One-and-half Decade Long Global Retrieval Dataset of UV-VIS Spectral Optical Depth and Single-scattering Albedo of Absorbing Aerosols above Clouds from A-train Active-Passive Synergy

Active and passive sensors onboard satellites and suborbital measurements have shown frequent aerosol-cloud overlapping situations over several regions worldwide on a monthly to seasonal scale. However, retrieving the optical properties of aerosols lofted over clouds poses challenges. Primarily, the assumption of aerosol single-scattering albedo (SSA) in the satellite-based algorithms is known to be one of the largest sources of uncertainty in quantifying the above-cloud aerosol optical depth (ACAOD). On the radiative forcing aspect, the sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the aerosol loading, the absorption capacity of aerosols (SSA), and the brightness of the underlying cloud cover.

 

We contribute to addressing the uncertainties surrounding the absorbing aerosols-cloud radiative interactions by offering a novel, NASA’s A-train-centric, one-and-half decade long (2006-2022) global retrieval product of aerosols above cloud that delivers 1) spectral ACAOD, 2) spectral SSA of light-absorbing aerosols lofted over the clouds, and 3) aerosol-corrected cloud optical depth (COD). The synergy algorithm combines lidar retrievals of ACAOD derived from the ‘De-polarization Ratio’ method applied to CALIOP and the top-of-atmosphere (TOA) spectral reflectance from OMI (354-388 nm) and MODIS (470-860 nm) sensors to deduce the joint aerosol-cloud product. The availability of accurate ACAOD accompanied by a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD allow retrieval of SSA for above-cloud aerosols scenes using the ‘color ratio’ algorithm applied to UV and VIS sensors.

 

We will present multiyear (2006-2022), regional retrievals of UV-VIS spectral aerosol SSA above clouds, and it’s a comparison against ORACLES airborne in situ and remote sensing measurements and ground-based AERONET inversions. A preliminary uncertainty analysis suggests that an uncertainty of 20% in ACAOD can result in an error of ~0.02 at 388 nm and ~0.01 at 470 nm in the retrieved SSA from OMI and MODIS, respectively. Furthermore, the presented aerosol-cloud remote sensing algorithm assumes implications for the recently launched EarthCARE and PACE missions with potential synergy of ATLID lidar and OCI imager. The availability of the global aerosol-cloud joint product will reenergize the community by offering 1) an improved representation of aerosol extinction and absorption properties over clouds and 2) much-needed observational estimates of the radiative effects of aerosols in cloudy regions for constraining the climate models.