FOLIA GEOGRAPHICA

Menu

Folia Geographica 2021, 63/2, pp.110–122

KÖPPEN-GEIGER CLIMATE SYSTEM CLASSIFICATION AND FORECASTING IN THAILAND

Nutthakarn PHUMKOKRUX A*

Received: July 28, 2021 | Revised: November 6, 2021 | Accepted: November 23, 2021

Paper No. 21-63/2-601

A* Ramkhamhaeng University, Department of Geography, Bangkok, 10240, Thailand
ORCID https://orcid.org/0000-0003-4224-6220
ph.nutthakarn@hotmail.com, ph.nutthakarn@ru.ac.th (corresponding author)


PDF FULL TEXT

Abstract
Köppen-Geiger Climate Classification system (KGC) is one of well-known climate classification method with only rainfall and temperature values. This study aims 1) to update current total monthly rainfall, average monthly temperature and KGC map of 1987 – 2019 period and 2) to predict total monthly rainfall, average monthly temperature and KGC map of 2020 – 2060 and 2061 – 2100 period. The study was extracted by gathering total monthly rainfall and average monthly temperature from 104 meteorological stations over Thailand then cooperated with GIS process to classify and present climate type of 1987 – 2019. Moreover, Beijing Climate Center Climate System Model version 1.1 (BCC-CSM1.1) was used to forecast rainfall and temperature value to determine climate zone of Thailand of 2020 – 2060 and 2061 – 2100 period. The results of present period illustrated that Thailand climate was classified into three types: dry-winter characteristics (Aw) as a major climate, following by Tropical monsoon climate (Am) and Dry-winter humid subtropical climate (Cwa). In contrast, predicted values displayed only “Aw” and “Am” appearing in the mid and late twenty-first century, respectively. “Aw” climate covered the most area of Thailand with 90.14%, 91.85% and 96.37% while “Am” climate covered 8.77%, 8.15% and 3.63% for present, mid, and late twenty-first centuries period, respectively of a small area of Eastern part and almost half Southern region. Furthermore, “Am” climate was also predicted to appear in east side of Northeast region in 2020 – 2060 period whereas “Cwa” was appeared in small area of Northern region in 1987 – 2019 period. The up-to-date maps of rainfall, temperature value and KGC zone can be evidences to remind about climate change and support the future work.

Key words
Köppen-Geiger Climate Classification, Climate Change, Rainfall Variability, Equatorial Climate and Climate of Thailand.

