Simulasi Dispersi SO2 Saat Letusan Gunung Marapi Menggunakan Model WRF-Chem Studi Kasus Tanggal 3-5 Desember 2023
Abstract
Letusan Gunung Marapi di Sumatra Barat pada 3 Desember 2023 menghasilkan emisi SO₂ yang berpotensi merusak lingkungan dan membahayakan kesehatan masyarakat. Penelitian ini bertujuan untuk memodelkan dispersi SO₂ akibat letusan tersebut menggunakan model WRF-Chem dengan mempertimbangkan faktor meteorologi. Data meteorologi global FNL dengan resolusi 0,25° x 0,25° digunakan sebagai masukan model, sedangkan validasi dilakukan menggunakan data observasi dari Stasiun GAW Bukit Koto Tabang. Proses simulasi menggunakan parameterisasi RADM2 untuk kimia gas dan YSU untuk planetary boundary layer. Hasil simulasi menunjukkan pola temporal dan spasial yang cukup baik, meskipun dengan nilai korelasi rendah untuk SO₂ (rata-rata 0,175), serta nilai MAE sebesar 1,296 dan RMSE sebesar 3,416 yang menunjukkan kecenderungan underestimate dibandingkan dengan observasi. Sebaliknya, parameter meteorologi khususnya suhu permukaan menunjukkan korelasi yang sangat kuat. Implikasi penelitian ini adalah perlunya validasi hasil model secara lebih komprehensif dengan menambahkan titik observasi untuk evaluasi yang lebih akurat. Selain itu, penelitian lanjutan perlu difokuskan pada pemilihan skema parameterisasi optimal untuk meningkatkan akurasi simulasi dispersi SO₂ secara signifikan
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References
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LeGrand, S. L., Polashenski, C., Letcher, T. W., Creighton, G. A., Peckham, S. E., & Cetola, J. D. (2019). The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1. Geoscientific Model Development, 12(1), 131–166. https://doi.org/10.5194/gmd-12-131-2019
Lin, Y.-L., Farley, R. D., & Orville, H. D. (1983). Bulk Parameterization of the Snow Field in a Cloud Model.
Mahdi, M., Istijono, B., Yossafra, Y., Ismail, F. A., Hakam, A., Adji, B. M., Saputra, D., Andriani, A., Narny, Y., Giffari, M. Al, Zis, S. F., & Yuliet, R. (2025). Identifikasi dan Pemetaan Masalah di Nagari Pasca Bencana Erupsi Gunung Marapi di Sumatera Barat. Jurnal Talenta Sipil, 8(1), 140. https://doi.org/10.33087/talentasipil.v8i1.705
Mellor, G. L., & Yamada, T. (1982). Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4), 851–875. https://doi.org/10.1029/RG020i004p00851
Oppenheimer, C., Scaillet, B., & Martin, R. S. (2011). Sulfur degassing from volcanoes: Source conditions, surveillance, plume chemistry and earth system impacts. Reviews in Mineralogy and Geochemistry, 73, 363–421.
Özbay, B. (2012a). Modeling the Effects of Meteorological Factors on SO2 and PM10 Concentrations with Statistical Approaches. Clean - Soil, Air, Water, 40(6), 571–577. https://doi.org/10.1002/clen.201100356
Özbay, B. (2012b). Modeling the Effects of Meteorological Factors on SO2 and PM10 Concentrations with Statistical Approaches. Clean - Soil, Air, Water, 40(6), 571–577. https://doi.org/10.1002/clen.201100356
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Robock, A. (2000). Ic Eruptions. Reviews of Geophysics, 1998, 191–219.
