Improved space borne detection of volcanic ash for real-time monitoring using 3-Band method

Guéhenneux, Yannick; Gouhier, Mathieu; Labazuy, Philippe

doi:10.1016/j.jvolgeores.2015.01.005

Cited by 33 publications

(39 citation statements)

References 55 publications

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“…For the separation between aerosol and ice clouds by IR nadir measurements spectral windows around 8.5, 11, and 12 µm (1176, 909, 833 cm −1 , respectively) are employed (Ackerman, 1997; Guehenneux et al, 2015). For these windows the optical properties of ice differ most strongly from aerosol such as volcanic ash, soil-derived aerosol, and sulfate aerosol (Ackerman, 1997).…”

Section: Ice Cloud Filtering 321 Window Selectionmentioning

confidence: 99%

“…The aerosol measurements from IR nadir instruments mainly focus on volcanic ash (e.g. Prata, 1989a;Guehenneux et al, 2015), mineral dust (e.g. Peyridieu et al, 2010;Klüser et al, 2011;Klueser et al, 2012;Liu et al, 2013), and smoke (Fromm et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…There are several methods available to detect aerosol, filter out ice clouds, and classify aerosol types. These methods comprise the split window/reverse absorption technique for volcanic ash (Prata, 1989a, b;Rose et al, 2013), trispectral approaches for volcanic ash and mineral dust (Ackerman et al, 1990;Ackerman, 1997;Guehenneux et al, 2015), and multispectral approaches for hyperspectral instruments (Gangale et al, 2010;Clarisse et al, 2010Clarisse et al, , 2013. Although the established methods are used for operational data products they are still subject to improvements (Guehenneux et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…These methods comprise the split window/reverse absorption technique for volcanic ash (Prata, 1989a, b;Rose et al, 2013), trispectral approaches for volcanic ash and mineral dust (Ackerman et al, 1990;Ackerman, 1997;Guehenneux et al, 2015), and multispectral approaches for hyperspectral instruments (Gangale et al, 2010;Clarisse et al, 2010Clarisse et al, , 2013. Although the established methods are used for operational data products they are still subject to improvements (Guehenneux et al, 2015). The capability of detecting sulfate aerosol with IR nadir measurements has been demonstrated for band measurements (Baran et al, 1993;Ackerman, 1997) and for hyperspectral instruments Gangale et al, 2010;.…”

Section: Introductionmentioning

confidence: 99%

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Infrared limb emission measurements of aerosol in the troposphere and stratosphere

et al. 2016

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Abstract. Altitude-resolved aerosol detection in the upper troposphere and lower stratosphere (UTLS) is a challenging task for remote sensing instruments. Infrared limb emission measurements provide vertically resolved global measurements at day-and nighttime in the UTLS. For high-spectralresolution infrared limb instruments we present here a new method to detect aerosol and separate between ice and nonice particles. The method is based on an improved aerosolcloud index that identifies infrared limb emission spectra affected by non-ice aerosol or ice clouds. For the discrimination between non-ice aerosol and ice clouds we employed brightness temperature difference correlations. The discrimination thresholds for this method were derived from radiative transfer simulations (including scattering) and Michel-

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Section: Ice Cloud Filtering 321 Window Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Infrared limb emission measurements of aerosol in the troposphere and stratosphere

et al. 2016

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“…The split window technique identifies airborne ash by means of a fixed threshold test applied to difference of Brightness Temperatures (BT) measured at the aforementioned wavelengths, i.e., BT 11 − BT 12 [29]. Advanced detection methods, minimizing the impact of atmospheric water vapor on the above-mentioned brightness temperature difference (BTD) or analyzing signals measured in other spectral bands such as MIR (Medium Infrared) and/or VIS (Visible) ones, have shown a higher efficiency in identifying ash clouds (e.g., [30][31][32][33][34][35][36][37][38]). RST ASH [16] is an ash detection method, based on the Robust Satellite Technique (RST) multi-temporal approach [39], running on both polar [14,15,40] and geostationary [17] satellite data.…”