REFERENCES

  1. AGRICULTURAL AND METEOROLOGICAL SOFTWARE, 2018. SD-GCM Tool [Computer software]. Retrieved from: https://agrimetsoft.com/SD-GCM.aspx. Accessed on 18 October 2020.
  2. ALVARES, C. C., STAPE, J. L., SENTELHAS, P. C., GONÇALVES, J. L., SPAROVEK, G. (2014). Köppen’s climate Classification map for Brazil, Meteorologische Zeitschrift, 22, 6, 711-728.
  3. BALTAGI, B., H. (2002). Simple Linear Regression. Econometrics, New York: Springer-Verlag Berlin Heidelberg New York, pp. 51-75.
  4. BATIMA P., NATSAGDORJ L., GOMBLUUDEV P., ERDENETSETSEG B. (2005). Observed Climate Change in Mongolia. AIACC Working Paper. 12: 1 – 26
  5. BECK, H. E., ZIMMERMANN, N. E., MCVICAR, T. R., VERGOPOLAN, N., BERG, A., WOOD, E. F. (2018). Present and future Köppen-Geiger climate classification maps at1-km resolution, Scientific Data, 5:180214, 1-12. DOI: 10.1038/sdata.2018.214
  6. BERILA, A. AND DUSHI, M. (2021). Measuring Surface Urban Heat Island in Response to Population Density Based on Remote Sensing Data and GIS Techniques: Application to Prishtina, Kosovo. Folia Geographica. 63(2)
  7. BO ́E, J., TERRAY, L., HABETS, F., AND MARTIN, E. (2007). Statistical and dynamical downscaling of the Seine basin climate for hydro-meteorological studies, International Journal of Climatology, 27, 1643–1655, DOI:10.1002/joc.1602
  8. CHEN, D, CHEN, H. W. (2013). Using the Köppen classification to quantify climate variation and change: An example for 1901–2010, Environmental Development, 6, 669–79, DOI: http://dx.doi.org/10.1016/j.envdev.2013.03.007
  9. DEPARTMENT OF MINERAL RESOURCES, 2016. Geology of Thailand. Retrieved from: http://www.dmr.go.th/main.php?filename=GeoThai_En Accessed on 29 May 2019,
  10. DE SÁ JÚNIOR, A., DE CARVALHO, L.G., DA SILVA, F.F., DE CARVALHO ALVES, M. (2012). Application of the Köppen classification for climatic zoning in the state of Minas Gerais, Brazil. Theoretical and Applied Climatology volume, 108, 1–7. DOI: https://doi.org/10.1007/s00704-011-0507-8
  11. DIAZ, H. F., EISCHEID, J. K. (2007). Disappearing ‘‘alpine tundra’’ Koppen climatic type in the western United States, Geophysical Research Letters, 34, L18707, 1-4, DOI:10.1029/2007GL031253
  12. GAO F., XIN X., WU T. (2012) Study on the prediction of regional and global temperature in decadal time scale with BCC_CSM1.1 (in Chinese). Chinese Journal of Atmospheric Sciences, 1-26
  13. GEIGER, R. (1954). Landolt-Börnstein – Zahlenwerte und Funktionen aus Physik, Chemie, Astronomie, Geophysikund Technik, alte Serie Vol.3, Ch. Klassifikation der Klimate nach W. Köppen. Berlin: Springer, pp. 603–607.
  14. GUDMUNDSSON, L., BREMNES, J. B., HAUGEN, J. E., ENGEN SKAUGEN, T. (2012). Technical Note: Downscaling RCM precipitation to the station scale using quantile mapping – a comparison of Methods. Hydrology and Earth System Sciences Discussions, 9, 6185–6201, DOI:10.5194/hessd-9-6185-2012
  15. JEDLÁK, M. (2013). Global Dimming as New Climate Phenomenon. Folia Geographica. 21: 38-47
  16. JANSRI, S AND KETPICHAINARONG, W. (2020). Investigating In-service Science Teachers Conceptions of Astronomy, and Determine the Obstacles in Teaching Astronomy in Thailand. International Journal of Educational Methodology. 6(4): 745 – 758.
  17. KISNER, C. (2008). Climate Change in Thailand: Impacts and Adaptation Strategies. In Electronic Climate Institute [online]. [accessed on 20 January 2020]. Retrieved from: https://climate.org/archive/topics/international-action/thailand.htm
  18. KLAMÁR, R., MATLOVIČ, R., IVANOVÁ, M., IŠTOK, R. AND KOZOŇ, J. (2014). Local Action Group as A Tool of Inter-Municipal Cooperation: Case Study of Slovakia. Folia Geographica. 61(1): 36-67
  19. KOMORIA, D., RANGSIWANICHPONGA, P., INOUEB, N., ONOC, K., WATANABED, S. AND KAZAMA, S. (2018). Distributed probability of slope failure in Thailand under climate change. Climate Risk Management, 20: 126-137
  20. KÖPPEN, W. (1900). Versuch einer Klassifikation der Klimate, vorzugweise nach ihren Beziehungen zur Pflanzenwelt. Geographische Zeitschrift, 6, 657–679.
  21. KÖPPEN, W. (1901). Versuch einer Klassifikation der Klimate, vorzugweise nach ihren Beziehungen zur Pflanzenwelt. Meteorologische Zeitschrift, 18, 106–120.
