Validation of Satellite Rainfall Product (GPM-IMERG) an Bali and Nusa Tenggara: A Comparison of Normal Seasons, El Nino and La Nina Events
DOI:
https://doi.org/10.24114/jg.v15i2.44967Abstract
Bali and Nusa Tenggara are regions where monsoonal wind changes and strange interactions between the ocean and atmosphere influence rainfall. The purpose of this research is to evaluate Integrated Multi-Satellite Retrievals for GPM (IMERG) rainfall data using in-situ observations from Bali and Nusa Tenggara, Indonesia, while considering seasonal variations and the El Nino-Southern Oscillation (ENSO) phenomenon. The study combines rainfall data from synoptic stations with rain gauge measurements over ten years, from January 2012 to December 2021, to obtain more accurate verification results. The study's findings indicate that, apart from the transitional seasons, IMERG data provides substantial estimates of monthly rainfall accumulation with low error values for both light and heavy rainfall. The study also reveals that the islands' complexity and topography can impact each province's validation values. The verification results show excellent accuracy in flat terrain areas and moderate elevations, while performance decreases in regions with high altitudes. These findings are significant because IMERG data can estimate rainfall for regions lacking monitoring stations during specific seasons and active ENSO conditions. Thus, this information can serve as a valuable tool to address the issue of data unavailability in hard-to-access areas and contribute to optimizing water resource management and weather-related disaster mitigation. Keywords: Validation, Rainfall, IMERG, ENSOReferences
Amerigeoss. 2022. GPM / IMERG Precipitation Data. Available in URL https://data.amerigeoss.org/dataset/gpm-imerg-precipitation-data
Asferizal, Ferial. 2022. Analisis Perbandingan Kehandalan Data Hujan GSMaP, TRMM, GPM dan PERSIANN Terhadap Data Obsevasi Dalam Rentang Waktu Penelitian 2020 - 2021. Journal of Infrastructure Planning and Design, [S.l.], v. 2, n. 1, p. 33-41, July 2022. https://journal.itera.ac.id/index.php/jipad/article/view/1014/343
As-syakur, A. R. 2007. Identifikasi hubungan fluktuasi nilai SOI terhadap curah hujan bulanan di kawasan Batukaru-Bedugul, Bali. Jurnal Bumi Lestari, 7(2), 123-129. https://adoc.pub/identifikasi-hubungan-fluktuasi-nilai-soi-terhadap-curah-huj.html
Athoillah, I., Sibarani, R. M., & Doloksaribu, D. E. (2017). Analisis spasial El Niño kuat tahun 2015 dan La Nina lemah tahun 2016 (pengaruhnya terhadap kelembapan, angin dan curah hujan di Indonesia). Jurnal Sains & Teknologi Modifikasi Cuaca, 18(1), 33-41. https://doi.org/10.29122/jstmc.v18i1.2140.
Azka, M. A., Dzikiro, T. K., Wardani, U. K., & Fadlan, A. 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. https://www.researchgate.net/publication/351853249_Uji_Akurasi_Data_Model_Estimasi_Curah_Hujan_Satelit_TRMM_GSMAP_Dan_GPM_Selama_Periode_Siklon_Tropis_Cempaka_dan_Dahlia_Di_Wilayah_Jawa
Azka, M. A., Sugianto, P. A., Silitonga, A. K., & Nugraheni, I. R. (2018). Uji akurasi produk estimasi curah hujan Satelit GPM IMERG di Surabaya, Indonesia. Jurnal Sains & Teknologi Modifikasi Cuaca, 19(2), 83-88. https://doi.org/10.29122/jstmc.v19i2.3153.
Badan Meteorologi Klimatologi dan Geofisika. https://www.bmkg.go.id/iklim/prakiraan-musim.bmkg Accessed 10 September 2022.
Bureau of Meteorology (BoM) Australia. www.bom.gov.au
Climate Data guide. 2022. Nino Indek regions (SST) Available in URL https://climatedataguide.ucar.edu/climate-data/nino-sst-indices-nino-12-3-34-4-oni-and-tni. Accessed 21 September 2022.
CLIMATE. 2022. What is the El Niño“Southern Oscillation (ENSO)? Available in URL https://www.climate.gov/news-features/blogs/enso/what-el-ni%C3%B1o%E2%80%93southern-oscillation-enso-nutshell. Accessed 5 Agustus 2022.
Fatkhuroyan., Wati, T., Sukmana, A., Kurniawan, R. (2018) Validation of Satellite Daily Rainfall Estimates Over Indonesia. https://doi.org/10.23917/forgeo.v32i2.6288.
