Application of Extreme Value Distribution on Temperature Data in South Sulawesi Province
DOI:
https://doi.org/10.24252/msa.v13i1.60223Keywords:
Extrem distribution, Peak Over Threshold, block maxima, GEV, GPD, Return Level, Temperature riskAbstract
Climate change in recent years has resulted in extreme changes in temperature in Indonesia, especially in South Sulawesi Province. Extreme temperature changes will affect human and investment activities, energy use, and disaster events. Therefore, this study aims to model the maximum and minimum temperature data in South Sulawesi Province for the last 75 years. The data used came from observations of maximum and minimum temperatures from January 1945 to December 2020 and were analyzed using the Generalized Extrem Value distribution with the maxima block approach and the Generalized Pareto Distribution with the Peak Overtreshold (POT) approach. The results of the analysis show that these two models can be used to model extreme minimum and maximum temperature data in South Sulawesi Province with the right and optimal selection of blocks and thresholds. The results of the calculation of the return level every 5 years in the projection of the next 50 years show an increase in maximum and minimum temperatures which suggests the need to mitigate the risk of temperature change in order to adapt to climate change.
References
World Bank Group and Asian Development Bank, Climate Risk Country Profile: Indonesia. World Bank, 2021. doi: 10.1596/36379.
A. S. Rikin, ‘Indonesia Sees Record Temperatures, Expects Blistering Heat to Continue Until Next Week’, Jakarta Globe.Id, 2019. Accessed: Mar. 03, 2025. [Online]. Available: https://jakartaglobe.id/news/indonesia-sees-record-temperatures-expects-blistering-heat-to-continue-until-next-week
E. Freimuth, ‘People Exposed to Climate Change: March-May 2024’, Climate Central, Jun. 2024.
J. He and X. Ma, ‘Extreme Temperatures and Firm-Level Stock Returns’, IJERPH, vol. 18, no. 4, p. 2004, Feb. 2021, doi: 10.3390/ijerph18042004.
X. Gu, P. Chen, and C. Fan, ‘Socio-demographic inequalities in the impacts of extreme temperatures on population mobility’, Journal of Transport Geography, vol. 114, p. 103755, Jan. 2024, doi: 10.1016/j.jtrangeo.2023.103755.
B. Alahmad et al., ‘Extreme Temperatures and Stroke Mortality: Evidence From a Multi-Country Analysis’, Stroke, vol. 55, no. 7, pp. 1847–1856, Jul. 2024, doi: 10.1161/strokeaha.123.045751.
W. Zhao et al., ‘Reliance on fossil fuels increases during extreme temperature events in the continental United States’, Commun Earth Environ, vol. 4, no. 1, Dec. 2023, doi: 10.1038/s43247-023-01147-z.
F. F. Vieira et al., ‘Statistical analysis of extreme temperatures in India in the period 1951–2020’, Theor Appl Climatol, vol. 152, no. 1–2, pp. 473–520, Apr. 2023, doi: 10.1007/s00704-023-04377-5.
S. Aminah, E. Riawan, M. R. Syahputra, and A. A. Kuntoro, ‘Identification of Extreme Precipitation Changes Due to Climate Change in Indonesia’, in Springer Proceedings in Physics, Singapore: Springer Nature Singapore, 2024, pp. 849–857. doi: 10.1007/978-981-97-0740-9_75.
C. G. Otiniano, Y. S. Oliveira, and Y. S. Maluf, ‘Probability Distribution of Extreme Events in Complex Systems: Application to Climate Data’, Symmetry, vol. 16, no. 12, p. 1639, Dec. 2024, doi: 10.3390/sym16121639.
Supari, F. Tangang, L. Juneng, and E. Aldrian, ‘Observed changes in extreme temperature and precipitation over Indonesia’, Intl Journal of Climatology, vol. 37, no. 4, pp. 1979–1997, Mar. 2017, doi: 10.1002/joc.4829.
M. Ahsanullah, Extreme Value Distributions, vol. 8. in Atlantis Studies in Probability and Statistics, vol. 8. Paris: Atlantis Press, 2016. doi: 10.2991/978-94-6239-222-9.
R. A. Fisher and L. H. C. Tippett, ‘Limiting forms of the frequency distribution of the largest or smallest member of a sample’, Math. Proc. Camb. Phil. Soc., vol. 24, no. 2, pp. 180–190, Apr. 1928, doi: 10.1017/S0305004100015681.
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