Ruiz, J. J., Saulo, C., & Nogués-Paegle, J. (2010). WRF Model Sensitivity to Choice of Parameterization over South America: Validation against Surface Variables. Monthly Weather Review, 138(8), 3342–3355. https://doi.org/10.1175/2010MWR3358.1
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Stuefer, M., Freitas, S. R., Grell, G., Webley, P., Peckham, S., McKeen, S. A., & Egan, S. D. (2013). Inclusion of ash and SO_2 emissions from volcanic eruptions in WRF-Chem: development and some applications. Geoscientific Model Development, 6(2), 457–468. https://doi.org/10.5194/gmd-6-457-2013
Tasić, V., Kovačević, R., & Milošević, N. (2013). Investigating the impacts of winds on SO2 concentrations in Bor, Serbia. Journal of Sustainable Development of Energy, Water and Environment Systems, 1(2), 141–151. https://doi.org/10.13044/j.sdewes.2013.01.0010
Turney. (2022). Pearson Correlation Coefficient (r) | Guide & Examples. Scribbr. https://www.scribbr.com/statistics/pearson-correlation-coefficient/
Xu, M., Jin, J., Wang, G., Segers, A., Deng, T., & Lin, H. X. (2021). Machine learning based bias correction for numerical chemical transport models. Atmospheric Environment, 248(January), 118022. https://doi.org/10.1016/j.atmosenv.2020.118022
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Ashkenazy, Y. (2023). The diurnal cycle and temporal trends of surface winds. Earth and Planetary Science Letters, 601, 117907. https://doi.org/10.1016/j.epsl.2022.117907
Brega, E., Caccamo, M. T., Castorina, G., Magazù, S., Morichetti, M., Munaò, G., Passerini, G., & Rizza, U. (2020a). WRF-Chem optimization for the estimation of etna volcanic ash fallout. arXiv, December 2015, 1–42.
Brega, E., Caccamo, M. T., Castorina, G., Magazù, S., Morichetti, M., Munaò, G., Passerini, G., & Rizza, U. (2020b). WRF-Chem optimization for the estimation of etna volcanic ash fallout. arXiv, December 2015, 1–42.
Carnelos, D. A., Jobbagy, E., & Piñeiro, G. (2024). Rainout and Washout Contributions to Wet Atmospheric Deposition in Southern South America. Water, Air, and Soil Pollution, 235(3). https://doi.org/10.1007/s11270-024-06991-z
Chakraborty, D., & Elzarka, H. (2018). Performance testing of energy models: are we using the right statistical metrics? Journal of Building Performance Simulation, 11(4), 433–448. https://doi.org/10.1080/19401493.2017.1387607
Diehl, T., Heil, A., Chin, M., Pan, X., Streets, D., Schultz, M., & Kinne, S. (2012). Anthropogenic, biomass burning, and volcanic emissions of black carbon, organic carbon, and SO2 from 1980 to 2010 for hindcast model experiments. Atmospheric Chemistry and Physics Discussions, 12, 24895–24954. https://doi.org/10.5194/acpd-12-24895-2012
Ek, M. B., Mitchell, K. E., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G., & Tarpley, J. D. (2003). Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. Journal of Geophysical Research: Atmospheres, 108(22), 1–16. https://doi.org/10.1029/2002jd003296
Freitas, S. R., Longo, K. M., Alonso, M. F., Pirre, M., Marecal, V., Grell, G., Stockler, R., Mello, R. F., & Sánchez Gácita, M. (2011). PREP-CHEM-SRC - 1.0: A preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models. Geoscientific Model Development, 4(2), 419–433. https://doi.org/10.5194/gmd-4-419-2011
Gómez-Navarro, J. J., Raible, C. C., & Dierer, S. (2015). Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain. Geoscientific Model Development, 8(10), 3349–3363. https://doi.org/10.5194/gmd-8-3349-2015
Hirtl, M., Stuefer, M., Arnold, D., Grell, G., Maurer, C., Natali, S., Scherllin-Pirscher, B., & Webley, P. (2019). The effects of simulating volcanic aerosol radiative feedbacks with WRF-Chem during the EyjafjallajÖkull eruption, April and May 2010. Atmospheric Environment, 198(October 2018), 194–206. https://doi.org/10.1016/j.atmosenv.2018.10.058
Hong, S.-Y., & Lim, J.-O. J. (2006). Hongandlim-JKMS-2006. Journal of the Korean Meteorological Society, 42(2), 129–151.
