Validation of GRASP algorithm product from POLDER/PARASOL dataand assessment of multi-angular polarimetry potential for aerosolmonitoring

Abstract. Proven by multiple theoretical and practical studies, multi-angular spectral polarimetry is ideal for comprehensive retrieval of properties of aerosols. Furthermore, a large number of advanced space polarimeters have been launched recently or planned to be deployed in the coming few years (Dubovik et al., 2019). Nevertheless, at present, practical utilization of aerosol products from polarimetry is rather limited, due to the relatively small amount of polarimetric observations compared to photometric observations, as well as challenges in making full use of the extensive information content available in these complex observations. Indeed, while in recent years several new algorithms have been developed to provide enhanced aerosol retrievals from satellite polarimetry, the practical value of available aerosol products from polarimeters yet remains to be proven. In this regard, this paper presents the analysis of aerosol products obtained by the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm from POLDER/PARASOL observations. After about a decade of development, GRASP has been adapted for operational processing of polarimetric satellite observations and several aerosol products from POLDER/PARASOL observations have been released. These updated PARASOL/GRASP products are publicly available (e.g., http://www.icare.univ-lille.fr , www.grasp-open.com/products/ ), the dataset used in the current study is registered under: https://doi.org/10.5281/zenodo.3887265 (Chen et al., 2020). The objective of this study is to comprehensively evaluate the GRASP aerosol products obtained from POLDER/PARASOL observations. First, the validation of the entire 2005–2013 archive was conducted by comparing to ground-based Aerosol Robotic Network (AERONET) data. The subjects of the validation are spectral aerosol optical depth (AOD), aerosol absorption optical depth (AAOD) and single scattering albedo (SSA) at 6 wavelengths, as well as Angstrom exponent (AE), fine mode AOD (AODF) and coarse mode AOD (AODC) interpolated to the reference wavelength 550 nm. Second, an inter-comparison of PARASOL/GRASP products with the PARASOL/Operational, MODIS Dark Target (DT), Deep Blue (DB) and Multi Angle Implementation of Atmospheric Correction (MAIAC) aerosol products for the year 2008 was performed. Over land both satellite data validations and inter-comparisons were conducted separately for different surface types, discriminated by bins of Normalized Difference Vegetation Index (NDVI): High Precision ), Optimized, and Models. These different products are consistent but were obtained using different assumptions in aerosol modeling with different accuracies of atmospheric radiative transfer (RT) calculations. Specifically, when using GRASP/HP or Optimized there is direct retrieval of the aerosol size distribution and spectral complex index of refraction. When using GRASP/Models, the aerosol is approximated by a mixture of several aerosol components, each with their own fixed size distribution and optical properties, and only the concentrations of those components are retrieved. GRASP/HP employs the most accurate RT calculations, while GRASP/Optimized and GRASP/Models are optimized to achieve the best trade-off between accuracy and speed. In all these options, the underlying surface reflectance is retrieved simultaneously with the aerosol properties and the radiative transfer calculations are performed on line during the retrieval. All validation results obtained for the full archive of PARASOL/GRASP products show solid quality of retrieved aerosol characteristics. The GRASP/Models retrievals, however, provided the most solid AOD products, e.g. AOD (550 nm) is unbiased, has the highest correlation (R~0.92) and the highest fraction of retrievals (~55.3 %) satisfying the accuracy requirements of the Global Climate Observing System (GCOS) when compared to AERONET observations. GRASP/HP and GRASP/Optimized AOD products show a non-negligible positive bias (~0.07) when AOD is low ( The results of a comparative analysis of PARASOL/GRASP and MODIS products showed that, based on validation against AERONET, the PARASOL/GRASP AOD (550 nm) product is of similar and sometimes of higher quality compared to the MODIS products. All AOD retrievals are more accurate and in good agreement over ocean. Over land, especially over bright surfaces, the retrieval quality degrades and the differences in total AOD products increase. The detailed aerosol characteristics, such as AE, AODF and AODC from PARASOL/GRASP are generally more reliable, especially over land. The global inter-comparisons of PARASOL/GRASP versus MODIS showed rather robust agreement, though some patterns and tendencies were observed. Over ocean, PARASOL/Models and MODIS/DT AOD agree well with the correlation coefficient of 0.92. Over land, the correlation between PARASOL/Models and the different MODIS products is lower, ranging from 0.76 to 0.85. There is no significant global offset; though over bright surfaces MODIS products tend to show higher values compared to PARASOL/Models when AOD is low, and smaller values for moderate and high AODs. Seasonal means suggest that PARASOL/GRASP products show more biomass burning aerosol loading in central Africa and dust over the Taklamakan Desert, but less AOD in the northern Sahara. It is noticeable also that the correlation for the data over AERONET sites is somewhat higher, suggesting that the retrieval assumptions generally work better over AERONET sites than over the rest of the globe. One of the potential reasons may be that MODIS retrievals, in general, rely more on AERONET climatology than GRASP retrievals. Overall, the analysis shows that the quality of AOD retrieval from multi-angular polarimetric observations like POLDER is at least comparable to those of single-viewing MODIS-like imagers. At the same time, the multi-angular polarimetric observations provide more information on other aerosol properties (e.g. spectral AODF, AODC, AE), as well as additional parameters such as AAOD and SSA.