The Impact of Arctic Aerosols on Clouds During one flight leg over the water on 4 April, large chunks of ice were seen floating in the Arctic Ocean after breaking up from the ice sheet along the coastline near Barrow, Alaska. Photo by Alexei Korolev.

[1] A modeling study of a low-lying mixed-phase cloud layer observed on 8 April 2008 during the Indirect and Semi-Direct Aerosol Campaign is presented. Large-eddy simulations with size-resolved microphysics were used to test the hypothesis that heterogeneous ice nucleus (IN) concentrations measured above cloud top can account for observed ice concentrations, while also matching ice size distributions, radar reflectivities, and mean Doppler velocities. The conditions for the case are favorable for the hypothesis: springtime IN concentrations are high in the Arctic, the predominant ice habit falls slowly, and overlying IN concentrations were greater than ice particle number concentrations. Based on particle imagery, we considered two dendrite types, broad armed (high density) and stellar (low density), in addition to high and low density aggregates. Two simulations with low-density aggregates reproduced observations best overall: one in which IN concentrations aloft were increased fourfold (as could have been present above water saturation) and another in which initial IN concentrations were vertically uniform. A key aspect of the latter was an IN reservoir under the well-mixed cloud layer: as the simulations progressed, the reservoir IN slowly mixed upward, helping to maintain ice concentrations close to those observed. Given the uncertainties of the measurements and parameterizations of the microphysical processes embedded in the model, we found agreement between simulated and measured ice number concentrations in most of the simulations, in contrast with previous modeling studies of Arctic mixed-phase clouds, which typically show a large discrepancy when IN are treated prognostically and constrained by measurements.

[1] Ambient particles and the dry residuals of mixed-phase cloud droplets and ice crystals were collected during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) near Barrow, Alaska, in spring of 2008. The collected particles were analyzed using Computer Controlled Scanning Electron Microscopy with Energy Dispersive X-ray analysis and Scanning Transmission X-ray Microscopy coupled with Near Edge X-ray Absorption Fine Structure spectroscopy to identify physico-chemical properties that differentiate cloud-nucleating particles from the total aerosol population. A wide range of individually mixed components was identified in the ambient particles and residuals including organic carbon compounds, inorganics, carbonates, and black carbon. Our results show that cloud droplet residuals differ from the ambient particles in both size and composition, suggesting that both properties may impact the cloud-nucleating ability of aerosols in mixed-phase clouds. The percentage of residual particles which contained carbonates (47%) was almost four times higher than those in ambient samples. Residual populations were also enhanced in sea salt and black carbon and reduced in organic compounds relative to the ambient particles. Further, our measurements suggest that chemical processing of aerosols may improve their cloud-nucleating ability.Comparison of results for various time periods within ISDAC suggests that the number and composition of cloud-nucleating particles over Alaska can be influenced by episodic events bringing aerosols from both the local vicinity and as far away as Siberia.

We present an algorithm for computing the probability density function of the product of two independent random variables, along with an implementation of the algorithm in a computer algebra system. We combine this algorithm with the earlier work on transformations of random variables to create an automated algorithm for convolutions of random variables. Some examples demonstrate the algorithm's application.

Atmospheric aerosols have major impacts on regional and global climate through scattering and absorption of solar radiation. A new instrument, the Cloud and Aerosol Spectrometer with Polarization (CASPOL) from Droplet Measurement Technologies measures light scattered by aerosols in the forward (4° to 12°) and backward (168° to 176°) directions, with an additional polarized detector in the backward direction. Scattering by a single particle can be measured by all three detectors for aerosols in a broad range of sizes, 0.6 μm < diameter < 50 μm. The CASPOL is a unique measurement tool, since unlike most in-situ probes, it can measure optical properties on a particle-by-particle basis. In this study, single particle CASPOL measurements for thirteen atmospherically relevant dusts were obtained and their optical scattering signatures were evaluated. In addition, Scanning Electron Microscopy (SEM) was used to characterize the shape and morphology of each type of dust. The total and polarized backscatter intensities varied with particle size for all dust types. Using a new optical signature technique all but one dust type could be categorized into one of three optical scattering groups. Additionally, a composite method was used to derive the optical signature of Arizona Test Dust (ATD) by combining the signatures of its major components. The derived signature was consistent with the measured signature of ATD. Finally, calculated backscattering cross sections for representative dust from each of the three main groups were found to vary by as much as a factor of 7, the difference between the backscattering cross sections of white quartz (5.3 &times; 10^&minus;10 cm⁻²) and hematite (4.1 &times; 10^&minus;9 cm⁻²)