A copula-based joint return period approach to characterising extreme rainfall in West Java
DOI:
https://doi.org/10.54386/jam.v27i4.3158Keywords:
Copula, Joint Return Period, Rainfall, West Java, Consecutive dry days, Consecutive wet daysAbstract
Climate change presents recurring challenges in understanding extreme weather events, particularly the persistence of dry and wet periods. West Java is among the region’s most vulnerable to such rainfall variability. This study analyses the relationship between consecutive dry days (CDD) and consecutive wet days (CWD). It estimates joint return periods (JRP) using a copula-based approach to assess the spatial characteristics of climate extremes in West Java. Marginal distributions were fitted for each indicator, followed by copula modelling using the Inference Function for Margins method and model selection based on the Akaike’s information criterion (AIC). The inverse Gaussian (ING) distribution was most suitable for CDD, while the generalised extreme value (GEV) distribution best represented CWD. We found that the Gaussian and Frank copulas best captured the overall dependence structure between CDD and CWD. JRP analysis showed that simultaneous extremes (AND scheme) were significantly rarer than single-variable extremes (OR scheme). These findings provide valuable input for identifying high-risk areas and developing more locally adaptive climate risk mitigation strategies.
References
Abraj, M.A.M., and Hewaarachchi, A.P. (2021). Joint return period estimation of daily maximum and minimum temperatures using copula method. Adv Appl Stat., 66 (2):175–190. http://dx.doi.org/10.17654/AS066020175
Anderson, T.W. (2010). Anderson-Darling tests of goodness-of-fit the Anderson-Darling statistic. Stanford Univ. pp. 1–7.
Arnell, N.W., Lowe, J.A., Challinor, A.J., and Osborn, T.J. (2019). Global and regional impacts of climate change at different levels of global temperature increase. Clim Change. 155(3): 377–391. https://doi.org/10.1007/s10584-019-02464-z
Beis, D.S., Pattipeilohy, W.J., and Hadi, A.S. (2022). Kajian identifikasi penurunan tren curah hujan, CDD dan CWD di Kota Kupang, Nusa Tenggara Timur. Bul GAW Bariri., 3 (1): 8–16. https://doi.org/10.31172/bgb.v3i1.62
Brown, P.J., Bradley, R.S., and Keimig, F.T. (2010). Changes in extreme climate indices for the Northeastern United States, 1870-2005. J. Clim., 23(24): 6555–6572. https://doi.org/10.1175/2010JCLI3363.1
Grasa, A.A. (1989). Econometric Model Selection: A New Approach. Kluwer Academic Publishers. Dordrecht, The Netherlands.
Miao, C., Sun, Q., Duan, Q., and Wang, Y. (2016). Joint analysis of changes in temperature and precipitation on the Loess Plateu deruing the period 1961-2011. Clim Dyn., 4 (7): 3221-3234. https://doi.org/10.1007/s00382-016-3022-x
Millar, R.B. (2011). Maximum Likelihood Estimation and Inference: With Examples in R, SAS, and ADMB. Wiley, Hoboken, USA.
Nainggolan, H.A., Burhanudin, Muslihah, D.W., and Virgianto, R.H. (2020). Inovasi Model Prediksi Titik Api Menggunakan Consecutive Dry Days (CDD) pada Wilayah Lahan Gambut Provinsi Riau. Bul GAW Bariri., 1(1): 12–19. https://doi.org/10.31172/bgb.v1i1.6
Najib, M.K., Nurdiati, S., and Sopaheluwakan, A. (2022). Copula based joint distribution analysis of the ENSO effect on the drought indicators over Borneo fire prone areas. Model Earth Syst. Environ., 8 (2): 2817-2826. https://doi.org/10.1007/s40808-021-01267-5
Nelsen, R.B. (2006). An Introduction to Copulas. Springer, New York.
Rahmatabadi, S.M, Irandoust, M., and Mirabbasi, R. (2023). Multivariate analysis of rainfall–runoff characteristics using copulas. J. Earth System Sci., 132 (2): 93. https://doi.org/10.1007/s12040-023-02105-1
Roshan A., Sedghi H., Sharifan R.A., and Porhemmat J. (2019). Climate change impacts on intensity duration frequency curves of precipitation: A case study of Shiraz synoptic station, Iran. J. Agrometeorol., 21 (2): 159-165. https://doi.org/10.54386/jam.v21i2.226
Salvadori, G., de Michele, and Durante, F. (2011). On the return period and design in a multivariate framework. Hydrol. Earth System Sci., 15 (11): 3293–330. https://doi.org/10.5194/hess-15-3293-2011
Sambou, M.J.G., Janicot, S., Pohl, B., Badiane, D., Dieng, A.L., and Gaye, A. (2019). Heat wave occurrences over senegal during spring: regionalization and synoptic patterns. Int J Climatol. 40 (1):. 440–457. https://doi.org/10.1002/joc.6220
Vandenberghe, S., Gr̈aler, B., Van Den Berg, M.J., Petroselli, A., Grimaldi, S., De Baets, B., and Verhoest, N. E. C. (2012). Multivariate return periods in hydrology: A critical and practical review focusing on synthetic design hydrograph estimation. Hydrol Earth Syst Sci. 17 (4): 6781–6828. https://doi.org/10.5194/hess-17-1281-2013
Walpole, Ronald, E., and Mayers R, H. (1995). Ilmu Peluang dan Statistika untuk Insinyur dan Ilmuwan. ITB, Bandung, Indonesia.
Wei, X., Zhang, H., Singh, V. P., Dang, C., Shao, S., and Wu, Y. (2020). Coincidence probability of streamflow in water resources area, water receiving area and impacted area: Implications for water supply risk and potential impact of water transfer. Hydrol. Res., 51(5): 1120–1135. https://doi.org/10.2166/nh.2020.106
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