  22. KOTTEK, M., GRIESER, J., BBECK, C., RUDOLF, B, RUBEL, F. (2006). World Map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15, 3, 259-263. DOI:10.1127/0941-2948/2006/0130
  23. KRITICOS, D. J., WEBBER, B. L., LERICHE, A., OTA, N., MACADAM, I., BATHOLS, J., SCOTT J. K. (2012). CliMond: global high-resolution historical and future scenario climate surfaces for bioclimatic Modelling. Methods in Ecology and Evolution, 3, 53-64, DOI: 10.1111/j.2041-210X.2011.00134.x
  24. LIMSAKUL, A., SINGHRUCK, P., AND WANG, L. (2017). Climatology and Spatio-Temporal Variability of Wintertime Total and Extreme Rainfall in Thailand During 1970 – 2012. Environment Asia, 10(2): 162-176
  25. LYON, C., BECKERMAN, A. P., MARCHANT, R., O’HIGGINS, P., DUNHILL, A., ALLEN, B., AZE, T., SAUPE, E., SMITH, C., HILL, D., STRINGER, L., RIEL-SALVATORE, J., MCKAY, J., AND BURKE, A. (2020). Climate change research and action must look beyond 2100. 10.31223/X5QG7D.
  26. MCCONNELL, D. A., STEER, D. (2015). Earth’s Climate System. The Good Earth: Introduction to Earth Science, New York: McGraw Hill Education, pp. 448-449.
  27. MIHINCĂU, D., ILIEȘ, D., C., WENDT, J., LIEȘ, A., ATASOY, E., SZABO-ALEXI F, P., MARCU, F., ALBU, A., V., HERMAN, G., V. (2019). Investigations on Air Quality in A School. Folia Geographica, 61(2): 190–204
  28. NEUKOM, R., STEIGER, N, GÓMEZ-NAVARRO, J.J., WANG, J., WERNER, J. P. (2019). No evidence for globally coherent warm and cold periods over the preindustrial Common Era, Nature, 571, 550–554, DOI: https://doi.org/10.1038/s41586-019-1401-2
  29. ONGOMA, V., RAHMAN, M.A., AYUGI, B. NISHA, F., GALVIN, S., SHILENJE, Z. W., OGWANG, B. A. (2021) Variability of diurnal temperature range over Pacific Island countries, a case study of Fiji. Meteorol Atmos Phys. 133, 85–95. https://doi.org/10.1007/s00703-020-00743-4
  30. PANOFSKY, H. W. AND BRIER, G. W. (1968). Some Applications of Statistics to Meteorology, Philadelphia: The Pennsyl-25vania State University Press.
  31. PEEL, M. C., FINLAYSON, B. L., MCMAHON, T. A. (2007). Updated World Map of the Köppen-Geiger Climate Classification. Hydrolody and Earth System Sciences, 11, 1633-1644. DOI: https://doi.org/10.5194/hess-11-1633-2007
  32. PHUMKOKRUX, N., RUKVERATHAM, S. (2020). Investigation of mean monthly maximum temperature of Thailand using mapping analysis method: A case study of summer 1987 to 2019. E3S Web of Conferences, 158, 1-5. DOI: https://doi.org/10.1051/e3sconf/202015801001
  33. RUHLI, R., V., VEGA, A., J. (2008). Climate Across Space. Climatology, Massachusetts: Jones and Bartlett Publishers, pp.173 – 177.
  34. SANDERSON, M. (1999). The classification of climates from Pythagoras to Koeppen. Bulletin of the American Meteorological Society, 80, 669–673. https://www.tmd.go.th/info/info.php?FileID=22 Accessed on 29 May 2018
  35. THAI METEOROLOGICAL DEPARTMENT, 2016. Climate of Thailand. Retrieved from: https://www.tmd.go.th/en/archive/thailand_climate.pdf. Accessed on 29 May 2020
  36. THORNTHWAITE, C. W. (1943). Problems in the classification of climates, Geographical Review, 33, 2, 233–255.
  37. WU, T. (2012). A mass-flux cumulus parameterization scheme for large-scale models: description and test with observations. Climate Dynamics. 38, 725 – 744. DOI 10.1007/s00382-011-0995-3
  38. XIN, X., ZHANG, L., ZHANG, J., WU, T., AND FANG, Y. (2013). Climate change projections over East Asia with BCC_CSM1.1 climate model under RCP scenarios. Journal of the Meteorological Society of Japan. 91. 413-429. 10.2151/jmsj.2013-401.
  39. XIN, X., WU, T., ZHANG, J. (2013a). Introduction of CMIP5 Experiments Carried out with the Climate System Models of Beijing Climate Center. Advances in Climate Change Research, 4, 1, 41-49. DOI:10.3724/SP.J.1248.2013.00041
  40. XIN, X., WU, T., LI, J., WANG, Z., LI, W., WU, F. (2013b). How Well does BCC_CSM1.1 Reproduce the 20th Century Climate Change over China?. Atmospheric and Oceanic Science Letters, 6, 1, 21-26, DOI: 10.1080/16742834.2013.11447053
  41. ZHANG, J., WU, T. (2012). The impact of external forcings on climate during the past millennium: Results from transient simulation with BCC_CSM1.1. Geophysical Research Abstracts, 14, EGU2012-448.