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The underwater Hunga Tonga-Hunga Ha’apai volcano erupted in the early hours of 15th January 2022 and injected volcanic gases and aerosols to over 50 km altitude. In this talk, we synthesise satellite, ground-based, in situ and radiosonde observations of the eruption to investigate the emissions, the horizontal and vertical dispersion, and the strength of the stratospheric aerosol and water vapour perturbations in the initial six months after the eruption. The aerosol plume was initially formed of two clouds at 30 and 28 km, mostly composed of submicron-sized sulfate particles, without ash, which is washed out within the first day following the eruption. The large amount of injected water vapour led to a fast conversion of SO2 to sulphate aerosols. We find that the Hunga Tonga-Hunga Ha’apai eruption produced the largest global perturbation of stratospheric aerosols since the Pinatubo eruption in 1991 and the largest perturbation of stratospheric water vapour observed in the satellite era. Then, using offline radiative transfer calculations driven by aerosol and water vapour observations, we quantify the net radiative impact across the two species. Immediately after the eruption, water vapour radiative cooling dominated the local stratospheric heating/cooling rates, producing a spectacular radiatively-driven plume descent of several kilometres. At the top-of-the-atmosphere and surface, volcanic aerosol cooling dominated the radiative forcing during this first dispersion phase. However, after two weeks, due to dilution, water vapour heating started to dominate the top-of-the-atmosphere radiative forcing, leading to a net warming of the climate system. On a longer timescale, sulphate particles, undergoing hygroscopic growth and coagulation, sediment and gradually separate from the moisture anomaly entrained in the ascending branch Brewer–Dobson circulation. This is the first time a warming effect on the climate system has been linked to volcanic eruptions, which usually produce a transient cooling.

We use a combination of seven space-borne instruments to study the unprecedented stratospheric plume after the Tonga eruption of 15 January 2022.The aerosol plume was initially formed of two clouds at 30 and 28 km mostly composed of submicron-sized sulfate particles, without ashes washed-out within the first day following the eruption. The large amount of injected water vapour led to a fast conversion of SO2 to sulfate aerosols and induced a descent of the plume to 24-26 km over the first 3 weeks by radiative cooling. Whereas SO2 has returned to background levels by the end of January, volcanic sulfates and water still persisted after 6 months, mainly confined between 35°S and 20°N until June due to the zonal symmetry of the summer stratospheric circulation at 22-26 km. Sulfate particles, undergoing hygroscopic growth and coagulation, sediment and gradually separate from the moisture anomaly entrained in the ascending branch Brewer-Dobson circulation. Sulfate aerosol optical depths derived from the IASI infrared sounder show that during the first two months the aerosol plume was not simply diluted and dispersed passively but rather organized in concentrated patches. Space-borne lidar winds suggest that those structures, generated by shear-induced instabilities, were associated with vorticity anomalies that may have enhanced the duration and impact of the plume.Reference: ACP Highlight, DOI: 10.5194/acp-22-14957-2022

We use a combination of spaceborne instruments to study the unprecedented stratospheric plume after the Tonga eruption of 15 January 2022. The aerosol plume was initially formed of two clouds at 30 and 28 km, mostly composed of submicron-sized sulfate particles, without ash, which is washed out within the first day following the eruption. The large amount of injected water vapour led to a fast conversion of SO2 to sulfate aerosols and induced a descent of the plume to 24–26 km over the first 3 weeks by radiative cooling. Whereas SO2 returned to background levels by the end of January, volcanic sulfates and water still persisted after 6 months, mainly confined between 35∘ S and 20∘ N until June due to the zonal symmetry of the summer stratospheric circulation at 22–26 km. Sulfate particles, undergoing hygroscopic growth and coagulation, sediment and gradually separate from the moisture anomaly entrained in the ascending branch Brewer–Dobson circulation. Sulfate aerosol optical depths derived from the IASI (Infrared Atmospheric Sounding Interferometer) infrared sounder show that during the first 2 months, the aerosol plume was not simply diluted and dispersed passively but rather organized in concentrated patches. Space-borne lidar winds suggest that those structures, generated by shear-induced instabilities, are associated with vorticity anomalies that may have enhanced the duration and impact of the plume.

International audience; Following the Hunga Tonga eruption (20.6°S, 175.4°W, mid-January 2022), we present a balloon-borne characterization of the stratospheric aerosol plume one week after its injection (on 23 and 26 January 2022, La Réunion island at 21.1°S, 55.3°E). Satellite observations show that flight (a) took place during the overpass of a denser plume of sulfate aerosols (SA) compared to a more diluted plume during flight. (b) Observations show that the sampled plumes (at around 22, 25 and 19 km altitude, respectively) consist exclusively of very small particles (with radius

We use a combination of spaceborne instruments to study the unprecedented stratospheric plume after the Tonga eruption of 15 January 2022. The aerosol plume was initially formed of two clouds at 30 and 28 km, mostly composed of submicron-sized sulfate particles, without ash, which is washed out within the first day following the eruption. The large amount of injected water vapour led to a fast conversion of SO2 to sulfate aerosols and induced a descent of the plume to 24–26 km over the first 3 weeks by radiative cooling. Whereas SO2 returned to background levels by the end of January, volcanic sulfates and water still persisted after 6 months, mainly confined between 35∘ S and 20∘ N until June due to the zonal symmetry of the summer stratospheric circulation at 22–26 km. Sulfate particles, undergoing hygroscopic growth and coagulation, sediment and gradually separate from the moisture anomaly entrained in the ascending branch Brewer–Dobson circulation. Sulfate aerosol optical depths derived from the IASI (Infrared Atmospheric Sounding Interferometer) infrared sounder show that during the first 2 months, the aerosol plume was not simply diluted and dispersed passively but rather organized in concentrated patches. Space-borne lidar winds suggest that those structures, generated by shear-induced instabilities, are associated with vorticity anomalies that may have enhanced the duration and impact of the plume.

