JDR Vol.14 No.1 pp. 135-150
doi: 10.20965/jdr.2019.p0135


Estimating the Volcanic Ash Fall Rate from the Mount Sinabung Eruption on February 19, 2018 Using Weather Radar

Magfira Syarifuddin*1,†, Satoru Oishi*2, Ratih Indri Hapsari*3, Jiro Shiokawa*4, Hanggar Ganara Mawandha*4, and Masato Iguchi*1

*1Sakurajima Volcano Research Center, Disaster Prevention Research Institute (DPRI), Kyoto University
1722-19 Sakurajima-Yokoyama, Kagoshima 891-1419, Japan

Corresponding Author,

*2Research Centre for Urban Safety and Security, Kobe University, Hyogo, Japan

*3Department of Civil Engineering, State Polytechnic of Malang, Malang, Indonesia

*4Graduate School of Engineering, Kobe University, Hyogo, Japan

July 31, 2018
January 21, 2019
February 1, 2019
volcanic ash, X-MP radar, ash microphysical model, radar remote sensing, volcanic eruption

This paper presents a theoretical method for estimating volcanic ash fall rate from the eruption of Sinabung Volcano on February 19, 2018 using an X-band multi-parameter radar (X-MP radar). The X-MP radar was run in a sectoral range height indicator (SRHI) scan mode for 6° angular range (azimuth of 221°–226°) and at an elevation angle of 7° to 40° angular range. The distance of the radar is approximately 8 km in the Southeastern direction of the vent of Mount Sinabung. Based on a three-dimensional (3-D) image of the radar reflectivity factor, the ash column height was established to be more than 7.7 km, and in-depth information on detectable tephra could be obtained. This paper aims to present the microphysical parameters of volcanic ash measured by X-MP radar, which are the tephra concentration and the fall-out rate. These parameters were calculated in a two-step stepwise approach microphysical model using the scaled gamma distribution. The first step was ash classification based on a set of training data on synthetic ash and its estimated reflectivity factor. Using a naïve Bayesian classification, the measured reflectivity factors from the eruption were classified into the classification model. The second step was estimating the volcanic ash concentration and the fall-out rate by power-law function. The model estimated a maximum of approximately 12.9 g·m-3 of ash concentration from the coarse ash class (mean diameter Dn= 0.1 mm) and a minimum of approximately 0.8 megatons of volcanic ash mass accumulation from the eruption.

