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Between 13 December 2020 and 21 February 2022, Etna volcano produced a sequence of 66 paroxysmal explosive eruptions, with Strombolian activity at the summit craters climaxing in lava fountains and eruption columns extending several kilometers above the craters, accompanied by minor and short-lasting lava flows from the crater rim. We selected three of these episodes that occurred within a short space of time, between 13 December 2020 and 12 March 2021, of different magnitude (i.e., erupted volume) and intensity (i.e., mass eruption rate or instantaneous eruption rate), and analyzed them from a multidisciplinary perspective. The aim was to gain insights into those parameters that mostly reveal the eruptive process for hazard assessment purposes. The multidisciplinary data consist of calibrated visible images, thermal images, seismic and infrasound data, ground deformation detected from the strainmeters, as well as satellite SEVIRI images. From these data, we obtained the timing of each paroxysmal event, the erupted volume in terms of tephra and lava flows, and the corresponding deflation of the source region, together with the development of the lava fountains and eruption columns with time. The results enabled determining that the smallest episode was that of 13 December 2020, which comprised three distinctive pulses but did not produce an eruptive column detectable from either monitoring cameras or satellites. The 28 February 2021 episode was remarkable for the short amount of time required to reach the climax, and was the most intense, whereas the 12 March 2021 event showed the longest duration but with an intensity between that of the previous two. Our results show that these three paroxysmal events display a typical trend, with the first event also being the smallest in terms of both erupted volume and intensity, the second being the most intense, and the third the one of greatest magnitude but less intense than the second. This is coherent with the end of the first paroxysmal phase on 1 April 2021, which was followed by 48 days of eruptive pause before starting again. In this context, the end of the paroxysmal phase was anticipated by a more effusive episode, thus heralding a temporary decline in the gas content within the feeding magma batch.

Thermal-infrared remote sensing is used to monitor and study hazardous volcanic phenomena. Thermal cameras are often used by monitoring centers and laboratories. A physical comprehension of their behavior is needed to perform quantitative measurements, which are strongly dependent on camera features and settings. This makes it possible to control the radiance measurements related to volcanic processes and, thus, to detect thermal anomalies, validate models, and extract source parameters. We review the theoretical background related to the camera behavior beside the main features affecting thermal measurements: Atmospheric transmission, object emissivity and reflectivity, camera characteristics, and external optics. We develop a Python package, PythTirCam-1.0, containing pyTirTran, a radiative transfer model based on the HITRAN database and the camera spectral response. This model is compared with the empirical algorithm implemented into a commercial camera. These two procedures are validated using a simple experiment involving pyTirConv, an algorithm developed to recover the radiometric thermal data from compressed images collected by monitoring centers. Python scripts corresponding to the described methods are provided as open-source code. This study can be applied to a wide variety of applications and, specifically, to different volcanic processes, from earth and space.