The underwater Hunga Tonga-Hunga Ha-apai (HT) volcano violently erupted on January 15th, 2022, injecting volcanic gases and aerosols at over 50 km altitude. Here we show the stratospheric aerosol and water vapour perturbations due to the HT eruption, the plume evolution during the first month dispersion and we estimate its short-term radiative impact. The HT eruption produced the largest perturbation of stratospheric aerosols and water vapour since the eruption of Pinatubo volcano in 1991. During the first three weeks following the eruption, water vapour radiative cooling dominates the plume’s heating/cooling rates, reaching values as large as -10 K/d and produces a fast plume descent of several km. At the top-of-the-atmosphere (TOA) and surface, volcanic aerosol cooling dominates the radiative forcing (RF) for the fresh plume. After two weeks, due to dispersion/dilution, water vapour heating starts to dominate the TOA RF, leading to a net warming of the climate system, which was never reported before for a volcanic plume. The surface RF, on the contrary, is dominated by the aerosol effect and reaches values of near -2 Wm-2, exceeding the hemispheric-averaged surface impact of stratospheric events of the last 30 years.

We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

We developed an optimal-estimation algorithm to simultaneously retrieve, for the first time, coexisting volcanic gaseous SO2 and sulfate aerosols (SA) from ground-based Fourier transform infrared (FTIR) observations. These effluents, both linked to magmatic degassing process and subsequent atmospheric evolution processes, have overlapping spectral signatures leading to mutual potential interferences when retrieving one species without considering the other. We show that significant overestimations may be introduced in SO2 retrievals if the radiative impact of coexistent SA is not accounted for, which may have impacted existing SO2 long-term series, e.g. from satellite platforms. The method was applied to proximal observations at Masaya volcano, where SO2 and SA concentrations, and SA acidity, were retrieved. A gas-to-particle sulfur partitioning of 400 and a strong SA acidity (sulfuric acid concentration: 65 %) were found, consistent with past in situ observations at this volcano. This method is easily exportable to other volcanoes to monitor magma extraction processes and the atmospheric sulfur cycle in the case of ash-free plumes.

The 6-month-long 2014–2015 Holuhraun eruption was the largest in Iceland for 200 years, emitting huge quantities of sulfur dioxide (SO2) into the troposphere, at times overwhelming European anthropogenic emissions. Weather, terrain and latitude made continuous ground-based or UV satellite sensor measurements challenging. Infrared Atmospheric Sounding Interferometer (IASI) data are used to derive the first time series of daily SO2 mass present in the atmosphere and its vertical distribution over the entire eruption period. A new optimal estimation scheme is used to calculate daily SO2 fluxes and average e-folding time every 12 h. For the 6 months studied, the SO2 flux was observed to be up to 200 kt day−1 and the minimum total SO2 erupted mass was 4.4±0.8 Tg. The average SO2 e-folding time was 2.4±0.6 days. Where comparisons are possible, these results broadly agree with ground-based near-source measurements, independent remote-sensing data and values obtained from model simulations from a previous paper. The results highlight the importance of using high-resolution time series data to accurately estimate volcanic SO2 emissions. The SO2 mass missed due to thermal contrast is estimated to be of the order of 3 % of the total emission when compared to measurements by the Ozone Monitoring Instrument. A statistical correction for cloud based on the AVHRR cloud-CCI data set suggested that the SO2 mass missed due to cloud cover could be significant, up to a factor of 2 for the plume within the first kilometre from the vent. Applying this correction results in a total erupted mass of 6.7±0.4 Tg and little change in average e-folding time. The data set derived can be used for comparisons to other ground- and satellite-based measurements and to petrological estimates of the SO2 flux. It could also be used to initialise climate model simulations, helping to better quantify the environmental and climatic impacts of future Icelandic fissure eruptions and simulations of past large-scale flood lava eruptions.

We developed a new retrieval algorithm based on the Infrared Atmospheric Sounding Interferometer (IASI) observations, called AEROIASI-H2SO4, to measure the extinction and mass concentration of sulphate aerosols (binary solution droplets of sulphuric acid and water), with moderate random uncertainties (typically ∼35% total uncertainty for column mass concentration estimations). The algorithm is based on a self-adapting Tikhonov–Phillips regularization method. It is here tested over a moderate-intensity eruption of Mount Etna volcano (18 March 2012), Italy, and is used to characterise this event in terms of the spatial distribution of the retrieved plume. Comparisons with simultaneous and independent aerosol optical depth observations from MODIS (Moderate Resolution Imaging Spectroradiometer), SO2 plume observations from IASI and simulations with the CHIMERE chemistry/transport model show that AEROIASI-H2SO4 correctly identifies the volcanic plume horizontal morphology, thus providing crucial new information towards the study of volcanic emissions, volcanic sulphur cycle in the atmosphere, plume evolution processes, and their impacts. Insights are given on the possible spectroscopic evidence of the presence in the plume of larger-sized particles than previously reported for secondary sulphate aerosols from volcanic eruptions.

Satellite remote sensing has been widely used to make measurements of sulphur dioxide (SO2) emissions from volcanoes. The Infrared Atmospheric Sounding Interferometer (IASI) is one such instrument that has been used to examine the emissions from large explosive eruptions. Much less work has been done using IASI to study the emissions from smaller eruptions, non-eruptive degassing or anthropogenic sources, and similarly it is rarely used for examining long term trends in activity. Now, when there are three IASI instruments in orbit and with over ten years of data, is the perfect opportunity to explore these topics. This study applied a ‘fast’ linear retrieval developed for IASI in Oxford, across the globe for a ten-year period. Global annual averages were dominated by the emissions from large eruptions (e.g. Nabro in 2011) but elevated signals could also be identified from smaller volcanic sources and industrial centres, suggesting the technique has promise for detecting lower level emissions. A systematic approach was then taken, rotating the linear retrieval output for each orbit at over 100 volcanoes worldwide, with the wind direction at the volcano’s vent, or in cases where the plume was emitted at a greater height, using the observed plume direction. This isolates the elevated signal downwind of the volcano. The rotated outputs were then averaged over monthly, annual and multi-annual time periods. Analysis of the upwind and downwind values establishes whether there is an elevated signal and its intensity. An inventory was then constructed from these observations which show how these emissions varied over a ten-year period. Trends in SO2 emission were compared against fluxes generated for the Ozone Monitoring Instrument (OMI) and the number of thermal anomalies detected by the MODVOLC algorithm developed for MODIS. It was identified for example, that long term trends are more easily identified at high altitude volcanoes such as Popocatepetl, Sabancaya and Nevado del Ruiz. This is consistent with the idea that the instrument performs better in regions with lower levels of water vapour (e.g. above the boundary layer).

