Synergistic and Unified Retrieval of Clouds, Aerosols and Precipitation from EarthCARE and the A-Train: the ACM-CAP and CCM-CAP Products

EarthCARE will continue the record of spaceborne radar, lidar, and radiometric measurements that was begun in 2006 by CloudSat, CALIPSO, MODIS and CERES within the A-Train of satellites. EarthCARE’s multispectral imager (MSI), three-view broadband radiometer (BBR), Doppler-capable cloud profiling radar (CPR) and high-spectral resolution atmospheric lidar (ATLID) provide some advances over the instruments within the A-Train, and the single platform will improve the coregistration of synergistic measurements. Ultimately, the greatest novelty of the EarthCARE mission may arise from its highly coordinated L2 production models, which cover products ranging from single-instrument detection, target classification, and retrieval products, to synergistic retrievals, radiative transfer modelling, and finally top-of-atmosphere radiative closure assessment. Central to the ESA L2 production model is the synergistic (ATLID-CPR-MSI) “best estimate” retrieval of all clouds, aerosols and precipitation in the atmosphere, called ACM-CAP. ACM-CAP is based on the CAPTIVATE optimal estimation retrieval algorithm, which includes sophisticated and efficient representations of hydrometeor fallspeeds to constrain ice particle density and raindrop size, ice particle scattering properties, radar and lidar multiple scattering, passive solar, thermal and microwave radiances, and the HETEAC model for aerosol properties. To test our retrieval and enhance scientific continuity between EarthCARE and the A-Train, we have developed an equivalent CloudSat-CALIPSO-MODIS retrieval product, called CCM-CAP, based on the same retrieval algorithm. In this talk we provide an overview of the ACM-CAP product, its capabilities and its place within the EarthCARE ESA production model. Using CCM-CAP, we present case studies and evaluation of the retrieved cloud and precipitation properties, and discuss how the challenges for unified retrievals in complex and layered scenes will inform the regimes of interest for validation and evaluation once EarthCARE data are available.