Improved retrieval of SO₂ plume height from TROPOMI using an iterative Covariance-Based Retrieval Algorithm

Abstract

Abstract. Knowledge of sulfur dioxide layer height (SO2 LH) is important to understand volcanic eruption processes, the climate impact of SO2 emissions and to mitigate volcanic risk for civil aviation. However, the estimation of SO2 LH from ground-based instruments is challenging in particular for rapidly evolving and sustained eruptions. Satellite wide-swath nadir observations have the advantage to cover large-scale plumes and the potential to provide key information on SO2 LH. In the ultraviolet, SO2 LH retrievals leverage the fact that, for large SO2 columns, the light path and its associated air mass factor (AMF) depends on the SO2 absorption (and therefore on the vertical distribution of SO2), and SO2 LH information can be obtained from the analysis of measured back-scattered radiances coupled with radiative transfer simulations. However, existing algorithms are mainly sensitive to SO2 LH for SO2 vertical columns of at least 20 DU. Here we develop a new SO2 LH algorithm and apply it to observations from the high-spatial-resolution TROPOspheric Monitoring Instrument (TROPOMI). It is based on an SO2 optical depth look-up table and an iterative approach. The strength of this scheme lies in the fact that it is a Covariance-Based Retrieval Algorithm (COBRA; Theys et al., 2021). This means that the SO2-free contribution of the measured optical depth is treated in an optimal way, resulting in an improvement of the SO2 LH sensitivity to SO2 columns as low as 5 DU, with a precision better than 2 km. We demonstrate the value of this new data through a number of examples and comparison with satellite plume height estimates (from IASI and CALIOP), and back-trajectory analyses. The comparisons indicate an SO2 LH accuracy of 1–2 km, except for some difficult observation conditions, in particular for optically thick ash plumes or partially SO2-filled scenes.

VogCast: A Framework for Modeling Volcanic Air Pollution and Its Application to the 2022 Eruption of Mauna Loa Volcano, Hawai'i

“…The impact of aged recirculated vog is particularly pronounced during the second half of the eruption period. Though the absolute column‐integrated concentrations of SO 2 cannot be directly estimated from operational TROPOMI data (Theys et al., 2022), the presence of an extensive persistent diffuse layer of vog was anecdotally confirmed by local observers. These elevated “background” concentrations were generally not captured by the model.…”

Monitoring Volcanic Plumes and Clouds Using Remote Sensing: A Systematic Review

“…For ash retrieval, techniques such as brightness temperature difference (BTD) algorithms use spectral differences between volcanic clouds and the background environment [29,33] to quantify ash parameters. Ultraviolet (UV) sensors onboard satellites, such as ozone monitoring instruments (OMIs) and tropospheric monitoring instruments (TROPOMIs), have been used to assess volcanic SO2 emissions [13,34,35 Table 1 summarizes the articles obtained from the systematic review procedure, which focused on satellite remote sensing-based approaches for monitoring volcanic clouds. Their main objectives were ash and SO 2 retrieval from volcanic eruptions using satellite sensors and applying specific algorithms and techniques.…”

“…For ash retrieval, techniques such as brightness temperature difference (BTD) algorithms use spectral differences between volcanic clouds and the background environment [29,33] to quantify ash parameters. Ultraviolet (UV) sensors onboard satellites, such as ozone monitoring instruments (OMIs) and tropospheric monitoring instruments (TROPOMIs), have been used to assess volcanic SO 2 emissions [13,34,35].…”

“…It is crucial to accurately detect, monitor, and forecast their dispersion to mitigate the hazardous consequences of volcanic clouds. Several methods are available for achieving this objective, including ground-based techniques [6][7][8], aircraft/unmanned aerial vehicles (UAVs) [9,10], satellite remote sensing [11][12][13], and numerical forecasting models [14]. In addition, multiplatform approaches can improve volcanic cloud detection and provide more reliable forecasting results [15,16].…”

Automatic retrieval of volcanic SO2 emission source from TROPOMI products

“…As mentioned before, because the plume height is not retrieved from the TROPOMI product but rather assumed to be equal to the volcano summit altitude, the generated trajectories can suffer errors. This could be improved in the future via the SO 2 Layer Height product (Hedelt et al, 2019), which provides accurate information about the height of the plumes, making reverse trajectory based algorithms more accurate (Theys et al, 2022). There are promising developments underway for that, as for major eruptions the TROPOMI SO 2 Layer Height product is available.…”