Comparison of Observed and Simulated Drop Size Distributions From Large Eddy Simulations With Bin Microphysics

Two case studies of marine stratocumulus (one nocturnal and drizzling, the other daytime and nonprecipitating) are simulated by the UCLA large-eddy simulation model with bin microphysics for comparison with aircraft in situ observations. A high-bin-resolution variant of the microphysics is implemented for closer comparison with cloud drop size distribution (DSD) observations and a turbulent collision–coalescence kernel to evaluate the role of turbulence on drizzle formation. Simulations agree well with observational constraints, reproducing observed thermodynamic profiles (i.e., liquid water potential temperature and total moisture mixing ratio) as well as liquid water path. Cloud drop number concentration and liquid water content profiles also agree well insofar as the thermodynamic profiles match observations, but there are significant differences in DSD shape among simulations that cause discrepancies in higher-order moments such as sedimentation flux, especially as a function of bin resolution. Counterintuitively, high-bin-resolution simulations produce broader DSDs than standard resolution for both cases. Examination of several metrics of DSD width and percentile drop sizes shows that various discrepancies of model output with respect to the observations can be attributed to specific microphysical processes: condensation spuriously creates DSDs that are too wide as measured by standard deviation, which leads to collisional production of too many large drops. The turbulent kernel has the greatest impact on the low-bin-resolution simulation of the drizzling case, which exhibits greater surface precipitation accumulation and broader DSDs than the control (quiescent kernel) simulations. Turbulence effects on precipitation formation cannot be definitively evaluated using bin microphysics until the artificial condensation broadening issue has been addressed

Stratocumulus Cloud Clearings and Notable Thermodynamic and Aerosol Contrasts across the Clear–Cloudy Interface

Data from three research flights, conducted over water near the California coast, are used to investigate the boundary between stratocumulus cloud decks and clearings of different sizes. Large clearings exhibit a diurnal cycle with growth during the day and contraction overnight and a multiday life cycle that can include oscillations between growth and decay, whereas a small coastal clearing was observed to be locally confined with a subdiurnal lifetime. Subcloud aerosol characteristics are similar on both sides of the clear–cloudy boundary in the three cases, while meteorological properties exhibit subtle, yet important, gradients, implying that dynamics, and not microphysics, is the primary driver for the clearing characteristics. Transects, made at multiple levels across the cloud boundary during one flight, highlight the importance of microscale (~1 km) structure in thermodynamic properties near the cloud edge, suggesting that dynamic forcing at length scales comparable to the convective eddy scale may be influential to the larger-scale characteristics of the clearing. These results have implications for modeling and observational studies of marine boundary layer clouds, especially in relation to aerosol–cloud interactions and scales of variability responsible for the evolution of stratocumulus clearings

Organization of Block Copolymers using NanoImprint Lithography: Comparison of Theory and Experiments

We present NanoImprint lithography experiments and modeling of thin films of block copolymers (BCP). The NanoImprint lithography is used to align perpendicularly lamellar phases, over distances much larger than the natural lamellar periodicity. The modeling relies on self-consistent field calculations done in two- and three-dimensions. We get a good agreement with the NanoImprint lithography setups. We find that, at thermodynamical equilibrium, the ordered BCP lamellae are much better aligned than when the films are deposited on uniform planar surfaces

Statistical comparison of properties of simulated and observed cumulus clouds in the vicinity of Houston during the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS)

We present statistical comparisons of properties of clouds generated by Large Eddy Simulations (LES) with aircraft observations of nonprecipitating, warm cumulus clouds made in the vicinity of Houston, TX during the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS), carried out in the summer of 2006. Aircraft data were sampled with the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) Twin Otter airplane. Five flights (days) that are most suitable for studying aerosol-cloud interactions are selected from the 22 flights. The model simulations are initiated with observed environmental profiles. The simulations are used to generate an ensemble of thousands of cumulus clouds for statistically meaningful evaluations. Statistical comparisons focus on the properties of a set of dynamical and thermodynamical variables, sampled either in the cloud or the cloud updraft core. The set of variables includes cloud liquid water content (LWC), number mixing ratio of cloud droplets (Nd), cloud effective radius (re), updraft velocity (w), and the distribution of cloud sizes. In general, good agreement between the simulated and observed clouds is achieved in the normalized frequency distribution functions, the profiles averaged over the cloudy regions, the cross-cloud averages, and the cloud size distributions, despite big differences in sample size between the model output and the aircraft data. Some unresolved differences in frequency distributions of w and possible differences in cloud fraction are noted. These comparisons suggest that the LES is able to successfully generate the cumulus cloud populations that were present during GoMACCS. The extent to which this is true will depend on the specific application

