Airborne Validation of Cloud Spatial Properties from the ATLID Instrument on EarthCARE

Abstract. The Goddard Lidar Observation and Validation Experiment (GLOVE) was a field campaign conducted from 27 January to 28 February 2025, at the NASA Armstrong Flight Research Center, situated at Edwards Air Force Base in California. One main objective of GLOVE was to validate atmospheric data products, including clouds and precipitation, obtained from the Earth Cloud, Aerosol, and Radiation Explorer (EarthCARE) satellite mission. Using the NASA high-altitude ER-2 aircraft, GLOVE deployed the Cloud Physics Lidar (CPL) to capture vertical profiles of aerosols and cloud features along EarthCARE's flight paths. This study validates the EarthCARE baselines BA and BD Atmospheric Lidar (ATLID) Level 2A Target Classification (A-TC) and Cloud Top Height (A-CTH) products against CPL observations from GLOVE. Results show substantial agreement between ATLID and CPL, with a better alignment under homogeneous than heterogeneous conditions, likely driven by ATLID's spatial averaging and multiple scattering effects. In addition, ATLID detects a higher fraction of cloud features than CPL, especially in baseline BA, with a mean probability of detection of 0.85, though at the expense of a higher false-positive rate, misclassifying about 7.6 % of clear-sky pixels as cloudy. Baseline BD has a smaller probability of detection (0.74) but reduces the false-positive rate to 4.8 %. Overall, cloud top height retrievals show good agreement with CPL. A-TC provides broader sample coverage with relatively good performance, while A-CTH retrieves fewer samples due to a stricter detection threshold, but achieves lower absolute errors and higher correlations. Results for baselines BA and BD show that the majority of samples in both A-TC and A-CTH meet the ATLID cloud top error requirement, with at least 76 % of cloud top estimates falling below the 0.3 km error threshold. The findings here highlight the role of spatial averaging, multiple scattering, and cloud heterogeneity in ATLID retrievals, factors that should be considered when using ATLID cloud products.