Atmospheric modelling allows to study large spatial scale events such as volcanic eruptions, which can emit large amounts of plume-confined particulate matter and gases, to evaluate their transport in the atmosphere and their subsequent impacts. However, to study more precisely these events, different issues have to be addressed. One notable example of these issues is the well-known excessive numerical diffusion in the atmospheric column in Eulerian models leading to excessive plume dispersion misrepresentation of the plume three-dimensional morphology and subsequent geographical extent of its impacts. Mount Etna volcano’s moderate eruption of March 18, 2012, which released about 3kT of sulphure dioxide in the atmosphere, has been simulated in this study with the CHIMERE chemistry-transport model. The simulated plume has been observed and tracked with satellite instruments (OMI and IASI) for several days during its transport over the Mediterranean Sea in order to compare with model outputs.Sensitivity tests have been performed to evaluate the impact of injection altitude and profile shape on the subsequent trajectory of the plume. It was shown that altitude is the most sensitive parameter when results remain weakly sensitive to the vertical shape of injection.In order to effectively address the problem of excessive numerical diffusion, we have included a new antidiffusive transport scheme in the vertical direction and a new strategy to use directly the vertical wind field provided by the forcing meteorological model. We show that both these improvements permit a substantial reduction in numerical diffusion. The use of the new antidiffusive vertical scheme has brought the strongest improvement in our model outputs. To a lesser extent, a more realistic representation of the vertical wind field has also been shown to reduce volcanic plume spreading. In summary, we show that these two improvements bring an improvement in the representation of the plume which is as strong as the improvement brought by increasing the number of vertical levels, but without an additional burden in computational power.This study has been supported by AID (Agence de l'Innovation de Défense) under grant TROMPET.

International audience; Excessive numerical diffusion is one of the major limitations in the representation of long-range transport by chemistry-transport models. In the present study, we focus on excessive diffusion in the vertical direction, which has been shown to be a major issue, and we explore three possible ways to address this problem: increase vertical resolution, use an advection scheme with antidiffusive properties, and represent more accurately the vertical wind. This study is done with the CHIMERE chemistry-transport model, for the March 18, 2012 eruption of Mount Etna, which has released about 3 kt of sulphur dioxide in the atmosphere into a plume that has been observed by satellite instruments (IASI and OMI) for several days. The change from the classical Van Leer et al., (1977) scheme to the Després and Lagoutière (1999) antidiffusive scheme in the vertical direction has been shown to bring the largest improvement to model outputs in terms of preserving the thin plume emitted by the volcano. To a lesser extent, improved representation of the vertical wind field has also been shown to reduce plume dispersion. Both these changes help reducing vertical diffusion in the model as much as a brute-force approach (increasing vertical resolution).; L'excès de diffusion numérique est l'une des limitations majeures pour la représentation du transport à longue distance dans les modèles de chimie-transport. La présente étude se concentre sur l'excès de diffusion verticale, dont il a été démontré que c'est un problème majeur. Nous explorons trois façons possibles d'aborder ce problème: raffiner la résolution verticale, utiliser un schéma de transport antidiffusif, et représenter le vent vertical de façon plus exacte. Cette étude est réalisée avec le modèle de chimie-transport CHIMERE pour l'éruption de l'Etna du 18 mars 2012, qui a libéré environ 3kT de dioxyde de soufre dans l'atmosphère, formant un panache qui a été observé par les instruments spatiaux IASI et OMI durant plusieurs jours. C'est la substitution du schéma classique de Van Leer (1977) par le schéma antidiffusif de Després et Lagoutière (1999) dans la direction verticale qui a apporté l'amélioration la plus substantielle dans les sorties du modèle, en termes de préservation du panache mince émis par le volcan. Dans une moindre mesure, la représentation améliorée du champ de vent vertical a également réduit la diffusion du panache. Ces deux changements ont réduit la diffusion verticale de façon aussi efficace qu'une approche en force brute (raffinement de la résolution verticale).

We present version 3 (V3) of the Cloud_cci ATSR-2/AATSR dataset. The dataset was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) program. The cloud properties were retrieved from the second Along- Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the Advanced ATSR (AATSR) on board Envisat, which spanned 2002–2012. The data comprises a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius and optical thickness alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top and bottom-of-atmosphere short- and long-wave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with collocated CALIPSO data. The cloud masking has improved significantly, particularly the ability to detect clear pixels The Kuiper Skill score has increased from .49 to .66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulous cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments, the Correlation with MAC-LWP increase from .4 to over .8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth’s Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new dataset is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol-cloud interactions, and providing contextual information for collocated ATSR-2/AATSR surface temperature and aerosol products. For the Cloud_cci ATSR-2/AATSRv3 dataset a new digital identifier has been issued: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 Poulsen et al. (2019).

