When it comes to data exploitation, the atmospheric domain is especially characterised by heterogeneity. A large variety of data in terms of sensing methods, time, geometry, resolution, format and dimensionality prevents the combined use.

Within SISTEMA, we develop solutions to exploit and extract the desired information from the atmospheric data triangle consisting of satellite, model and in-situ data. One example of an application built around the fusion of diverse atmospheric data is performed within the MUSE project. There, we combine model output with EO observational data to develop applications in aviation. The resulting service helps to support emergency response during hazard events (e.g., volcanic eruptions) or minimize long-term damage in aviation, e.g., due to cumulative aerosol intake or corrosion.

Atmospheric data from remote sensing systems also plays a crucial role when it comes to accurate, transparent, comparable, consistent and complete reporting and monitoring of GHG inventories and fluxes. Satellite data with high accuracy and good spatio-temporal coverage and resolution can improve an independent quantification on emissions. Furthermore, satellite data can improve the quantification of emissions and their changes over time, by providing information on a better coverage and through more frequent revisits (days to weeks).

Wildfires are affecting the Yacutia Region, in Siberia, Russia, since May 2021. In this modified true color image from Sentinel-2 from July 26th, 2021, the almost 800Km2 burned area and the 50km fire line can be clearly identified and measured

The Ozone hole over Antarctica as viewed from the Sentinel-5P satellite.
European NO2 CAMS model simulations

Related projects

⸺ MUSE (ongoing)

The objective of the MUltisource data package tools and SErvices (MUSE) is to develop and integrate a data-agnostic fusion tool to simultaneously manipulate products coming from different satellite sensors. To demonstrate the maturity and the flexibility of the system, a set of thematic services is implemented in strict connection with experts end users.

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