Validation of TRMM and GPM Satellite Data Using Daily Precipitation Observations

Rafika Andari (1), Nurhamidah (2), Darwizal Daoed (3), Marzuki (4)
(1) Department of Civil Engineering, Faculty of Engineering, Andalas University, Padang 25163, Indonesia
(2) Department of Civil Engineering, Faculty of Engineering, Andalas University, Padang 25163, Indonesia
(3) Department of Civil Engineering, Faculty of Engineering, Andalas University, Padang 25163, Indonesia
(4) Department of Physics, Faculty of Mathematical and Natural Sciences, Andalas University, Padang, 25163, Indonesia
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How to cite (IJASEIT) :
Andari, Rafika, et al. “Validation of TRMM and GPM Satellite Data Using Daily Precipitation Observations”. International Journal on Advanced Science, Engineering and Information Technology, vol. 14, no. 2, Apr. 2024, pp. 555-62, doi:10.18517/ijaseit.14.2.18980.
Accurate precipitation data holds immense significance in hydrological analysis. A common challenge in this field often stems from the lack of comprehensive data availability. High-resolution satellite-based precipitation measurements covering large areas offer a potential solution. However, disparities in the resolution of observed rainfall data can impact data accuracy. The main goal of this study is to evaluate the accuracy of rainfall data obtained from the TRMM and GPM satellites in the Kuranji watershed. The evaluation was conducted on the performance of the GPM IMERG-F from the Integrated Multi-satellite Retrievals for the GPM mission and the TRMM 3B42RT on a daily scale spanning from 2015 to 2019 over the Kuranji watershed. The daily precipitation measurements were validated using three widely used statistical metrics (R, RMSE, and RB). The precipitation detection capability (POD, FAR, and CSI) was also considered in this assessment. The findings demonstrate that both satellite estimations exhibit a substantial correlation coefficient (0.68 for GPM, 0.62 for TRMM) with the measurements obtained from gauges, along with an inclination to overestimate precipitation. GPM IMERG-F and TRMM 3B42RT manifest a consistent spatial pattern in daily precipitation distribution, effectively representing the observed precipitation distribution. The greater probability of detection (POD), critical success index (CSI), and lower false alarm ratio (FAR) exhibited by GPM IMERG-F at varying rainfall intensities suggests its superior performance in accurately identifying observed precipitations. This finding supports the preference for GPM IMERG-F data over TRMM 3B42RT data across various applications, hydrology, and related disciplines in the future.

T.. Alsumaiti, K. Hussein, D.. Ghebreyesus, and H . Sharif, “Performance of the CMORPH and GPM IMERG products over the United Arab Emirates,” Remote Sens., vol. 12, no. 9, 2020, doi:10.3390/RS12091426.

X. Wang, Y. Ding, C. Zhao, and J. Wang, “Similarities and improvements of GPM IMERG upon TRMM 3B42 precipitation product under complex topographic and climatic conditions over Hexi region, Northeastern Tibetan Plateau,” Atmos. Res., vol. 218, pp. 347–363, 2019, doi: 10.1016/j.atmosres.2018.12.011.

F. Su, Y. Hong, and D. P. Lettenmaier, “Evaluation of TRMM multisatellite precipitation analysis (TMPA) and its utility in hydrologic prediction in the La Plata Basin,” J. Hydrometeorol., vol. 9, no. 4, pp. 622–640, 2008, doi: 10.1175/2007JHM944.1.

M. Mamenun, H. Pawitan, and A. Sopaheluwakan, “Validasi dan Koreksi Data Satelit TRMM pada Tiga Pola Hujan di Indonesia,” Jurnal Meteorologi dan Geofisika, vol. 15, no. 1, Apr. 2014, doi: 10.31172/jmg.v15i1.169.

D. S. Krisnayanti, D. F. B. Welkis, F. M. Hepy, and D. Legono, “Evaluasi Kesesuaian Data Tropical Rainfall Measuring Mission (TRMM) dengan Data Pos Hujan Pada Das Temef di Kabupaten Timor Tengah Selatan,” J. Sumber Daya Air, vol. 16, no. 1, pp. 51–62, 2020, doi: 10.32679/jsda.v16i1.646.

