ALBERT

Description: Sulphur dioxide (SO2) fluxes of active degassing volcanoes are routinely measured with ground-based equipment to characterize and monitor volcanic activity. SO2 of unmonitored volcanoes or from explosive volcanic eruptions, can be measured with satellites. However, remote-sensing methods based on absorption spectroscopy generally provide integrated amounts of already dispersed plumes of SO2 and satellite derived flux estimates are rarely reported. Here we review a number of different techniques to derive volcanic SO2 fluxes using satellite measurements of dispersed and large-scale plumes of SO2 and investigate the temporal evolution of the total emissions of SO2 for three very different volcanic events in 2011: Puyehue-Cordón Caulle (Chile), Nyamulagira (DR Congo) and Nabro (Eritrea). High spectral resolution satellite instruments operating both in the UV-visible (OMI/Aura and GOME-2/MetOp-A) and thermal infrared (IASI/MetOp-A) spectral ranges, and multispectral satellite instruments operating in the thermal infrared (MODIS/Terra-Aqua) are used. We show that satellite data can provide fluxes with a sampling of a day or less (few hours in the best case). Generally the flux results from the different methods are consistent, and we discuss the advantages and weaknesses of each technique. Although the primary objective of this study is the calculation of SO2 fluxes, it also enables to assess the consistency of the SO2 products from the different sensors used.

Description: In this paper we combine SO2/ash plume dispersion modelling, satellite and surface remote sensing observations to study the regional influence of a relatively weak volcanic eruption from Mount Etna on the optical and micro-physical properties of Mediterranean aerosols. We analyse the Mount Etna eruption episode of 25–27 October 2013. The evolution of the plume along the trajectory is investigated by means of the FLEXPART (FLEXible PARTicle dispersion model) Lagrangian dispersion model. The satellite dataset includes true colour images, retrieved values of volcanic SO2 and ash, and estimates of SO2 and ash emission rates derived from MODIS (MODerate resolution Imaging Spectroradiometer) observations, and estimates of cloud top pressure from SEVIRI (Spinning Enhanced Visible and InfraRed Imager). Surface remote sensing measurements of aerosol and SO2 made at the ENEA Station for Climate Observations (35.52° N, 12.63° E, 50 m a.s.l.) on the island of Lampedusa are used in the analysis. The combination of these different datasets suggests that SO2 and ash, despite the initial injection occurred at about 7.0 km altitude, reached altitudes around 10–12 km and influenced the aerosol size distribution at a distance more than 350 km downwind. This study indicates that even a relatively weak volcanic eruption may produce an observable effect on the aerosol properties at the regional scale. The impact of secondary sulphate particles on the aerosol size distribution at Lampedusa is discussed, and estimates of the clear sky direct aerosol radiative forcing are derived. Daily shortwave radiative forcing efficiencies are calculated with the LibRadtran model. They are estimated between −39 and −48 W m−2 AOD−1 at the top of the atmosphere, and between −66 and −49 W m−2 AOD−1, at the surface, with the variability in the estimates mainly depending on the aerosol single scattering albedo. These results suggest that sulphate particles played a large role, while the contribution by ash particles was small in the volcanic plume arriving at Lampedusa during this event.

Description: Volcanic ash clouds detection and retrieval represent a key issue for the aviation safety due to the harming effects they can provoke on aircrafts. A lesson learned from the recent Icelandic Eyjafjalla volcano eruption is the need to obtain accurate and reliable retrievals on a real time basis. The current most widely adopted procedures for ash detection and retrieval are based on the Brightness Temperature Difference (BTD) inversion observed at 11 and 12 μm that allows volcanic and meteo clouds discrimination. While ash cloud detection can be readily obtained, a reliable quantitative ash cloud retrieval can be so time consuming to prevent its utilization during the crisis phase. In this work a fast and accurate Neural Network (NN) approach to detect and retrieve volcanic ash cloud properties has been developed using multispectral IR measurements collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) over Mt. Etna volcano during 2001, 2002 and 2006 eruptive events. The procedure consists in two separate steps: the ash detection and ash mass retrieval. The detection is reduced to a classification problem by identifying two classes of "ashy" and "non-ashy" pixels in the MODIS images. Then the ash mass is estimated by means of the NN, replicating the BTD-based model performances. The results obtained from the entire procedure are very encouraging; indeed the confusion matrix for the test set has an accuracy greater than 90 %. Both ash detection and retrieval show a good agreement when compared to the results achieved by the BTD-based procedure. Moreover, the NN procedure is so fast to be extremely attractive in all the cases when the quick response time of the system is a mandatory requirement.

