Cloud microphysical response to entrainment and mixing is locally inhomogeneous and globally homogeneous: Evidence from the lab.

Entrainment of dry air into clouds strongly influences cloud optical and precipitation properties and the response of clouds to aerosol perturbations. The response of cloud droplet size distributions to entrainment-mixing is examined in the Pi convection-cloud chamber that creates a turbulent, steady-state cloud. The experiments are conducted by injecting dry air with temperature (Te) and flow rate (Qe) through a flange in the top boundary, into the otherwise well-mixed cloud, to mimic the entrainment-mixing process. Due to the large-scale circulation, the downwind region is directly affected by entrained dry air, whereas the upwind region is representative of the background conditions. Droplet concentration (Cn) and liquid water content (L) decrease in the downwind region, but the difference in the mean diameter of droplets (Dm) is small. The shape of cloud droplet size distributions relative to the injection point is unchanged, to within statistical uncertainty, resulting in a signature of inhomogeneous mixing, as expected for droplet evaporation times small compared to mixing time scales. As Te and Qe of entrained air increase, however, Cn, L, and Dm of the whole cloud system decrease, resulting in a signature of homogeneous mixing. The apparent contradiction is understood as the cloud microphysical responses to entrainment and mixing differing on local and global scales: locally inhomogeneous and globally homogeneous. This implies that global versus local sampling of clouds can lead to seemingly contradictory results for mixing, which informs the long-standing debate about the microphysical response to entrainment and the parameterization of this process for coarse-resolution models.

Performance of optical sensors for cloud measurements deployed by the ARM Aerial Facility during ACE-ENA.

During the Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA), a variety of in situ optical sensors using shadow imaging, scattering and holography were deployed by the Atmospheric Radiation Measurement (ARM) Aerial Facility to determine cloud properties. Taking advantage of the wide, overlapping range of instrumentation, we compare in situ cloud data from several different measurement methods for droplets up to 100 µm. Data processing was tailored to the encountered conditions, leading to good agreement. Improvements include noise reduction for holography and better out-of-focus correction for shadow imaging. Comparison between direct liquid water content measurements and optical sensors showed better agreement at higher droplet number concentrations (>120/c m 3).

The role of turbulent fluctuations in aerosol activation and cloud formation.

Aerosol indirect effects are one of the leading contributors to cloud radiative properties relevant to climate. Aerosol particles become cloud droplets when the ambient relative humidity (saturation ratio) exceeds a critical value, which depends on the particle size and chemical composition. In the traditional formulation of this problem, only average, uniform saturation ratios are considered. Using experiments and theory, we examine the effects of fluctuations, produced by turbulence. Our measurements, from a multiphase, turbulent cloud chamber, show a clear transition from a regime in which the mean saturation ratio dominates to one in which the fluctuations determine cloud properties. The laboratory measurements demonstrate cloud formation in mean-subsaturated conditions (i.e., relative humidity <100%) in the fluctuation-dominant activation regime. The theoretical framework developed to interpret these measurements predicts a transition from a mean- to a fluctuation-dominated regime, based on the relative values of the mean and standard deviation of the environmental saturation ratio and the critical saturation ratio at which aerosol particles activate or become droplets. The theory is similar to the concept of stochastic condensation and can be used in the context of the atmosphere to explore the conditions under which droplet activation is driven by fluctuations as opposed to mean supersaturation. It provides a basis for future development of cloud droplet activation parameterizations that go beyond the internally homogeneous parcel calculations that have been used in the past.

Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions.

The influence of aerosol concentration on the cloud-droplet size distribution is investigated in a laboratory chamber that enables turbulent cloud formation through moist convection. The experiments allow steady-state microphysics to be achieved, with aerosol input balanced by cloud-droplet growth and fallout. As aerosol concentration is increased, the cloud-droplet mean diameter decreases, as expected, but the width of the size distribution also decreases sharply. The aerosol input allows for cloud generation in the limiting regimes of fast microphysics ([Formula: see text]) for high aerosol concentration, and slow microphysics ([Formula: see text]) for low aerosol concentration; here, [Formula: see text] is the phase-relaxation time and [Formula: see text] is the turbulence-correlation time. The increase in the width of the droplet size distribution for the low aerosol limit is consistent with larger variability of supersaturation due to the slow microphysical response. A stochastic differential equation for supersaturation predicts that the standard deviation of the squared droplet radius should increase linearly with a system time scale defined as [Formula: see text], and the measurements are in excellent agreement with this finding. The result underscores the importance of droplet size dispersion for aerosol indirect effects: increasing aerosol concentration changes the albedo and suppresses precipitation formation not only through reduction of the mean droplet diameter but also by narrowing of the droplet size distribution due to reduced supersaturation fluctuations. Supersaturation fluctuations in the low aerosol/slow microphysics limit are likely of leading importance for precipitation formation.