Santos, R. M. . Neto, R. M. da Silva, and S. G. F. Costa, “Cluster analysis applied to spatiotemporal variability of monthly precipitation over Paraíba state using tropical rainfall measuring mission (TRMM) data,” Remote Sens., vol. 11, no. 6, 2019, doi: 10.3390/rs11060637.

T. Kubota et al., “Global precipitation map using satellite-borne microwave radiometers by the GSMaP project: Production and validation,” IEEE Transactions on Geoscience and Remote Sensing, vol. 45, no. 7. pp. 2259–2275, 2007, doi: 10.1109/TGRS.2007.895337.

T. Ushio et al., “A kalman filter approach to the global satellite mapping of precipitation (GSMaP) from combined passive microwave and infrared radiometric data,” J. Meteorol. Soc. Japan, vol. 87 A, no. June 2008, pp. 137–151, 2009, doi: 10.2151/jmsj.87A.137.

K. Aonashi, “Gsmap passive microwave precipitation retrieval algorithm: Algorithm description and validation,” J. Meteorol. Soc. Japan, vol. 87, pp. 119–136, 2009, doi: 10.2151/jmsj.87A.119.

G. Huffman, “The TRMM Multi-satellite Precipitation Analysis (TMPA),” Satellite Rainfall Applications for Surface Hydrology. pp. 3–22, 2010, doi: 10.1007/978-90-481-2915-7_1.

A. Khan, M. Koch, and K. Chinchilla, “Evaluation of Gridded Multi-Satellite Precipitation Estimation (TRMM-3B42-V7) Performance in the Upper Indus Basin (UIB),” Climate, vol. 6, no. 3, p. 76, Sep. 2018, doi: 10.3390/cli6030076.

X. H. Li, “Suitability of the TRMM satellite rainfalls in driving a distributed hydrological model for water balance computations in Xinjiang catchment, Poyang lake basin,” J. Hydrol., vol. 426, pp. 28–38, 2012, doi: 10.1016/j.jhydrol.2012.01.013.

N. Yang et al., “Evaluation of the TRMM multisatellite precipitation analysis and its applicability in supporting reservoir operation and water resources management in Hanjiang basin, China,” J. Hydrol., vol. 549, pp. 313–325, 2017, doi: 10.1016/j.jhydrol.2017.04.006.

G. J. Huffman et al., “The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales,” J. Hydrometeorol., vol. 8, no. 1, pp. 38–55, 2007, doi: 10.1175/JHM560.1.

Z. Liu, “Comparison of versions 6 and 7 3-hourly TRMM multi-satellite precipitation analysis (TMPA) research products,” Atmos. Res., vol. 163, pp. 91–101, 2015, doi: 10.1016/j.atmosres.2014.12.015.

S. Prakash, A. K. Mitra, I. M. Momin, D. S. Pai, E. N. Rajagopal, and S. Basu, “Comparison of TMPA-3B42 versions 6 and 7 precipitation products with gauge-based data over India for the southwest monsoon period,” J. Hydrometeorol., vol. 16, no. 1, pp. 346–362, 2015, doi:10.1175/JHM-D-14-0024.1.

A. K. Sahoo, J. Sheffield, M. Pan, and E. F. Wood, “Evaluation of the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) for assessment of large-scale meteorological drought,” Remote Sensing of Environment, vol. 159, pp. 181–193, Mar. 2015, doi: 10.1016/j.rse.2014.11.032.

A. Y. Hou et al., “The global precipitation measurement mission,” Bull. Am. Meteorol. Soc., vol. 95, no. 5, pp. 701–722, 2014, doi:10.1175/BAMS-D-13-00164.1.

C. Liu and E. J. Zipser, “The global distribution of largest, deepest, and most intense precipitation systems,” Geophys. Res. Lett., vol. 42, no. 9, pp. 3591–3595, 2015, doi: 10.1002/2015GL063776.