Feidas, H. (2010) Validation of Satellite Rainfall Products over Greece https://doi.org/10.1007/s00704-009-0135-8.
Huang WR, Chang YH, Liu PY. 2018. Assessment of IMERG precipitation over Taiwan at multiple timescales. Atmos. Res., 214, 239-249." https://doi.org/10.1016/j.atmosres.2018.08.004.
Liu, C. Y., Aryastana, P., Liu, G. R., & Huang, W. R. (2020). Assessment of satellite precipitation product estimates over Bali Island. Atmospheric Research, 244, 105032. https://doi.org/10.1016/j.atmosres.2020.105032.
Mohammed, S. A., Hamouda, M. A., Mahmoud, M. T., and Mohamed, M. M.: Performance of GPM-IMERG precipitation products under diverse topographical features and multiple-intensity rainfall in an arid region, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2019-547, 2020. https://doi.org/10.5194/hess-2019-547.
NOAA, 2019. El Niño/Southern Oscillation (ENSO) Technical Discussion, accessed https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/enso_disc_aug2019/ensodisc.pdf 21 September 2022
Nuarsa, I. W., Adnyana, I., & As-syakur, A. 2015. Pemetaan Daerah Rawan Kekeringan Di Bali-Nusa Tenggara Dan Hubungannya Dengan Enso Menggunakan Aplikasi Data Penginderaan Jauh. Bumi Lestari, 15(1), 20-30. https://www.researchgate.net/publication/311729609_Pemetaan_Daerah_Rawan_Kekeringan_di_Bali-Nusatenggara_dan_Hubungannya_dengan_ENSO_Menggunakan_Aplikasi_Data_Penginderaan_Jauh
Nugraha, A. C. N., Marfai, M. A., Cahyadi, R., & Sunarti, B. H. (2019). Climate change impacts on water resources in Bali, Indonesia. Water, 11(4), 779. https://doi.org/10.3390/w11040779.
Nurdiati, S., Sopaheluwakan, A & Septiawan, P. 2021. Spatial and Temporal Analysis El Nino Impact on Land and Forest Fire in Kalimantan and Sumatra. Agromet 35 (1): 1-10. https://doi.org/10.29244/j.agromet.35.1.1-10.
Nuryanto, D. E. (2012). Keterkaitan Antara Monsun Indo-Australia dengan Variabilitas Musiman Curah Hujan di Benua Maritim Indonesia Secara Spasial Berbasis Hasil Analisis Data Satelit TRMM. Jurnal Meteorologi dan Geofisika, 13(2). https://doi.org/10.31172/jmg.v13i2.123.
Ovando, G., Sayago, S., Bellini, Y., Belmonte, M. L., & Bocco, M. (2021). Precipitation estimations based on remote sensing compared with data from weather stations over agricultural region of Argentina pampas. Remote Sensing Applications: Society and Environment, 23, 100589. https://doi.org/10.1016/j.rsase.2021.100589.
Pandiangan, A. E. C., Syahputra, M. R., & Hadi, T. W. (2022, December). IMERG-E satellite rainfall estimation error decomposition for early warning use in several parts of Indonesia. In IOP Conference Series: Earth and Environmental Science (Vol. 1105, No. 1, p. 012037). IOP Publishing. https://doi.org/10.1088/1755-1315/1105/1/012037.
Parwati, N. (2015). Assessment of rainfall prediction models for monsoonal region of India. International Journal of Current Research, 7(12), 22452-22457.
Partarini, N. M. C., Sujono, J., & Pratiwi, E. P. A. 2021. Koreksi dan Validasi Data Curah Hujan Satelit GPM-IMERG dan CHIRPS di Das Selorejo, Kabupaten Malang. Civil Engineering, Environmental, Disaster & Risk Management Symposium (CEEDRiMS).
Prakash S, Mitra AK, AghaKouchak A. 2018. A preliminary assessment of GPM- based multi-satellite precipitation estimates over a monsoon-dominated region. Journal of Hydrometeorology 556: 865“876. https://doi.org/10.1016/j.jhydrol.2016.01.029.
Prasetyo, B., Irwandi, H., & Pusparini, N. (2018). Karakteristik curah hujan berdasarkan ragam topografi di Sumatera Utara. Jurnal Sains & Teknologi Modifikasi Cuaca, 19(1), 11-20. https://doi.org/10.29122/jstmc.v19i1.2787.