This study focuses on two new aspects of inverse modelling of volcanic emissions. First, we derive an observation operator for satellite retrievals of plume height, and second, we solve the inverse problem using an algorithm based on the 4D-Var data assimilation method. The approach is first tested in a twin experiment with simulated observations and further evaluated by assimilating IASI SO2 plume height and total column retrievals in a source term inversion for the 2010 eruption of Eyjafjallajökull. The inversion resulted in temporal and vertical reconstruction of the SO2 emissions during 1–20 May 2010 with formal vertical and temporal resolutions of 500 m and 12 h.The plume height observation operator is based on simultaneous assimilation of the plume height and total column retrievals. The plume height is taken to represent the vertical centre of mass, which is transformed into the first moment of mass (centre of mass times total mass). This makes the observation operator linear and simple to implement. The necessary modifications to the observation error covariance matrix are derived.Regularization by truncated iteration is investigated as a simple and efficient regularization method for the 4D-Var-based inversion. In the twin experiments, the truncated iteration was found to perform similarly to the commonly used Tikhonov regularization, which in turn is equivalent to a Gaussian a priori source term. However, the truncated iteration allows the level of regularization to be determined a posteriori without repeating the inversion.In the twin experiments, assimilating the plume height retrievals resulted in a 5–20 % improvement in root mean squared error but simultaneously introduced a 10–20 % low bias on the total emission depending on assumed emission profile. The results are consistent with those obtained with real data. For Eyjafjallajökull, comparisons with observations showed that assimilating the plume height retrievals reduced the overestimation of injection height during individual periods of 1–3 days, but for most of the simulated 20 days, the injection height was constrained by meteorological conditions, and assimilation of the plume height retrievals had only small impact. The a posteriori source term for Eyjafjallajökull consisted of 0.29 Tg (with total column and plume height retrievals) or 0.33 Tg (with total column retrievals only) erupted SO2 of which 95 % was injected below 11 or 12 km, respectively.

We developed a new retrieval algorithm based on the Infrared Atmospheric Sounding Interferometer (IASI) observations, called AEROIASI-Sulphates, to measure vertically-resolved sulphate aerosols (SA) extinction and mass concentration profiles, with limited theoretical uncertainties (typically ~25 % total uncertainty for SA mass column estimations). The algorithm, based on a self-adapting Tikhonov-Phillips regularization method, is applied to a medium-sized-intensity eruption of Mount Etna volcano (18 March 2012). Comparisons with simultaneous and independent SO2 plume observations and simulations show that AEROIASI-Sulphates correctly identifies the volcanic plume morphology both horizontally and vertically. This method provided, for the first time, crucial information pieces to describe the gaseous-to-particulate volcanic sulphur mass balance (60 % of the injected sulphur mass is converted to particulate matter, after ~24 hours) and to estimate the regional shortwave direct radiative forcing (a regional forcing of −0.8 W/m2 is exerted in the eastern Mediterranean) for moderate volcanic eruptions.

We developed an optimal-estimation algorithm to simultaneously retrieve, for the first time, co-emitted volcanic gaseous SO2 and sulphate aerosols (SA) from groundbased FTIR observations. These effluents, both linked to magmatic/degassing and subsequent atmospheric evolution processes, have overlapping spectral signatures leading to mutual potential interferences when retrieving one species without considering the other.We show that significant overestimations may be introduced in SO2 retrievals if the radiative impact of co-existent SA is not accounted for, which may have impacted existing SO2 long-term series, e.g. from satellite platform. The method was applied to proximal observations at Masaya volcano, where SO2 and SA concentrations, and SA acidity were retrieved. A gas-to-particle sulphur partitioning of 400 and a strong SA acidity (sulphuric acid concentration: 65 %) where found, consistently with past in-situ observations at this volcano. This method is easily exportable to other volcanoes, to monitor magma extraction processes and the atmospheric sulphur cycle.

Ash clouds are a geographically far reaching hazard associated with volcanic eruptions. To minimise the risk that these pose to aircraft and to limit disruption to the aviation industry, it is important to closely monitor the emission and atmospheric dispersion of these plumes. The altitude of the plume is an important consideration and is an essential input into many models of ash cloud propagation. CO2 slicing is an established technique for obtaining the top height of meteorological clouds and previous studies have demonstrated that there is potential for this method to be used for volcanic ash. In this study, the CO2 slicing technique has been adapted for volcanic ash and applied to spectra obtained from the Infrared Atmospheric Sounding Interferometer (IASI). Simulated ash spectra are first used to select the most appropriate channels and then demonstrate that the technique has merit for determining the altitude of the ash. These results indicate a strong match between the true heights and CO2 slicing output with a root mean square error (RMSE) of less than 800 m. Following this, the technique was applied to spectra obtained with IASI during the Eyjafjallajökull and Grimsvötn eruptions in 2010 and 2011 respectively, both of which emitted ash clouds into the troposphere, and which have been extensively studied with satellite imagery. The CO2 slicing results were compared against those from an optimal estimation scheme, also developed for IASI, and a satellite borne LiDAR is used for validation. Overall, the CO2 slicing tool performs better than the optimal estimation scheme. The CO2 slicing heights returned a RMSE value of 2.2 km when compared against the LiDAR. This is lower than the RMSE for the optimal estimation scheme (2.8 km). The CO2 slicing technique is a relatively fast tool and the results suggest that this method could be used to get a first approximation of the ash cloud height, potentially for use for hazard mitigation, or as an input for other retrieval techniques or models of ash cloud propagation.

International audience; In this study, we present a method for extracting the volcanic cloud top height (VCTH) as a plume elevation model (PEM) from orthorectified Landsat 8 data (Level 1). A similar methodology was previously applied to raw Landsat-8 data (Level 0). But level 0 data are not the standard product provided by the National Aeronautics and Space Administration (NASA)/United States Geological Survey (USGS). Level 0 data are available only on demand and consist on 14 data stripes multiplied by the number of multispectral bands. The standard product for Landsat 8 is the ortho image, available free of charge for end-users. Therefore, there is the need to adapt our previous methodology to Level 1 Landsat data. The advantages of using the standard Landsat products instead of raw data mainly include the fast -ready to use- availability of the data and free access to registered users, which is of major importance during volcanic crises. In this study, we adapt the PEM methodology to the standard Landsat-8 products, with the aim of simplifying the procedure for routine monitoring, offering an opportunity to produce PEM maps. In this study, we present the method. Our approach is applied to the 26 October 2013 Mt. Etna episodes comparing results independent VCTH measures from the spinning enhanced visible and infrared imager (SEVIRI) and the moderate resolution imaging spectroradiometer (MODIS).

