The Eect of ENSO on Seasonal Rainfall Using the Monte-Carlo Bootstrap Method in the Southern Part of Java, Indonesia

• Autorzy: Nugroho Bayu Dwi Apri , Ardhitama Aristya , Arif Chusnul , Wijayanti Syintianuri Intan , Al Adilah Afatul Husna , Hadi Intan Permata , Annisa Hertiyana Nur , Sartohadi Junun

Identyfikatory

DOI

10.12912/27197050/181175

• Języki publikacji: EN

Abstrakty

EN

ENSO is a global climate phenomenon that has been able to affect weather and climate conditions in Indonesia, especially in the southern part of Java Island, which is represented by Yogyakarta province. Subseasonal to seasonal (S2S) is a seasonal period that tries to bridge the gap between a relatively short period and a climate that has a relatively long period. The author has conducted a study that aims to determine the effect of the global ENSO phenomenon on the increase and decrease in rainfall in the southern part of the Java island region during the S2S season. In this study, the data obtained from the Nino 3.4 data and seasonal rainfall data in The southern part of Java, which is represented by Yogyakarta province in the years 2001–2022 were used. The method used is the Monte-Carlo Bootstrap permutation resampling method. The results show that in general the southern part of the Java Island region is affected by El Nino and La Nina phenomena both in the peak period of the rainy season and the peak of the dry season of JFM, JJA, ASO, and OND although the responses from several sample areas have different effects.

Słowa kluczowe

EN

ENSO; subseason; season; rainfall; Monte-Carlo Bootstrap; Java Island

• Wydawca: Lubelski Oddział Polskiego Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology ; WNGB Wydawnictwo Naukowe
• Czasopismo: Ecological Engineering & Environmental Technology
• Rocznik: 2024
• Tom: Vol. 25, iss. 3
• Strony: 211--219
• Opis fizyczny: Bibliogr. 15 poz., rys., tab.

Twórcy

autor

Nugroho Bayu Dwi Apri

• Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Jl. Flora 1 Bulaksumur Sleman, Yogyakarta, Indonesia

• https://orcid.org/0000-0003-0999-9159

autor

Ardhitama Aristya

• Yogyakarta Special Region Climatology Station Regency, Road Km. 5.5 Duwet, Sendangadi, Mlati Sleman, Yogyakarta, Indonesia
• Faculty of Agricultural Technology, Universitas Gadjah Mada Jl. Flora 1 Bulaksumur Sleman, Yogyakarta, Indonesia

• https://orcid.org/0009-0002-9012-7189

autor

Arif Chusnul

• Department of Civil and Environmental Engineering, IPB University, Bogor, West Java, Indonesia

autor

Wijayanti Syintianuri Intan

• Department of Soil Science, Faculty of Agriculture, Universitas Gadjah Mada, Jl. Flora Bulaksumur Sleman, Yogyakarta, Indonesia

• https://orcid.org/0009-0001-8185-1135

autor

Al Adilah Afatul Husna

• Master program of Geo-Information for Spatial Planning and Disaster Risk Management, Universitas Gadjah Mada, Jl. Teknika Utara Pogung Kidul Sleman, Yogyakarta, Indonesia

• https://orcid.org/0000-0002-7144-8297

autor

Hadi Intan Permata

• Department of Soil Science, Faculty of Agriculture, Universitas Gadjah Mada, Jl. Flora Bulaksumur Sleman, Yogyakarta, Indonesia

• https://orcid.org/0009-0006-2607-0957

autor

Annisa Hertiyana Nur

• Department of Agricultural and Biosystems Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Jl. Flora 1 Bulaksumur Sleman, Yogyakarta, Indonesia

• https://orcid.org/0000-0002-6844-4631

autor

Sartohadi Junun

• Department of Soil Science, Faculty of Agriculture, Universitas Gadjah Mada, Jl. Flora Bulaksumur Sleman, Yogyakarta, Indonesia
• Center of Land Resources Management, Universitas Gadjah Mada, Yogyakarta, Indonesia

Bibliografia

• 1. Aldrian, E. 2008. Indonesian Marine Meteorology. Jakarta: Meteorology and Geophysics Agency.
• 2. Arriyadi, D. 2017. Utilization of sub seasonal to seasonal model output to predict rainfall based on upper air parameters [Thesis]. Bogor: Bogor Agricultural Institute.
• 3. Hamada, J.I. 1995. Climatological Study on Rainfall Variation in Indonesia [thesis]. Kyoto: KyotoUniversity.
• 4. Hendon H.H. 2003. Indonesian rainfall variability: impacts of ENSO and local air-sea interaction. Journal of Climate, 16(1), 775–1790. https://doi.org/10.1175/1520-0442(2003)016<1775:irvioe>2.0.co;2
• 5. Huang B., Thorne P.W., Banzon V.F., et al 2017. Extended reconstructed sea surface temperature version 5 (ERSSTv5): upgrades, validations, and intercomparisons. J Clim. https://doi.org/10.1175/JCLI-D-16-0836.1
• 6. Irawan, B. 2006. El Niño and La Niña climate anomaly phenomena: Long-term trends and their influence on food production. Agro Economic Research Forum, 24(1), 28–45.
• 7. Mulyana, E. 2002. Analysis of zonal winds in Indonesia during the enso period. Journal of Weather Modification Science & Technology, 3(2), 115–120. doi: 10.29122/jstmc.v3i2.2167.
• 8. Mulyana, E. 2002. The relationship between enso and rainfall variations in Indonesia. Journal of Weather Modification Science & Technology, 3(1), 1–4. doi: 10.29122/jstmc.v3i1.2153.
• 9. Qian, J.H., Robertson, A.W., & Moron, V. 2010. Interactions among ENSO, the monsoon, and diurnal cycle in rainfall variability over Java, Indonesia. Journal of the Atmospheric Sciences, 67(11), 3509–3524.
• 10.Radini. 2015. Projection of changes in rainfall patterns in Indonesia using short-term climate change scenarios [Thesis]. Bogor: Bogor Agricultural Institute.
• 11. Safitri, S. 2015. El Nino, La Nina and their Impact on life in Indonesia. Criksetra: Journal of History Education, 4(2), 153–156.
• 12. Sitompul, Z., Nurjani, E. 2013. The influence of El Nino Southern Oscillation (ENSO) on seasonal and annual rainfall in Indonesia. Indonesian Earth Journal, 2(1), 11–18.
• 13. Supari, Tangang, F., Salimun, E., Aldrian, E., Sopaheluwakan, A., Juneng, L. 2018. ENSO modulation of seasonal rainfall and extremes in Indonesia. Climate Dynamics, 51(7–8), 2559–2580. https://doi.org/10.1007/s00382-017-4028-8
• 14. Vitart, F., Ardilouze, C., Bonet, A., Brookshaw, A., Chen, M., Codorean, C., Deque, M., Ferranti, L., Fucile, E., et al. 2016. The sub-seasonal to seasonal prediction (S2S) database project. Bulletin of the American Meteorological Society, 98(1), 1–38. https://doi.org/10.1175/BAMS-D-16-0017.1.
• 15. White, C.J., Carlsen, H., Robertson, A.W., Klein, R.J.T., Lazo., Kumar, A., Vitart, F., de Perez, EC., Ray, AJ., et al. 2017. Potential applications of sub seasonal to seasonal (S2S) predictions. Meteorological Applications. https://doi.org/10.1002/ met.1654.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).