Description: A new procedure for the simultaneous estimation of SO2 and ash abundances in a volcanic plume using thermal infrared (TIR) MODIS data is presented. Plume altitude and temperature are the only two input parameters needed to run the procedure, while surface emissivity, atmospheric profiles and radiative transfer models are not required to perform the atmospheric corrections. The proposed space-based retrievals are simple, extremely fast and can be easily extended and applied to any volcano. By linearly interpolating the radiances of the edges of the detected volcanic plume, the Volcanic Plume Removal (VPR) procedure here described, computes the radiances that would have been measured at the sensor if the plume was missing and reconstructs a new image without the plume. The comparison of the new image with the original data containing the plume highlights the plume presence and allows the computation of the plume transmittance in three TIR-MODIS bands: 29, 31 and 32 (8.6, 11.0 and 12.0 μm). The procedure results are very good when the surface under the plume is rather uniform, as it is often the case with plume widths of few tens of kilometers. As a consequence it works very well when the plume is above the sea, but still produces fairly good estimates in more challenging and not easily modeled conditions, such as images with land or uniform cloud layers under the plume. In the aforementioned bands the plume transmittances are derived in two steps: (1) using a simple model with the plume at a fixed altitude and neglecting the layer of atmosphere above it; (2) refining the first result with a polynomial relationship obtained by means of MODTRAN simulations adapted for the geographical region, the ash type and the atmospheric profiles. Bands 31 and 32 are SO2 transparent and, from their transmittances, the ash particle effective radius (Re) and the aerosol optical depth at 550 nm (AOD550) are computed. A simple relation between the ash transmittances of bands 31 and 29 is demonstrated and used for the SO2 columnar content estimation. Comparing the results of the VPR procedure with the MODTRAN simulations for more than 200 thousands different cases, the frequency distribution of the differences says that: the Re error is less than ±0.5 μm in more than the 60% of the cases; the AOD550 error is less than ±0.125 in the 80% of the cases; the SO2 error is less than ±0.5 g m−2 in more than the 60% of the considered cases. The VPR procedure has been applied in two case studies of recent eruptions occurred at Mt. Etna volcano, Italy and successfully compared with the results obtained with the well known SO2 and ash retrievals based look-up tables (LUTs). By recomputing the parameters of the polynomial relationship, the VPR procedure can be easily extended to other ash types and applied to different volcanoes.

Description: The simultaneous presence of SO2 and ash in a volcanic plume can lead to a significant error in the SO2 column abundance retrieval when multispectral Thermal InfraRed (TIR) data are used. The ash particles within the plume with effective radii from 1 to 10 μm reduce the Top Of Atmosphere (TOA) radiance in the entire TIR spectral range, including the channels used for SO2 retrieval. The net effect is a significant SO2 overestimation. In this work the interference of ash is discussed and two correction procedures for satellite SO2 volcanic plume retrieval in the TIR spectral range are developed to achieve an higher computational speed and a better accuracy. The ash correction can be applied when the sensor spectral range includes the 7.3 and/or 8.7 μm SO2 absorption bands, and the split window bands centered around 11 and 12 μm required for ash retrieval. This allows the possibility of simultaneous estimation of both volcanic SO2 and ash in the same data set. The proposed ash correction procedures have been applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Spin Enhanced Visible and Infrared Imager (SEVIRI) measurements. Data collected during the 24 November 2006 Mt. Etna eruption have been used to illustrate the technique. The SO2 and ash estimation is carried out by using a best weighted least squares fit method and the Brightness Temperature Difference (BTD) procedures, respectively. The simulated TOA radiance Look-Up Table (LUT) needed for the SO2 column abundance and the ash retrievals have been computed using the MODTRAN 4 Radiative Transfer Model. The results show the importance of the ash correction on SO2 retrievals at 8.7 μm, where the corrected SO2 column abundance values are less than 50% of the uncorrected values. The ash correction on SO2 retrieval at 7.3 μm is much less important and only significant for low SO2 column abundances. Results also show that the simplified and faster correction procedure underestimates the ash correction compared with the more time consuming but more accurate correction procedure. Such underestimation is greater for instruments having better ground pixel resolution, i.e. greater for MODIS than for SEVIRI.

