Classifying observed aerosols into types (e.g., urban-industrial, biomass burning, mineral dust, maritime) helps to understand aerosol sources, transformations, effects, and feedback mechanisms; to improve accuracy of satellite retrievals; and to quantify aerosol radiative impacts on climate. The number of aerosol parameters retrieved from spaceborne sensors has been growing, from the initial aerosol optical depth (AOD) at one or a few wavelengths to a list that now includes AOD, complex refractive index, single scattering albedo (SSA), and depolarization of backscatter, each at several wavelengths, plus several particle size and shape parameters. Making optimal use of these varied data products requires objective, multidimensional analysis methods. We describe such a method, which makes explicit use of uncertainties in input parameters. It treats an N-parameter retrieved data point and its N-dimensional uncertainty as an extended data point, E. It then uses a modified Mahalanobis distance, D EC , to assign an observation to the class (cluster) C that has minimum D EC from the point. We use parameters retrieved from the Aerosol Robotic Network (AERONET) to define seven prespecified clusters (pure dust, polluted dust, urban-industrial/developed economy, urban-industrial/developing economy, dark biomass smoke, light biomass smoke, and pure marine), and we demonstrate application of the method to a 5 year record of retrievals from the spaceborne Polarization and Directionality of the Earth's Reflectances 3 (POLDER 3) polarimeter over the island of Crete, Greece. Results show changes of aerosol type at this location in the eastern Mediterranean Sea, which is influenced by a wide variety of aerosol sources.

Abstract. The Cloud Aerosol LIdar with Orthogonal

Abstract. We assess the consistency between instantaneously collocated level-2 aerosol optical depth (AOD) retrievals from MODIS-Aqua (C5) and CALIOP (Version 2 & 3), comparing the standard MODIS AOD (MYD04 L2) data to the AOD calculated from CALIOP aerosol extinction profiles for both the previous release (V2) and the latest release (V3) of CALIOP data. Based on data collected in January 2007, we investigate the most useful criteria for screening the MODIS and CALIOP retrievals to achieve the best agreement between the two data sets. Applying these criteria to eight months of data (Jan, Apr, Jul, Oct 2007 and 2009), we find an order of magnitude increase for the CALIOP V3 data density (by comparison to V2), that is generally accompanied by equal or better agreement with MODIS AOD. Differences in global, monthly mean, over-ocean AOD (532 nm) between CALIOP and MODIS range between 0.03 and 0.04 for CALIOP V3, with CALIOP generally biased low, when all available data from both sensors are considered. Rootmean-squares (RMS) differences in instantaneously collocated AOD retrievals by the two instruments are reduced from values ranging between 0.14 and 0.19 using the unscreened V3 data to values ranging from 0.09 to 0.1 for the screened data. A restriction to scenes with cloud fractions less than 1 % (as defined in the MODIS aerosol retrievals) generally results in improved correlation (R 2 > 0.5), except for the month of July when correlations remain relatively lower. Regional assessments show hot spots in disagreement between the two sensors in Asian outflow during April and off the coast of South Africa in July.

Abstract. Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June–October), aerosol particles reaching 3–5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ∼350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ∼100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.