Active remote sensing of volcanic plumes: models, algorithms and applications

My Research focuses on Remote Sensing of volcanic ash clouds. Volcanic eruptions represent a serious threat to human safety that might have a considerable impact on global economic activities. Prevention and mitigation of risk related to volcanic activity needs comprehension and better knowledge of eject materials. The different data derived from observation of ground-based and satellite-based sensors have been used to train the prediction models. Firstly I have properly adapted and extended the "T_Matrix code”(Michshenko et al., 1996a-1996b-1998-200), which implements the method EBCM (Extended Boundary Condition Method) and represents the theoretical solution to the problem of scattering by non-spherical particles, to include the optical wavelength of NIR, VIS and UV. The ash particles main electromagnetic and microphysical parameters, implemented in the simulator HAPESS (Hydro Ash Particle Ensemble Scatter Simulator), allowed creating a Monte Carlo generation of Radar and Lidar synthetic signatures used to perform the physically-oriented algorithm VASR. The latter is a crucial technique to retrieve information about volcanic source parameters, and it basically consists in two main sub-steps: classification and estimation. Applying Maximum A Posteriori Probability (MAP) criterion on radar/lidar measured observables, is then possible to make a classification of ash category and then applying the regressive power-laws, previously calculated, we can estimate the ash concentration, the number-weighted mean diameter and other volcanic source parameters used to train the ash plume dispersal models. If we use a Maximum Likelihood (ML) approach to retrieve these volcanic parameters, we need only to select the useful values corresponding to specific criteria. The physical-based methodology VASR has been extended to ingest different ash particles kinds, such as mixture and coexistence between meteorological and volcanic-origin particles. In this research work we will see the potential of this method and the innovative aspect of this methodology, such as the Mass Flow Rate (MFR) estimation; it opens new possibilities in the applied research field to volcanic eruption study and the resulting impact in the atmosphere. The first case study considered is related to the ground-based observation of volcanic ash plume, erupted from the Eyjafjallajökull volcano on May 2010. We have used different sensor data to estimate the concentration, top plume altitude and MFR. Some volcanic source parameters derived from radar data show a good agreement with estimations derived from other models and methodologies. When the different sensor data were available at the same time, we have combined them with our information in order to validate and corroborate the validity of our technique. Another case analysed is related to Grimsvötn eruption 2011. In this case we have analysed only a short time series of data, in order to obtain the MFR estimates and related MFR profiles, and to verify, also in this case, a good agreement of MFR estimations derived by the radar and the 1D model. The Holuhraun case analysed is the more interesting case because it was characterized by turbulent phenomena happened, such as dust devils, due both to particular environmental conditions and to the situ morphology. In this case, different sensors have observed the same ash plume. Both radars estimations show the same ash class and the similar occurrence. Considering the different sensitivity of two sensors also the volcanic source parameters show a good agreement between them. The particular environmental condition we allow to suppose also the mixed-phase ash classes. The analysed Etna cases, using the scanning lidar system, show how this sensor can be complementary to radar systems. The lidar observations of the smallest dispersed ash particle in the atmosphere can help finding the main microphysical ash features and the areas characterized by a specific mass concentration of the smallest ash particles. This information may help quantifying the impact that ash emissions have on aviation safety to prevent the flights in the areas of high ash contamination (2x10-4g/m3) in compliance with the International Civil Aviation Organization directives [International Civil Aviation Organization (ICAO), 2010]. This case study, starting from the inter-comparison between the VALR algorithm and ash dispersal model, highlights a 25% smaller ash contaminated area considering different dimensional ash particles; this allows us to define a 25% security margin in the interdicted area in comparison with the area obtained applying the ash dispersal model. The last case analysed is related to Calbuco eruption on April 2015. This strong and very tephra-rich eruption generated a bigger dispersed ash plume observed by different sensors on board of some satellite platforms carrying various active and passive remote sensors. In this particular case we have used the brightness temperature data derived by VIS-IR radiometer of GOES-13 (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer) radiometer on board of National Oceanic and Atmospheric Administration's (NOAA's) Polar Orbiting Environmental Satellites (POES) satellites and VIIRS Visible Infrared Imaging Radiometer Suite radiometers on board of S-NPP (Suomi National Polar-orbiting Partnership) to perform only a firstly quantitative analysis, using the known brightness temperature difference BTD between the optical band, in order to discriminate between the ash and meteorological cloud. The CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar and IIR (Imaging Infrared Radiometer) radiometer on board of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite overpassing at the same time as other satellite sensors confirms the presence of the ash plume, as observed by other sensors data analysis. Using the Caliop data we have classified and estimated the main ash classes detected in the plume vertical section observed, confirming the presence of dispersed very small ash particles. This case is very interesting because combining the information derived by satellite sensors, such as the extension of ash plume detected with the vertical structure derived by Caliop, we can have a good information about the 3D structure of dispersed ash plume.