Open Access

Using Himawari-8, estimation of SO2 cloud altitude at Aso volcano eruption, on October 8, 2016

Earth, Planets and Space201870:19

Received: 7 September 2017

Accepted: 29 January 2018

Published: 6 February 2018


It is vital to detect volcanic plumes as soon as possible for volcanic hazard mitigation such as aviation safety and the life of residents. Himawari-8, the Japan Meteorological Agency’s (JMA’s) geostationary meteorological satellite, has high spatial resolution and sixteen observation bands including the 8.6 μm band to detect sulfur dioxide (SO2). Therefore, Ash RGB composite images (RED: brightness temperature (BT) difference between 12.4 and 10.4 μm, GREEN: BT difference between 10.4 and 8.6 μm, BLUE: 10.4 μm) discriminate SO2 clouds and volcanic ash clouds from meteorological clouds. Since the Himawari-8 has also high temporal resolution, the real-time monitoring of ash and SO2 clouds is of great use. A phreatomagmatic eruption of Aso volcano in Kyushu, Japan, occurred at 01:46 JST on October 8, 2016. For this eruption, the Ash RGB could detect SO2 cloud from Aso volcano immediately after the eruption and track it even 12 h after. In this case, the Ash RGB images every 2.5 min could clearly detect the SO2 cloud that conventional images such as infrared and split window could not detect sufficiently. Furthermore, we could estimate the height of the SO2 cloud by comparing the Ash RGB images and simulations of the JMA Global Atmospheric Transport Model with a variety of height parameters. As a result of comparison, the top and bottom height of the SO2 cloud emitted from the eruption was estimated as 7 and 13–14 km, respectively. Assuming the plume height was 13–14 km and eruption duration was 160–220 s (as estimated by seismic observation), the total emission mass of volcanic ash from the eruption was estimated as 6.1–11.8 × 108 kg, which is relatively consistent with 6.0–6.5 × 108 kg from field survey.


Ash RGBHimawari-8Atmospheric transport modelSO2 Aso volcano


In an eruption event, in order to estimate the amount of damage promptly, it is important to know the eruption source parameters such as mass eruption rate, plume height and eruption duration. For example, the Japan Meteorological Agency (JMA) operates the Volcanic Ash Fall Forecast (VAFF) system to issue forecasts of areas where ash or lapilli fall is expected around a volcanic eruption (Hasegawa et al. 2015). In this operation, the JMA Regional Atmospheric Transport Model (JMA-RATM) uses initial conditions including total eruption mass which is estimated using the relationship between the total mass and the top height of the plume and eruption duration. In the Volcanic Ash Advisory Center (VAAC) operation, after an eruption, Volcanic Ash Advisories (VAA) are issued at 6-h intervals (normally at 00, 06, 12 and 18 UTC) for as long as an ash cloud is identified in satellite imagery (Tokyo VAAC 2016). For the forecast of volcanic ash by the JMA Global Atmospheric Transport Model (JMA-GATM) in the Tokyo VAAC of the JMA, the top height of ash clouds is an essential parameter.

We can estimate total mass using the relationship between a mass eruption rate and a plume height (e.g., Mastin et al. 2009). However, in some cases, it is not easy to estimate the top height of plumes because meteorological clouds obscure remote cameras and satellite observation. Since weather radar observation is much more sensitive to large particles than small particles such as fine ash or SO2 gas which are found around the top of the plumes, there are cases in which radar is not useful for estimation of plume height. However, the total eruption mass is sensitive to the top height, and its accurate estimation is indispensable. In addition, for disaster prevention, promptness is vital. Especially, for aviation safety, timely estimation is of great importance. In this context, the Himawari-8 satellite allows very timely volcanic plume monitoring.

Himawari-8, which is a new geostationary meteorological satellite, was put into operation on July 7, 2015 (Bessho et al. 2016). It has significantly advanced features, having sixteen observation bands compared to five in its predecessor. The spatial resolution is 2 km for infrared bands. Furthermore, it has high observation frequencies. Full disk images are taken every 10 min, Japan area images are taken every 2.5 min, and landmark area images are taken every 0.5 min.