Fine-Scale Droplet Clustering in Atmospheric Clouds: 3D Radial Distribution Function from Airborne Digital Holography.

The extent of droplet clustering in turbulent clouds has remained largely unquantified, and yet is of possible relevance to precipitation formation and radiative transfer. To that end, data gathered by an airborne holographic instrument are used to explore the three-dimensional spatial statistics of cloud droplet positions in homogeneous stratiform boundary-layer clouds. The three-dimensional radial distribution functions g(r) reveal unambiguous evidence of droplet clustering. Three key theoretical predictions are observed: the existence of positive correlations, onset of correlation in the turbulence dissipation range, and monotonic increase of g(r) with decreasing r. This implies that current theory captures the essential processes contributing to clustering, even at large Reynolds numbers typical of the atmosphere.

Locally narrow droplet size distributions are ubiquitous in stratocumulus clouds.

Marine stratocumulus clouds are the "global reflectors," sharply contrasting with the underlying dark ocean surface and exerting a net cooling on Earth's climate. The magnitude of this cooling remains uncertain in part owing to the averaged representation of microphysical processes, such as the droplet-to-drizzle transition in global climate models (GCMs). Current GCMs parameterize cloud droplet size distributions as broad, cloud-averaged gammas. Using digital holographic measurements of discrete stratocumulus cloud volumes, we found cloud droplet size distributions to be narrower at the centimeter scale, never resembling the cloud average. These local distributions tended to form pockets of similar-looking cloud regions, each characterized by a size distribution shape that is diluted to varying degrees. These observations open the way for new modeling representations of microphysical processes.

Physical science research needed to evaluate the viability and risks of marine cloud brightening.

Marine cloud brightening (MCB) is the deliberate injection of aerosol particles into shallow marine clouds to increase their reflection of solar radiation and reduce the amount of energy absorbed by the climate system. From the physical science perspective, the consensus of a broad international group of scientists is that the viability of MCB will ultimately depend on whether observations and models can robustly assess the scale-up of local-to-global brightening in today's climate and identify strategies that will ensure an equitable geographical distribution of the benefits and risks associated with projected regional changes in temperature and precipitation. To address the physical science knowledge gaps required to assess the societal implications of MCB, we propose a substantial and targeted program of research-field and laboratory experiments, monitoring, and numerical modeling across a range of scales.

Improved particle size estimation in digital holography via sign matched filtering.

A matched filter method is provided for obtaining improved particle size estimates from digital in-line holograms. This improvement is relative to conventional reconstruction and pixel counting methods for particle size estimation, which is greatly limited by the CCD camera pixel size. The proposed method is based on iterative application of a sign matched filter in the Fourier domain, with sign meaning the matched filter takes values of ±1 depending on the sign of the angular spectrum of the particle aperture function. Using simulated data the method is demonstrated to work for particle diameters several times the pixel size. Holograms of piezoelectrically generated water droplets taken in the laboratory show greatly improved particle size measurements. The method is robust to additive noise and can be applied to real holograms over a wide range of matched-filter particle sizes.

Clustering of charged inertial particles in turbulence.

Holographic measurements of the clustering of electrically charged, inertial particles in homogenous and isotropic turbulent flow reveal novel particle dynamics. When particles are identically charged, Coulomb repulsion introduces a length scale below which inertial clustering is suppressed such that the radial distribution function (RDF) mimics that of a nonideal gas. The result is described with a Fokker-Planck framework modeling inertial clustering as a diffusion-drift process modified to include Coulomb interaction. The peak in the RDF is well predicted by the balance between the particle terminal velocity under Coulomb repulsion and a time-averaged "drift" velocity obtained from the nonuniform sampling of fluid strain and rotation due to finite particle inertia. The resulting functional form of the RDF matches the measurements closely, providing support for the drift-diffusion description of particle clustering.

