Using a Ten-Year Collocated MODIS, CALIOP, and Model Dataset to Explore the First Aerosol Indirect Effect over Southeast Asia

Over the greater Southeast Asia and Maritime Continent, satellite observations and model simulations cannot by themselves give full insight into relationships between clouds and aerosols. Southeast Asia is particularly sensitive to changes in precipitation, but has some of the world's largest observability and predictability challenges. Here we present a new collocated dataset designed to tackle these challenges: the Curtain Cloud-Aerosol Regional A-Train dataset, or CCARA. CCARA combines satellite observations from Aqua's Moderate-resolution Imaging Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) with the Navy Aerosol Analysis and Prediction System (NAAPS). CCARA is designed with the capability to investigate aerosol-cloud relationships and provides coincident and vertically resolved cloud and aerosol observations for a ten-year period. Using model reanalysis aerosol fields from the NAAPS and coincident cloud liquid effective radius retrievals from MODIS (removing cirrus contamination using CALIOP), we investigate the first aerosol indirect effect. We find overall that, as expected, aerosol loading anti-correlates with cloud effective radius, with maximum sensitivity in cumulous mediocris clouds with heights in the 3-4.5 km level. The highest sensitivity in droplet effective radius to modeled aerosol perturbations in particle concentrations were found in the more remote regions of the western Pacific Ocean and Indian Ocean. Conversely, there was much less variability in cloud droplet size near emission sources over both land and water. We hypothesize this is suggestive of a high background aerosol population already saturating the cloud condensation nuclei budget. Future work will incorporate CloudSat precipitation observations into CCARA to further investigate aerosol indirect effects, namely aerosol-precipitation relationships.