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Abstract. Field-deployable real-time aerosol mass spectrometers (AMSs) typically use an aerodynamic lens as an inlet that collimates aerosols into a narrow beam over a wide range of particle sizes. Such lenses need constant upstream pressure to work consistently. Deployments in environments where the ambient pressure changes, e.g., on aircraft, typically use pressure-controlled inlets (PCIs). These have performed less well for supermicron aerosols, such as the larger particles in stratospheric air and some urban hazes. In this study, we developed and characterized a new PCI design (“CU PCI-D”) coupled with a recently developed PM2.5 aerodynamic lens, with the goal of sampling the full accumulation mode of ambient aerosols with minimal losses up to upper troposphere and lower stratosphere (UTLS) altitudes. A new computer-controlled lens alignment system and a new 2D particle beam imaging device that improves upon the Aerodyne aerosol beam width probe (BWP) have been developed and tested. These techniques allow for fast automated aerosol beam width and position measurements and ensure the aerodynamic lens is properly aligned and characterized for accurate quantification, in particular for small sizes that are hard to access with monodisperse measurements. The automated lens alignment tool also allows position-dependent thermal decomposition to be investigated on the vaporizer surface. The CU PCI-D was tested on the TI3GER campaign aboard the NCAR/NSF G-V aircraft. Based on comparisons with the co-sampling UHSAS particle sizer, the CU aircraft AMS with the modified PCI consistently measured ∼ 89 % of the accumulation-mode particle mass in the UTLS. 

Abstract. Aircraft-based measurements enable large-scale characterization of gas-phase atmospheric composition, but these measurements are complicated by the challenges of sampling from high-speed flow. Under such sampling conditions, the sample flow will likely experience turbulence, accelerating and mixing of potential contamination of the gas-phase from the condensed-phase components on walls, and reduced vapor transmission due to losses to the inner walls of the sampling line. While a significant amount of research has gone into understanding aerosol sampling efficiency for aircraft inlets, a similar research investment has not been made for gas sampling. Here, we analyze the performance of a forward-facing laminar flow gas inlet to establish its performance as a function of operating conditions, including ambient pressure, freestream velocities, and sampling conditions. Using computational fluid dynamics (CFD) modeling we simulate flow inside and outside the inlet to determine the extent of freestream turbulent interaction with the sample flow and its implication for gas sample transport. The CFD results of flow features in the inlet are compared against measurements of air speed and turbulent intensity from full-sized high-speed wind tunnel experiments. These comparisons suggest that the Reynolds-averaged Navier–Stokes (RANS) CFD simulations using the shear stress transport (SST) modeling approach provide the most reasonable prediction of the turbulence characteristics of the inlet. 

Abstract. Aircraft-based measurements enable large-scale characterization of gas-phase atmospheric composition, but these measurements are complicated by the challenges of sampling from high-speed flow. Under such sampling conditions, the sample flow will likely experience turbulence, accelerating | mixing of potential contamination of the gas-phase from the condensed-phase components on walls and reduced vapor transmission due to losses to the inner walls of the sampling line. While a significant amount of research has gone into understanding aerosol sampling efficiency for aircraft inlets, a similar research investment has not been made for gas sampling. Here, we analyze the performance of a forward-facing laminar flow gas inlet to establish its performance as a function of operating conditions, including ambient pressure, freestream velocities, and sampling conditions. Using computational fluid dynamics (CFD) modeling we simulate flow inside and outside the inlet to determine the extent of freestream turbulent interaction with the sample flow and its implication for gas sample transport. The CFD results of flow features in the inlet are compared against measurements of air speed and turbulent intensity from full-sized high-speed wind-tunnel experiments. These comparisons suggest that the Reynolds Averaged Navier-Stokes (RANS) CFD simulations using the Shear Stress Transport (SST) modeling approach provide the most reasonable prediction of the turbulence characteristics of the inlet. 

ABSTRACT We present the high-z quasar candidate archive (HzQCA), summarizing the spectroscopic observations of 207 z ≳ 5 quasar candidates using Keck/LRIS, Keck/MOSFIRE, and Keck/NIRES. We identify 14 candidates as z ∼ 6 quasars, with 10 of them newly reported here and 63 candidates as brown dwarfs. In the remaining sources, 79 candidates are unlikely to be quasars; 2 sources are inconclusive; the others could not be fully reduced or extracted. Based on the classifications, we investigate the distributions of quasars and contaminants in colour space with photometry measurements from DELS (z), VIKING/UKIDSS (YJHKs/YJHK), and unWISE (W1W2). We find that the identified brown dwarfs are consistent with the empirical brown dwarf model that is commonly used in quasar candidate selection methods. To refine spectroscopic confirmation strategies, we simulate synthetic spectroscopy of high-z quasars and contaminants for all three instruments. The simulations utilize the spectroscopic data in HzQCA. We predict the required exposure times for quasar confirmation and propose an optimal strategy for spectroscopic follow-up observations. For instance, we demonstrate that we can identify a mJ = 21.5 at z = 7.6 or a mJ = 23.0 at z = 7.0 within 15 min of exposure time with LRIS. With the publication of the HzQCA, we aim to provide guidance for future quasar surveys and candidate classification. 

Abstract We present 123 cloud-resolving simulations to study how temperatures of anvil clouds and radiative tropopause (RT) change with surface warming. Our simulation results show that the RT warms at approximately the same rate as anvil clouds. This relationship persists across a variety of modeling choices, including surface temperature, greenhouse gas concentration, and the representation of radiative transfer. We further show that the shifting ozone profile associated with climate warming may give rise to a fixed RT temperature as well as a fixed anvil temperature. This result points to the importance of faithful treatment of ozone in simulating clouds and climate change; the robust anvil–RT relationship may also provide alternative ways to understand what controls anvil temperature. 

Abstract Convective self-aggregation refers to a phenomenon in which random convection can self-organize into large-scale clusters over an ocean surface with uniform temperature in cloud-resolving models. Previous literature studies convective aggregation primarily by analyzing vertically integrated (VI) moist static energy (MSE) variance. That is the global MSE variance, including both the local MSE variance at a given altitude and the covariance of MSE anomalies between different altitudes. Here we present a vertically resolved (VR) MSE framework that focuses on the local MSE variance to study convective self-aggregation. Using a cloud-resolving simulation, we show that the development of self-aggregation is associated with an increase of local MSE variance, and that the diabatic and adiabatic generation of the MSE variance is mainly dominated by the boundary layer (BL; the lowest 2 km). The results agree with recent numerical simulation results and the available potential energy analyses showing that the BL plays a key role in the development of self-aggregation. Additionally, we find that the lower free troposphere (2–4 km) also generates significant MSE variance in the first 15 days. We further present a detailed comparison between the global and local MSE variance frameworks in their mathematical formulation and diagnostic results, highlighting their differences. 

Abstract The subject of electromagnetism has often been called electrodynamics to emphasize the dominance of the electric field in dynamic light–matter interactions that take place under non-relativistic conditions. Here we show experimentally that the often neglected optical magnetic field can nevertheless play an important role in a class of optical nonlinearities driven by both the electric and magnetic components of light at modest (non-relativistic) intensities. We specifically report the observation of magneto-electric rectification, a previously unexplored nonlinearity at the molecular level which has important potential for energy conversion, ultrafast switching, nano-photonics, and nonlinear optics. Our experiments were carried out in nanocrystalline pentacene thin films possessing spatial inversion symmetry that prohibited second-order, all-electric nonlinearities but allowed magneto-electric rectification.