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A method for the retrieval of aerosol optical and microphysical properties from in situ light-scattering measurements is presented and the results are compared with existing measurement techniques. The Generalized Retrieval of Aerosol and Surface Properties (GRASP) is applied to airborne and laboratory measurements made by a novel polar nephelometer. This instrument, the Polarized Imaging Nephelometer (PI-Neph), is capable of making high-accuracy field measurements of phase function and degree of linear polarization, at three visible wavelengths, over a wide angular range of 3 to 177°. The resulting retrieval produces particle size distributions (PSDs) that agree, within experimental error, with measurements made by commercial optical particle counters (OPCs). Additionally, the retrieved real part of the refractive index is generally found to be within the predicted error of 0.02 from the expected values for three species of humidified salt particles, with a refractive index that is well established. The airborne measurements used in this work were made aboard the NASA DC-8 aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field campaign, and the inversion of this data represents the first aerosol retrievals of airborne polar nephelometer data. The results provide confidence in the real refractive index product, as well as in the retrieval's ability to accurately determine PSD, without assumptions about refractive index that are required by the majority of OPCs.

The Dark‐target (DT) aerosol algorithm retrieves spectral Aerosol Optical Depth (AOD) and other aerosol properties from Moderate‐resolution Imaging Spectrometer (MODIS) reflectance observations. Over the ocean, the DT algorithm is known to contain scattering‐angle‐dependent biases in its retrievals of AOD, Angstrom Exponent (AE), and Fine Mode Fraction (FMF) for dust aerosols. Following a two‐step strategy to improve the DT retrieval of dust over ocean, for which the first step is to identify dusty pixels (reported in “Part 1”), in this “Part 2,” we report on construction of a new dust model lookup table (LUT) and the strategy for applying it within the existing DT algorithm. In particular, we evaluate different characterizations of dust optical properties from a variety of frameworks and databases, and compare them with the current DT retrieval assumptions. Substituting the standard operational LUT with a spheroid dust model with identified dusty pixels shows significant improvement when compared with collocated AERONET‐identified dusty pixels. Specifically, the application of the new dust model to dusty pixels reduces their AOD bias from 0.06 to 0.02 while improving the fraction of retrievals within expected error from 64% to 82%. At the same time, the overall bias in AE is reduced from 0.13 to 0.06, and the scattering‐angle‐dependent AE bias is largely eliminated. In testing on two full months of data (April and July), the new retrieval will reduce the monthly mean AOD by up to 0.1 and 0.2 in the north Atlantic and Arabian seas, respectively. The average AE and FMF are also reduced in these dust heavy regions

We have developed a method for evaluating the fidelity of the Aerosol Robotic Network (AERONET) retrieval algorithms by mimicking atmospheric extinction and radiance measurements in a laboratory experiment. This enables radiometric retrievals that use the same sampling volumes, relative humidities, and particle size ranges as observed by other in situ instrumentation in the experiment. We use three Cavity Attenuated Phase Shift (CAPS) monitors for extinction and University of Maryland Baltimore County’s (UMBC) three-wavelength Polarized Imaging Nephelometer (PI-Neph) for angular scattering measurements. We subsample the PI-Neph radiance measurements to angles that correspond to AERONET almucantar scans, with simulated solar zenith angles ranging from 50 ∘ to 77 ∘ . These measurements are then used as input to the Generalized Retrieval of Aerosol and Surface Properties (GRASP) algorithm, which retrieves size distributions, complex refractive indices, single-scatter albedos, and bistatic LiDAR ratios for the in situ samples. We obtained retrievals with residuals less than 8% for about 90 samples. Samples were alternately dried or humidified, and size distributions were limited to diameters of less than 1.0 or 2.5 μ m by using a cyclone. The single-scatter albedo at 532 nm for these samples ranged from 0.59 to 1.00 when computed with CAPS extinction and Particle Soot Absorption Photometer (PSAP) absorption measurements. The GRASP retrieval provided single-scatter albedos that are highly correlated with the in situ single-scatter albedos, and the correlation coefficients ranged from 0.916 to 0.976, depending upon the simulated solar zenith angle. The GRASP single-scatter albedos exhibited an average absolute bias of +0.023–0.026 with respect to the extinction and absorption measurements for the entire dataset. We also compared the GRASP size distributions to aerodynamic particle size measurements, using densities and aerodynamic shape factors that produce extinctions consistent with our CAPS measurements. The GRASP effective radii are highly correlated (R = 0.80) and biased under the corrected aerodynamic effective radii by 1.3% (for a simulated solar zenith angle of θ ∘ = 50 ∘ ); the effective variance indicated a correlation of R = 0.51 and a relative bias of 280%. Finally, our apparatus was not capable of measuring backscatter LiDAR ratios, so we measured bistatic LiDAR ratios at a scattering angle of 173 degrees. The GRASP bistatic LiDAR ratios had correlations of 0.71 to 0.86 (depending upon simulated θ ∘ ) with respect to in situ measurements, positive relative biases of 2–10%, and average absolute biases of 1.8–7.9 sr.

