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Improving volcanic sulfur dioxide cloud dispersal forecasts by progressive assimilation of satellite observations

par Boichu, Marie;Khvorostyanov, Dmitry;Clarisse, Lieven ;Clerbaux, Cathy
Référence Geophysical research letters, 41, 7, page (2637-2643)
Publication Publié, 2014-04

Article révisé par les pairs

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Résumé :

Forecasting the dispersal of volcanic clouds during an eruption is of primary importance, especially for ensuring aviation safety. As volcanic emissions are characterized by rapid variations of emission rate and height, the (generally) high level of uncertainty in the emission parameters represents a critical issue that limits the robustness of volcanic cloud dispersal forecasts. An inverse modeling scheme, combining satellite observations of the volcanic cloud with a regional chemistry-transport model, allows reconstructing this source term at high temporal resolution. We demonstrate here how a progressive assimilation of freshly acquired satellite observations, via such an inverse modeling procedure, allows for delivering robust sulfur dioxide (SO2) cloud dispersal forecasts during the eruption. This approach provides a computationally cheap estimate of the expected location and mass loading of volcanic clouds, including the identification of SO2-rich parts. Key Points Refined SO2 cloud dispersal forecasts by assimilation of satellite observations Refined estimation of source emissions using an inverse modeling approach Compared to standard methods, cloud SO2-rich parts are robustly forecasted © 2014. American Geophysical Union. All Rights Reserved.