Efficient multiphoton sampling of molecular vibronic spectra on a superconducting bosonic processor

The efficient simulation of quantum systems is a primary motivating factor for developing controllable quantum machines. For addressing systems with underlying bosonic structure, it is advantageous to utilize a naturally bosonic platform. Optical photons passing through linear networks may be configured to perform quantum simulation tasks, but the efficient preparation and detection of multiphoton quantum states of light in linear optical systems are challenging. Here, we experimentally implement a boson sampling protocol for simulating molecular vibronic spectra [Nature Photonics $\textbf{9}$, 615 (2015)] in a two-mode superconducting device. In addition to enacting the requisite set of Gaussian operations across both modes, we fulfill the scalability requirement by demonstrating, for the first time in any platform, a high-fidelity single-shot photon number resolving detection scheme capable of resolving up to 15 photons per mode. Furthermore, we exercise the capability of synthesizing non-Gaussian input states to simulate spectra of molecular ensembles in vibrational excited states. We show the re-programmability of our implementation by extracting the spectra of photoelectron processes in H$_2$O, O$_3$, NO$_2$, and SO$_2$. The capabilities highlighted in this work establish the superconducting architecture as a promising platform for bosonic simulations, and by combining them with tools such as Kerr interactions and engineered dissipation, enable the simulation of a wider class of bosonic systems

Aerosol-cloud relationships in continental shallow cumulus

Aerosol-cloud relationships are derived from 14 warm continental cumuli cases sampled during the 2006 Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS) by the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft. Cloud droplet number concentration is clearly proportional to the subcloud accumulation mode aerosol number concentration. An inverse correlation between cloud top effective radius and subcloud aerosol number concentration is observed when cloud depth variations are accounted for. There are no discernable aerosol effects on cloud droplet spectral dispersion; the averaged spectral relative dispersion is 0.30 ± 0.04. Aerosol-cloud relationships are also identified from comparison of two isolated cloud cases that occurred under different degrees of anthropogenic influence. Cloud liquid water content, cloud droplet number concentration, and cloud top effective radius exhibit subadiabaticity resulting from entrainment mixing processes. The degree of LWC subadiabaticity is found to increase with cloud depth. Impacts of subadiabaticity on cloud optical properties are assessed. It is estimated that owing to entrainment mixing, cloud LWP, effective radius, and cloud albedo are decreased by 50–85%, 5–35%, and 2–26%, respectively, relative to adiabatic values of a plane-parallel cloud. The impact of subadiabaticity on cloud albedo is largest for shallow clouds. Results suggest that the effect of entrainment mixing must be accounted for when evaluating the aerosol indirect effect

Worldwide data sets constrain the water vapor uptake coefficient in cloud formation

Cloud droplet formation depends on the condensation of water vapor on ambient aerosols, the rate of which is strongly affected by the kinetics of water uptake as expressed by the condensation (or mass accommodation) coefficient, α_c. Estimates of α_c for droplet growth from activation of ambient particles vary considerably and represent a critical source of uncertainty in estimates of global cloud droplet distributions and the aerosol indirect forcing of climate. We present an analysis of 10 globally relevant data sets of cloud condensation nuclei to constrain the value of αc for ambient aerosol. We find that rapid activation kinetics (α_c > 0.1) is uniformly prevalent. This finding resolves a long-standing issue in cloud physics, as the uncertainty in water vapor accommodation on droplets is considerably less than previously thought

Characteristic Vertical Profiles of Cloud Water Composition in Marine Stratocumulus Clouds and Relationships With Precipitation

This study uses airborne cloud water composition measurements to characterize the vertical structure of air‐equivalent mass concentrations of water‐soluble species in marine stratocumulus clouds off the California coast. A total of 385 cloud water samples were collected in the months of July and August between 2011 and 2016 and analyzed for water‐soluble ionic and elemental composition. Three characteristic profiles emerge: (i) a reduction of concentration with in‐cloud altitude for particulate species directly emitted from sources below cloud without in‐cloud sources (e.g., Cl^− and Na^+), (ii) an increase of concentration with in‐cloud altitude (e.g., NO_2− and formate), and (iii) species exhibiting a peak in concentration in the middle of cloud (e.g., non–sea‐salt SO_4^2−, NO_3−, and organic acids). Vertical profiles of rainout parameters such as loss frequency, lifetime, and change in concentration with respect to time show that the scavenging efficiency throughout the cloud depth depends strongly on the thickness of the cloud. Thin clouds exhibit a greater scavenging loss frequency at cloud top, while thick clouds have a greater scavenging loss frequency at cloud base. The implications of these results for treatment of wet scavenging in models are discussed