Sand and dust storms are extreme and rapidly evolving meteorological phenomena that generate significant amounts of mineral particles in the atmosphere. They play a significant role in different aspects of weather, climate and atmospheric chemistry and represent a serious hazard for life, health, property, environment and economy.

The objective of the DUST2MSG project is to derive an hourly dust product from the Meteosat Zero Degree Service and Indian Ocean Data Coverage area with the latest version of the CISAR algorithm capable of retrieving aerosol and cloud properties over any types of surface. Retrieval of high aerosol load from space observation is challenging as is can easily be erroneous flagged as clouds. The CISAR algorithm (Govaerts and Luffarelli, 2018; Luffarelli and Govaerts, 2019) has been extended to the retrieval of cloud optical properties to overcome the need of an external cloud mask. After a so-called training period, the CISAR algorithm process all available satellite observations, i.e. both cloudy and cloud free sky. This algorithm has already been successfully applied for the joint retrieval of surface, aerosol and cloud properties over any types of surface from SEVIRI, SLSTR and PROBA-V data.


Selected Docs



Intermediate results: The Godzilla dust storm

In June 2020 an extremely thick dust plume, named Godzilla, moved from the Sahara region to the Caribbeans. The Western African coast where the dust storms originates is observed by both MSG1 and MSG4. The videos below show the CISAR combined AOT/COT retrieval over the region of interest compared to CAMS dataset during the same time window. It can be seen that the thick dust storm is correctly retrieved by CISAR, following its spatial and temporal evaluation.

Combined AOT/COT retrieval obtained applying the CISAR algorithm to combined observations from MSG1 and MSG4 capturing the Godzilla dust storm in June 2020 originating in the Sahara region and moving towards the West.
CAMS AOT dataset over the Godzilla dust storm in June 2020.

Progress Meeting 1

The first progress meeting took place online (via Microsoft Teams) on the 20/10/2022. The added value of combining two geostationary satellites with different viewing geometry is assessed by analysing the information content associated to the aerosols by means of the Jacobian, i.e. the partial derivative of the signal with respect to the state variable. The observations acquisition thus aims at maximising the associated information content. The CISAR algorihtm has been updated to process data acquired by SEVIRI on-board MSG1 and MSG4. First results in the common area are shown in the animation below over the Nile delta region.


Combined AOT/COT retrieval obtained applying the CISAR algorithm to combined observations from MSG1 and MSG4. First results obtained over the Nile delta during January 2020.


Kick-off meeting

The DUST2MSG kick-off meeting took place online (via Microsoft Teams) on the 30/11/2021.





Rayference has been created in 2013 as a private business company (SME) by Yves Govaerts and provides advanced technical and scientific expertise on Earth Observation, more specifically in the area of radiative transfer, inverse modelling, vicarious calibration and fundamental and thematic climate data record generation. Rayference contributes to the preparation of new space missions in the area of air quality and global surface monitoring. It is also involved in climate monitoring research projects and the design of algorithms for the operational retrieval of geophysical products. Rayference is a member of the CEOS IVOS working group.

Rayference project activities include:

  • Project Management
  • Algorithm Evolution
  • Product Generation and Validation
  • Outreach and Publication

Key personnel


Yves Govaerts

Project Leader


Lucio Franceschini

Data processing


Marta Luffarelli

Algorithm prototyping


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