M. Tan and Z. Duan, “Assessment of GPM and TRMM precipitation products over Singapore,” Remote Sens., vol. 9, no. 7, 2017, doi:10.3390/rs9070720.

J. Wang, W. . Peterson, and D. . Wolff, “Validation of satellite-based precipitation products from TRMM to GPM,” Remote Sens., vol. 13, no. 9, 2021, doi: 10.3390/rs13091745.

M. Arshad et al., “Evaluation of GPM-IMERG and TRMM-3B42 precipitation products over Pakistan,” Atmos. Res., vol. 249, p. 105341, 2021, doi: 10.1016/j.atmosres.2020.105341.

X. Yang, Y. Lu, M. L. Tan, X. Li, G. Wang, and R. He, “Nine-Year Systematic Evaluation of the GPM and TRMM Precipitation Products in the Shuaishui River Basin in East-Central China,” Remote Sensing, vol. 12, no. 6, p. 1042, Mar. 2020, doi: 10.3390/rs12061042.

Y. Wu, Z. Zhang, Y. Huang, Q. Jin, X. Chen, and J. Chang, “Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products in the Yangtze River Basin, China,” Water, vol. 11, no. 7, p. 1459, Jul. 2019, doi: 10.3390/w11071459.

M. Kumar, O. Hodnebrog, A. . Daloz, S. Sen, S. Badiger, and J. Krishnaswamy, “Measuring precipitation in Eastern Himalaya: Ground validation of eleven satellite, model and gauge interpolated gridded products,” J. Hydrol., vol. 599, 2021, doi:10.1016/j.jhydrol.2021.126252.

A. Boluwade, “Spatial-temporal assessment of satellite-based rainfall estimates in different precipitation regimes in water-scarce and data-sparse regions,” Atmosphere (Basel)., vol. 11, no. 9, 2020, doi:10.3390/ATMOS11090901.

S. Setti, K. Yumnam, M. Rathinasamy, and A. Agarwal, “Assessment of satellite precipitation products at different time scales over a cyclone prone coastal river basin in India,” J. Water Clim. Chang., vol. 14, no. 1, pp. 38–65, 2023, doi: 10.2166/wcc.2022.166.

E. Sharifi, R. Steinacker, and B. Saghafian, “Assessment of GPM-IMERG and other precipitation products against gauge data under different topographic and climatic conditions in Iran: Preliminary results,” Remote Sens., vol. 8, no. 2, 2016, doi: 10.3390/rs8020135.

F. Yuan, “Applications of TRMM- and GPM-era multiple- satellite precipitation products for flood simulations at sub-daily scales in a sparsely gauged watershed in Myanmar,” Remote Sens., vol. 11, no. 2, 2019, doi: 10.3390/rs11020140.

M. Benkirane, “Hydro Statistical Assessment of TRMM and GPM Precipitation Products against Ground Precipitation over a Mediterranean Mountainous Watershed (in the Moroccan High Atlas),” Appl. Sci., vol. 12, no. 16, 2022, doi: 10.3390/app12168309.

Q. Ma et al., “Performance evaluation and correction of precipitation data using the 20-year IMERG and TMPA precipitation products in diverse subregions of China,” Atmos. Res., vol. 249, 2021, doi:10.1016/j.atmosres.2020.105304.

Z. Shirmohammadi-Aliakbarkhani and A. Akbari, “Ground validation of diurnal TRMM 3B42 V7 and GPM precipitation products over the northeast of Iran,” Theor. Appl. Climatol., vol. 142, no. 3, pp. 1413–1423, 2020, doi: 10.1007/s00704-020-03392-0.

M. A. Azka, P. A. Sugianto, A. K. Silitonga, and I. R. Nugraheni, “Uji Akurasi Produk Estimasi Curah Hujan Satelit Gpm Imerg Di Surabaya, Indonesia,” J. Sains Teknol. Modif. Cuaca, vol. 19, no. 2, p. 83, 2018, doi: 10.29122/jstmc.v19i2.3153.

