision, J.D. (1998). Critical evaluation of precipitable water and atmospheric turbidity
in Canada using measured hourly solar irradiance. Solar Energy, 62(4), 291-307.
Gueymard, C.A. (2001). Parametrized transmittance model for direct beam and circumsolar spectral irradiance.
Solar Energy, 71(5), 325-346.
Gueymard, C.A. (2005). Importance of atmospheric turbidity and associated uncertainties in solar radiation and
luminous efficacy modeling. Energy, 30(9), 1603-1621.
Hontoria, L., Aguilera, J. and Zufiria, P. (2005). An application of the multilayer perceptron: Solar radiation maps
in Spain. Solar Energy, 79(5), 523-530.
Ineichen, P. (2006). Comparison of eight clear sky broadband models against 16 independent data banks.
Solar Energy, 80(4), 468-478.
Iqbal, M. (1983). An Introduction to Solar Radiation. Academic Press, New York.
Iziomon, M.G. and Mayer, H. (2002). Assessment of some global solar radiation parameterizations.
Solar Energy, 64(2), 1631–1643.
Janjai, S., Kumharn,W. and Laksanaboonsong, J. (2003). Determination of Angstrom’s turbidity
coefficient over Thailand. Renewable Energy, 28(11), 1685–1700.
Janjai, S., Laksanaboonsong, J. and Thongsathiya, A. (2005). Development of a method for generating
operational solar radiation maps from satellite data for a tropical environment. Solar Energy, 78(6),
-751.
Janjai, S. and Keawprasert, T. (2006). Design and performance of a solar tunnel dryer with a polycarbonate
cover. International Energy Journal, 7(3), 187-194.
Martinez-Lozano, J.A., Utrillas, M.P., Tena, F. and Cachorro, V.E. (1998). The parameterization of the atmospheric
aerosol optical depth using the angstrom power law. Solar Energy, 63(5), 303-311.
Nunez, M. (1993). The development of a satellite-based insulation model for the Tropical Pacific Ocean.
Journal of Climatology ,13(6), 607-627.
Phokate, S. 2009. A determination of atmospheric turbidity coefficient from visibility data.
KKU Engineering Journal, 36(4), 333-338. (in Thai).
Phokate, S. (2011). Calculation of solar radiation absorption from precipitable water vapor in the atmosphere of
Thailand. Burapha Science Journa,l 16(1), 77-83. (in Thai).
Pinazo, J.M., Canada, J. and Bosca, V. (1995). A new method to determine Angstrom’s turbidity coefficient: Its
application for Valencia. Solar Energy , 54(4), 219-226.
Polo, J., Zarzalejo, F. L., Salvador, P., and Ramirez, L. (2009). Ångström Turbidity and ozone column estimations
from spectral solar irradiance in a semi-desertic environment in Spain. Solar Energy, 83(2), 257-263.
Rahoma, U.A. and Hassan, A.H. (2012). Determination of atmospheric turbidity and its correlation with
cimatologically parameters. American Journal of Environmental Science, 8(6), 597-604.
Utrillas, M.P., Martinaz-Lozano, J..A., Cachorro, V.E. and Tena, F. (2000). Comparison of aerosol optical
thickness retrieval from spectroradiometer measurement and from two radiative transfer model.
Solar Energy, 68(2), 197-205.
Wan Nik, W.B., Ibrahim, M.Z., Samo, K.B. and Muzathik, A M. (2012). Monthly mean hourly global solar
radiation estimation. Solar Energy, 86(1), 379-387.
Wiginton, L.K., Nguyen, H.T. and Pearce, J. M. (2010). Quantifying rooftop solar photovoltaic potential for
regional renewable energy policy. Computers, Environment and Urban Systems, 34, 345-357.
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