Aeolus lidar surface return (LSR) at 355 nm as a new Aeolus Level-2A product
Authors: Labzovskii Lev D. , van Zadelhoff Gerd-Jan , Donovan David P. , de Kloe Jos , Tilstra L. Gijsbert , Stoffelen Ad , Josset Damien , Stammes Piet 
Published: December 2024

Abstract. The Atmospheric Laser Doppler Instrument (ALADIN) aboard Aeolus was the first spaceborne high-resolution lidar and measured vertical profiles of aerosol optical properties at 355 nm at an incidence angle of ∼ 35°. Although Aeolus was primarily developed to provide vertical profiles of wind speed, aerosols and cloud products, its lidar surface returns (LSRs) have been shown to contain useful information about ultraviolet (UV) surface reflectivity and have agreed well with passive remote sensing reflectance. With a focus on the process to incorporate the LSR algorithm into the Aeolus Level-2A product, we describe the methodology and evaluate the results of the adopted LSR retrieval. The algorithm combines attenuated backscattering parameters (Level-2 Aeolus Profile Processor Algorithm, L2 AEL-PRO, data) with information on the surface bin detection (Level-1 data) to produce attenuated LSR estimates (e.g., surface-integrated attenuated backscatter) for all bins where the ground was detected. The correction for producing final LSR estimates at the original Aeolus resolution is performed using the Aeolus L2 retrievals, namely, the aerosol optical depth (AOD) and Rayleigh optical depth, to ensure that LSRs are free of the effects of atmospheric attenuating features, such as optically thick clouds and thick aerosol conditions (AOD > 1.0). The evaluation shows that Aeolus LSR estimates produced using this approach agree well with the UV Lambertian-equivalent reflectivity (LER) from the Global Ozone Monitoring Experiment-2 (GOME-2; LERG) and TROPOspheric Monitoring Instrument (TROPOMI; LERT) climatologies at all spatial scales. For four reference orbits (10 September 2018, 30 November 2018, 11 January 2019 and 1 May 2019), all cloud and aerosol-free LSR estimates agree well with both LER references, with correlation coefficient (r) values varying from 0.55 to 0.71. For monthly scales, the agreement was moderate to high for the LSR–LERT comparison (r = 0.61–0.77 depending on the month) and weak to moderate for the LSR–LERG comparison (r = 0.44–0.64). Globally, the averaged 2.5° × 2.5° LSR estimates exhibit very high agreement with both the LERG (0.90) and LERT (0.92) references. With respect to reproducing the regional monthly dynamics, LSR and LER agree very well in snow- or ice-covered regions (r > 0.90), semiarid regions (r > 0.90), arid regions (r > 0.70), and some regions with mixed vegetation (like Australia; r = 0.94), whereas no agreement was found for ocean regions due to the Aeolus optical setup, which is favorable for the ocean subsurface but not for direct surface backscatter probing. We unveiled four reflectivity clusters of LSRs at the 2.5° × 2.5° grid scale, manifesting a transition from white to darker surfaces in descending LSR magnitude order: (1) ice, (2) snow, (3) surface without snow and (4) water. Regionally, the LSR–LER agreement can vary and yields the highest correlation values in regions where snow is present in winter, indicating the excellent sensitivity of Aeolus LSRs to white surfaces such as snow. This finding is corroborated by the very good agreement of LSRs with modeled snow cover that we demonstrated (r = 0.62–0.74 between these parameters in such regions), while the sensitivity to purely vegetation-driven changes in the surface is lower, as indicated by the comparison between LSRs and the normalized difference vegetation index (NDVI) without snow (r < 0.30 in the regional analysis). By demonstrating the usability of LSRs for scientific applications at non-nadir angles, our work deepens the knowledge about LSRs, which has mostly been based on nadir-looking Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) studies in the past. Using experiences from both the nadir-looking CALIPSO and the highly non-nadir Aeolus mission, a framework for the effective LSR utilization using future lidar missions such as EarthCARE and Aeolus-2 can be effectively designed.