A. Faisol, Budiyono, and E. Novita, “Evaluasi Data Hujan Harian Global Precipitation An Evaluation of Daily Precipitation Data from Global Precipitation Digital Repository Universitas Jember,” Pros. Semin. Nasioanal MIPA UNIPA IV, vol. IV, 2019.

I. Kurniawan, “Evaluasi Data GPM-IMERG (Global Precitipation Measurement - Integrated Multi-Satellite Retrieval For GPM) di Provinsi NTB,” Megasains, vol. 13, no. 01, pp. 6–13, 2022, doi:10.46824/megasains.v13i01.62.

C. Y. Liu, P. Aryastana, G. R. Liu, and W. R. Huang, “Assessment of satellite precipitation product estimates over Bali Island,” Atmos. Res., vol. 244, no. April, p. 105032, 2020, doi:10.1016/j.atmosres.2020.105032.

I. W. A. Yuda, R. Prasetia, A. R. As-Syakur, T. Osawa, and M. Nagai, “An assessment of IMERG rainfall products over Bali at multiple time scale,” E3S Web Conf., vol. 153, pp. 1–12, 2020, doi:10.1051/e3sconf/202015302001.

R. Ramadhan et al., “Evaluation of GPM IMERG Performance Using Gauge Data over Indonesian Maritime Continent at Different Time Scales,” Remote Sens., vol. 14, no. 5, pp. 1–24, 2022, doi:10.3390/rs14051172.

R. Ramadhan et al., “Capability of GPM IMERG Products for Extreme Precipitation Analysis over the Indonesian Maritime Continent,” Remote Sens., vol. 14, no. 2, 2022, doi: 10.3390/rs14020412.

H. Yusnaini et al., “Statistical Comparison of IMERG Precipitation Products with Optical Rain Gauge Observations over Kototabang, Indonesia,” J. Ilmu Fis. | Univ. Andalas, vol. 14, no. 1, pp. 10–20, 2021, doi: 10.25077/jif.14.1.10-20.2022.

R. Ramadhan et al., “Ground Validation of GPM IMERG-F Precipitation Products with the Point Rain Gauge Records on the Extreme Rainfall Over a Mountainous Area of Sumatra Island,” J. Penelit. Pendidik. IPA, vol. 8, no. 1, pp. 163–170, 2022, doi:10.29303/jppipa.v8i1.1155.

D. Yunita Samosir, I. Made Yuliara, and R. Prasetia, “Perbandingan dan Analisis Pola Spasial Curah Hujan Data IMERG (Integrated Multi-Satellite Retrievals for GPM) dan Data Observasi di Provinsi Bali Comparison and Analysis of Rainfall Spatial Patterns IMERG (Integrated Multi-Satellite Retrievals for GPM) Da,” SINTA 4 Accredit. Start., vol. 22, no. 2, pp. 67–76, 2021, [Online]. Available:

A. Faisol and B. Ollin Paga, “Komparasi Citra Satelit Hujan Resolusi Tinggi dalam Mengestimasi Curah Hujan Harian di Provinsi Papua Barat Comparison of High-Resolution Rainfall Satellite Image in Estimating Daily Rainfall in West Papua,” vol. 4, no. 1, pp. 2620–4738, 2021.

D. W. Pratiwi, J. Sujono, and A. P. Rahardjo, “Evaluasi Data Hujan Satelit untuk Prediksi Data Hujan Pengamatan Menggunakan Cross Correlation,” Pros. Semnastek, 2017, [Online]. Available:

J. M. Ginting, J. Sujono, and D. R. Jayadi, “Analisis Hubungan Data Hujan Satelit dengan Hujan Terukur ARR Kalibawang,” Pros. Konf. Pascasarj. Tek. Sipil, no. November, pp. 89–102, 2019.

S. D. Marta, E. Suhartanto, and J. S. Fidari, “Validasi Data Curah Hujan Satelit dengan Data Stasiun Hujan di DAS Ngasinan Hulu, Kabupaten Trenggalek, Jawa Timur,” J. Teknol. dan Rekayasa Sumber Daya Air, vol. 3, no. 1, pp. 35–45, 2023, doi:10.21776/ub.jtresda.2023.003.01.04.