This work provides a synopsis of aerosol phase function (F (sub 11)) and polarized phase function (F (sub 12)) measurements made by the Polarized Imaging Nephelometer (PINeph) during the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Deep Convection Clouds and Chemistry (DC3) field campaigns. In order to more easily explore this extensive dataset, an aerosol classification scheme is developed that identifies the different aerosol types measured during the deployments. This scheme makes use of ancillary data that include trace gases, chemical composition, aerodynamic particle size and geographic location, all independent of PI-Neph measurements. The PI-Neph measurements are then grouped according to their ancillary data classifications and the resulting scattering patterns are examined in detail. These results represent the first published airborne measurements of F (sub 11) and minus F (sub 12) divided by F (sub 11) for many common aerosol types. We then explore whether PI-Neph light-scattering measurements alone are sufficient to reconstruct the results of this ancillary data classification algorithm. Principal component analysis (PCA) is used to reduce the dimensionality of the multi-angle PI-Neph scattering data and the individual measurements are examined as a function of ancillary data classification. Clear clustering is observed in the PCA score space, corresponding to the ancillary classification results, suggesting that, indeed, a strong link exists between the angular scattering measurements and the aerosol type or composition. Two techniques are used to quantify the degree of clustering and it is found that in most cases the results of the ancillary data classification can be predicted from PI-Neph measurements alone with better than 85 percent recall. This result both emphasizes the validity of the ancillary data classification as well as the PI-Neph's ability to distinguish common aerosol types without additional information.

Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

A comprehensive understanding of atmospheric aerosols is necessary both to understand Earth's climate as well as produce skillful air quality forecasts. In order to advance our understanding of aerosols, the Laboratory for Aerosols, Clouds and Optics (LACO) has recently developed the Imaging Polar Nephelometer instrument concept for the in situ measurement of aerosol scattering properties. Imaging Nephelometers provide measurements of absolute phase function and polarized phase function over a wide angular range, typically 3 degrees to 177 degrees, with an angular resolution smaller than one degree. The first of these instruments, the Polarized Imaging Nephelometer (PI-Neph), has taken part in five airborne field experiments and is the only modern aerosol polar nephelometer to have flown aboard an aircraft. A method for the retrieval of aerosol optical and microphysical properties from I-Neph measurements is presented and the results are compared with existing measurement techniques. The resulting retrieved particle size distributions agree to within experimental error with measurements made by commercial optical particle counters. Additionally, the retrieved real part of the refractive index is generally found to be within the predicted error of 0.02 from the expected values for three species of humidified salt particles, whose refractive index is well established. A synopsis is then presented of aerosol scattering measurements made by the PI-Neph during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and the Deep Convection Clouds and Chemistry (DC3) field campaigns. To better summarize these extensive datasets a novel aerosol classification scheme is developed, making use of ancillary data that includes gas tracers, chemical composition, aerodynamic particle size and geographic location, all independent of PI-Neph measurements. Principal component analysis (PCA) is then used to reduce the dimensionality of the multi-angle PI-Neph scattering data and the results are examined as a function aerosol type. Strong clustering is observed in the PCA score space, corresponding to the ancillary classification results, suggesting a robust link between the angular scattering measurements and the aerosol type. Retrievals of the DC3 scattering data suggest the presence of a significant amount of mineral dust aerosol in the inflow of storms sampled during this campaign. The retrieved size distributions of all fine mode dominated aerosols measured during SEAC4RS were found to be remarkably similar. There were however consistent differences between the angular light scattering patterns of biomass burning samples and the other fine mode aerosols, which the GRASP retrieval attributed almost entirely to a higher real refractive index in the biomass burning samples.