For the detection and analysis of volcanic eruptions, one of the most strikingly enhanced points is that the 16 observation bands include new bands #10 (7.3 μm) and #11(8.6 μm) which have sensitivity for SO2 gas (Watson et al. 2004). Ash RGB (one of the visualization schemes of satellite data; see the “Ash RGB” section for details) using band #11, #13 (10.4 μm) and #15 (12.4 μm) are tricolored satellite images (RGB image) that can discriminate SO2 clouds and ash clouds from meteorological clouds. The predecessor of Himawari-8 was the Multi-functional Transport Satellite-2 (MTSAT-2, also called Himawari-7), which was also used for the detection and analysis of ash clouds. MTSAT-2 had no bands sensitive to SO2 gas, so that SO2 clouds could not be detected, and infrared (IR, 10.8 μm) and a split window (10.8–12.0 μm) were mainly used to discriminate volcanic ash clouds from meteorological clouds (Prata 1989a, b).

In the Japan area, there are other satellites and sophisticated retrieval schemes which have been developed and are available for detection or analysis of volcanic ash or SO2 clouds. Low Earth orbit satellites provide high-spectral resolution data (Cooke et al. 2014). For example, Yang et al. (2007) developed retrieval of SO2 from the Ozone Monitoring Instrument (OMI). However, since they are Earth orbit satellites, there are very few chances of observations of ash clouds immediately after an eruption. Geosynchronous satellites provide high temporal resolution allowing detection in near real time (Francis et al. 2012). For geosynchronous satellites, a retrieval algorithm of physical properties of ash cloud (e.g., ash cloud height, optical depth, effective particle radius and mass loading) was developed (Pavolonis and Sieglaff 2010).

On the other hand, the Ash RGB is composite imagery and provides no quantitative information such as the amount of ash or SO2 in the column and no vertical profile such as the top height of ash or SO2 clouds. However, because flow of SO2 clouds depends on the wind field, SO2 clouds at each altitude flow with different directions and speeds. In this sense, a time series of the Ash RGB should include information of the vertical profile in the atmosphere with vertical wind shear. Therefore, it is possible that vertical information of SO2 clouds can be obtained from a time series of the Ash RGB and wind field.

In this study, we applied the Ash RGB for the case of SO2 cloud of the 2016 Aso volcano eruption. The Ash RGB could clearly track the SO2 cloud from Aso volcano. Furthermore, we estimated the altitude of the SO2 cloud by comparing the Ash RGB images and the SO2 numerical simulation results using the JMA-GATM which has processes such as wind advection, gravitational settling, turbulent diffusion and wet/dry deposition. This model is used for volcanic ash forecasts for the safety of aviation services in the Tokyo VAAC operation. Volcanic ash falls by gravitational settling, while the gravitational effect is negligible for SO2 clouds.

For the SO2 simulation, we executed the JMA-GATM without gravity settling, in which tracers act as SO2 cloud. For the estimation of the altitude of SO2 cloud, we tried a variety of vertical profiles of SO2 tracers and sought the best initial vertical profile of SO2 cloud which is consistent with the two-dimensional spread estimated by the Ash RGB images from Himawari-8. In addition, considering pilots’ reports and OMI, a limitation of the Ash RGB for the thin SO2 region was inferred.

Aso volcano

In Japan, there are 111 active volcanos which have erupted within 10,000 years or which have vigorous fumarolic activity. Of these, 50 volcanos were selected by the Coordinating Committee for Prediction of Volcanic Eruption and are constantly monitored by seismometers, tiltmeters, infrasound microphones, remote cameras, etc. (Yamasato et al. 2013). Aso volcano in Kyushu, Japan (Fig. 1) is one of these.
Fig. 1

Map of the Aso volcano. The large triangle indicates Aso volcano. The smaller triangles indicate other volcanos

Aso volcano, including Aso caldera and post-caldera central cones, is one of the most active volcanos in Japan. Nakadake, one of the central cones, is the only active cone and consists of seven craterlets. Of these, only one crater (called “First Crater”) has been active in the past 80 years (JMA and VSJ 2013). Most recently, several ash emissions occurred in 2003–2005, and volcanic gases and ash were emitted in 2014–2016 (e.g., Miyabuchi et al. 2008).

