Abstract Thermal observations of volcanic activity when the volcano is partially covered by clouds or observed under a wide-scan angle are often removed from further analyses. In the event of a volcanic crisis, such a reduced set of data is not adequate. Even when the observation conditions are favourable, the full observation set is still required to provide decision-makers with quality information about the data. Automatic quality estimation and outlier detection was not estimated in the past. We propose to analytically define the uncertainty for individual observations based on the measurement circumstances. To additionally reduce the temporal noise of the radiant power ( RP ) time series we apply a Kalman Filter (KF). The KF is able to recursively analyse an unevenly sampled time series. Based on some proposed rules, it can also detect outliers. We apply the proposed methodology to the 2008–09 Etna eruption monitored by MODIS (Moderate Resolution Imaging Spectroradiometer). The analysis of the results shows that the topography has a greater influence on RP than previously considered.

Abstract The activity status of a volcano can be evaluated from the remotely measured radiant power ( RP ). The measured RP contains noise due to reasons such as atmospheric effects and instrument characteristics. Here we first show how to estimate the uncertainty of each single RP measurement. To additionally reduce the temporal noise of the RP time series we apply a Kalman filter. The Kalman filter is able to recursively analyse an unevenly sampled time series. To validate our filtering scheme, we applied it to an eruption of Etna in 2002, as well as to the eruption of Nyamuragira in 2010. In the case of the Etna eruption, the denoised time series agrees well with in situ observations of a waxing and waning flow. For the case of Nyamuragira, the enhanced time series of RP shows more fluctuation probably due to cloud coverage. Thus, we propose a multiple instrument approach that increases the temporal resolution of the RP time series and reduces the associated noise.

Surface volcanic gases may reflect volatile budgets in magma and forecast impending eruptions, and their release to the atmosphere may affect climate. The dynamics of magma degassing is complicated, however, by differences in the solubility, partitioning, and diffusion of the various volatiles, all of which can vary with pressure, temperature, and melt composition. To constrain possible gas outputs, we carried out experiments to determine how Cl partitions between water bubbles and silicate melt, and decompression experiments to examine how Cl behaves during closed- and open-system degassing. We incorporated our findings and those from the literature for CO 2 and S into a steady, isothermal, and homogeneous flow model to estimate fluxes of gases at the vent from ascending water-rich magma, assuming different scenarios for the onset and development of permeability in bubbly magma. We find that, for given permeability scenarios, total gas fluxes vary with magma flux, but ratios of gas species do not change. The S/Cl and SO 2 /CO 2 ratios do change, however, depending on whether the magma is oxidized or reduced. After magma fragments into a Plinian eruption column, gases continue to escape from cooling pumice in the plume, but here the rate of gas release is controlled by diffusion, which varies with temperature. Degassing of pumice and ash was modeled by linking a steady-state plume model, which gives the vertical variation of mean temperature and velocity of particles inside the plume, to a conductive cooling model of pumices, which controls diffusion of Cl, CO 2 , and S in pumice. We find that gas loss increases with column height (mass flux) and initial temperature, because in both cases pumices cool over a longer time period, allowing more gas to diffuse out of the matrix glass. The amount of gas released also depends on the size distribution of particles in the erupting mixture, with less being released for a finely skewed distribution.