Section: Methodsmentioning

confidence: 99%

Monitoring the Agung (Indonesia) Ash Plume of November 2017 by Means of Infrared Himawari 8 Data

et al. 2018

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Abstract:The Agung volcano (Bali; Indonesia) erupted in later November 2017 after several years of quiescence. Because of ash emissions, hundreds of flights were cancelled, causing an important air traffic disruption in Indonesia. We investigate those ash emissions from space by applying the RST ASH algorithm for the first time to Himawari-8 data and using an ad hoc implementation scheme to reduce the time of the elaboration processes. Himawari-8 is a new generation Japanese geostationary meteorological satellite, whose AHI (Advanced Himawari Imager) sensor offers improved features, in terms of spectral, spatial and temporal resolution, in comparison with the previous imagers of the MTSAT (Multi-Functional Transport Satellite) series. Those features should guarantee further improvements in monitoring rapidly evolving weather/environmental phenomena. Results of this work show that RST ASH was capable of successfully detecting and tracking the Agung ash plume, despite some limitations (e.g., underestimation of ash coverage under certain conditions; generation of residual artefacts). Moreover, estimates of ash cloud-top height indicate that the monitored plume extended up to an altitude of about 9.3 km above sea level during the period 25 November at 21:10 UTC-26 November at 00:50 UTC. The study demonstrates that RST ASH may give a useful contribution for the operational monitoring of ash clouds over East Asia and the Western Pacific region, well exploiting the 10 min temporal resolution and the spectral features of the Himawari-8 data.

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Impact of the lateral blast on the spatial pattern and grain size characteristics of the 18 May 1980 Mount St. Helens fallout deposit

et al. 2015

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The 18 May 1980 eruption of Mount St. Helens started with a lateral blast that fed a pyroclastic surge, which then uplifted to form a co‐blast plume. Thirty minutes later, Plinian activity started at the vent and fluctuated in intensity for ~9 h. The resulting fallout deposit, documented to > 600 km from vent, presents some striking features: (1) displacement of the overall deposit to the north of the vent, (2) a secondary thickness and mass maximum at ~300 km from vent, (3) a total grain size distribution dominated by fine ash (62 wt % of the deposit < 63 µm), and (4) individual grain size distributions that vary dramatically in the crosswind direction from strongly bimodal in the south to skewed unimodal in the north. Results from a new deconvolution of the individual grain size distributions show that they are a combination of a coarse subpopulation that decreases in size with distance from vent and a constant fine subpopulation with a mean of ∼15 µm. Relative proportions of each subpopulation vary asymmetrically in the crosswind directions, with the fine subpopulation preponderant toward the north and the coarse one dominating the south of the deposit, both reach their absolute maxima in mass on the deposit axis. Componentry analyses of selected samples show that blast‐derived material is greatly enriched toward the north of the deposit. These results indicate that the co‐blast plume dispersed fine‐grained material over great distances and dominated the fine subpopulation. Comparison with reanalysis data of atmospheric wind fields and satellite images of the spreading ash cloud suggests contrasting ash transport and depositional processes for the (early) co‐blast plume and the (later) vent‐derived Plinian plumes. The co‐blast plume is displaced to the north; it had a high overshoot height, and eastward dispersion via strong winds low in the stratosphere (~10–15 km). The Plinian plumes were lower and dispersed most of the material to the southeast as the direction of high‐velocity winds shifted just before the late climactic Plinian eruptive phase. Fine ash (fine subpopulation) was deposited continuously throughout the deposit, with an increase of sedimentation rate ~300 km from the vent where there is a secondary maximum in the deposit mass and thickness. Fine ash probably settled by a combination of enhanced sedimentation mechanisms, including not only aggregation but also gravitational convective instabilities of cloud base, hydrometeor formation and destruction, and entrainment of small particles by larger ones. Finally, we show that half of the deposit (by mass) in the medial area was deposited by the co‐blast plume, and that a significant proportion of the Mount St. Helens fallout deposit is nonjuvenile, which has implications for the magmatic budget of this eruption.

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Improved space borne detection of volcanic ash for real-time monitoring using 3-Band method

Cited by 33 publications

References 55 publications

Infrared limb emission measurements of aerosol in the troposphere and stratosphere

Infrared limb emission measurements of aerosol in the troposphere and stratosphere

Monitoring the Agung (Indonesia) Ash Plume of November 2017 by Means of Infrared Himawari 8 Data

Impact of the lateral blast on the spatial pattern and grain size characteristics of the 18 May 1980 Mount St. Helens fallout deposit

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