At Nakadake, a phreatomagmatic eruption occurred at 01:46 JST on October 8, 2016. Prior to this eruption, the last explosive eruption including large infrasonic waves was January 26, 1980. A seismometer showed that the duration of the eruption was approximately 160–220 s (Fig. 2) (Shimbori 2017).
Fig. 2

The volcanic earthquake (vertical component) as measured by a seismogram from Aso volcano eruption, 8 Oct., 2016, 01:46:30–01:50:30JST. The observation point is located approximately 1.2 km west from the vent. The black arrow indicates the eruption time (around 01:46:36JST)

For the 2016 eruption, because meteorological cloud obscured the remote cameras, the top height of volcanic plumes could not be estimated immediately after the eruption. The Tokyo VAAC issued a VAA with the top height of the plume as 39,000 feet estimated using Infrared (band #13) of Himawari-8 (Tokyo VAAC 2016). In this eruption, ash and lapilli fall spread several kilometers, mainly to the northeast by the ambient wind. For example, lapilli which fell approximately 4.5 km from the vent broke windowpanes, and lapilli which fell approximately 6.5 km away broke more than 1500 solar panels (Sasaki et al. 2017). Further, there were some other effects such as malfunctions of train signals, changes of routes and delays of airplanes, ash fall on crops and damage to agricultural greenhouses. In addition, electricity was cut to 29,000 households around the volcano, and the power outage also caused some disruptions to the water supply.


When a volcanic eruption occurs, we need to know and understand the details of the eruption as soon as possible for estimating the magnitude of eruption and damage around the volcano, and for predictions such as ash fall forecasts for residents and airborne ash forecasts for aviation safety. For this purpose, we can make the most of Himawari-8. Enhancement of spatial resolution and observation frequencies are very useful for analysis and monitoring of eruption plumes. Compared to MTSAT-2, Himawari-8′s most enhanced point for monitoring eruption plumes is the addition of bands #10 and #11 which are sensitive to SO2 gas. These bands enable us to detect “SO2 rich” plumes which are overlooked by using conventional images such as IR (band #13) and a split window (band #13–#15) for Himawari-8.

In this study, the Ash RGB is based on the report of the Meteorological Satellite Center (2015). It is composed of 3 beams: the RED beam is correlated with the brightness temperature (BT) difference (− 4 to 2 [K]) of band #15 and #13, the GREEN beam is correlated with the BT difference (− 4 to 5 [K]) of band #13 and #11, and the BLUE beam is correlated with band #13(208–243 [K]). In the Ash RGB image, the pinkish color corresponds to ash, and the bright green–yellow color corresponds to SO2.

Figure 3 shows the Ash RGB images for Aso volcano in this study. The plume which was released from Aso volcano was identified approximately 10 min after eruption from the Ash RGB, and blown eastward while spreading to the north and south by the wind. Within 1 or 2 h after the eruption, the cloud could be tracked by IR (band #13) or the split window even though it was not clear. However, 3 or 4 h after the eruption, the plume could not be tracked. On the other hand, the Ash RGB could track it clearly 12 h after the eruption (see Fig. 5). The color of the Ash RGB in the cloud region indicated SO2, so that the cloud was presumed to be “SO2 rich”.
Fig. 3

The Ash RGB (upper row), band #13 image (middle row) and split window (band #13–#15) image (bottom row). The left column is 02:45JST (approximately 1 h after eruption), the center column is 04:45JST (approximately 3 h after eruption), and the right column is 06:45JST (approximately 5 h after eruption)

Model description and methodology

The numerical simulation provides forecasting of SO2 clouds by using an initial condition (i.e., initial SO2 distribution for the numerical model). However, the simulation result depends on the accuracy of the initial conditions. If the initial conditions are not set accurately, the numerical simulations will provide an inaccurate forecast. Conversely, initial conditions providing a forecast which is consistent with observations should have realistic initial distribution. In this case, a simulation result using realistic top and bottom height of SO2 clouds for the initial conditions of the model should be consistent with the Ash RGB images.

