Modeling of Maximum Temperature in Northeast Thailand
Abstract
The aim of this study was to find the optimal model of maximum and minimum temperature in central northeast of Thailand by using the Generalized Extreme Value distribution (GEV) and Generalized Pareto distribution (GPD). The return levels for each return period of maximum temperature were also found. Time series data that used in this study were the maximum temperature during 1985 to 2015 from the Meteorological Department of Thailand in 25 meteorological stations from Meteorological Department. An “extreme” package in R program. The results of the study indicate that the optimal model of maximum temperature of stations is Weibull distribution and Gumbel distribution 15 and 10 stations respectively and GPD of maximum temperature of stations is Exponential distribution 22 stations and Pareto Distribution 3 stations. Based on return levels 5-years 10-years 25-years 50-years and 100-years, the temperature in the northeast of Thailand. Nongkhai Meteorogical station has the highest return level of maximum temperature for each return period to solve and prevent the temperature increasing problem, Nongkhai Meteorogical station should be the first considered Keywords : Extreme value, Maximum temperature, Generalized extreme value distribution, Generalized pareto distribution, Return levelReferences
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of Thailand. Burapha Science Journal, 18(1), 95-104. (in Thai)
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Techniques. University of the Thai Chamber of Commerce Journal, 27(2), 138-150. (in Thai)
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Thailand, Proceeding for The Asian Conference on Sustainability, Energy & the Environment (acsee2014),
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from http://www.tmd.go.th/ncct/article/2550.pdf
Thailand. Burapha Science Journal, 20(1), 106-117. (in Thai)
Charin, B., Srisodaphol, W., & Busababodhin, P. (2014) Modeling for extreme temperature of central northeast
region of Thailand, Proceeding of International Conference on Applied Statistics 2014 (ICAS 2014),
May 21-24, 2014, Pullman Khon Kaen Raja Orchid, Khon Kaen, Thailand, pp. 67-72.
Climatological Center. (2012).Retrived September 22, 2016 from http://joelandchoom.net/tmdsummaries/2012
%202555%20Annual%20Summary%20in%20Thai.pdf
Coles, S. (2001). An Introduction to Statistical Modeling of Extremes Values. Great Britain: Springer-varlag
London Limited.
Embrecht, P., Klüppelberg, C., & Mikosch, T. (1997). Modelling extremal Events for insurance and
finance.Springer- Verlag,Berlin.
Keawmun, A., Budchamruei, P., & Busababodhin, P. (2015) “Modeling Monthly Precipitation in Central Northeast
of Thailand,” KKU Science Journal, 43(1), 137-147. (in Thai)
Panpharisa, K. Manad K., & Putipong B. (2013). Modeling Annual Extreme Precipitation in upper Northern Region
of Thailand. Burapha Science Journal, 18(1), 95-104. (in Thai)
Panichkitkosolkul, W. (2007). Forecasting Monthly Rainfall of Nong Khai Province by Statistical Forecasting
Techniques. University of the Thai Chamber of Commerce Journal, 27(2), 138-150. (in Thai)
Rattanawan, S., Busababodhin, P., & Kumphon, B. (2014). Modeling for Extreme rainfall in lower Northeastern of
Thailand, Proceeding for The Asian Conference on Sustainability, Energy & the Environment (acsee2014),
Osaka, Japan, 12-15 June 2014: 162-171.
Sitthichivapak, K. (2007). Variability and climate change. Retrieved 28, September 2015,
from http://www.tmd.go.th/ncct/article/2550.pdf
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Published
2017-01-27
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Research Article
