Distribution of Accuracy of TRMM Daily Rainfall in Makassar Strait

G Giarno(1*), Muhammad Pramono Hadi(2), Slamet Suprayogi(3), Sigit Heru Murti(4)

(1) Faculty of Geography, Gadjah Mada University, Jl. Kaliurang, Bulaksumur, Yogyakarta 55281
(2) Faculty of Geography, Gadjah Mada University, Jl. Kaliurang, Bulaksumur, Yogyakarta 55281
(3) Faculty of Geography, Gadjah Mada University, Jl. Kaliurang, Bulaksumur, Yogyakarta 55281
(4) Faculty of Geography, Gadjah Mada University, Jl. Kaliurang, Bulaksumur, Yogyakarta 55281
(*) Corresponding Author

Abstract

This research aims to evaluate rainfall estimates of satellite products in regions that have high variations of rainfall pattern. The surrounding area of Makassar Strait have chosen because of its distinctive rainfall pattern between the eastern and western parts of the Makassar Strait. For this purpose, spatial distribution of Pearson’s coefficient correlation and Root Mean Square Error (RMSE) is used to evaluate accuracy of rainfall in the eastern part of Kalimantan Island and the western part of Sulawesi Island. Moreover, we also used the contingency table to complete the parameter accuracy of the TRMM rainfall estimates. The results show that the performance of TRMM rainfall estimates varies depending on space and time. Overall, the coefficient correlation between TRMM and rain observed from no correlation was -0.06 and 0.78 from strong correlation. The best correlation is on the eastern coast of South West Sulawesi located in line with the Java Sea. While, no variation in the correlation was related to flatland such as Kalimantan Island. On the other hand, in the mountain region, the correlation of TRMM rainfall estimates and observed rainfall tend to decrease. The RMSE distribution in this region depends on the accumulation of daily rainfall. RMSE tends to be high where there are higher fluctuations of fluctuating rainfall in a location. From contingency indicators, we found that the TRMM rainfall estimates were overestimate. Generally, the absence of rainfall during the dry season contributes to improving TRMM rainfall estimates by raising accuracy (ACC) in the contingency table.

Keywords

rainfall pattern; accuracy of TRMM; monsoon; Indonesia; Makassar Strait

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References

Aldrian, E, and Susanto, R.D. (2003) Identification of three dominant rainfall regions within Indonesia and their relationship to sea surface temperature. International Journal of Climatology. Vol.23. pp.1435-1452.

Aldrian, E., Gates, L. D. and Widodo, F. H. (2007). Seasonal variability of Indonesian rainfall in ECHAM4 simulations and in the reanalyses: The role of ENSO, Theoretical and Applied Climatology, Vol.87,pp.41-59.

Arakawa O and Kitoh A (2005) Rainfall diurnal variation over the Indonesian maritime continent simulated by 20 km-mesh GCM. SOLA. Vol.1, pp.109-112.

As-syakur, A. R. (2010) Pola spasial pengaruh kejadian la nina terhadap curah hujan di indonesia tahun 1998/1999; observasi menggunakan data TRMM multisatellite precipitation analysis (TMPA) 3B43, Prosiding Pertemuan Ilmiah Tahunan MAPIN XVII Bandung.

Biasutti, M., Yuter, S.E., Burleyson C.D. and Sobel, A.H. (2012) Very high resolution rainfall patterns measured by TRMM precipitation radar: seasonal and diurnal cycles. Climate Dynamics. Vol.39, pp.239–258.

BMKG Maros (2015) Buletin prakiraan hujan 2015.

D'Arrigo, R. and Wilson, R. (2008) Short Communication : El Ni˜no and Indian Ocean influences on Indonesian drought: implications for forecasting rainfall and crop productivity. International Journal of Climatology. Vol.28, pp.611-616.

Giarno, Zadrach L. D. and Mustofa, M. A (2012) Kajian awal musim hujan and awal musim kemarau di Indonesia, Jurnal Meteorologi and Geofisika. Vol.1, pp.1–8.

Gunawan, D. (2008) 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.

Guo, H., Chen, S., Bao, A., Hu, J., Yang, B. and Stepanian, P. M. (2016) Comprehensive Evaluation of High-Resolution Satellite-Based Precipitation Products over China. Atmosphere. Vol.7, No.6, pp.1-25.

Hashiguchi, H., Tabata Y., Yamamoto, M.K., Marzuki, Mori S., Yamanaka, M.D., Syamsudin F. and Manik T (2013) Observational Study on Diurnal Precipitation Cycle over Indonesian Maritime Continent. Journal of Disaster Research. Vol.8, pp.1–9.