Down Syndrome (DS) is an essential genetic disease that involves many other body systems along with cerebral functions. The postnatal approach to treat this genetic disease includes intervention on various related disorders (e.g., heart failure, respiratory, oral, ear, and hearing disorders). However, different proposed treatments do not significantly improve the quality of life of these subjects. Another approach to the treatment of DS considering the possibility to intervene on the embryo was recently introduced. As of this, the current study has reviewed different outcomes regarding DS treatment in an animal model, namely the Ts65Dn mouse. The obtained results encouraged spending more time, efforts, and resources in this field. Besides, various treatment strategies were tried to include genetic modification, treatment with vasoactive intestinal peptide derivatives or fluoxetine. However, the main obstacle to the use of these possible treatments is the ethical issues it raises. The progression of the pregnancy in spite of awareness that DS affects the unborn and prenatal treatment of DS injured embryo are relevant dilemmas. Thus, talented researchers should spend more efforts to improve the quality of life for people affected by DS, which will allow probably a better approach to the ethical issues.

The vulnerability of the European airspace to volcanic eruptions was brought to the attention of the public and the scientific community by the 2010 eruptions of the Icelandic volcano Eyjafjallajökull. As a consequence of this event, ash concentration thresholds replaced the ĝ zero tolerance to ashĝ€ rule, drastically changing the requirements on satellite ash retrievals. In response to that, the ESA funded several projects aiming at creating an optimal end-to-end system for volcanic ash plume monitoring and prediction. Two of them, namely the SACS-2 and SMASH projects, developed and improved dedicated satellite-derived ash plume and sulfur dioxide level assessments. The validation of volcanic ash levels and height extracted from the GOME-2 and IASI instruments on board the MetOp-A satellite is presented in this work. EARLINET lidar measurements are compared to different satellite retrievals for two eruptive episodes in April and May 2010. Comparisons were also made between satellite retrievals and aircraft lidar data obtained with the UK's BAe-146-301 Atmospheric Research Aircraft (managed by the Facility for Airborne Atmospheric Measurements, FAAM) over the United Kingdom and the surrounding regions. The validation results are promising for most satellite products and are within the estimated uncertainties of each of the comparative data sets, but more collocation scenes would be desirable to perform a comprehensive statistical analysis. The satellite estimates and the validation data sets are better correlated for high ash optical depth values, with correlation coefficients greater than 0.8. The IASI retrievals show a better agreement concerning the ash optical depth and ash layer height when compared with the ground-based and airborne lidar data., SCOPUS: ar.j, info:eu-repo/semantics/published

Sulfur dioxide (SO2) is an important atmospheric constituent that plays a crucial role in many atmospheric processes. Volcanic eruptions are a significant source of atmospheric SO2 and its effects and lifetime depend on the SO2 injection altitude. The Infrared Atmospheric Sounding Interferometer (IASI) on the METOP satellite can be used to study volcanic emission of SO2 using high-spectral resolution measurements from 1000 to 1200 and from 1300 to 1410 cm−1 (the 7.3 and 8.7 µm SO2 bands) returning both SO2 amount and altitude data. The scheme described in Carboni et al. (2012) has been applied to measure volcanic SO2 amount and altitude for 14 explosive eruptions from 2008 to 2012. The work includes a comparison with the following independent measurements: (i) the SO2 column amounts from the 2010 Eyjafjallajökull plumes have been compared with Brewer ground measurements over Europe; (ii) the SO2 plumes heights, for the 2010 Eyjafjallajökull and 2011 Grimsvötn eruptions, have been compared with CALIPSO backscatter profiles. The results of the comparisons show that IASI SO2 measurements are not affected by underlying cloud and are consistent (within the retrieved errors) with the other measurements. The series of analysed eruptions (2008 to 2012) show that the biggest emitter of volcanic SO2 was Nabro, followed by Kasatochi and Grímsvötn. Our observations also show a tendency for volcanic SO2 to reach the level of the tropopause during many of the moderately explosive eruptions observed. For the eruptions observed, this tendency was independent of the maximum amount of SO2 (e.g. 0.2 Tg for Dalafilla compared with 1.6 Tg for Nabro) and of the volcanic explosive index (between 3 and 5).

Radiative transfer models used in remote sensing and hazard assessment of volcanic ash require knowledge of ash optical parameters. Here, we characterise the bulk and glass compositions of a representative suite of volcanic ash samples with known complex refractive indices (n + ik: where n is the real and k is the imaginary part). Using a linear regression model, we develop a new parameterization allowing the complex refractive index of volcanic ash to be estimated from ash SiO2 content or ratio of non-bridging oxygens to tetrahedrally-coordinated cations (NBO/T). At visible wavelengths, n correlates better with bulk than glass composition (both SiO2 and NBO/T), and k correlates better with SiO2 content than NBO/T. Over a broader spectral range (0.4–19 μm), bulk correlates better than glass composition, and NBO/T generally correlates better than SiO2 content for both parts of the refractive index. In order to understand the impacts of our new parameterization on satellite retrievals, we compared IASI satellite (wavelengths 3.62–15.5 μm) mass loading retrievals using our new approach with retrievals that assumed a generic (Eyjafjallajökull) ash refractive index. There are significant differences in mass loading using our calculated indices specific to ash type rather than a generic index. Where mass loadings increase, there is often improvement in retrieval quality (corresponding to cost function decrease). This new parameterization of refractive index variation with ash composition will help to improve remote sensing retrievals for the rapid identification of ash and quantitative analysis of mass loadings from satellite data on operational timescales.