Rahma, N. F., Suhartanto, E., & Harisuseno, D., 2019: Validasi Data Curah Hujan TRMM (Tropical Rainfall Measuring Mission) dengan Pos Stasiun Hujan di Sub DAS Sumber Brantas. Jurnal Mahasiswa Teknik Pengairan Universitas Brawijaya, 2(2), 1“13.
Sahlu, D, Nikolopoulos EI, Moges SA, Anagnostou EN, Hailu D. 2016. First evaluation of the day-1 IMERG over the upper Blue Nile Basin. J. Hydrometeorol. 2016, 17, 2875“2882 https://doi.org/10.1175/JHM-D-15-0230.1.
Salles L, Satgé F, Roig H, Almeida T, Olivetti D, Ferreira W. 2019. Seasonal Effect on Spatial and Temporal Consistency of the New GPM-Based IMERG-v5 and GSMaP-v7 Satellite Precipitation Estimates in Brazil's Central Plateau Region. Water 2019, 11, 668. https://doi.org/10.3390/w11040668.
Situmorang, I. D. W. (2010). Analisis Pengelompokan Curah Hujan Berbasis Sistem Informasi Geografis (SIG).
Sunarti, B. H., Marfai, M. A., & Cahyadi, R. (2019). Climate change and its impact on the water resources of East Nusa Tenggara Province, Indonesia. Water, 11(4), 780. https://doi.org/10.3390/w11040780.
Sungmin O, and Kirstetter P. 2018. Evaluation of diurnal variation of GPM IMERG derived summer precipitation over the contiguous US using MRMS data. Q. J. Roy. Meteor.Soc. 3218
Suprayogi, H., Soetamto, S., Ma™rufi, A., & Gusmira, E. (2016). Analisis Komponen Angin Meridional Dasarian Lapisan 850 Milibar Di Ranai Sebagai Indikator Awal Musim Hujan Dan Curah Hujan Dasarian Di Jawa, Bali Dan Nusa Tenggara.
Tan ML, and Duan Z. 2017. Assessment of GPM and TRMM Precipitation Products over Singapore. Remote Sens. 2017, 9, 720; doi:10.3390/rs9070720 https://doi.org/10.3390/w11040668.
Tangang, F., Salimun, E., Aldrian, E., Sopaheluwakan, A., & Juneng, L. (2018). ENSO modulation of seasonal rainfall and extremes in Indonesia. Climate Dynamics, 51, 2559-2580. https://doi.org/10.1007/s00382-017-4028-8.
Tukidi. (2010). Karakter Curah Hujan Di Indonesia. Jurnal Geografi. Vol 7, No 2 https://doi.org/10.1002/2016JD025418.
WMO. 2014. WMO-No. 1145: El Niño/Southern Oscillation (ENSO). World Meteorological Organization. Geneva.
Xu R, Tian F, Yang L, Hu H, Lu H, Hou A. 2017. Ground validation of GPM IMERG and TRMM 3B42V7 rainfall products over the southern Tibetan plateau based on a high-density rain-gauge network. J. Geophys. Res. Atmos. 122, 910“924
Yosilia, M. A. (2014). Analisis Hubungan El Nino dengan Kekeringan Meteorologis Menggunakan SPI (Standardized Precipitation Index) di Pulau Bali (Doctoral dissertation, Universitas Gadjah Mada).
Yuda, I. W. A., Prasetia, R., As-syakur, A. R., Osawa, T., & Nagai, M. (2020). An assessment of IMERG rainfall products over Bali at multiple time scales. In E3s web of conferences (Vol. 153, p. 02001). EDP Sciences. https://doi.org/10.1051/e3sconf/202015302001.
Yudistira, D., & Hutauruk, R. C. H. (2021). Peluang bencana banjir pada saat hujan lebat dan sangat lebat di kawasan Pantura Provinsi Jawa BaratnPeluang Bencana Banjir Pada Saat Hujan Lebat dan Sangat Lebat di Kawasan Pantura Provinsi Jawa Barat. Buletin GAW Bariri, 2(1), 16-23. https://doi.org/10.31172/bgb.v2i1.34.
Yuniasih, B., Harahap, W.N., & Wardana, D.A.S. 2022. Anomali Iklim El Nino dan La Nina di Indonesia pada 2013-2022. Agrowisata: Jurnal groteknologi Vol.6 (2022). No.2. https://doi.org/10.55180/agi.v6i2.332.
Zhang, D., Yang, M., Ma, M., Tang, G., Wang, T., Zhao, X., Ma, S., Wu, J., & Wang, W. (2022). Can GPM IMERG Capture Extreme Precipitation in North China Plain? Remote Sensing, 14(4), 928. https://doi.org/10.3390/rs14040928.