Hidayat, R. and Kizu, S. (2010) Influence of the Madden–Julian Oscillation on Indonesian rainfall variability in austral summer. International Journal of Climatology. Vol.30, pp.1816-1825.

Heiblum, R.H., Koren, I. and Altaratz, O. (2011) Analyzing coastal precipitation using TRMM observations. Atmos. Chem. Phys. Vol.11, pp.13201–13217.

Hsu, K. L., Gao, X., Sorooshian, S. and Gupta, H. V. (1997) Precipitation estimation from remotely sensed information using artificial neural networks. Journal of Applied Meteorology. Vol.36, No.9, pp.1176–1190.

Hu, Q., Yang, D., Li, Z., Mishra, A. K., Wang, Y. and Yang, H. (2014). Multi-scale evaluation of six high-resolution satellite monthly rainfall estimates over a humid region in China with dense rain gauges, International Journal of Remote Sensing, Vol.35, No.4, pp. 1272–1294.

Huffman, G. J., Adler, R. F. and Bolvin, D. T. (2007) The TRMM Multisatellite Precipitation Analysis (TMPA): quasi-global, multiyear, combined sensor precipitation estimates at fine scales, Journal of Hydrometeorology, Vol.8, No.1, pp. 38–55.

Jolliffe, I.T. and Stephenson, D.B. (2003) Forecast verification : A practitioner’s guide in atmospheric science, Jhon Wiley & Sons.

Joyce, R. J., Janowiak, J. E. and Arkin, P. A. (2004) CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. Journal of Hydrometeorology. Vol.5, No.3, pp.487–503.

Kim, K.; Park, J., Baik, J. and Choi, M. (2017) Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42 over Far-east Asia. Atmos. Res, Vol. 187, pp. 95–105.

Kneis, D., Chatterjee, C. and Singh, R. (2014) Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi). Hydrology and Earth System Sciences. Vol.18, pp.2493–2502.

Lee, H. S. (2015) General Rainfall Patterns in Indonesia and the Potential Impacts of Local Seas on Rainfall Intensity. Water. Vol.7, pp.1750-1768.

Li, X. H., Zhang, Q. and Xu, C. Y. (2012) Suitability of the TRMM satellite rainfalls in driving a distributed hydrological model for water balance computations inXinjiang catchment, Poyang lake basin. Journal of Hydrology. Vol.426, pp.28–38.

Liechti, T. C., Matos, J. P., Boillat, J.L. and Schleiss, A. J. (2012) Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin. Hydrology and Earth System Scinces. Vol.16, pp.489–500.

Liu, J., Zhu, A. X., and Duan, Z. (2015). Evaluation of TRMM 3B42 precipitation product using rain gauge data in meichuan watershed, Poyang Lake Basin, China, Journal of Resources and Ecology, Vol. 3, No. 4, pp. 359–366.

Mahmud, M. R., Numata, S., Matsuyama, H., Hosaka, T. and Hashim, M. (2015) Assessment of Effective Seasonal Downscaling of TRMM Precipitation Data in Peninsular Malaysia. Remote Sensing. Vol.7, pp.4092-411.

Mair, A., and Fares, A. (2004) Comparison of rainfall interpolation methods in a mountainous region of a tropical island, Journal of Hydrologic Engineering, Vol.4, pp.371-383.

Mariani, S. and Casaioli, M. (2008) Forecast verification : A summary of common approaches and examples of application. Univerta degli studi di Trento, FORALPS.

Martono, M. and Wardoyo, T. (2017) Impacts of El Niño 2015 and the Indian Ocean Dipole 2016 on Rainfall in the Pameungpeuk and Cilacap Regions. Forum Geografi. Vol. 31, No.2, pp.184–195.

Moazamia, S., Golianc, S., Kavianpoura, M. R. and Hong, Y. (2013) Comparison of PERSIANN and V7 TRMM Multi-satellite Precipitation Analysis (TMPA) products with rain gauge data over Iran. International Journal of Remote Sensing. Vol.34, No.22, pp.8156–8171.

Murphy, A. H. (1993) What is a good forecast? An essay on nature of goodness in weather forecasting. Wea. Forecasting. Vol.8, pp.281-293.

Neale, R., and Sligo, J. (2003). The Maritime Continent and Its Role in the Global Climate: A GCM Study. Journal of Climate. Vol.16, pp.834-848.

Prakash, S., Mitra, A. K., Momin, I. M., Gairola, R. M., Pai, D. S., Rajagopal, E. N. and Basu, S. (2015) A review of recent evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) research products against ground-based obeservations over Indian land and oceanic regions. Muasam. Vol.66, No.3, pp.355-366.

