EVALUATION OF TRMM 3B42 SATELLITE RAINFALL ESTIMATION WITH OBSERVATION DATA IN KOLAKA, 2019
DOI:
https://doi.org/10.59052/edufisika.v7i2.20374Keywords:
Evaluation, Observation, Precipitation, TRMM 3B42 SatelliteAbstract
Precipitation data in Indonesia is currently carried out by in situ observation, which allows for blank data due to observer errors or due to damaged equipment. The TRMM satellite is one of the satellites that is widely used to fill in the blank rainfall data in Indonesia. This study aims to determine the results of the accuracy between the TRMM 3B42 satellite rainfall estimation data and surface observation data sourced from the Sangia Ni Bandera Kolaka Meteorological Station in 2019. Both data were statistically tested using the correlation coefficient calculation method, error calculation using the Root Mean method Squared Error (RMSE), and significance test. The results showed that the best relationship was produced by dry months compared to wet months. In general, in the time series graph, the satellite data and observation data show a fairly similar fluctuation pattern, but in some cases the TRMM satellite data is much smaller than the observation data. The best time scale for the relationship between the two data is the basic time scale, because it produces significant results for all periods of the month, and has a high correlation value with a small error value.
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References
Acak, E. D. P., Gabungan, F. P. M., Korelasi, K., & Stokastik, A. K. (2020). Statistika Matematika.
Andrade, C. (2019). The p value and statistical significance: misunderstandings, explanations, challenges, and alternatives. Indian journal of psychological medicine, 41(3), 210-215.
Atthahirah, M. (2019). Validasi Data Curah Hujan TRMM (Tropical Rainfall Measuring Mission) dengan Pos Stasiun Hujan di Sub DAS Bango (Doctoral dissertation, Universitas Brawijaya).
Chicco, D., Warrens, M. J., & Jurman, G. (2021). The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. PeerJ Computer Science, 7, e623.
Dwijayanto, A. Validasi Pola Musim di Pulau Jawa Berdasarkan Data Curah Hujan Bulanan Tahun 2001-2010.
Elfira, S. (2019). Variasi Diurnal Struktur Vertikal Hujan Di Sumatera Dan Lautan Sekitar Berdasarkan Pengamatan Satelit Trmm-Pr (Doctoral dissertation, Universitas Andalas).
Huffman G.J., Adler R.F., Bolvin D.T., Nelkin E.J. (2010) The TRMM Multi-Satellite Precipitation Analysis (TMPA). In: Gebremichael M., Hossain F. (eds) Satellite Rainfall Applications for Surface Hydrology. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2915-7_1
Kim, K., Park, J., Baik, J., & Choi, M. (2017). Evaluation of topographical and seasonal feature using gpm imerg and trmm 3b42 over far-east asia. Atmospheric Research, 187, 95-105.
Paski, J. A. I. (2017). Pengaruh asimilasi data penginderaan jauh (radar dan satelit) pada prediksi cuaca numerik untuk estimasi curah hujan. Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital, 14(2), 79-88.
Putri Jarwanti, D. (2021). Validasi data curah hujan satelit trmm (tropical rainfall measuring mission) dengan data pos penakar hujan di das grindulu, kabupaten pacitan, JAWA TIMUR (Doctoral dissertation, Universitas Brawijaya).
Ramadlon, M. M., & Hariyanto, T. (2014). Analisa Perbandingan Curah Hujan Berdasarkan Data Citra Noaa Avhrr dengan Data Curah Hujan di Lapangan. Geoid, 10(1), 1-7.
Rahma, N. F. (2019). Validasi Data Curah Hujan TRMM (Tropical Rainfall Measuring Mission) dengan Pos Stasiun Hujan di Sub DAS Sumber Brantas (Doctoral dissertation, Universitas Brawijaya).
Sipayung, S. B., Cholianawati, N., Susanti, I., & Maryadi, E. (2014). Pengembangan model persamaan empiris dalammemprediksi terjadinya longsor di daerahaliran sungai (das) citarum (jawa barat) berbasis data satelit TRMM. Jurnal Sains Dirgantara, 12(1).
Zulkafli, Z., Buytaert, W., Onof, C., Manz, B., Tarnavsky, E., Lavado, W., & Guyot, J. L. (2014). A comparative performance analysis of TRMM 3B42 (TMPA) versions 6 and 7 for hydrological applications over Andean–Amazon river basins. Journal of Hydrometeorology, 15(2), 581-592.
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