From 2011 to 2015, 49 lava fountains occurred at Etna volcano. In this work, the measurements carried out from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument, on board the Meteosat Second Generation (MSG) geostationary satellite, are processed to realize a proximal monitoring of the eruptive activity for each event. The SEVIRI measurements are managed to provide the time series of start and duration of eruption and fountains, Time Averaged Discharge Rate (TADR) and Volcanic Plume Top Height (VPTH). Due to its temperature responsivity, the eruptions start and duration, fountains start and duration and TADR are realized by exploiting the SEVIRI 3.9 μm channel, while the VPTH is carried out by applying a simplified procedure based on the SEVIRI 10.8 μm brightness temperature computation. For each event, the start, duration and TADR have been compared with ground-based observations. The VPTH time series is compared with the results obtained from a procedures-based on the volcanic cloud center of mass tracking in combination with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) back-trajectories. The results indicate that SEVIRI is generally able to detect the start of the lava emission few hours before the ground measurements. A good agreement is found for both the start and the duration of the fountains and the VPTH with mean differences of about 1 h, 50 min and 1 km respectively.

The planetary boundary layer (PBL) includes the portion of the atmosphere which is directly influenced by the presence of the earth's surface. Aerosol particles trapped within the PBL can be used as tracers to study the boundary-layer vertical structure and time variability. As a result of this, elastic backscatter signals collected by lidar systems can be used to determine the height and the internal structure of the PBL. The present analysis considers three different methods to estimate the PBL height. The first method is based on the determination of the first-order derivative of the logarithm of the range-corrected elastic lidar signals. Estimates of the PBL height for specific case studies obtained through this approach are compared with simultaneous estimates from the potential temperature profiles measured by radiosondes launched simultaneously to lidar operation. Additional estimates of the boundary layer height are based on the determination of the first-order derivative of the range-corrected rotational Raman lidar signals. This latter approach results to be successfully applicable also in the afternoon–evening decaying phase of the PBL, when the effectiveness of the approach based on the elastic lidar signals may be compromised or altered by the presence of the residual layer. Results from these different approaches are compared and discussed in the paper, with a specific focus on selected case studies collected by the University of Basilicata Raman lidar system BASIL during the Convective and Orographically-induced Precipitation Study (COPS).

Accurate tracking and forecasting of ash dispersal in the atmosphere and quantification of its uncertainty are of fundamental importance for volcanic risk mitigation. Numerical models and satellite sensors offer two complementary ways to monitor ash clouds in real time, but limits and uncertainties affect both techniques. Numerical forecasts of volcanic clouds can be improved by assimilating satellite observations of atmospheric ash mass load. In this paper, we present a data assimilation procedure aimed at improving the monitoring and forecasting of volcanic ash clouds produced by explosive eruptions. In particular, we applied the Local Ensemble Transform Kalman Filter (LETKF) to the results of the Volcanic Ash Transport and Dispersion model HYSPLIT. To properly simulate the release and atmospheric transport of volcanic ash particles, HYSPLIT has been initialized with the results of the eruptive column model PLUME-MoM. The assimilation procedure has been tested against SEVIRI measurements of the volcanic cloud produced during the explosive eruption occurred at Mt. Etna on 24 December 2018. The results show how the assimilation procedure significantly improves the representation of the current ash dispersal and its forecast. In addition, the numerical tests show that the use of the sequential Ensemble Kalman Filter does not require a precise initialization of the numerical model, being able to improve the forecasts as the assimilation cycles are performed.

