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.

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 five-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 South-East Atlantic, where they interact with one of the largest subtropical stratocumulus 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, and 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 questions centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects; (b) effects of aerosol absorption on atmospheric circulation and clouds; (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 data set it produced.

During the Observations of Aerosols above Clouds and Their Interactions (ORACLES) 2016 and 2017 field experiments, the Third Generation Advanced Precipitation and Cloud Radar (APR-3) flew aboard the NASA P-3 aircraft taking over 10 million profiles of stratocumulus clouds in the southeast Atlantic Ocean. This study documents cloud structure, precipitation frequency and intensity, and atmospheric stability for each flight during both field experiments. A larger cloud fraction was estimated for 2016, likely due to a larger estimated inversion strength (EIS) in the experiment area (between 6 and 10 K) compared to 2017 where EIS was on average 4–6 K lower. We used an optimal estimation retrieval to derive precipitation rates for all measurable clouds during both experiments. Over 30% of clouds observed during the 2016 experiment exhibited precipitation reaching the surface, but retrieved drizzle rates were below 0.01 mm h−1 in all but 40% of these profiles. This is in sharp contrast to the 2017 campaign where over 53% of precipitating profiles had rainfall rates larger than 0.01 mm h−1. The differences in cloud and rain fractions between the two years are most likely due to differences in the sampling environments; however, enough variations in cloud, virga, and rain fraction exist for similar environmental conditions such that additional analysis of cloud and aerosol interactions—specifically their effect on precipitation processes—needs further exploration. The extensive APR-3 sampling of drizzling stratocumulus under similar thermodynamic conditions provides a rich dataset for examining the influence of biomass burning aerosols on cloud fraction, morphology, and precipitation characteristics in this climatically important region.

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS).The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from groundbased microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the groundbased retrievals.The two closure activities -done for clear-sky scenesuse the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG-and MILOcorrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover -a condition not accounted for in the radiance closure experiments.