N. A. Arrokhman, S. Wahyuni, and E. Suhartanto, “Evaluasi Kesesuaian Data Satelit untuk Curah Hujan dan Evaporasi Terhadap Data Pengukuran di Kawasan Waduk Sutami,” J. Teknol. dan Rekayasa Sumber Daya Air, vol. 1, no. 2, pp. 904–916, 2021, doi:10.21776/ub.jtresda.2021.001.02.46.

M. Adib Azka, T. Kadar Dzikiro, U. Kusuma Wardani, and A. Fadlan Sekolah Tinggi Meteorologi Klimatologi dan Geofisika, “Uji Akurasi Data Model Estimasi Curah Hujan Satelit TRMM, GSMAP, Dan GPM Selama Periode Siklon Tropis Cempaka dan Dahlia Di Wilayah Jawa Validation of TRMM, GSMAP, and GPM Modeling Data Accuracy During Tropical Cyclone Event in Java Region,” Semin. Nas. Penginderaan Jauh, no. July 2018, pp. 983–991, 2018.

E. Hidayah, W. Y. Widiarti, P. P. Putra, A. A. Dewantie, M. Z. Alhamda, and H. Prastika, “Evaluation Of Hydrologic Modelling Using Satellite Product, And Mmr Rainfall In East Java, Indonesia,” J. Ecol. Eng., vol. 22, no. 11, pp. 246–260, 2021, doi:10.12911/22998993/142843.

M. D. Syaifullah, “Validasi Data Trmm Terhadap Data Curah Hujan Aktual Di Tiga Das Di Indonesia,” J. Meteorol. dan Geofis., vol. 15, no. 2, pp. 109–118, 2014, doi: 10.31172/jmg.v15i2.180.

A. I. Suryani, “Kajian Reklamasi Lahan Daerah Aliran Sungai Batang Kuranji Kota Padang,” J. Spasial, vol. 1, no. 1, 2017, doi:10.22202/js.v1i1.1571.

A. S. Gebregiorgis et al., “To What Extent is the Day 1 GPM IMERG Satellite Precipitation Estimate Improved as Compared to TRMM TMPA-RT?,” J. Geophys. Res. Atmos., vol. 123, no. 3, pp. 1694–1707, 2018, doi: 10.1002/2017JD027606.

X. Min, C. Yang, and N. Dong, “Merging satellite and gauge rainfalls for flood forecasting of two catchments under different climate conditions,” Water (Switzerland), vol. 12, no. 3, pp. 1–17, 2020, doi:10.3390/w12030802.

G. Tang, M. . Clark, S. . Papalexiou, Z. Ma, and Y. Hong, “Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets,” Remote Sens. Environ., vol. 240, 2020, doi:10.1016/j.rse.2020.111697.

M. . Mahmoud, S. . Mohammed, M. . Hamouda, and M. . Mohamed, “Impact of topography and rainfall intensity on the accuracy of imerg precipitation estimates in an arid region,” Remote Sens., vol. 13, no. 1, pp. 1–17, 2021, doi: 10.3390/rs13010013.

M. L. Tan and H. Santo, “Comparison of GPM IMERG, TMPA 3B42 and PERSIANN-CDR satellite precipitation products over Malaysia,” Atmos. Res., vol. 202, no. September 2017, pp. 63–76, 2018, doi:10.1016/j.atmosres.2017.11.006.

M. N. Anjum et al., “Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan,” Atmos. Res., vol. 205, pp. 134–146, 2018, doi: 10.1016/j.atmosres.2018.02.010.

J. R. Rozante, D. A. Vila, J. B. Chiquetto, A. de A. Fernandes, and D. S. Alvim, “Evaluation of TRMM/GPM blended daily products over Brazil,” Remote Sens., vol. 10, no. 6, pp. 1–17, 2018, doi:10.3390/rs10060882.

