Diurnal Variation of Visibility with its related Meteorological Factors in Thailand
Article Sidebar
Main Article Content
Abstract
Visibility is an important factor in our daily life and visibility is considered a standard meteorological parameter. The objective was to study diurnal variation of visibility in Thailand and its related meteorological factors. A research study of secondary data consisting of visibility data, cloud data, relative humidity data and rainfall data for a weather 3 hours for 10 years (2009 - 2018) of 43 stations (from all regions in Thailand). To study the diurnal variation and analyze the correlation by using the rescaling (min-max normalization) analysis of visibility and meteorological factors. The results revealed that the diurnal variation and diurnal correlation of visibility and meteorological factors were consistent. Relative humidity has the greatest impact on changes in visibility diurnal variation. Relative humidity greater than 90 percent, except for the Southern (West Coast) is 66.65 percent and this results in low visibility because of the 24-hour variations of the relative humidity and light scattering of aerosols depends on ambient relative humidity since hygroscopic particles absorb significant water at high relative humidity. The factor affecting relative humidity and cloud was air temperature, diurnal variation of pressure, physical characteristics of measurement area and measurement time.
Article Details
References
Bäumer, D., Vogel, B., Versick, S., Rinke, R., Möhler, O., and Schnaiter, M. (2008). Relationship of visibility, aerosol optical thickness and aerosol size distribution in an ageing air mass over South-West Germany. Atmospheric Environment, 42(5), 989-998. https://doi.org/10.1016/j.atmosenv.2007.10.017
Chotipong, A. (2018). Air pollution a problem in China. Environmental Journal, 22(1), 54-63. (in Thai)
Deng, H., Tan, H., Li, F., Cai, M., Chan, P. W., Xu, H., Huang, X. and Wu, D. (2016). Impact of relative humidity on visibility degradation during a haze event: A case study. Science of The Total Environment, 569-570, 1149-1158. https://doi.org/10.1016/j.scitotenv.2016.06.190
Deng, J., Wang, T., Jiang, Z., Xie, M., Zhang, R., Huang, X., and Zhu, J. (2011). Characterization of visibility and its affecting factors over Nanjing, China. Atmospheric Research, 101(3), 681-691. https://doi.org/10.1016/j.atmosres.2011.04.016
Department of Disaster Prevention and Mitigation. (2014). Disaster Risk Management Terminology. Bangkok: Ministry of Interior. (in Thai)
Huo, J., and Lu, D. (2009). Cloud Determination of All-Sky Images under Low-Visibility Conditions. Journal of Atmospheric and Oceanic Technology, 26(10), 2172-2181. https://doi.org/10.1175/2009JTECHA1324.1
Hyvärinen, O., Julkunen, J., and Nietosvaara, V. (2007). Climatological Tools for Low Visibility Forecasting. Pure and Applied Geophysics, 164(6), 1383-1396. https://doi.org/10.1007/s00024-007-0224-5
Khaosod Online. (2017). Mae Hong Son: Pollution index & Low visibility. [Online]. Retrieved February 7, 2019, from: https://www.khaosod.co.th/around-thailand/news_261990 (in Thai)
Kneringer, P., Dietz, S. J., Mayr, G. J., and Zeileis, A. (2019). Probabilistic Nowcasting of Low-Visibility Procedure States at Vienna International Airport During Cold Season. Pure and Applied Geophysics, 176(5), 2165-2177. https://doi.org/10.1007/s00024-018-1863-4
Li, X., Huang, L., Li, J., Shi, Z., Wang, Y., Zhang, H., Ying, Q., Yu, X., Lioa, H., and Hu, J. (2019). Source contributions to poor atmospheric visibility in China. Resources, Conservation and Recycling, 143, 167-177. https://doi.org/10.1016/j.resconrec.2018.12.029
López, G., Bosch, J., Pulido-Calvo, I. and Gueymard, C. (2017). Visibility estimates from atmospheric and radiometric variables using artificial neural networks. Air Pollution XXV, 211.
Matichon Online. (2019). South battles Sumatra Island in Indonesia smog hazard. [Online]. Retrieved February 7, 2019, from: https://www.matichon.co.th/local/quality-life/news_1667171 (in Thai)
Malm, W. C. (2016). Visibility. Colorado, The United States of America: Elsevier.
Ruangjun, S., and Exell, R. (2008). Regression Models for Forecasting Fog and Poor Visibility at Donmuang Airport in Winter. Asian J. Energy Environ, 9, 215-230.
Sabetghadam, S., Ahmadi-Givi, F., and Golestani, Y. (2012). Visibility trends in Tehran during 1958–2008. Atmospheric Environment, 62, 512-520. https://doi.org/10.1016/j.atmosenv.2012.09.008
Singh, A., Bloss, W., and Pope, F. (2017). 60 years of UK visibility measurements: Impact of meteorology and atmospheric pollutants on visibility. Atmospheric Chemistry and Physics, 17, 2085-2101. https://doi.org/10.5194/acp-17-2085-2017
Thai Meteorological Department. (2015). Meteorology knowledge. [Online]. Retrieved January 8, 2020, from: https://www.tmd.go.th/info/info.php?FileID=23 (in Thai)
Tsai, Y. I., Lin, Y. and Lee, S. (2003). Visibility Variation with Air Qualities in the Metropolitan Area in Southern Taiwan. Water, 144. https://doi.org/10.1023/A:1022901808656
UK Air Pollution Information System APIS. (2016). Reduction of visibility. [Online]. Retrieved December 17, 2019, from: http://www.apis.ac.uk/overview/issues/overview_reduction_of_visibility.htm