The Influence of ENSO (El Nino/Southern Oscillation) on Rainfall Distribution in Sa Kaeo Province
Abstract
This research aims to investigate the influence of ENSO on the amount of rainfall in Sa Kaeo province using twenty-two observed annual rainfall datasets in Sa Keao province and its adjacent regions, archived at the Meteorological Department of Thailand, which were covered the normal years (2008, 2009, 2012, 2013, 2014 and 2017), the period of El Nino (2015 and 2016) and La Nina phenomenon (2010 and 2011), respectively. Then, R programing language (version 3.4.4) with the geographical packages were applied in this research.The result showed that the ten years averaged annual rainfall was in the range of 1,287.57 to 1,743.33 mm, with an average of 1,443.49 mm. In addition, rainfall was more widespread in the west and the south than the north of Sa Keao province. In El Niño periods, the amount of rainfall was approximately 984.90 to 1,711.67 mm, with an average of 1,328.44 mm. The eastern and northern regions are most affected, while the southern areas of Sa Kaeo province are least affected. In La Nina periods, the average amount of precipitation was approximately around 1,397.55 to 1,916.9 mm, with an average of 1,601.38 mm. Moreover, all areas of Sa Kaeo province was affected by positive annual rainfall anomalies, except the east and the north of Sa Kaeo Province. In addition, the phenomenal years of El Nino and La Niña not only affect the year of birth, but the influence remains until the next year. Keywords : ENSO ; El Nino ; La Nina ; rainfall ; Sa Kaeo ProvinceReferences
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from http://122.155.1.141/upload/minisite/file_attach/45/58e74afe2335b.pdf
Dunnington, D. (2017). Package prettymapr. Retrieved December 8, 2018, from http://cran.r-project.org/
web/packages/prettymapr/prettymapr.pdf.
Khunwishit, S., & Rammanee, Y. (2018). Climate-Related Disaster Impacts, Risk Perception and Adaptation
of Farmer Households in Songkhla Lake Basin. Political Science and Public Administration
Journal, 9(1), 81-111. (in Thai)
Lorpittayakorn, P. (2017). The Influence of El Nino on Rainfall Distribution during Wet and Dry Seasons in
Eastern Thailand. Thai Journal of Science and Technology, 25(6), 945-959. (in Thai)
Lorpittayakorn, P. (2018). The Influence of La Nina on Rainfall Distribution during Wet and Dry Seasons in
Eastern Thailand. Thai Journal of Science and Technology, 26(1), 1-16. (in Thai)
Na-U-Dom, T. (2018). Application of R programming for the geoinformatic display. The Journal of Applied
Science, 17(2), 118-128.
National Hydro informatics and Climate Data Center. (2019). Summary of drought situations 2009-2010.
Retrieved December 15, 2019, from http://www.thaiwater.net/web/index.php/drought/110-drought-
2553/237-drought-nov52-april53.html. (in Thai)
NASA Official. (2019). Monthly NINO3.4 Index data Available Source. Retrieved Fabruary 12, 2019, from
https://www.cpc.ncep.noaa.gov/data/indices/sstoi.indices.
Nelson, G. C., Rosegrant, M. W., Jawoo, K., Robertson, R., Sulser, T., Zhu Tingju, Ringler. (2009). Climate
change: Impacton Agricultureand Costs of Adaptation. (Research report). DC. International Food
Policy ResearchInstitute Washington University.
Noichaisin, L. (2014). Geoinformation Technology for Natural Disaster Studies in Thailand. Burapha Science
Journal, 19(2), 179-188. (in Thai)
Office of Prevention and Mitigation Sa Kaeo. (2016). Annual Reprt 2016. Retrieved December 7, 2019, from
http://122.155.1.141/upload/minisite/file_attach/45/58e74afe2335b.pdf. (in Thai)
R Core Team. (2018). R: A language and environment for statistical computing R Foundation for Statistical
Computing. . Retrieved Fabruary 13, 2019, from https://www.R-project.org/.
Pebesma, E. (2018). Package ‘sp’. . Retrieved December 8, 2018, from https://cran.r-project.org/web/
packages/sp/sp.pdf.
Pebesma, E. (2019). Package ‘gstat’. Retrieved December 8, 2018, from https://cran.r.project.org/web/
packages/gstat/gstat.pdf.
Pebesma, E. (2019). Package ‘raster’. . Retrieved December 8, 2018, from https://cran.rproject.org/web/
packages/raster/raster.pdf.
Sriwicha, S., Busababodhin, P. and Kumphon, B. (2016).The Impact of ENSO on Rainfall in the
Northeast of Thailand. Burapha Science Journal, 21(3), 190-202.
Thai Meteorological Department. (2017). El nino. Retrieved January 3, 2019, from http:// www.tmd.go.th/ info/info.php?FileID=17. (in Thai)
Thai Meteorological Department. (2017). La nina. Retrieved January 3, 2019, from http://www.tmd.go.th/ info/info.php?FileID=18. (in Thai)
Thai Meteorological Department. (2018). Weather in Sa Kaeo Province. Retrieved January 5, 2019, from
http://climate.tmd.go.th/data/province/.pdf. (in Thai)
Thirumalai, K., Pedro N. D., Okumura, Y., and Deser, C. (2017). Extreme temperatures in Southeast Asia
caused by El Nino and worsened by global warming. Nature Communications, 8(10), 1-8.
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Published
2021-01-06
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Research Article