Cytomegaloviruses (CMV) are highly species-specific due to millennia of co-evolution and adaptation to their host, with no successful experimental cross-species infection in primates reported to date. Accordingly, full genome phylogenetic analysis of multiple new CMV field isolates derived from two closely related nonhuman primate species, Indian-origin rhesus macaques (RM) and Mauritian-origin cynomolgus macaques (MCM), revealed distinct and tight lineage clustering according to the species of origin, with MCM CMV isolates mirroring the limited genetic diversity of their primate host that underwent a population bottleneck 400 years ago. Despite the ability of Rhesus CMV (RhCMV) laboratory strain 68-1 to replicate efficiently in MCM fibroblasts and potently inhibit antigen presentation to MCM T cells in vitro, RhCMV 68-1 failed to productively infect MCM in vivo, even in the absence of host CD8+ T and NK cells. In contrast, RhCMV clone 68-1.2, genetically repaired to express the homologues of the HCMV anti-apoptosis gene UL36 and epithelial cell tropism genes UL128 and UL130 absent in 68-1, efficiently infected MCM as evidenced by the induction of transgene-specific T cells and virus shedding. Recombinant variants of RhCMV 68-1 and 68-1.2 revealed that expression of either UL36 or UL128 together with UL130 enabled productive MCM infection, indicating that multiple layers of cross-species restriction operate even between closely related hosts. Cumulatively, these results implicate cell tropism and evasion of apoptosis as critical determinants of CMV transmission across primate species barriers, and extend the macaque model of human CMV infection and immunology to MCM, a nonhuman primate species with uniquely simplified host immunogenetics.

Purpose Large-panel genomic tumor testing (GTT) is an emerging technology with great promise but uncertain clinical value. Previous research has documented variability in academic oncologists’ perceptions and use of GTT, but little is known about community oncologists’ perceptions of GTT and how perceptions relate to clinicians' intentions to use GTT. Methods Community oncology physicians ( N  = 58) participating in a statewide initiative aimed at improving access to large-panel GTT completed surveys assessing their confidence in using GTT, attitudes regarding the value of GTT, perceptions of barriers to GTT implementation, and future intentions to use GTTs. Descriptive and multivariable regression analyses were conducted to characterize these perceptions and to explore the relationships between them. Results There was substantial variability in clinicians’ perceptions of GTT. Clinicians generally had moderate confidence in their ability to use GTT, but lower confidence in patients’ ability to understand test results and access targeted treatment. Clinicians had positive attitudes regarding the value of GTT. Clinicians’ future intentions to use GTT were associated with greater confidence in using GTT and greater perceived barriers to implementing GTT, but not with attitudes about the value of GTT. Conclusions Community oncologists’ perceptions of large-panel genomic tumor testing are variable, and their future intentions to use GTT are associated with both their confidence in and perceived barriers to its use, but not with their attitudes towards GTT. More research is needed to understand other factors that determine how oncologists perceive and use GTT in clinical practice.

Multijet events at large transverse momentum ($p$T) are measured at $\\sqrt{s}$ = 13 TeV using data recorded with the CMS detector at the LHC, corresponding to an integrated luminosity of 36.3 fb-1. The multiplicity of jets with $p$T > 50 GeV that are produced in association with a high-$p$T dijet system is measured in various ranges of the $p$T of the jet with the highest transverse momentum and as a function of the azimuthal angle difference Δ$\\phi$1,2 between the two highest $p$T jets in the dijet system. The differential production cross sections are measured as a function of the transverse momenta of the four highest $p$T jets. The measurements are compared with leading and next-to-leading order matrix element calculations supplemented with simula tions of parton shower, hadronization, and multiparton interactions. In addition, the measurements are compared with next-to-leading order matrix element calculations combined with transverse-momentum dependent parton densities and transverse-momentum dependent parton shower.

The production of Z bosons associated with jets is measured in pp collisions at $\\sqrt{s}=13\\,\\text {TeV}$ with data recorded with the CMS experiment at the LHC corresponding to an integrated luminosity of 36.3 fb-1. The multiplicity of jets with transverse momentum $p$T > 30 GeV is measured for different regions of the Z boson’s $p$T (Z ), from lower than 10 GeV to higher than 100 GeV. The azimuthal correlation $Δ\\phi$ between the Z boson and the leading jet, as well as the correlations between the two leading jets are measured in three regions of $p$T(Z ). The measurements are compared with several predictions at leading and next-to-leading orders, interfaced with parton showers. Predictions based on transverse-momentum dependent parton distributions and corresponding parton showers give a good description of the measurement in the regions where multiple parton interactions and higher jet multiplicities are not important. The effects of multiple parton interactions are shown to be important to correctly describe the measured spectra in the low $p$T(Z ) regions.