Particulate brown carbon (BrC) in the atmosphere absorbs light at subvisible wavelengths and has poorly constrained but potentially large climate forcing impacts. BrC from biomass burning has virtually unknown lifecycle and atmospheric stability. Here, BrC emitted from intense wildfires was measured in plumes transported over 2 days from two main fires, during the 2013 NASA SEAC4RS mission. Concurrent measurements of organic aerosol (OA) and black carbon (BC) mass concentration, BC coating thickness, absorption Ångström exponent, and OA oxidation state reveal that the initial BrC emitted from the fires was largely unstable. Using back trajectories to estimate the transport time indicates that BrC aerosol light absorption decayed in the plumes with a half‐life of 9 to 15 h, measured over day and night. Although most BrC was lost within a day, possibly through chemical loss and/or evaporation, the remaining persistent fraction likely determines the background BrC levels most relevant for climate forcing.

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The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the polar orbiter Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) is an elastic backscatter lidar that produces a global uniformly-calibrated aerosol data set. Several Calibration/Validation (Cal/Val) studies for CALIOP conducted with ground-based lidars and CALIOP data showed large aerosol profile disagreements, both random and systematic. In an attempt to better understand these problems, we undertook a series of ground-based lidar measurements in Atlanta, Georgia, which did not provide better agreement with CALIOP data than the earlier efforts, but rather prompted us to investigate the statistical limitations of such comparisons. Meaningful Cal/Val requires intercomparison data sets with small enough uncertainties to provide a check on the maximum expected calibration error. For CALIOP total attenuated backscatter, reducing the noise to the required level requires averaging profiles along the ground track for distances of at least 1,500 km. Representative comparison profiles often cannot be acquired with ground-based lidars because spatial aerosol inhomogeneities introduce systematic error into the averages. These conclusions have implications for future satellite lidar Cal/Val efforts, because planned satellite lidars measuring aerosol backscatter, wind vector, and CO2 concentration profiles may all produce data requiring considerable along-track averaging for meaningful Cal/Val.

Abstract. The expedited near-real-time Level 1.5 CloudAerosol Lidar with Orthogonal Polarization (CALIOP) version 3 products were evaluated against data from the groundbased European Aerosol Research Lidar Network (EAR-LINET). The statistical framework and results of the threeyear evaluation of 48 CALIOP overpasses with ground tracks within a 100 km distance from operating EARLINET stations are presented and include analysis for the following CALIOP classifications of aerosol type: dust, polluted dust, clean marine, clean continental, polluted continental, mixed and/or smoke/biomass burning. For the complete data set comprising both the planetary boundary layer (PBL) and the free troposphere (FT) data, the correlation coefficient (R) was 0.86. When the analysis was conducted separately for the PBL and FT, the correlation coefficients were R = 0.6 and R = 0.85, respectively. From analysis of selected specific cases, it was initially thought that the presence of FT layers, with high attenuated backscatter, led to poor agreement of the PBL backscatter profiles between the CALIOP and EARLINET and prompted a further analysis to filter out such cases; however, removal of these layers did not improve the agreement as R reduced marginally from R = 0.86 to R = 0.84 for the combined PBL and FT analysis, increased marginally from R = 0.6 up to R = 0.65 for the PBL on its own, and decreased marginally from R = 0.85 to R = 0.79 for the FT analysis on its own. This suggests considerable variability, across the data set, in the spatial distribution of the aerosol over spatial scales of 100 km or less around some EARLINET stations rather than influence from elevated FT layers. For specific aerosol types, the correlation coefficient between CALIOP backscatter profiles and the EARLINET data ranged from R = 0.37 for polluted continental aerosol in the PBL to R = 0.57 for dust in the FT.

Abstract. The expedited near-real-time Level 1.5 Cloud–Aerosol Lidar (Light Detection and Ranging) with Orthogonal Polarization (CALIOP) products were evaluated against data from the ground-based European Aerosol Research Lidar Network (EARLINET). Over a period of three years, lidar data from 48 CALIOP overpasses with ground tracks within a 100 km distance from an operating EARLINET station were deemed suitable for analysis and they included a valid aerosol classification type (e.g. dust, polluted dust, clean marine, clean continental, polluted continental, mixed and/or smoke/biomass burning). For the complete dataset comprising both PBL and FT data, the correlation coefficient was 0.86, and when separated into separate layers, the PBL and FT correlation coefficients were 0.6 and 0.85 respectively. The presence of FT layers with high attenuated backscatter led to poor agreement in PBL backscatter profiles between the CALIOP and EARLINET measurements and prompted a further analysis filtering out such cases. However, the correlation coefficient value for the complete dataset decreased marginally from 0.86 to 0.84 while the PBL coefficient increased from 0.6 up to 0.65 and the FT coefficient also decreased from 0.85 to 0.79. For specific aerosol types, the correlation coefficient between CALIOP backscatter profiles and ground-based lidar data ranged from 0.37 for polluted continental aerosol in the planetary boundary layer (PBL) to 0.57 for dust in the free troposphere (FT). The results suggest different levels of agreement based on the location of the dominant aerosol layer and the aerosol type.

We observed the stratospheric aerosol layer at 34° north latitude with a photon-counting 1574 nm lidar on three occasions in 2011. During all of the observations, we also operated a nearby 523.5 nm micropulse lidar and acquired National Weather Service upper air data. We analyzed the lidar data to find scattering ratio profiles and the integrated aerosol backscatter at both wavelengths and then calculated the color ratio and wavelength exponent for lidar backscattering from the stratospheric aerosols. The visible-light integrated backscatter values of the layer were in the range 2.8-3.5×10⁻⁴ sr⁻¹ and the infrared integrated backscatter values ranged from 2.4 to 3.7×10⁻⁵  sr⁻¹. The wavelength exponent was determined to be 1.9±0.2.