Hugues Brenot and Manuel Soler from ALARM Project will co-present the lecture on Selective detection of dust or ash clouds from hyperspectral (LEO) and broadband (GEO) sensors in the context of the SACS/ALARM early warning system at the 4th International Conference on Atmospheric Dust (4-7 Oct 2021).


The use of satellite sensors is essential to detect and mitigate the risk of airborne hazards (i.e. volcanic plumes or desert sandstorms) for aviation, as flying through them can have a strong impact on engines (abrasion and damages caused by aerosols) and on the health of passengers (e.g. due to associated hazardous trace gases). Near real-time satellite observations of aerosols can improve situational awareness for Air Traffic Management (ATM).
We study volcanic plumes & desert dust clouds and the interest of combining geostationary and polar orbiting satellite observations. On one hand, using Geostationary Equatorial Orbit (GEO) imagers, we consider brightness temperatures/radiances of all the channels (e.g. the 11 channels from SEVIRI) and the ash & dust RGB composite products, as defined by EUMETSAT on a global coverage ( The inherent limitation of the broadband sensors onboard GEO satellites lies in a lack of discrimination between volcanic, dust, smoke and convective clouds. The advantage of GEO is the high temporal and spatial resolution of these observations. On the other hand, hyperspectral sensors onboard Low Earth Orbit (LEO) platforms (e.g. IASI on board MetOp-A&-B&-C; see the Support to Aviation Control Service — SACS; can provide selective detection of ash and dust particles. The disadvantage is the limited number of overpasses although this can be improved using several LEO satellite sensors and in the near future hyperspectral GEO sensors (GEMS, TEMPO, Sentinel-4).
We plan to show the combined use of GEO and LEO satellite sensors to improve near real-time quasi-continuous selective detection of natural hazardous clouds (ash and dust) from geostationary sensors, and the implementation of NetCDF Alert products (NCAP data). Such tailored products are developed in the frame of the ALARM H2020 project (

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