Extensive Soot Compaction by Cloud Processing from Laboratory and Field Observations.

Soot particles form during combustion of carbonaceous materials and impact climate and air quality. When freshly emitted, they are typically fractal-like aggregates. After atmospheric aging, they can act as cloud condensation nuclei, and water condensation or evaporation restructure them to more compact aggregates, affecting their optical, aerodynamic, and surface properties. Here we survey the morphology of ambient soot particles from various locations and different environmental and aging conditions. We used electron microscopy and show extensive soot compaction after cloud processing. We further performed laboratory experiments to simulate atmospheric cloud processing under controlled conditions. We find that soot particles sampled after evaporating the cloud droplets, are significantly more compact than freshly emitted and interstitial soot, confirming that cloud processing, not just exposure to high humidity, compacts soot. Our findings have implications for how the radiative, surface, and aerodynamic properties, and the fate of soot particles are represented in numerical models.

Cloud System Evolution in the Trades-CSET: Following the Evolution of Boundary Layer Cloud Systems with the NSF/NCAR GV.

The Cloud System Evolution in the Trades (CSET) study was designed to describe and explain the evolution of the boundary layer aerosol, cloud, and thermodynamic structures along trajectories within the north-Pacific trade-winds. The study centered on 7 round-trips of the NSF NCAR Gulfstream V (GV) between Sacramento, CA and Kona, Hawaii between 1 July and 15 August 2015. The CSET observing strategy was to sample aerosol, cloud, and boundary layer properties upwind from the transition zone over the North Pacific and to resample these areas two days later. GFS forecast trajectories were used to plan the outbound flight to Hawaii with updated forecast trajectories setting the return flight plan two days later. Two key elements of the CSET observing system were the newly developed HIAPER Cloud Radar (HCR) and the High Spectral Resolution Lidar (HSRL). Together they provided unprecedented characterizations of aerosol, cloud and precipitation structures that were combined with in situ measurements of aerosol, cloud, precipitation, and turbulence properties. The cloud systems sampled included solid stratocumulus infused with smoke from Canadian wildfires, mesoscale cloud-precipitation complexes, and patches of shallow cumuli in very clean environments. Ultra-clean layers observed frequently near the top of the boundary layer were often associated with shallow, optically thin, layered veil clouds. The extensive aerosol, cloud, drizzle and boundary layer sampling made over open areas of the Northeast Pacific along 2-day trajectories during CSET is unprecedented and will enable modeling studies of boundary layer cloud system evolution and the role of different processes in that evolution.

Nonthermal ice nucleation observed at distorted contact lines of supercooled water drops.

Ice nucleation is the crucial step for ice formation in atmospheric clouds and therefore underlies climatologically relevant precipitation and radiative properties. Progress has been made in understanding the roles of temperature, supersaturation, and material properties, but an explanation for the efficient ice nucleation occurring when a particle contacts a supercooled water drop has been elusive for over half a century. Here, we explore ice nucleation initiated at constant temperature and observe that mechanical agitation induces freezing of supercooled water drops at distorted contact lines. Results show that symmetric motion of supercooled water on a vertically oscillating substrate does not freeze, no matter how we agitate it. However, when the moving contact line is distorted with the help of trace amounts of oil or inhomogeneous pinning on the substrate, freezing can occur at temperatures much higher than in a static droplet, equivalent to ∼10^{10} increase in nucleation rate. Several possible mechanisms are proposed to explain the observations. One plausible explanation among them, decreased pressure due to interface curvature, is explored theoretically and compared with the observational results quasiquantitatively. Indeed, the observed freezing-temperature increase scales with contact line speed in a manner consistent with the pressure hypothesis. Whatever the mechanism, the experiments demonstrate a strong preference for ice nucleation at three-phase contact lines compared to the two-phase interface, and they also show that movement and distortion of the contact line are necessary contributions to stimulating the nucleation process.

A Vocabulary Approach to Partial Streamline Matching and Exploratory Flow Visualization.

