Atmospheric aerosol is one of the main drivers of climate changes. Importance of accurate global aerosol characterization for climate studies and air pollution monitoring is a well recognized problem (e.g., see IPCC AR5 by Boucher et al.2013). In addition to the traditional spectral Aerosol Optical Depth (AOD) such characterization should also include such extended aerosol information asaerosol size and type.
The global information about aerosol can be obtained from space-borne measurements only. Therefore, climate studies are becoming more and more relying on high quality aerosol characterization from space. At present time there are a number of different satellites on Earth orbit dedicated to aerosol studies. However, due to limited information content, the main aerosol products of the most of satellite missions is AOD while the accuracy of aerosol size and type retrieval from space-borne remote sensing still requires essential improvement.
The problem of accurate extended aerosol characterization from satellite measurements is strongly affected by the complexity of reliable separation of atmosphere and surface signals. In addition to this, the information content of the measurements should be enough for aerosol characterization itself.
Since the end of the POLDER/PARASOL mission in 2013, no single currently operating satellite satisfies completely the requirements for extended aerosol characterisation. At the same time, different satellites dedicated to atmospheric studies may overpass the same area on Earth surface during the same day but at different times or different relative positions. As a result, being properly collocated, such combined measurements can provide multi-angular,multi-temporal measurements in extended spectral range. More independent satellite measurements with different complementary capabilities are combined,the richer the information content of combined measurements becomes. Thetreatment of these data seems to be beyond the capacity of most of the existent traditional algorithms since the processing of multi-instrument observations is not commonly used. In contrast, such retrieval algorithms of the new generation like GRASP (Generalized Retrieval of Atmosphere and Surface Properties) were specifically designed for synergetic processing of diverse observations and can be highly useful for multi-instrument data processing (Dubovik et al. 2011,2021).
The GRASP multi-pixel retrieval concept has already been successfully applied to the observations of different single space-borne instruments: polar-orbiting like POLDER/PARASOL, MERIS, AATSR/ENVISAT, OLCI/Sentinel-3, TROPOMI/S-5p and geostationary, for example, Himawari, satellites. Moreover, the synergetic approaches were successfully approved on the synergy of MERIS and AATSR measurements (ESA CAWA-2 project) as well as on the synergy of the ground-based and satellite (AERONET+OLCI, AERONET+ TROPOMI/Sentinel-5p etc retrieval) measurements (ESA GROSAT project (Litvinov et al., 2021), https://www.graspsas.com/projects/grosat/).
In the SYREMIS project we develop the prototyped synergetic retrieval with GRASP algorithm of combined measurements from diverse satellite instruments to bring the accuracy and scope of space-borne aerosol characterization to a new level required for climate studies and air-quality monitoring. In particular, these developments are expected to enhance the accuracy of traditional spectral AOD retrieval and allow the characterization of such aerosol properties as particle size, absorption, and chemical composition. Moreover, the proposed synergetic retrieval is expected to increase essentially the spatial and temporal coverage of the available aerosol product, which is absolutely required to identify aerosol sources and monitor aerosol transport. In this regard, the enhanced synergetic aerosol product is projected to have a significant impact on regional and global climate models (for example, CAMS and MERRA-2 global models). It is also expected to achieve the monitoring of natural or anthropogenic aerosol emissions which is crucial for air quality monitoring.
The synergetic retrieval in SYREMIS project is planned to be tested on the currently operating polar-orbiting (TROPOMI/Sentinel-5p, OLCI/Sentinel-3, SLSTR/Sentinel-3) and geostationary (Himawari) satellites. Moreover, the constellation of these multi-mission satellites is expected to be extended in future by the new generation of satellites like Sentinel-5, 3MI/EPS-SG, Sentinel-4, etc.
The input for the synergetic retrieval may be diverse measurements from different satellites. Themain attention in this project will be played on the operating polar orbiting and geostationary satellites to enhance current state of aerosol characterization and to test the developments on the actual aerosol events. In particular,the multi-mission constellation in this project includes measurements from such polar-orbiting satellites like OLCI/Sentinel-3 A and B, TROPOMI/Sentinel-5p as well as the geostationary Himawari. On one hand such a constellation will extend the spectral range of the measurements. On another hand it will provide unprecedented spatial and temporal coverage which is crucial for global climate studies and air-quality monitoring. Moreover, the synergetic retrieval tested on this constellation can be easily adapted for future instruments like 3MI, Sentinel-5, Sentinel-4 etc.
The brief description of the selected satellites for the prototyped synergetic retrievalis summarized in Table 1.
OLCI/Sentinel-3A and OLCI/Sentinel-3B
– Polar-orbiting, global coverage
– One observation per grid point (4 by 4 pixels)
– Moderate spatial resolution
– Radiance measurements in VIS and NIR spectral range
– Polar-orbiting, global coverage
– Hyperspectral measurements in UV, VIS, NIR, SWIR spectral range
– Geostationary. Coverage area: Asia
– Every 10 min daily measurements
– Radiance measurements in VIS, NIR and SWIR spectral range
Table 1.Multi-mission constellation for prototyped synergetic retrieval
The synergetic multi-mission retrieval developed in SYREMIS is expected to enhance essentially the characterization of such aerosol produced from space-borne measurements as spectral AOD, SSA, and aerosol size characteristics etc. The proposed synergetic retrievals are expected both to improve accuracy of the retrievals and increase spatial and temporal coverage of the aerosol dataset. As a result, the enhanced synergetic aerosol product is expected to be of particularly high value for global climate studies and aerosol data assimilation in global aerosol models such as CAMS and MERRA-2.
2. Dubovik O. et al.,“Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations“ 2011 : Atmospheric Measurement Techniques,
3. O. Dubovik, D, Fuertes, P. Litvinov at al. “A Comprehensive Description of Multi-Term LSM for Applying Multiple a PrioriConstraints in Problems of Atmospheric Remote Sensing: GRASP Algorithm,Concept, and Applications” Front. Remote Sens., 19 October 2021
4. Litvinov P., O. Dubovik, Ch. Cheng, B. Torres,I. Dubovik et al. “Combined Retrieval from Ground Based and Space-borneMeasurements: New Possibilities for Surface Validation and Beyond.” AGU, 1-17December, 2020.