Satellite remote sensing is a valuable method for detecting and quantifying sulfur dioxide (SO2) emissions at volcanoes. The use of ultraviolet satellite instruments for monitoring purposes has been assessed in numerous studies, but there are advantages to using infrared measurements, including that they can operate at night and during high-latitude winters. This study focuses on the Infrared Atmospheric Sounding Interferometer (IASI). Retrievals developed for this instrument have been shown to be successful when applied to large eruptions, but little has been done to explore their potential for detecting and quantifying emissions from smaller and lower altitude emissions or for the assessment of ongoing activity. Here a “fast” linear retrieval has been applied across the globe to detect volcanic sources of SO2. The results are dominated by emissions from explosive eruptions, but signals are also evident from weak eruptions, passive degassing, and anthropogenic activity. Ecuador and Kamchatka were selected for further study with a more processing intensive iterative retrieval which can quantify the SO2 amount. At Tungurahua in Ecuador, good agreement was seen between IASI, the Ozone Monitoring Instrument (OMI) and ground-based flux data, demonstrating that the retrieval is capable of capturing relative changes in activity. Similarly, good agreement was found between IASI and OMI in Kamchatka. In this high-latitude region, OMI is unable to operate for 3 or 4 months in each year. It is therefore suggested that IASI could be used alongside other instruments for evaluating changes in volcanic activity.

A detection method is demonstrated for volcanic sulphur dioxide and ammonia from agriculture using data from the MetOp Infrared Atmospheric Sounding Interferometer (IASI). The method is an extension of the Brightness Temperature Difference (BTD) technique which uses the difference in brightness temperature between a small number of channels sensitive to the target species and spectral background to determine the presence of the target species. The method described here allows instead for the use of large numbers of channels with an optimal set of linear weights which effectively suppress the spectral background allowing low-noise filters to be produced which are capable of distinguishing the target species from other parameters such as interfering species, surface and atmospheric temperature, and cloudiness without retrieving these parameters explicitly. Once generated, the filters can be applied quickly and easily to identify events of interest over a large global dataset, in near-real-time if required, and in some circumstances a degree of quantitative information can be extracted about the abundance of the target species. The theory behind the generation of the filters is first described. The filters are then used in the detection of volcanic sulphur dioxide from the eruption of the Kasatochi volcano in Alaska, beginning in August 2008, and in the detection of ammonia emissions related to agriculture over Southern Asia in May 2008. The performance of new the filters is compared against that obtained using existing filters.

The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations – this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.

The remote sensing of volcanic sulphur dioxide (SO2) is important because it is used as a proxy for volcanic ash, which is dangerous to aviation and is generally more difficult to discriminate. This paper presents an Artificial Neural Network (ANN) algorithm that recognizes volcanic SO2 in the atmosphere using hyperspectral remotely sensed data from the IASI instrument aboard the Metop-A satellite. The importance of this approach lies in exploiting all thermal infrared spectral information of IASI and its application to near real-time volcanic monitoring in a fast manner. In this paper, the ANN algorithm is demonstrated on data of the Eyjafjallajokull volcanic eruption (Iceland) during the months of April and May 2010, and on the Grimsvotn eruption occurring during May 2011. The algorithm consists of a two output neural network classifier trained with a time series consisting of some hyperspectral eruption datasets collected during 14 April to 14 May 2010 and a few from 22 to 26 May 2011. The inputs were all channels (441) in the IASI v3 band and the target outputs (truth) were the corresponding retrievals of SO2 amount obtained with an optimal estimation method. The validation results for the Eyjafjallajokull independent data-sets had an overall accuracy of 100% and no commission errors, therefore demonstrating the feasibility of estimating the presence of SO2 using a neural network approach also a in cloudy sky conditions. Although the validation of the neural network classifier on datasets from the Grimsvotn eruption had no commission errors, the overall accuracies were lower due to the presence of omission errors. Statistical analysis revealed that those false negatives lie near the detection threshold for discriminating pixels affected by SO2. This demonstrated that the accuracy in classification is strictly related to the sensitivity of the model. The lower accuracy obtained in detecting SO2 for Grimsvotn validation dates might also be caused by less statistical knowledge of such an eruption during the training phase.

[1] Airborne volcanic ash poses a significant danger to aircraft, but is difficult to quantify accurately using satellite data, while sulphur dioxide is much easier to detect accurately, but is much less of a direct hazard to aviation. This paper investigates the reliability of using SO2 as a proxy for the location of volcanic ash, using an SO2 retrieval from the Infrared Atmospheric Sounding Interferometer (IASI) and ash detections from IASI and the Advanced Along Track Scanning Radiometer (AATSR). Using a numerical “missed ash fraction” applied to the eruptions of Eyjafjallajokull in 2010 and Puyehue-Cordon Caulle in 2011 reveals that the SO2 flag typically misses ∼30% of the detectable ash. Furthermore, the missed ash fraction is found to be highly variable, both between the two eruptions and over the course of each eruption, with values of over 80% found on some days. The detection threshold of the AATSR ash flag is also investigated using radiative transfer calculations, allowing the threshold of the IASI flag to be inferred, and these are related to the ash contamination levels.

A new optimal estimation algorithm for the retrieval of sulphur dioxide (SO2) has been developed for the Infrared Atmospheric Sounding Interferometer (IASI) using the channels between 1000–1200 and 1300–1410 cm−1. These regions include the two SO2 absorption bands centred at about 8.7 and 7.3 μm (the ν1 and ν3 bands respectively). The retrieval assumes a Gaussian SO2 profile and returns the SO2 column amount in Dobson units and the altitude of the plume in millibars (mb). Forward modelled spectra (against which the measurements are compared) are based on the Radiative Transfer for TOVS (RTTOV) code. In our implementation RTTOV uses atmospheric profiles from European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological data. The retrieval includes a comprehensive error budget for every pixel derived from an error covariance matrix that is based on the SO2-free climatology of the differences between the IASI and forward modelled spectra. The IASI forward model includes the ability to simulate a cloud or ash layer in the atmosphere. This feature is used to illustrate that: (1) the SO2 retrieval is not affected by underlying cloud but is affected if the SO2 is within or below a cloud layer; (2) it is possible to discern if ash (or other atmospheric constituents not considered in the error covariance matrix) affects the retrieval using quality control based on the fit of the measured spectrum by the forward modelled spectrum. In this work, the algorithm is applied to follow the behaviour of SO2 plumes from the Eyjafjallajökull eruption during April and May 2010. From 14 April to 4 May (during Phase I and II of the eruption) the total amount of SO2 present in the atmosphere, estimated by IASI measurements, is generally below 0.02 Tg. During the last part of the eruption (Phase III) the values are an order of magnitude higher, with a maximum of 0.18 Tg measured on the afternoon of 7 May.

