Preprints
https://doi.org/10.5194/egusphere-2024-2941
https://doi.org/10.5194/egusphere-2024-2941
20 Sep 2024
 | 20 Sep 2024
Status: this preprint is open for discussion.

Assimilation of volcanic sulfur dioxide products from IASI and TROPOMI into the chemical transport model MOCAGE: case study of the 2021 La Soufrière Saint-Vincent eruption

Mickaël Bacles, Jonathan Améric, and Vincent Guidard

Abstract. Sulfur dioxide emitted during volcanic eruptions can be hazardous for aviation safety. As part of their activities, the Volcanic Ash Advisory Centres (VAACs) are therefore interested in the real-time atmospheric monitoring of this gas. A recent development aims at improving the forecasts of volcanic sulfur dioxide quantities made by the MOCAGE chemistry transport model. For this purpose, observations from both TROPOMI and IASI (B and C) instruments located on separate polar orbiting satellites are assimilated in the model. These sulfur dioxide measurements are based on the eruption event of the La Soufrière Saint-Vincent volcano in April 2021. Observations from the OMI instrument are considered as validation data. The resulting assimilation experiments show that the combined assimilation of IASI and TROPOMI observations always leads to a better forecast compared to the independent assimilation of data from each instrument. Sulfur dioxide atmospheric field forecasts are better when the available observations are numerous and cover a long time window.

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Mickaël Bacles, Jonathan Améric, and Vincent Guidard

Status: open

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Mickaël Bacles, Jonathan Améric, and Vincent Guidard
Mickaël Bacles, Jonathan Améric, and Vincent Guidard

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Short summary
Sulfur dioxide emitted during volcanic eruptions can be hazardous for aviation safety. A recent development aims at improving the forecasts of volcanic sulfur dioxide quantities made by the MOCAGE chemistry transport model. Both TROPOMI and IASI instruments are assimilated in the model. We focus on the eruption event of the La Soufrière Saint-Vincent volcano in April 2021. The combined assimilation of IASI and TROPOMI observations always leads to a better analyses and forecasts.