Prasetia, R., As-syakur, A. R., and Osawa, T. (2013). Validation of TRMM Precipitation Radar satellite data over Indonesian region, Theory Applied Climatology, Vol.112, Pp.575–587.

Qian, J.H. (2007) Why precipitation is mostly concentrated over islands in the maritime continent. Journal of The Atmospherics Sciences, Vol.65, pp.1428–1441.

Rahman, M.M., Arya, D. S., Goelb, N. K. and Mitra, A. K. (2012) Rainfall statistics evaluation of ECMWF model and TRMM data over Bangladesh for flood related studies. Meteorological Applications. Vol.19, pp.501–512.

Rahmawati, N. and Lubczynski, M. W. (2017) Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia. Theoretical and Applied Climatology, 1–20. https://doi.org/10.1007/s00704-017-2290-7.

Renggono, F. (2011) Pola sebaran hujan di DAS Larona. Jurnal Sains & Teknologi Modifikasi Cuaca. Vol.12, pp.17–24.

Sharifi, E., Steinacker, R. and Saghafian, B. (2016) Assessment of GPM-IMERG and other precipitation products against gauge data under different topographic and climatic conditions in Iran: Preliminary results, Remote Sensing, Vol. 8, 135.

Sorooshian, S., Hsu, K. L., Gao, X., Gupta, H. V., Imam, B. and Braithwaite, D. (2000) Evaluation of PERSIANN system satellitebased estimates of tropical rainfall. Bulletin of the American Meteorological Society. Vol.81, No.9, pp.2035–2046.

Supari, Tangang, F., Salimun, E., Aldrian, E., Sopaheluwakan, A., & Juneng, L. (2017). ENSO modulation of seasonal rainfall and extremes in Indonesia. Climate Dynamics, 1–22. https://doi.org/10.1007/s00382-017-4028-8.

Tan, M. L., Ibrahim, A. L., Duan, Z., Cracknell, A. P., and Chaplot, V. (2015) Evaluation of six high-resolution satellite and ground-based precipitation products over malaysia, Remote Sensing, Vol.7, pp.1504-1528.

Tan, M. L. and Duan, Z. (2017) Assessment of GPM and TRMM Precipitation Products over Singapore, Remote Sensing, Vol.9, No.720, pp.1-16.

Tang, G.Q., Zeng, Z.Y., Long, D., Guo, X.L., Yong, B., Zhang, W.H. and Hong, Y. (2016) Statistical and hydrological comparisons between TRMM and GPM level-3 products over a midlatitude basin: Is day-1 IMERG a good successor for TMPA 3B42V7?. Journal of Hydrometeorology. Vol.6, No.17, pp.121–137.

Thiemig, V., Rojas, R., Zambrano-Bigiarini, M., Levizzani, V. and de Roo, A. (2012) Validation of satellite based precipitation products over sparsely Gauged African River basins. Journal of Hydrometeorology. Vol.13, No.6, pp.1760–1783.

Xie, P., Yoo, S. H. and Joyce, R. J. (2011) Bias Corrected CMORPH : A 13 Year Analysis of High Resolution Global Precipitation, http://ftp.cpc.ncep.noaa.gov/precip/CMORPH V1.0/REF/EGU1104 Xie bias-CMORPH.pdf.

Xue, X., Hong, Y. and Limaye, A. S. (2013) Statistical and hydrological evaluation of TRMM-based Multi-satellite Precipitation Analysis over the Wangchu Basin of Bhutan: are the latest satellite precipitation products 3B42V7 ready for use in ungauged basins?. Journal of Hydrology. Vol.499, pp.91–99.

Wealands, S.R., Grayson, R.B. and Walker, J.P. (2004) Investigating spatial pattern comparison methods for distributed hydrological model assessment, Proceedings of Complexity and Integrated Resources Management, Sponsored by the International Environmental Modeling and Software Society, iEMSs 2004 International Conference, University of Osnabrück, Germany, pp.14–17.

WMO (1994) Guide to hydrological practice : Data acquisition and processing analysis and forecasting and other applications. WMO-No.168.

Yuan, F., Zhang, L., Win, K. W. W., Ren, L., Zhao, C., Zhu, Y., Jiang, S. and Liu, Y. (2017) Assessment of GPM and TRMM Multi-Satellite Precipitation Products in Streamflow Simulations in a Data-Sparse Mountainous Watershed in Myanmar. Remote Sensing. Vol.9, No.302, pp.1-23.

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