Measuring the similarity of integral curves is fundamental to many important flow data analysis and visualization tasks such as feature detection, pattern querying, streamline clustering, and hierarchical exploration. In this paper, we introduce FlowString, a novel vocabulary approach that extracts shape invariant features from streamlines and utilizes a string-based method for exploratory streamline analysis and visualization. Our solution first resamples streamlines by considering their local feature scales. We then classify resampled points along streamlines based on the shape similarity around their local neighborhoods. We encode each streamline into a string of well-selected shape characters, from which we construct meaningful words for querying and retrieval. A unique feature of our approach is that it captures intrinsic streamline similarity that is invariant under translation, rotation and scaling. We design an intuitive interface and user interactions to support flexible querying, allowing exact and approximate searches for partial streamline matching. Users can perform queries at either the character level or the word level, and define their own characters or words conveniently for customized search. We demonstrate the effectiveness of FlowString with several flow field data sets of different sizes and characteristics. We also extend FlowString to handle multiple data sets and perform an empirical expert evaluation to confirm the usefulness of this approach.

Heterogeneous surface crystallization observed in undercooled water.

We report laboratory observations of higher freezing temperatures when an ice-forming nucleus is near the surface of an undercooled water drop than when the nucleus is immersed in the drop. The nucleation rate at the water surface is a factor of 10(10) greater than in bulk water, thereby complementing and providing evidence for homogeneous surface crystallization, which has been hypothesized recently. Interpretation of the data via classical nucleation theory shows that the free energy of formation of a critical ice germ is decreased by a factor of approximately 2 when the substrate is near the air-water interface. Furthermore, the analysis suggests that the jump frequency of molecules from the liquid to the solid may be greatly enhanced at the interface.

Holographic measurements of inhomogeneous cloud mixing at the centimeter scale.

Optical properties and precipitation efficiency of atmospheric clouds are largely determined by turbulent mixing with their environment. When cloud liquid water is reduced upon mixing, droplets may evaporate uniformly across the population or, in the other extreme, a subset of droplets may evaporate completely, leaving the remaining drops unaffected. Here, we use airborne holographic imaging to visualize the spatial structure and droplet size distribution at the smallest turbulent scales, thereby observing their response to entrainment and mixing with clear air. The measurements reveal that turbulent clouds are inhomogeneous, with sharp transitions between cloud and clear air properties persisting to dissipative scales (<1 centimeter). The local droplet size distribution fluctuates strongly in number density but with a nearly unchanging mean droplet diameter.

Inertial clustering of particles in high-Reynolds-number turbulence.

We report experimental evidence of spatial clustering of dense particles in homogenous, isotropic turbulence at high Reynolds numbers. The dissipation-scale clustering becomes stronger as the Stokes number increases and is found to exhibit similarity with respect to the droplet Stokes number over a range of experimental conditions (particle diameter and turbulent energy dissipation rate). These findings are in qualitative agreement with recent theoretical and computational studies of inertial particle clustering in turbulence. Because of the large Reynolds numbers a broad scaling range of particle clustering due to turbulent mixing is present, and the inertial clustering can clearly be distinguished from that due to mixing of fluid particles.

Phase signature for particle detection with digital in-line holography.

The spatial phase resulting from the digital reconstruction of an in-line hologram of a particle field is shown to yield a unique pattern that can be used for particle detection. This phase signature is present only when viewed along with the reference light. The existence of the phase pattern is verified computationally and confirmed in laboratory experiments with holograms of calibrated glass spheres. The phase signature provides an alternative to the widely used intensity method for particle detection.

Depth-of-focus reduction for digital in-line holography of particle fields.

Poor axial precision caused, in part, by large depth of focus (tau) has been a vexing problem in extraction of particle position from digital in-line holograms. A simple method is proposed to combat this depth-of-focus difficulty. The method is based on decoupling of size and position information. With d, Delta, and lambda being particle diameter, CCD pixel size, and the wavelength, respectively, our main theoretical result is the reduction of tau from tau - d2/lambda to tau - Delta2/lambda for particles of known size. This result is confirmed in laboratory experiments with holograms of calibrated glass spheres.

Airborne digital holographic system for cloud particle measurements.

An in-line holographic system for in situ detection of atmospheric cloud particles [Holographic Detector for Clouds (HOLODEC)] has been developed and flown on the National Center for Atmospheric Research C-130 research aircraft. Clear holograms are obtained in daylight conditions at typical aircraft speeds of 100 m s(-1). The instrument is fully digital and is interfaced to a control and data-acquisition system in the aircraft via optical fiber. It is operable at temperatures of less than -30 degrees C and at typical cloud humidities. Preliminary data from the experiment show its utility for studies of the three-dimensional spatial distribution of cloud particles and ice crystal shapes.