A new optimal estimation algorithm for the retrieval of volcanic ash properties has been developed for use with the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval method uses the wave number range 680–1200 cm−1, which contains window channels, the CO2 ν2 band (used for the height retrieval), and the O3 ν3 band.Assuming a single infinitely (geometrically) thin ash plume and combining this with the output from the radiative transfer model RTTOV, the retrieval algorithm produces the most probable values for the ash optical depth (AOD), particle effective radius, plume top height, and effective radiating temperature. A comprehensive uncertainty budget is obtained for each pixel. Improvements to the algorithm through the use of different measurement error covariance matrices are explored, comparing the results from a sensitivity study of the retrieval process using covariance matrices trained on either clear-sky or cloudy scenes. The result showed that, due to the smaller variance contained within it, the clear-sky covariance matrix is preferable. However, if the retrieval fails to pass the quality control tests, the cloudy covariance matrix is implemented.The retrieval algorithm is applied to scenes from the Eyjafjallajökull eruption in 2010, and the retrieved parameters are compared to ancillary data sources. The ash optical depth gives a root mean square error (RMSE) difference of 0.46 when compared to retrievals from the MODerate-resolution Imaging Spectroradiometer (MODIS) instrument for all pixels and an improved RMSE of 0.2 for low optical depths (AOD

This study focuses on two new aspects on inverse modelling of volcanic emissions. First, we derive an observation operator for satellite retrievals of plume height, and second, we solve the inverse problem using the 4D-Var method. The approach is demonstrated by assimilating IASI SO2 plume height and total column retrievals in a source term inversion for the 2010 eruption of Eyjafjallajökull. The inversion resulted in temporal and vertical reconstruction of the SO2 emissions during the 1–20 May, 2010 with formal vertical and temporal resolutions of 500 m and 12 hours. The plume height observation operator is based on simultaneous assimilation of the plume height and total column retrievals. The plume height is taken to represent the vertical centre of mass, which is transformed into the first moment of mass. This makes the observation operator linear and simple to implement. The necessary modifications to the observation error covariance matrix are derived. Regularisation by truncated iteration is investigated as a simple and efficient regularisation method for the 4D-Var based inversion. In an experiment with synthetic observations, the truncated iteration was found to perform similarly to the commonly used Tikhonov regularisation. However, the truncated iteration allows the amount of regularisation to be varied a posteriori, without repeating the inversion. For inverting the Eyjafjallajökull SO2 emission at the temporal and vertical resolution used in this study, the 4D-Var method required about 70 % less computational effort than commonly used methods based on performing a separate model simulation for each degree of freedom in the estimated source term. Compared to the inversion using only total column retrievals, assimilating the plume height resulted in a vertical emission profile more closely matching the ash plume heights observed by radar. The a posteriori source term gave an estimate of 0.29 Tg erupted SO2 of which 95 % was injected below 11 km.

An inter-comparison study of the aerosol optical thickness (AOT) at 0.55 μm retrieved using different satellite instruments and algorithms based on the analysis of backscattered solar light is presented for a single scene over central Europe on October 13th, 2005. For the first time comparisons have been performed for as many as six instruments on multiple satellite platforms. Ten different algorithms are briefly discussed and inter-compared. It was found that on the scale of a single pixel there can be large differences in AOT retrieved over land using different retrieval techniques and instruments. However, these differences are not as pronounced for the average AOT over land. For instance, the average AOT at 0.55 μm for the area 7–12E, 49–53N was equal to 0.14 for MISR, NASA MODIS and POLDER algorithms. It is smaller by 0.01 for the ESA MERIS aerosol product and larger by 0.04 for the MERIS BAER algorithm. AOT as derived using AATSR gives on average larger values as compared to all other instruments, while SCIAMACHY retrievals underestimate the aerosol loading. These discrepancies are explained by uncertainties

In this paper, a sensitivity analysis and procedure development for volcanic-plume sulfur dioxide and ash retrievals using ground thermal infrared camera have been carried out. The semiconductor device camera, considered as a reference, has a spectral range of 8-14 ìm with noise equivalent temperature difference that is better than 100 mK at 300 K. The camera will be used to monitor and assess the hazards of Mt. Etna volcano to mitigate the risk and impact of volcanic eruptions on the civil society and transports. A minimum number of filters have been selected for sulfur dioxide (SO 2) and volcanic ash retrievals. The sensitivity study has been carried out to determine the SO 2 and volcanic ash minimum concentration detectable by the system varying the camera geometry and the atmospheric profiles. Results show a meaningful sensitivity increase considering high instrument altitudes and low camera-elevation angles. For all geometry configurations and monthly profiles, the sensitivity limit varies between 0.5 and 2 g.m -2 for SO 2 columnar abundance and between 0.02 and 1 for ash optical depth. Two procedures to detect SO 2 and ash, based on the least square fit method and on the brightness temperature difference (BTD) algorithm, respectively, have also been proposed. Results show that high concentration of atmospheric water vapor columnar content significantly reduces the ash-plume effect on the BTD. A water vapor-correction procedure introduced improves the ash retrievals and the cloud discrimination in every season, considering all the camera geometries. © 2009 IEEE.