The presence of volcanic clouds in the atmosphere affects air quality, the environment, climate, human health and aviation safety. The importance of the detection and retrieval of volcanic SO₂ lies with risk mitigation as well as with the possibility of providing insights into the mechanisms that cause eruptions. Due to their intrinsic characteristics, satellite measurements have become an essential tool for volcanic monitoring. In recent years, several sensors, with different spectral, spatial and temporal resolutions, have been launched into orbit, significantly increasing the effectiveness of the estimation of the various parameters related to the state of volcanic activity. In this work, the SO₂ total masses and fluxes were obtained from several satellite sounders—the geostationary (GEO) MSG-SEVIRI and the polar (LEO) Aqua/Terra-MODIS, NPP/NOAA20-VIIRS, Sentinel5p-TROPOMI, MetopA/MetopB-IASI and Aqua-AIRS—and compared to one another. As a test case, the Christmas 2018 Etna eruption was considered. The characteristics of the eruption (tropospheric with low ash content), the large amount of (simultaneously) available data and the different instrument types and SO₂ columnar abundance retrieval strategies make this cross-comparison particularly relevant. Results show the higher sensitivity of TROPOMI and IASI and a general good agreement between the SO₂ total masses and fluxes obtained from all the satellite instruments. The differences found are either related to inherent instrumental sensitivity or the assumed and/or calculated SO₂ cloud height considered as input for the satellite retrievals. Results indicate also that, despite their low revisit time, the LEO sensors are able to provide information on SO₂ flux over large time intervals. Finally, a complete error assessment on SO₂ flux retrievals using SEVIRI data was realized by considering uncertainties in wind speed and SO₂ abundance.

On the morning of 24 December 2018, an eruptive event occurred at Etna, which was followed the next day by a strong sequence of shallow earthquakes. The eruptive episode lasted until 30 December, ranging from moderate strombolian to lava fountain activity coupled with vigorous ash/gas emissions and a lava flow effusion toward the eastern volcano flank of Valle del Bove. In this work, the data collected from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instruments on board the Meteosat Second Generation (MSG) geostationary satellite are used to characterize the Etna activity by estimating the proximal and distal eruption parameters in near real time. The inversion of data indicates the onset of eruption on 24 December at 11:15 UTC, a maximum Time Average Discharge Rate (TADR) of 8.3 m³/s, a cumulative lava volume emitted of 0.5 Mm³, and a Volcanic Plume Top Height (VPTH) that reached a maximum altitude of 8 km above sea level (asl). The volcanic cloud ash and SO₂ result totally collocated, with an ash amount generally lower than SO₂ except on 24 December during the climax phase. A total amount of about 100 and 35 kt of SO₂ and ash respectively was emitted during the entire eruptive period, while the SO₂ fluxes reached peaks of more than 600 kg/s, with a mean value of about 185 kg/s. The SEVIRI VPTH, ash/SO₂ masses, and flux time series have been compared with the results obtained from the ground-based visible (VIS) cameras and FLux Automatic MEasurements (FLAME) networks, and the satellite images collected by the MODerate resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua- polar satellites. The analysis indicates good agreement between SEVIRI, VIS camera, and MODIS retrievals with VPTH, ash, and SO₂ estimations all within measurement errors. The SEVIRI and FLAME SO₂ flux retrievals show significant discrepancies due to the presence of volcanic ash and a gap of data on the FLAME network. The results obtained in this study show the ability of geostationary satellite systems to characterize eruptive events from the source to the atmosphere in near real time during the day and night, thus offering a powerful tool to mitigate volcanic risk on both local population and airspace and to give insight on volcanic processes.

Water vapour measurements from a ground‐based Raman lidar and an airborne differential absorption lidar, complemented by high‐resolution numerical simulations from two mesoscale models (AROME‐WMED and Meso‐NH), are considered to investigate three transition events from Mistral/Tramontane to southerly marine flow taking place in the Montpellier region (southern France) in the time frame September–October 2012, during the Hydrological Cycle in the Mediterranean Experiment Special Observation Period 1. Low‐level wind reversals associated with these transitions are found to have a strong impact on water vapour transport, leading to a large variability of the water vapour vertical and horizontal distributions. Water vapour mixing ratio within the boundary layer is found to vary from typical values in the range 4–8 g kg⁻¹ during the Mistral/Tramontane flows to values in the range 8–15 g kg⁻¹ during the southerly marine flows. The increase/decrease in water vapour mixing ratio within the boundary layer may be abrupt and marked during these transition periods, with values increasing/decreasing by a factor of 2–4 within 1 h. The high spatial and temporal resolutions of the lidar data allow monitoring the time evolution of the water vapour field during these transitions from predominantly northerly Mistral/Tramontane flow to a predominantly southerly flow, permitting identification of the quite sharp separation between these flows, which is also satisfactorily well captured by the mesoscale models. Water vapour measurements from the ground‐based lidar are complemented by particle backscatter measurements from the same system, which reveal the significant variability in the aerosol and cloud fields associated with these transition events.