Cite this article as:
M. Syarifuddin, S. Oishi, R. Hapsari, J. Shiokawa, H. Mawandha, and M. Iguchi, “Estimating the Volcanic Ash Fall Rate from the Mount Sinabung Eruption on February 19, 2018 Using Weather Radar,” J. Disaster Res., Vol.14, No.1, pp. 135-150, 2019.
Data files:
  1. [1] M. Hendrasto, Surono, A. Budianto, Kristianto, H. Triastuty, N. Haerani, A. Basuki, Y. Suparman, S. Primulyana, O. Prambada, A. Loeqman, N. Indrastuti, A. S. Andreas, U. Rosadi, S. Adi, M. Iguchi, T. Ohkura, S. Nakada, and M. Yoshimoto, “Evaluation of volcanic activity at Sinabung Volcano, after more than 400 years of quiet,” J. Disaster Res., Vol.71, No.1, pp. 37-47, 2012.
  2. [2] AHA Center, “Mount Sinabung, Indonesia 2018 eruption and update – Flash update No.01,” [accessed January 21, 2019]
  3. [3] F. S. Marzano, E. Picciotti, M. Montopolli, and G. Vulpiani, “Inside volcanic clouds – Remote sensing of ash plumes using microwave weather radars,” Bull. Am. Met. Soc., Vol.94, pp. 1567-1586, 2013.
  4. [4] A. J. Prata and C. Bernardo, “Retrieval of volcanic ash particle size, mass and optical depth from a ground-based thermal infrared camera,” J. Vol.Geo. Res., Vol.186, pp. 91-107, 2009.
  5. [5] W. I. Rose, G. J. S. Bluth, and G. G. J. Ernst, “Integrating retrievals of volcanic cloud ashcharacteristics from satellite remote sensors-A summary,” Philos. Trans. R. Soc. London A, Math, Phys. Sci., Vol.358, No.1770, pp. 1585-1606, 2000.
  6. [6] S. Wen and W. I. Rose, “Retrieval of sizes and total masses of particles in volcanic clouds using AVHRRbands 4 and 5,” J. Geophys. Res. Lett., Vol.26, No.22, pp. 3389-3392, 1999.
  7. [7] D. M. Harris and W. I. Rose, “Estimating particle sizes, concentrations, and total mass of ash in volcanic clouds using weather radar,” J. Geophys. Res, Vol.88, No.C15, pp. 10969-10983, 1983.
  8. [8] W. I. Rose, D. Delene, D. Scheneider, G. Bluth, A. Krueger, I. Sprod, C. McKee, H. Davies, and G. Ernst, “Ice in the 1994 Rabaul eruption cloud: Implications for volcano hazard and atmospheric effects,” Nature, Vol.375, No.6531, pp. 477-479, 1995.
  9. [9] M. Maki and R. J. Doviak, “Volcanic ash size distribution determined by weather radar,” Proc. IGARSS, Sydney, Australia, Jul.9-13, pp. 1810-1811, 2001.
  10. [10] F. S. Marzano, G. Vulpiani, and W. I. Rose, “Microphysical characterization of microwave radar reflectivity due to volcanic ash clouds,” IEEE Trans. Geosci. Remote Sen., Vol.44, No.2, pp. 313-327, 2006.
  11. [11] F. S. Marzano and G. Vulpiani, “Volcanic ash cloud retrieval by ground-based microwave weather radar,” IEEE Trans. Geosci. Remote Sen., Vol.44, No.11, pp. 3235-3246, 2006.
  12. [12] G. Dubosclard, R. Cordesses, P. Alard, C. Hervier, M. Coltelli, and J. Kornprobst, “First testing of a volcano Doppler radar (Voldorad) at Mt. Etna,” J. Geophys. Res., Vol.26, No.22, pp. 3389-3392, 1999.
  13. [13] P. J. Speirs and D. A. Robertson, “Measurement of airborne volcanic ash using millimeter-wave radars,” 35th Conf. on Radar Meteorology, 2011.
  14. [14] S. G. Park, V. N. Bringi, V. Chandrasekar, M. Maki, and K. Iwanami, “Correction of radar reflectivity and differential reflectivity for rain reflectivity for rain Attenuation at X band: Part I: Theoretical and Empirical Basis,” J. Atmos. Ocean Tech., Vol.22, pp. 1621-1631, DOI:10.1175/JTECH1803.1, 2005.
  15. [15] S. Oishi, M. Iida, M. Muranishi, M. Ogawa, R. I. Hapsari, and M. Iguchi, “Mechanism of volcanic tephra falling detected by X-band multi parameter radar,” J. Disaster Res., Vol.11, No.1, pp. 43-52, 2016.
  16. [16] L. Wilson, “Explosive volcanic eruptions – II: The atmospheric trajectories of pyroclasts,” Geophys, J.R. Astron. Soc., Vol.30, No.2, pp. 381-392, 1972.
  17. [17] S. Fukao and K. Hamazu, “Radar for Meteorological and Atmospheric Observation,” pp. 196-200, Springer, Japan, 2014.
  18. [18] The Watchers,” Massive eruption at Sinabung volcano, ash to 16.7 km (55000 feet) a.s.l,” [accessed July 28, 2018]
  19. [19] Global Volcanism Program, “Report on Sinabung (Indonesia),” S. K. Sennert (ed.), Weekly Volcanic Activity Report, 14 February-20 February 2018, Smithsonian Institution and US Geological Survey, 2018. [accessed July 28, 2018]
  20. [20] F. T. Ulaby, R. K. Moore, and A. K. Fung, “Microwave Remote Sensing Volume 1: Fundamentals and Radiometry,” Reading, MA: Addison-Wesley, 1981.
  21. [21] D. R. McCulloch, J. Lawry, M. A. Rico-Ramirez, and I. D. Cluckie, “Detecting bright band using AI techniques in radar hydrology,” Remote Sensing for Environmental Monitoring and Change Detection (Proc. of Symp. HS3007 at IUGG2007, Perugia), IAHS publ. 316, pp. 37-46, 2007.
  22. [22] G. Wen, A. Protat, P. T. May, W. Moran, and M. Dixon, “A Cluster-Based Method for Hydrometeor Classification Using Polarimetric Variables Part II: Classification,” J. Atmos. Ocean Tech., Vol.33, pp. 45-60, DOI:10.1175/ JTECH-D-14-00084, 2016.
  23. [23] F. Marzano, D. Scranari, M. Montopoli, and G. Vulpiani, “Supervised Classification and Estimation of Hydrometeors From C-Band Dual-Polarized Radars: A Bayesian Approach, IEEE Trans. Geosci. Remote Sen., Vol.46, No.1, 2008.
  24. [24] G. Veitch and A. W. Woods, “Particle aggregation in volcanic eruption columns,” J. Geophys. Res., Vol.106, No.B11, pp. 26425-26441, 2001.
  25. [25] V. M. Zobin, “Seismic Signals Associated with Pyroclastic Flows, Rockfalls, and Lahars,” V. M. Zobins (ed.), Introduction to Volcanic Seismology (Second Edition), Elsevier, pp. 261-293, 2012
  26. [26] L. G. Mastin, “A multidisciplinary effort to assign realistic source parameters to models of volcanic ash-cloud transport and dispersion during eruptions,” J. Volcanol. Geotherm. Res., Vol.186, pp. 10-21, 2009.
  27. [27] J. L. Heffter and B. J. B. Stunder, “Volcanic Ash Forecast Transport and Dispersion (VAFTAD) model,” Weather Forecast., Vol.8, pp. 534-541, 1993.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Feb. 19, 2019