Hong, S.-Y., Lim, K.-S. S., Lee, Y.-H., Ha, J.-C., Kim, H.-W., Ham, S.-J., & Dudhia, J. (2010). Evaluation of the WRF Double-Moment 6-Class Microphysics Scheme for Precipitating Convection. Advances in Meteorology, 2010, 1–10. https://doi.org/10.1155/2010/707253
Hu, X. M., Nielsen-Gammon, J. W., & Zhang, F. (2010a). Evaluation of three planetary boundary layer schemes in the WRF model. Journal of Applied Meteorology and Climatology, 49(9), 1831–1844. https://doi.org/10.1175/2010JAMC2432.1
Hu, X. M., Nielsen-Gammon, J. W., & Zhang, F. (2010b). Evaluation of three planetary boundary layer schemes in the WRF model. Journal of Applied Meteorology and Climatology, 49(9), 1831–1844. https://doi.org/10.1175/2010JAMC2432.1
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., & Collins, W. D. (2008). Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research Atmospheres, 113(13), 2–9. https://doi.org/10.1029/2008JD009944
Karagulian, F., Belis, C. A., Dora, C. F. C., Prüss-Ustün, A. M., Bonjour, S., Adair-Rohani, H., & Amann, M. (2015). Contributions to cities’ ambient particulate matter (PM): A systematic review of local source contributions at global level. Atmospheric Environment, 120, 475–483. https://doi.org/10.1016/j.atmosenv.2015.08.087
Laeger, K., Petrelli, M., Andronico, D., Misiti, V., Scarlato, P., Cimarelli, C., Taddeucci, J., Del Bello, E., & Perugini, D. (2017a). High-resolution geochemistry of volcanic ash highlights complex magma dynamics during the Eyjafjallajökull 2010 eruption. American Mineralogist, 102(6), 1173–1186. https://doi.org/10.2138/am-2017-5860
Laeger, K., Petrelli, M., Andronico, D., Misiti, V., Scarlato, P., Cimarelli, C., Taddeucci, J., Del Bello, E., & Perugini, D. (2017b). High-resolution geochemistry of volcanic ash highlights complex magma dynamics during the Eyjafjallajökull 2010 eruption. American Mineralogist, 102(6), 1173–1186. https://doi.org/10.2138/am-2017-5860
Lakitan, B. (2002). Dasar-Dasar Klimatologi. PT Raja Grafindo Persada.
LeGrand, S. L., Polashenski, C., Letcher, T. W., Creighton, G. A., Peckham, S. E., & Cetola, J. D. (2019). The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1. Geoscientific Model Development, 12(1), 131–166. https://doi.org/10.5194/gmd-12-131-2019
Lin, Y.-L., Farley, R. D., & Orville, H. D. (1983). Bulk Parameterization of the Snow Field in a Cloud Model.
Mahdi, M., Istijono, B., Yossafra, Y., Ismail, F. A., Hakam, A., Adji, B. M., Saputra, D., Andriani, A., Narny, Y., Giffari, M. Al, Zis, S. F., & Yuliet, R. (2025). Identifikasi dan Pemetaan Masalah di Nagari Pasca Bencana Erupsi Gunung Marapi di Sumatera Barat. Jurnal Talenta Sipil, 8(1), 140. https://doi.org/10.33087/talentasipil.v8i1.705
Mellor, G. L., & Yamada, T. (1982). Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4), 851–875. https://doi.org/10.1029/RG020i004p00851
Oppenheimer, C., Scaillet, B., & Martin, R. S. (2011). Sulfur degassing from volcanoes: Source conditions, surveillance, plume chemistry and earth system impacts. Reviews in Mineralogy and Geochemistry, 73, 363–421.
