Overview of remote sensing multi-instrument synergy retrieval realized using GRASP retrieval platform

Generalized Retrieval of Atmosphere and Surface Properties (GRASP) is an algorithm provided as open-source software for remote sensing observations (Dubovik et al., 2021). The algorithm is designed for the interpretation of diverse remote sensing observations and is suitable for realizing synergetic processing using observations from multiple sensors. GRASP is based on several fundamental principles. It utilizes complete and rigorous modeling of atmospheric radiation applicable for simulating a variety of observations. The numerical inversion is implemented as an elaborated, statistically optimized fitting following the Multi-Term Least Square (MTLS) minimization concept, which serves as the basis for the efficient combination of different observations. For example, this concept allows for the use of multiple a priori constraints, which are essential when retrieving a large number of parameters of different types (e.g., describing properties of aerosols, gases, surface reflectance, etc.). This concept is also applied in “multi-pixel retrieval” scenarios, where the retrieval is implemented simultaneously for a large group of coordinated observations (such as observations in different satellite pixels). By processing these observations together, the retrieval incorporates prior knowledge regarding the temporal and spatial variability of the retrieved parameters. For instance, land surface reflectance tends to remain stable over weeks, while aerosols can change within hours or days. Similarly, aerosol properties typically vary minimally across several kilometers, whereas the land surface can exhibit high spatial heterogeneity. The algorithm’s design for interpreting diverse remote sensing data makes it ideal for the synergetic processing of observations from multiple sensors. This approach enables efficient synergy even for observations that are not fully coincident or co-located.

At present, GRASP has been used to develop a number of synergy retrievals. This presentation overviews and discusses the following key GRASP applications:

- Ground-based remote sensing synergies:

- Sun/sky-radiometer + lidar;

- Sun/sky-radiometer + Pandora spectrometer;

- Sun/sky-radiometer + Pandora spectrometer + lidar;

- Satellite remote sensing synergies:

- combining the same platform instruments with different capabilities (e.g. radiometers + spectrometers measuring;  radiometers + lidars; combining   UV, VIS, SWIR and TIR measurements, etc.);

- multi-platform LEO + LEO observations;

- multi-platform LEO + GEO observations;

- Satellite + ground-based remote sensing synergies:

-retrieval both atmospheric and surface reflectance properties from co-located ground-based and satellite observations.

The discussed developments are realized using observations from Copernicus Sentinel-2, -3, -5P, MTG, EPS-SG, and EarthCARE, and are implemented within the frameworks of the EU PANORAMA, ESA AIRSENSE, EarthCARE+, and other projects.

Dubovik, O., D. Fuertes, P. Litvinov, et al. , “A Comprehensive Description of Multi- Term LSM for Applying Multiple a Priori Constraints in Problems of Atmospheric Remote Sensing: GRASP Algorithm, Concept, and Ap-plications”, Front. Remote Sens. 2:706851. doi: 10.3389/frsen.2021.706851, 2021.