S. Wang, J. Liu, J. Wang, X. Qiao, and J. Zhang, “Evaluation of GPM IMERG V05B and TRMM 3B42V7 Precipitation products over high mountainous tributaries in Lhasa with dense rain gauges,” Remote Sens., 2019, [Online]. Available:

L. A. Blacutt, D. L. Herdies, L. G. G. de Gonçalves, D. A. Vila, and M. Andrade, “Precipitation comparison for the CFSR, MERRA, TRMM3B42 and Combined Scheme datasets in Bolivia,” Atmos. Res., vol. 163, pp. 117–131, 2015, doi: 10.1016/j.atmosres.2015.02.002.

B. Yong et al., “First evaluation of the climatological calibration algorithm in the real-time TMPA precipitation estimates over two basins at high and low latitudes,” Water Resour. Res., vol. 49, no. 5, pp. 2461–2472, 2013, doi: 10.1002/wrcr.20246.

T. Condom, P. Rau, and J. C. Espinoza, “Correction of TRMM 3B43 monthly precipitation data over the mountainous areas of Peru during the period 1998-2007,” Hydrol. Process., vol. 25, no. 12, pp. 1924–1933, 2011, doi: 10.1002/hyp.7949.

E. . Ebert, J. . Janowiak, and C. Kidd, “Comparasion of Near-Real-TIme Precipitation Estimates from Satellite Observations and Numerical Models,” Am. Meteorol. Soc., pp. 47–64, 2007, doi:10.1007/978-3-540-89725-5_19.

R. Ramadhan et al., “A Preliminary Assessment of the GSMaP Version 08 Products over Indonesian Maritime Continent against Gauge Data,” Remote Sens., vol. 15, no. 4, 2023, doi:10.3390/rs15041115.

A. Nkunzimana, S. Bi, M. A. A. Alriah, T. Zhi, and N. A. D. Kur, “Comparative Analysis of the Performance of Satellite-Based Rainfall Products Over Various Topographical Unities in Central East Africa: Case of Burundi,” Earth Sp. Sci., vol. 7, no. 5, pp. 0–3, 2020, doi:10.1029/2019EA000834.

M. Rachdane, E. M. El Khalki, M. E. Saidi, M. Nehmadou, A. Ahbari, and Y. Tramblay, “Comparison of High-Resolution Satellite Precipitation Products in Sub-Saharan Morocco,” Water (Switzerland), vol. 14, no. 20, 2022, doi: 10.3390/w14203336.

A. Veloria, G. J. Perez, G. Tapang, and J. Comiso, “Improved rainfall data in the Philippines through concurrent use of GPM IMERG and ground-based measurements,” Remote Sens., vol. 13, no. 15, pp. 1–21, 2021, doi: 10.3390/rs13152859.

F. Xu et al., “Systematical Evaluation of GPM IMERG and TRMM 3B42V7 Precipitation Products in the Huang-Huai-Hai Plain, China,” Remote Sensing, vol. 11, no. 6, p. 697, Mar. 2019, doi:10.3390/rs11060697.

R. Ramadhan et al., “Evaluation of GPM IMERG Products for Extreme Precipitation over Indonesia,” J. Phys. Conf. Ser., vol. 2309, no. 1, 2022, doi: 10.1088/1742-6596/2309/1/012008.

W. Wang, H. Lu, T. Zhao, L. Jiang, and J. Shi, “Evaluation and Comparison of Daily Rainfall From Latest GPM and TRMM Products Over the Mekong River Basin,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 6, pp. 2540–2549, Jun. 2017, doi: 10.1109/jstars.2017.2672786.

C. Chen et al., “Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China,” Remote Sensing, vol. 10, no. 6, p. 944, Jun. 2018, doi: 10.3390/rs10060944.

Y. Song, J. Zhang, X. Meng, Y. Zhou, Y. Lai, and Y. Cao, “Comparison study of multiple precipitation forcing data on hydrological modeling and projection in the qujiang river basin,” Water (Switzerland), vol. 12, no. 9, 2020, doi: 10.3390/w12092626.

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