Özbay, B. (2012a). Modeling the Effects of Meteorological Factors on SO2 and PM10 Concentrations with Statistical Approaches. Clean - Soil, Air, Water, 40(6), 571–577. https://doi.org/10.1002/clen.201100356
Özbay, B. (2012b). Modeling the Effects of Meteorological Factors on SO2 and PM10 Concentrations with Statistical Approaches. Clean - Soil, Air, Water, 40(6), 571–577. https://doi.org/10.1002/clen.201100356
Purwaningsih, E. (2019). Volcanic Contingency Plans Based on Geospatial Information Case Study: Mount Marapi West Sumatera. Seminar Nasional Geomatika. https://doi.org/DOI:10.24895/SNG.2018.3-0.1081
PVMBG. (2023a). Press Release Erupsi Gunung Marapi Sumatera BARAT 3 Desember 2023. vsi.esdm.go.id. https://vsi.esdm.go.id/press-release/press-release-erupsi-gunung-marapi-sumatera-barat-3-desember-2023
PVMBG. (2023b). Press Release Erupsi Gunung Marapi Sumatera BARAT 3 Desember 2023. vsi.esdm.go.id. https://vsi.esdm.go.id/press-release/press-release-erupsi-gunung-marapi-sumatera-barat-3-desember-2023
Ridwan, R., & Kudsy, M. (2011). Parameterisasi Model Cuaca Wrf-Arw Untuk Mendukung Kegiatan Teknologi Modifikasi Cuaca (Tmc) Di Sumatera, Sulawesi, Dan Jawa. Jurnal Sains & Teknologi Modifikasi Cuaca, 12(1), 1. https://doi.org/10.29122/jstmc.v12i1.2184
Robock, A. (2000). Ic Eruptions. Reviews of Geophysics, 1998, 191–219.
Ruiz, J. J., Saulo, C., & Nogués-Paegle, J. (2010). WRF Model Sensitivity to Choice of Parameterization over South America: Validation against Surface Variables. Monthly Weather Review, 138(8), 3342–3355. https://doi.org/10.1175/2010MWR3358.1
Stockwell, W. R., Middleton, P., Chang, J. S., & Xiaoyan Tang. (1990). The second generation regional acid deposition model chemical mechanism for regional air quality modeling. Journal of Geophysical Research, 95(D10). https://doi.org/10.1029/jd095id10p16343
Stuefer, M., Freitas, S. R., Grell, G., Webley, P., Peckham, S., McKeen, S. A., & Egan, S. D. (2013). Inclusion of ash and SO_2 emissions from volcanic eruptions in WRF-Chem: development and some applications. Geoscientific Model Development, 6(2), 457–468. https://doi.org/10.5194/gmd-6-457-2013
Tasić, V., Kovačević, R., & Milošević, N. (2013). Investigating the impacts of winds on SO2 concentrations in Bor, Serbia. Journal of Sustainable Development of Energy, Water and Environment Systems, 1(2), 141–151. https://doi.org/10.13044/j.sdewes.2013.01.0010
Turney. (2022). Pearson Correlation Coefficient (r) | Guide & Examples. Scribbr. https://www.scribbr.com/statistics/pearson-correlation-coefficient/
Xu, M., Jin, J., Wang, G., Segers, A., Deng, T., & Lin, H. X. (2021). Machine learning based bias correction for numerical chemical transport models. Atmospheric Environment, 248(January), 118022. https://doi.org/10.1016/j.atmosenv.2020.118022
Zulistyawan, K. A., Virgianto, R. H., & Wicaksono, N. R. W. (2024). SO2 Dispersion Simulation During Mount Merapi Eruption Using WRF-Chem Model (Case Study on June 21–23, 2020). Dalam H. and H. M. and T. and N. G. A. and B. A. and E. S. Lestari Sopia and Santoso (Ed.), Proceedings of the International Conference on Radioscience, Equatorial Atmospheric Science and Environment and Humanosphere Science (hlm. 1–11). Springer Nature Singapore.
Authors
Aslam, F. M., Sayful Amri, Fadhli Aslama Afghani, & Imawan Mashuri. (2026). Simulasi Dispersi SO2 Saat Letusan Gunung Marapi Menggunakan Model WRF-Chem Studi Kasus Tanggal 3-5 Desember 2023. Jurnal Geografi, Edukasi Dan Lingkungan (JGEL), 10(1), 173–189. https://doi.org/10.22236/jgel.v10i1.18543
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