Surface Validation Dataset in Worldwide Locations Based on the Synergetic Retrieval from Satellite and Ground Based Measurements

Remote sensing is the main source of information about global state of atmosphere and surface. During the last decade a big progress has been achieved in aerosol, cloud and trace gasses characterization from space-borne and ground-based remote sensing.

Ground-based AERONET direct measurement and inversion products are the main validation dataset for satellite aerosol retrieval. Despite of evident need of the universal, global and robust reference dataset for surface, it still does not exist.

Essential enhancement of the surface retrieval accuracy, as well as its unification, can be achieved by inverting simultaneously AERONET ground-based and satellite measurements. In such approach the main information about aerosol comes from AERONET direct sun and diffuse sky-radiance measurements, whereas the information about surface reflection properties originates from satellite observations. This approach has already been implemented in GRASP retrieval developments in the frame of ESA GROSAT project (www.grasp-sas.com/projects/grosat). On one hand such combined synergetic retrieval allows robust generation of the global surface reference dataset. On another hand it allows investigating the limitation/uncertainties of aerosol and surface forward models and their effect on retrieval.

The forward models used in the inversion of remote sensing measurements are based on certain physical approximations and assumptions, which are related to specific measurement characteristics of an instrument. These "forward model limitations/uncertainties" may essentially limit the possibility of synergetic retrieval from different instrument with diverse measurement capabilities. Moreover, they always manifest themselves in parameters retrieved from remote sensing.

Here, on the basis of the new possibilities of GROSAT combined retrieval, we present the surface reference dataset obtained from diverse space-borne instruments: PARASOL, S5P/TROPOMI, S2 and S3/OLCI. Considering different forward approaches in aerosol and surface modeling (Dubovik et al., 2022, 2011, 2014; Litvinov at al., 2011; 2012) the manifestation of the forward model uncertainties in the surface reference dataset will be discussed.