In this study, the numerical simulations of SO2 clouds are performed by the JMA-GATM which is based on Iwasaki et al. (1998). The JMA-GATM is a Lagrangian model which calculates the time evolution of location of many tracer particles as volcanic ash particles. Each particle’s displacement during 1 time step \(\delta t\) is as follows:
$$x\left( {t + \delta t} \right) = x\left( t \right) + \bar{u} \delta t + \varGamma \sqrt {2K_{\text{h}} \delta t}$$
$$y\left( {t + \delta t} \right) = y\left( t \right) + \bar{v} \delta t + \varGamma \sqrt {2K_{\text{h}} \delta t}$$
$$z\left( {t + \delta t} \right) = z\left( t \right) + \bar{w} \delta t + \mathop \sum \limits_{\delta t'} \varGamma \sqrt {2K_{{{\text{v}} }} \delta t'} - V_{\text{g}} \delta t$$
where \(x\left( t \right),y\left( t \right),z\left( t \right)\) are the locations at the time t, and \(\bar{u}, \bar{v}\) are wind velocities at the tracer location. \(\bar{w}\) is vertical wind which is calculated diagnostically from horizontal divergence of \(\bar{u}, \bar{v}\). The third terms in each equation represent sub-grid scale deviations of horizontal and vertical wind. \(K_{\text{h}} ,\,K_{\text{v}}\) are horizontal and vertical diffusion coefficients, and \(\varGamma\) is random displacement whose statistical distribution takes the Gaussian distribution function with mean 0 and standard deviation 1. \(V_{\text{g}}\) is the terminal fall velocity, which mainly depends on the size of the tracer.

The wind velocities \(\bar{u}, \bar{v}, \bar{w}\) are included in the meteorological field predicted by the Global Spectral Model (JMA-GSM) (JMA 2013) for numerical weather prediction. Horizontal and vertical diffusions are formulated assuming the random walk model, in which the probability density of the displacements is Gaussian distribution with \(\varGamma \sqrt {2K_{\text{h}} \delta t}\) for horizontal diffusion with \(K_{\text{h}}\) = 4.0 × 103 m2/s and \(\varGamma \sqrt {2K_{{{\text{v}} }} \delta t^{\prime } }\) for vertical diffusion. For the vertical diffusion, \(K_{\text{v}}\) is based on Louis et al. (1982), \(\delta t^{\prime }\) is divided into a smaller value than \(\delta t\). Wet and dry deposition processes are included in the JMA-GATM. The tracers are scavenged by the wet/dry deposition process. Actually, wet deposition includes washout (below-cloud scavenging) and rainout (in-cloud scavenging). However, the JMA-GATM includes only washout which scavenges the tracer using precipitation calculated from JMA-GSM. Tracers near the surface are scavenged by dry deposition which calculates deposition velocity from aerodynamic resistance (Kitada et al.1986). The gravitational settling is calculated based on Suzuki (1983).

In this numerical simulation, 10,000 tracers in the JMA-GATM as SO2 tracers are set above Aso volcano as a straight line source from bottom height to top height for 3 min from the eruption time, 01:46JST 8 October 2016 (FT = 0 h), and simulations were done up to 15 h after the eruption. In this simulation, an initial vertical profile of SO2 cloud is used with a bottom height of 2–16 km (every 1 km) and top height 5–17 km (every 1 km), i.e., 2–5, 2–6 km, etc., up to 2–17 km. This was repeated for every new bottom and top height in increments of 1 km; therefore, the final vertical profile was 16–17 km. Considering that the top height is larger than the bottom height, the total number of experiments is 117.