The impact of volcanic emissions, especially from passive degassing and minor explosions, is a source of uncertainty in estimations of aerosol indirect effects. Observations of the impact of volcanic aerosol on clouds contribute to our understanding of both present-day atmospheric properties and of the pre-industrial baseline necessary to assess aerosol radiative forcing. We present systematic measurements over several years at multiple active and inactive volcanic islands in regions of low present-day aerosol burden. The time-averaged indirect aerosol effects within 200 km downwind of island volcanoes are observed using Moderate Resolution Imaging Spectroradiometer (MODIS, 2002–2013) and Advanced Along-Track Scanning Radiometer (AATSR, 2002–2008) data. Retrievals of aerosol and cloud properties at Kīlauea (Hawai'i), Yasur (Vanuatu) and Piton de la Fournaise (la Réunion) are rotated about the volcanic vent to be parallel to wind direction, so that upwind and downwind retrievals can be compared. The emissions from all three volcanoes – including those from passive degassing, Strombolian activity and minor explosions – lead to measurably increased aerosol optical depth downwind of the active vent. Average cloud droplet effective radius is lower downwind of the volcano in all cases, with the peak difference ranging from 2–8 μm at the different volcanoes in different seasons. Estimations of the difference in Top of Atmosphere upward Short Wave flux upwind and downwind of the active volcanoes from NASA's Clouds and the Earth's Radiant Energy System (CERES) suggest a downwind elevation of between 10 and 45 Wm−2 at distances of 150–400 km from the volcano, with much greater local (< 80 km) effects. Comparison of these observations with cloud properties at isolated islands without degassing or erupting volcanoes suggests that these patterns are not purely orographic in origin. Our observations of unpolluted, isolated marine settings may capture processes similar to those in the pre-industrial marine atmosphere.

Since 2010, several papers have been published that reveal a pattern of discrepancies between stratospheric aerosol data from the Optical Spectrograph and Infrared Imaging System (OSIRIS) instrument and other measurements and model simulations of volcanic plumes from Kasatochi, Sarychev Peak, and Nabro volcanoes. OSIRIS measurements show two discrepancies, a posteruption lag in aerosol onset/increase and a low bias in maximum stratospheric aerosol optical depth. Assumed robustness of the OSIRIS data drove various conclusions, some controversial, such as the contention that the June 2011 Nabro plume was strictly tropospheric, and entered the stratosphere indirectly via the Asian monsoon. Those conclusions were driven by OSIRIS data and a Smithsonian Institution report of strictly tropospheric injection heights. We address the issue of Nabro's eruption chronology and injection height, and the reasons for the OSIRIS aerosol discrepancies. We lay out the time line of Nabro injection height with geostationary image data, and stratospheric plume evolution after eruption onset using retrievals of sulfur dioxide and sulfate aerosol. The observations show that Nabro injected sulfur directly to or above the tropopause upon the initial eruption on 12/13 June and again on 16 June 2011. Next, OSIRIS data are examined for nonvolcanic and volcanically perturbed conditions. In nonvolcanic conditions OSIRIS profiles systematically terminate 1–4 km above the tropopause. Additionally, OSIRIS profiles terminate when 750 nm aerosol extinction exceeds ∼0.0025 km−1, a level that is commonly exceeded after volcanic injections. Our findings largely resolve the discrepancies in published works involving OSIRIS aerosol data and offer a correction to the Nabro injection-height and eruption chronology.

The remote sensing of volcanic ash plumes from space can provide a warning of an aviation hazard and knowledge on eruption processes and radiative effects. In this paper new algorithms are presented to provide volcanic plume properties from measurements by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the Advanced Along Track Scanning Radiometer (AATSR) and the Spinning Enhanced Visible and Infrared Imager (SEVIRI). A challenge of remote sensing is to provide near-real-time methods to identify, and so warn of, the presence of volcanic ash. To achieve this, a singular vector decomposition method has been developed for the MIPAS instrument on board the Environmental Satellite. This method was applied to observations of the ash clouds from the eruptions of Nabro and the Puyehue-Cordón Caulle in 2011 and led to a sensitive volcanic signal flag which was capable of tracking changes in the volcanic signal spectra as the plume evolved. A second challenge for remote sensing is to identify the ash plume height. This is a critical parameter for the initialization of algorithms that numerically model the evolution and transport of a volcanic plume. As MIPAS is a limb sounder, the identification of ash also provides an estimate of height provided the plume is above about 6 km. This is complemented by a new algorithm, Stereo Ash Plume Height Retrieval Algorithm, that identifies plume height using the parallax between images provided by Along Track Scanning Radiometer-type instruments. The algorithm was tested on an image taken at 14:01 GMT on 6 June 2011 of the Puyehue-Cordón Caulle eruption plume and gave a height of 11.91±1.4 km, which agreed with the value derived from the location of the plume shadow (12.7±1.8 km). This plume height was similar to the height observed by MIPAS (12±1.5 km) at 02:56 GMT on 6 June. The quantitative use of satellite imagery and the full exploitation of high-resolution spectral measurements of ash depends upon knowing the optical properties of the observed ash. Laboratory measurements of ash from the 1993 eruption of Mt Aso, Japan have been used to determine the refractive indices from 1 to 20 mm. These preliminary measurements have spectral features similar to ash values that have been used to date, albeit with slightly different positions and strengths of the absorption bands. The refractive indices have been used to retrieve ash properties (plume height, optical depth and ash effective radius) from AATSR and SEVIRI instruments using two versions of Oxford-RAL Retrieval of Aerosol and Cloud (ORAC) algorithm. For AATSR a new ash cloud type was used in ORAC for the analysis of the plume from the 2011 Eyjafjallajökull eruption. For the first c. 500 km of the plume ORAC gave values for plume height of 2.5-6.5 km, optical depth 1-2.5 and effective radius 3-7 μpm, which are in agreement with other observations. A weakness of the algorithm occurs when underlying cloud invalidates the assumption of a single cloud layer. This is rectified in a modified version of ORAC applied to SEVIRI measurements. In this case an extra model of a cloud underlying the ash plume was included in the range of applied models. In cases where the plume overlay cloud, this new model worked well, showing good agreement with correlative Cloud-Aerosol Lidar with Orthogonal Polarization observations. © The Geological Society of London 2013.