UJI AKURASI PRODUK ESTIMASI CURAH HUJAN SATELIT GPM IMERG DI SURABAYA, INDONESIA
Main Article Content
Abstract
Curah hujan merupakan parameter meteorologi yang sangat berpengaruh dalam kehidupan. Saat ini, pengamatan secara in situ sangat kurang representatif untuk digunakan sebagai analisis karena jangkauannya yang sangat sempit sehingga memerlukan instrumen pendukung seperti satelit agar dapat memberikan gambaran yang lebih baik terkait distribusi hujan. Namun, data satelit juga belum tentu sepenuhnya benar karena resolusi dan kondisi dari setiap wilayah berbeda. Penelitian ini bertujuan untuk mendapatkan nilai akurasi, bias, korelasi, root mean square error (RMSE), dan mean absolute error (MAE) data estimasi curah hujan GPM IMERG dengan data curah hujan pengamatan langsung. Penelitian ini dilakukkan di Surabaya dengan menggunakan data estimasi curah hujan GPM IMERG dan data curah hujan pengamatan langsung dari Stasiun Meteorologi Kelas I Juanda Surabaya selama tahun 2017 mewakili musim hujan, musim kemarau, dan periode transisi. Hasil penelitian menunjukkan bahwa data curah hujan produk GPM IMERG memiliki korelasi yang sangat baik untuk memperkirakan akumulasi curah hujan bulanan. Sedangkan, untuk akumulasi harian, memiliki korelasi yang sangat rendah. Sementara itu untuk akumulasi sepuluh harian, data curah hujan produk satelit GPM IMERG memiliki korelasi yang baik terutama di periode musim hujan dan musim kemarau, akan tetapi memiliki korelasi yang rendah selama periode transisi dari musim hujan ke musim kemarau atau sebaliknya. Pada umumnya, produk ini sangat bagus dalam menentukan ada atau tidaknya hujan, tetapi performanya sangat rendah dalam menentukan besarnya intensitas curah hujan.
Article Details
Authors who publish with this journal agree to the following terms:
a). Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
b). Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
c). Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
d). Each author must sign the copyright transfer statement. The article will not be published unless this form has been signed and received.
OPEN ACCESS POLICY
Jurnal Sains & Teknologi Modifikasi Cuaca provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
JSTMC by BBTMC-BPPT is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Permissions beyond the scope of this license may be available at http://ejurnal.bppt.go.id/index.php/JSTMC
References
De Coning, E. (2013). Optimizing Satellite-based Precipitation Estimation for Nowcasting of Rainfall and Flash Flood Events over the South African Domain. Remote Sensing, 5(11), 5702–5724. doi: 10.3390/rs5115702
Hou, A.Y., Kakar, R.K., Neeck, S., Azarbarzin, A.A., Kummerow, C.D., Kojima, M., Oki, R., Nakamura, K., Iguchi, T. (2014). The Global Precipitation Measurement Mission. Bulletin of the American Meteorological Society, 95(5), 701–722. doi: 10.1175/BAMS-D-13-00164.1
Huffman, G.J., Bolvin, D.T., Braithwaite, D., Hsu, K., Joyce, R., Kidd, C., Nelkin, E.J., Xie, P. (2015). Algorithm Theoretical Basis Document (ATBD) Version 4.5: NASA Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG). NASA: Greenbelt, MD, USA.
Kidd, C., Huffman, G. (2011). Global Precipitation Measurement. Meteorological Applications, 18(3), 334–353. doi: 10.1002/met.284
Kidd, C., Kniveton, D.R., Todd, M.C., Bellerby, T.J. (2003). Satellite Rainfall Estimation Using Combined Passive Microwave and Infrared Algorithms. Journal of Hydrometeorology, 4(6), 1088–1104. doi: 10.1175/1525-7541(2003)004<1088:SREUCP>2.0.CO;2
Kidd, C., Levizzani, V. (2011). Status of Satellite Precipitation Retrievals. Hydrology and Earth System Sciences, 15(4), 1109-1116. doi: 10.5194/hess-15-1109-2011
O, S., Foelsche, U., Kirchengast, G., Fuchsberger, J., Tan, J., Petersen, W.A. (2017). Evaluation of GPM IMERG Early, Late and Final Rainfall Estimates Using WegenerNet Gauge Data in Southeastern Austria. Hydrology and Earth System Sciences, 21(12), 6559–6572. doi: 10.5194/hess-21-6559-2017
Sharifi, E., Steinacker, R., 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, 8(2), 135. doi: 10.3390/rs8020135
Stanski, H.R., Wilson, L.J., Burrows W.R. (1989). Survey of Common Verification Methods in Meteorology. WMO World Weather Watch Technical Report No.8, WMO/TD No.358.
Sugiyono. (2004). Statistik Untuk Penelitian. Bandung: Alfa Beta.
Tapiador, F.J., Turk, F.J., Petersen, W., Hou, A.Y., GarcÃa-Ortega, E., Machado, L.A.T., Angelis, C.F., Salio, P., Kidd, C., Huffman, G.J., de Castro, M. (2012). Global Precipitation Measurement: Methods, Datasets and Applications. Atmospheric Reseach, 104–105, 70–97. doi: 10.1016/j.atmosres.2011.10.021
Wilks, D.S. (1995). Statistical Method in the Atmospheric Sciences. San Diego: Academic Press Inc.
Yong, B., Liu, D., Gourley, J.J., Tian, Y., Huffman, G.J., Ren, L., Hong, Y. (2015). Global View of Real-time TRMM Multisatellite Precipitation Analysis: Implications for Its Successor Global Precipitation Measurement Mission. Bulletin of the American Meteorological Society, 96(2), 283–296. doi: 10.1175/BAMS-D-14-00017.1