Integrating geostationary satellite data into CAMS: Insights from the CAMEO project and GEMS data assimilation

The new satellite technology of the GEO-Ring constellation, offering high-quality, high-temporal-resolution observations of trace gases and aerosols, represents a transformative advance in air quality monitoring. Within the framework of the Horizone Europe CAMEO (CAMS Servive Evolution) project, efforts have focused on integrating GEMS satellite retrievals into ECMWF’s Integrated Forecast System (IFS) to enhance atmospheric composition analyses and forecasts under the Copernicus Atmosphere Monitoring Service (CAMS).

During the first phase of the project, updates to the IFS enabled the assimilation of geostationary GEMS data alongside polar-orbiting satellite observations. Initial evaluations of GEMS version 2 products provided valuable insights into their strengths and limitations, including the identification of biases and their impact on model forecasts.

The operational integration of GEMS NRT NO₂ and O₃ data into the IFS cycle CY49R1 was successfully achieved, with continuous monitoring by CAMS. The release of NRT GEMS retrieval version 3 in December 2024 demonstrated substantial improvements in data quality. Preliminary results indicate significant reductions in biases compared to version 2, particularly for NO₂. The high temporal and spatial resolution of GEMS retrievals captures diurnal patterns, such as rush hour peaks and seasonal variability, being critical for urban air pollution dynamics. For NO₂, comparisons of the NRT GEMS NO2 version 2 data with the IUP-UB alternative retrieval from the University of Bremen revealed improved agreement with TROPOMI and model outputs, reducing biases. For GEMS O₃, assimilation experiments show comparable analysis results to TROPOMI, whereas validations by independent observations show local forecast improvements, particularly over polluted regions.  

By combining geostationary and polar-orbiting satellite data, this work highlights the potential for a synergistic approach to address gaps in air quality monitoring. The findings underscore the important role of geostationary platforms in complementing polar-orbiting satellites, capturing dynamic atmospheric processes, and advancing global air quality forecasts. Future efforts to integrate TEMPO and Sentinel-4 data into the CAMS global monitoring system promise cutting-edge improvements in air quality modeling.