Constraints on Aerosol Direct Effects From Simultaneous Retrievals of Aerosol Optical Depth and Effective Radius Near Clouds

Aerosol-cloud interactions continue to contribute significant uncertainty to radiative forcing calculations. While comprehensive aerosol retrieval algorithms using passive satellite observations have been developed for areas far from clouds, retrievals in near-cloud regions are often discarded due to complicating factors such as three-dimensional cloud radiative effects. Consequently, these transition regions between clouds and clear sky remain largely under-explored.

To better understand the interaction of near-cloud aerosols with clouds and radiation, we will introduce a newly developed machine-learning method to simultaneously retrieve their aerosol optical depth and effective radius. The joint retrieval is critical for separating the contribution of aerosol load and particle size, which offers insights into aerosol hygroscopic growth and other associated physical and dynamic processes. Evaluation of retrievals against aircraft data will be shown. Case studies using MODIS (The Moderate Resolution Imaging Spectroradiometer) and GOES (Geostationary Operational Environmental Satellite) measurements during the EUREC⁴A (European Elucidating the Role of Clouds-Circulation Coupling in Climate) experiment in the Caribbean will be discussed, focusing on the direct radiative effects of near-cloud aerosols, and findings that will shed lights on modeling aerosol-radiation interactions.