Clustering of Precipitation Pattern in Indonesia Using TRMM Satellite Data

H. Kuswanto, D. Setiawan, A. Sopaheluwakan

Abstract


This paper identifies the climatic regions in Indonesia based on the rainfall pattern similarity using TRMM data. Indonesia is a tropical climate region with three main climate clusters, i.e. monsoonal, anti-monsoonal and semi-monsoonal. The clusters were formed by examining rainfall observation datasets recorded at a number of stations over Indonesia with coarse spatial resolution. Clustering based on higher resolution datasets is needed to characterize the rainfall pattern over remote areas with no stations. TRMM provides a high resolution gridded dataset. A statistical test has been applied to evaluate the significance of TRMM bias, and it indicated that the TRMM based satellite precipitation product is a reasonable choice to be used as an input to cluster regions in Indonesia based on the similarity of rainfall patterns. The clustering by Euclidean distance revealed that Indonesia can be grouped into three significantly different rainfall patterns. Compared to the existing references, there have been regions where the rainfall pattern has been shifted. The results in this research thus update the previously defined climate regions in Indonesia.


Keywords


cluster; monsoon; TRMM; remote sensing; precipitation

Full Text:

PDF

References


M. C. Wheeler, J. L. McBride, Australian-Indonesian Monsoon, Springer, 2015

E. Aldrian, R. D. Susanto, “Identification of three dominant rainfall regions within Indonesia and their relationship to sea surface temperature”, International Journal of Climatology, Vol. 23, No. 12, pp. 1435-1452, 2003

NASDA, TRMM Data Users Handbook, NASDA, 2001

https://trmm.gsfc.nasa.gov/

J. Simpson, C. Kummerow, W. K. Tao, R. F. Adler, “On the tropical rainfall measuring mission (TRMM)”, Meteorology and Atmospheric Physics, Vol. 60, No. 1-3, pp. 19–36, 1996

J. Liu, Z. Duan, J. Jiang, A. X. Zhu, “Evaluation of three satellite precipitation products TRMM 3B42, CMORPH, and PERSIANN over a subtropical watershed in China”, Advances in Meteorology, Vol. 2015, Article ID 151239, 2015

M. Darand, J. Amanollahi, S. Zandkarimi, “Evaluation of the performance of TRMM multi-satellite precipitation analysis (TMPA) estimation over Iran”, Atmospheric Research, Vol. 190, pp. 121-127, 2017

R. Prasetia, A. R. A. Syakur, T. Osawa, “Validation of TRMM precipitation radar satellite data over Indonesian region”, Theoretical and Applied Climatology, Vol. 112, No. 3-4, pp. 575-587, 2012

A. R. As-Syakur, T. Tanaka, T. Osawa, M. S. Mahendra, “Indonesian rainfall variability observation using TRMM multi-satellite data”, International Journal of Remote Sensing, Vol. 34, No. 21, pp. 7723-7738, 2013

D. Gunawan, “Perbandingan curah hujan bulanan dari data pengamatan permukaan, satelit TRMM and model permukaan NOAH”, Jurnal Meteorologi and Geofisika, Vol. 9, No. 1, pp. 1-10, 2008

M. P. H. Giarno, S. Suprayogi, S. H. Murti, “Distribution of accuracy of TRMM daily rainfall in Makassar strait”, Forum Geografi, Vol. 32, No. 1, pp. 38-52, 2018

B. Collischonn, W. Collischonn, C. E. M. Tucci, “Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates”, Journal of Hydrology, Vol. 360, No. 1-4, pp. 207-216, 2008

T. Zhao, A. Yatagai, “Evaluation of TRMM 3B42 product using a new gauge-based analysis of daily precipitation over China”, International Journal Climatology, Vol. 34, pp. 2749-2762, 2013

M. L. Tan, Z. Duan, “Assessment of GPM and TRMM precipitation products over Singapore”, Remote Sensing, Vol. 9, No. 7, Article ID 720, 2017

J. Hur, S. V. Raghavan, N. S. Nguyen, S. Y. Liong, “Are satellite products good proxies for gauge precipitation over Singapore?”, Theoretical and Applied Climatology, Vol. 132, No. 3-4, pp. 921-932, 2018

S. N. M. Zad, Z. Zulkafli, F. M. Muharram, “Satellite rainfall (TRMM 3B42-V7) performance assessment and adjustment over Pahang River Basin, Malaysia”, Remote Sensing, Vol. 10, No. 3, Article ID 388, 2018

T. Omotosho, J. S. Mandeep, M. Abdullah, A. Adediji, “Distribution of one-minute rain rate in Malaysia derived from TRMM satellite data”, Annales Geophysicae, Vol. 31, No. 11, pp. 2013-2022, 2013

A. R. Orpin, V. E. Kostylev, “Towards a statistically valid method of textural sea floor characterization of benthic habitats”, Marine Geology, Vol. 225, No. 1-4, pp. 209-222, 2006

P. J. Rousseeuw, “Silhouettes: A graphical aid to the interpretation and validation of cluster analysis”, Journal of Computational and Applied Mathematics, Vol. 20, pp. 53-65, 1987

J. F. Hair, R. E. Anderson, R. L. Tatham, W. C. Black, Multivariate Data Analysis with Reading, Prentice Hall, 1995

L. Kaufman, P. J. Rousseeuw, Finding Groups in Data, John Wiley & Sons, 1990

T. H. Udayashankara, “Impact of climate change on rainfall pattern and reservior level”, Journal of Water Resource Engineering and Management, Vol. 3, No. 1, pp. 10-14, 2016

A. G. Pendergrass, D. L. Hartmann, “Changes in the distribution of rainfall frequency and intensity in response to global warming”, Journal of Climate, Vol. 27, No. 22, pp. 8372-8383, 2014

J. Crossman, M. N. Futter, P. G. Whitehead, “The Significance of Shifts in Precipitation Patterns: Modelling the Impacts of Climate Change and Glacier Retreat on Extreme Flood Events in Denali National Park, Alaska”, PLOS ONE, Vol. 8, No. 9, Article ID e74054, 2013

J. D. Miranda, C. Armas, F. M. Padila, F. I. Pugnaire, “Climatic change and rainfall patterns: Effects on semi-arid plant communities of the Iberian Southeast”, Journal of Arid Environment, Vol. 75, No. 12, pp. 1302-1309, 2011

M. Case, F. Ardiasyah, E. Spector, Climate Change in Indonesia-Implications for Humans and Nature, WWF, 2007

M. Measay, “Indonesia: A vulnerable country in the face of climate change”, Global Majority E-Journal, Vol. 1, No. 1, pp. 31-45, 2010




eISSN: 1792-8036     pISSN: 2241-4487