The meteorological fields of the JMA-GSM forecast with an initial time of 21JST October 7, 2016 are used. The meteorological fields such as wind, temperature, pressure and precipitation are taken as grid point values every 3 h (00, 03, 06, 09, 12, 15, 18, 21JST). The time step \(\delta t\) in Eqs. (1)–(3) is 600 [s]. For the location of each tracer at each time step, the meteorological field which is used in the processes is interpolated linearly by time and space. Because tracers in the JMA-GATM simulations have the role of SO2 cloud, the gravitational settling is switched off.

Results of numerical simulations

Representative results of the 117 experiments by the JMA-GATM are shown in Fig. 4. The spread of SO2 cloud in each result significantly depends on the initial vertical profile. For example, for an initial SO2 cloud with an altitude of 2–7 km, the cloud was blown and spread widely from north–northeast to east–northeast from the volcano (upper row in Fig. 4). For an initial SO2 cloud with an altitude of 7–14 km, it was blown and spread more narrowly from east–northeast to east compared to the 2–7 km cloud, but spread north–south (middle row in Fig. 4). For an initial SO2 cloud with an altitude of 14–17 km, we can see that the cloud was blown to the east while spreading in an east–west direction (bottom row in Fig. 4). These differences are caused by wind direction shear and wind speed shear. That is, at the time of eruption, in lower altitudes such as from the surface to 7 km, the wind direction is north–northeast to east–northeast. On the other hand, at altitudes of 7–14 km, the wind direction is east–northeast to east, and at altitudes of 14–17 km, the wind blows eastward with wind speed shear. These differences between directions of SO2 cloud at each altitude were seen 20–30 min after eruption and later.
Fig. 4

Results of the SO2 simulations by JMA-GATM. Upper row: simulation from initial altitude of SO2 at 2–7 km. Middle row: simulation from initial altitude of SO2 at 7–14 km. Bottom row: simulation from initial altitude of SO2 at 14–17 km. The left column is approximately 1 h after eruption (02:46JST). The center column is approximately 3 h after eruption (04:46JST). The right column is approximately 5 h after eruption (06:46JST). The color bar indicates the height [m] of SO2 tracers


Comparing the Ash RGB and the result of the model simulations, SO2 vertical profiles with 7–13 and 7–14 km altitudes seem to be most likely. The simulation results show that SO2 cloud under 7 km was blown to the northeast unlike distribution indicated from the Ash RGB (upper row of Fig. 3). However, actually thin SO2 cloud seemed to be blown under 7 km from other observations (to be discussed below). For the simulations with SO2 cloud over 14 km, the south end of the cloud was spreading to the east and west by wind speed shear unlike SO2 cloud deduced from the Ash RGB. Because the SO2 cloud spread at 7–13 and 7–14 km is very similar, we could not discriminate the top height of 13–14 km.

In the simulations, the north end of the SO2 cloud reached Kanto, Japan, as did SO2 cloud observed by the Ash RGB 12 h after eruption. However, in the south of approximately 35° north latitude, the simulation is not similar to the SO2 cloud of the Ash RGB. The SO2 cloud of the Ash RGB is located west of that of the simulation. This difference is possibly caused by the wind of the atmospheric fields.

For further understanding of the results of our simulations, it must be noted that there is uncertainty of the horizontal diffusion coefficient. Because the coefficient depends on the resolution of the meteorological numerical model (Iwasaki et al. 1998), it is difficult to find a universal value. In our study, we determined the coefficient by comparing the Ash RGB and results with some ordered value. However, for a more detailed analysis such as quantitative comparison of ash fall amount around the volcano, the coefficient should be determined more carefully (e.g., Tanaka and Yamamoto 2002).