Description: A new procedure is presented for simultaneous estimation of SO2 and ash abundance in a volcanic plume, using thermal infrared (TIR) MODIS data. Plume altitude and temperature are the only two input parameters required to run the procedure, while surface emissivity, temperature, atmospheric profiles, ash optical properties, and radiative transfer models are not necessary to perform the atmospheric corrections. The procedure gives the most reliable results when the surface under the plume is uniform, for example above the ocean, but still produces fairly good estimates in more challenging and not easily modelled conditions, such as above land or meteorological cloud layers. The developed approach was tested on the Etna volcano. By linearly interpolating the radiances surrounding a detected volcanic plume, the volcanic plume removal (VPR) procedure described here computes the radiances that would have been measured by the sensor in the absence of a plume, and reconstructs a new image without plume. The new image and the original data allow computation of plume transmittance in the TIR-MODIS bands 29, 31, and 32 (8.6, 11.0 and 12.0 μm) by applying a simplified model consisting of a uniform plume at a fixed altitude and temperature. The transmittances are then refined with a polynomial relationship obtained by means of MODTRAN simulations adapted for the geographical region, ash type, and atmospheric profiles. Bands 31 and 32 are SO2 transparent and, from their transmittances, the effective ash particle radius (Re), and aerosol optical depth at 550 nm (AOD550) are computed. A simple relation between the ash transmittances of bands 31 and 29 is demonstrated and used for SO2 columnar content (cs) estimation. Comparing the results of the VPR procedure with MODTRAN simulations for more than 200 000 different cases, the frequency distribution of the differences shows the following: the Re error is less than ±0.5 μm in more than 60% of cases; the AOD550 error is less than ±0.125 in 80% of cases; the cs error is less than ±0.5 g m−2 in more than 60% of considered cases. The VPR procedure was applied in two case studies of recent eruptions occurring at the Mt Etna volcano, Italy, and successfully compared with the results obtained from the established SO2 and ash assessments based on look-up tables (LUTs). Assessment of the sensitivity to the plume altitude uncertainty is also made. The VPR procedure is simple, extremely fast, and can be adapted to other ash types and different volcanoes.

Description: Volcanic ash clouds detection and retrieval represent a key issue for aviation safety due to the harming effects on aircraft. A lesson learned from the recent Eyjafjallajokull eruption is the need to obtain accurate and reliable retrievals on a real time basis. In this work we have developed a fast and accurate Neural Network (NN) approach to detect and retrieve volcanic ash cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) data in the Thermal InfraRed (TIR) spectral range. Some measurements collected during the 2001, 2002 and 2006 Mt. Etna volcano eruptions have been considered as test cases. The ash detection and retrievals obtained from the Brightness Temperature Difference (BTD) algorithm are used as training for the NN procedure that consists in two separate steps: ash detection and ash mass retrieval. The ash detection is reduced to a classification problem by identifying two classes: "ashy" and "non-ashy" pixels in the MODIS images. Then the ash mass is estimated by means of the NN, replicating the BTD-based model performances. A segmentation procedure has also been tested to remove the false ash pixels detection induced by the presence of high meteorological clouds. The segmentation procedure shows a clear advantage in terms of classification accuracy: the main drawback is the loss of information on ash clouds distal part. The results obtained are very encouraging; indeed the ash detection accuracy is greater than 90%, while a mean RMSE equal to 0.365 t km−2 has been obtained for the ash mass retrieval. Moreover, the NN quickness in results delivering makes the procedure extremely attractive in all the cases when the rapid response time of the system is a mandatory requirement.