Search

Volcanic eruptions release sulfur dioxide (SO2), impacting air quality, ecosystems, and aviation. To comprehensively assess these effects, high-temporal-resolution SO2 emission data is crucial. In this study, we use an inverse modeling procedure, assimilating SO2 column measurements from TROPOMI and OMPS low-Earth orbit satellites into an Eulerian chemistry-transport model. This procedure allows us to derive precise hourly SO2 mass flux and injection heights. TROPOMI, with its exceptional spatial resolution, excels at detecting short-lived, concentrated SO2 plumes near the source shortly before satellite overpasses. This high-resolution data enables more robust identification and precise characterization of strong SO2 emissions, surpassing the capabilities of lower-resolution OMPS measurements, which may overlook or underestimate vigorous degassing periods. Notably, this high-resolution data also facilitates the detection of pre-eruptive SO2 emissions. Cloud cover can obscure SO2 plumes from satellite observations, but our inverse modeling procedure effectively distinguishes and tracks them by assimilating successive satellite overpass data. Furthermore, this procedure proves less susceptible to ash emissions compared to geostationary Himawari-8/AHI observations. We apply our methodology to study the 2018 Ambrym eruption, a former major volcanic SO2 emitter. This eruption marked the end of long-lived lava lake activity and initiated a submarine eruption through a massive magma intrusion. Our detailed SO2 flux time series unveils the evolution of the eruption and identifies distinct SO2 sources, including lava flows and shallow magma intrusions. In summary, the assimilation of TROPOMI data into inverse modeling procedures offers significant potential for enhancing our understanding of magma transport and environmental impacts during volcanic eruptions. [ABSTRACT FROM AUTHOR]

Deep convection overshooting the lowermost stratosphere is well known for its role in the local stratospheric water vapour (WV) budget. While it is seldom the case, local enhancements of WV associated with stratospheric overshoots are often published. Nevertheless, one debatable topic prevails on the global impact of this event with respect to the temperature-driven dehydration of air parcels entering the stratosphere. As a first step, it is crucial to quantify their role at a local scale before assessing their impact at a large-scale in a meteorological model. It would lead to a forcing scheme for overshoots in the global models. This paper reports on the local enhancements of WV linked to stratospheric overshoots, observed during the TRO-Pico campaign conducted in March 2012 in Bauru, Brazil, using the BRAMS (Brazilian version of RAMS) mesoscale model. Since numerical simulation depends on the choice of several preferred parameters, each having its uncertainties, we vary the microphysics or the vertical resolution while simulating the overshoots. Thus, we produce a set of simulations illustrating the possible variations in representing the stratospheric overshoots. To resolve better the stratospheric hydration, we opt for simulations with the 800-m-horizontal-grid-point presentation. Next, we validate these simulations against the Bauru S-band radar echo tops and the TRO-Pico balloon-borne observations of WV and particles. Two of the three simulations' setups yield results compatible with the TRO-Pico observations. From these two simulations, we determine approximately 333 t to 2000 t of WV mass prevailing in the stratosphere due to an overshooting plume depending on the simulation setup. About 70% of the ice mass remains between the 380K to 385K isentropic levels. The overshooting top comprises pristine ice and snow, while aggregates only play a role just above the tropopause. Interestingly, the horizontal cross-section of the overshooting top is about 450km² at 380K isentrope, which is similar to the horizontal-grid-point resolution of a simulation that cannot compute overshoots explicitly. These results could establish a forcing scheme of overshooting hydration or dehydration in a large-scale simulation. [ABSTRACT FROM AUTHOR]