Comparing the Ash RGB image and the OMI measurements at approximately 12 h after eruption, they are very similar in spread except for the area around the north end of the SO2 cloud (Fig. 5). That is, OMI detected a more northern region (~ 37° north) of SO2 than the Ash RGB (~ 35–36° north). For the simulation of an initial profile with an altitude of 5–14 km, the SO2 cloud spread to the north region like the observation of OMI, unlike the Ash RGB. The locations of pilots’ reports which noted the smell of SO2 are consistent with the simulation of an initial profile with an altitude of 5–14 km (height errors are approximately ± 2 km, except for point h in Fig. 5) and OMI. Therefore, it seems the Ash RGB could not detect the thin SO2 region under an altitude of 7 km.
Fig. 5

The two left figures are the time series (FT = 1(02:46JST)-FT13(14:46JST)) of the JMA-GATM simulations and pilots’ reports. (The upper figure is the result from an initial altitude of SO2 at 5–14 km. The bottom figure is the result from an initial altitude of SO2 at 7–14 km.) The lettered points are pilots’ reports including “VA SMELL” or “SULFUR” as follows: a;06:00JST(FL270–320), b;09:16JST(FL210), c;09:34JST(FL210–240), d;09:50JST(FL180), e;10:20JST(FL190), ff’;10:28JST(FL090), g;10:39JST(FL290), h;13:32JST(FL090–100), xx’;06:08JST(FL370–390), y;08:31JST(FL170), zz’;10:40JST(FL360). FL is flight level (FL100 = 10,000 feet). The right upper figure is SO2 observation from Aura/OMI, 00:35–02:17JST (NASA-GFSC et al. 2016). The right bottom figure is the Ash RGB at 12:46JST

We can calculate total mass using the duration of eruption of 160–220 s and a top height 13–14 km using the relationship \(H = 2.00 \times \dot{V}^{0.241}\) (Mastin et al. 2009), where H is the top height (km) of the eruption plume, and \(\dot{V}\) is the volumetric flow rate (m3 dense-rock equivalent (DRE) per second). Assuming magma density is 2500 kg/m3, the total mass of the eruption is 6.1–11.8 × 108 kg, which is consistent with field survey 6.0–6.5 × 108 kg (Miyabuchi et al. 2017). In addition, the current study estimation of a top height of 13–14 km is also consistent with the JMA-RATM simulation (Shimbori 2017) that showed volcanic ash fall forecast calculated with a top height of 13.1 km is most consistent with ash fall distribution observation. Therefore, the current simulation results are consistent with both field survey and previous simulation results.


A phreatomagmatic eruption of Aso volcano in Kyushu, Japan, occurred at 01:46 JST October 8, 2016. The Ash RGB images using three observation bands of Himawari-8, including the bands sensitive to SO2, could detect an “SO2 rich” cloud which could not be detected by conventional IR (band #13) or split window images more than 12 h after the eruption.

In this study, we estimated the altitude at which the SO2 cloud was blown by comparing the Ash RGB images and the simulation by the JMA-GATM. It is estimated that the height of the SO2 cloud was 7–13 or 7–14 km. OMI measurements and pilots’ reports suggest that the Ash RGB images could not detect thin SO2 cloud, and thin SO2 cloud existed at the altitude of 5–7 km.

Using a top height of 13–14 km and an eruption duration of 160–220 s from the volcanic earthquake, the total emission mass of the eruption is estimated as 6.1–11.8 × 108 kg. It is relatively consistent with 6.0–6.5 × 108 kg from field survey.



brightness temperature


Japan Meteorological Agency


JMA Global Atmospheric Transport Model


JMA Regional Atmospheric Transport Model


Ozone Monitoring Instrument


Volcanic Ash Advisory


Authors’ contributions

KI performed the SO2 simulations and comparison between observation and simulation results. YH implemented the algorithm of the Ash RGB from Himawari-8 and analyzed them. TS gathered the observation data such as volcanic earthquake and pilots’ reports and analyzed them. All authors read and approved the final manuscript.


The numerical simulations in this study were performed using a Fujitsu FX100 supercomputer system at the Meteorological Research Institute.

Authors’ information

Kensuke Ishii is a researcher at the Meteorological Research Institute. Yuta Hayashi is an examination officer at the National Personnel Authority. Toshiki Shimbori is a senior researcher at the Meteorological Research Institute.

Competing interests

The authors declare that they have no competing interests.

Ethics approval and consent to participate

Not applicable.

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Authors’ Affiliations

Volcanology Research Department, Meteorological Research Institute, Tsukuba, Japan
National Personnel Authority, Chiyoda-ku, Japan


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