Cloud droplets to drizzle: Contribution of transition drops to microphysical and optical properties of marine stratocumulus clouds

Aircraft measurements of the ubiquitous marine stratocumulus cloud type, with over 3000 km of in situ data from the Pacific during the Cloud System Evolution in the Trades experiment, show the ability of the Holographic Detector for Clouds (HOLODEC) instrument to smoothly interpolate the small and large droplet data collected with Cloud Droplet Probe and 2DC instruments. The combined, comprehensive instrument suite reveals a surprisingly large contribution in the predrizzle size range of 40–80 μm (transition droplets, or drizzlets), a range typically not measured and assumed to reside in a condensation‐to‐collision minimum between cloud droplet and drizzle modes. Besides shedding light on the onset of collision coalescence, drizzlets are essential contributors to optical and chemical properties because of a substantial contribution to the total surface area. When adjusted to match spatial resolution of spaceborne remote sensing, the missing drizzlets bring in situ measurements to closer agreement with satellite observations

Absorbing aerosols at high relative humidity: linking hygroscopic growth to optical properties

One of the major uncertainties in the understanding of Earth's climate system is the interaction between solar radiation and aerosols in the atmosphere. Aerosols exposed to high humidity will change their chemical, physical, and optical properties due to their increased water content. To model hydrated aerosols, atmospheric chemistry and climate models often use the volume weighted mixing rule to predict the complex refractive index (RI) of aerosols when they interact with high relative humidity, and, in general, assume homogeneous mixing. This study explores the validity of these assumptions. A humidified cavity ring down aerosol spectrometer (CRD-AS) and a tandem hygroscopic DMA (differential mobility analyzer) are used to measure the extinction coefficient and hygroscopic growth factors of humidified aerosols, respectively. The measurements are performed at 80% and 90%RH at wavelengths of 532 nm and 355 nm using size-selected aerosols with different degrees of absorption; from purely scattering to highly absorbing particles. The ratio of the humidified to the dry extinction coefficients (<i>f</i>RH<sub>ext</sub>(%RH, Dry)) is measured and compared to theoretical calculations based on Mie theory. Using the measured hygroscopic growth factors and assuming homogeneous mixing, the expected RIs using the volume weighted mixing rule are compared to the RIs derived from the extinction measurements. <br><br> We found a weak linear dependence or no dependence of <i>f</i>RH(%RH, Dry) with size for hydrated absorbing aerosols in contrast to the non-monotonically decreasing behavior with size for purely scattering aerosols. No discernible difference could be made between the two wavelengths used. Less than 7% differences were found between the real parts of the complex refractive indices derived and those calculated using the volume weighted mixing rule, and the imaginary parts had up to a 20% difference. However, for substances with growth factor less than 1.15 the volume weighted mixing rule assumption needs to be taken with caution as the imaginary part of the complex RI can be underestimated

Comparison of TOMS and AVHRR volcanic ash retrievals from the August 1992 eruption of Mt. Spurr

On August 19, 1992, the Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-12 and NASA\u27s Total Ozone Mapping Spectrometer (TOMS) onboard the Nimbus-7 satellite simultaneously detected and mapped the ash cloud from the eruption of Mt. Spurr, Alaska. The spatial extent and geometry of the cloud derived from the two datasets are in good agreement and both AVHRR split window IR (11–12µm brightness temperature difference) and the TOMS UV Aerosol Index (0.34–0.38µm ultraviolet backscattering and absorption) methods give the same range of total cloud ash mass. Redundant methods for determination of ash masses in drifting volcanic clouds offer many advantages for potential application to the mitigation of aircraft hazards

Cloud microphysical effects of turbulent mixing and entrainment

Turbulent mixing and entrainment at the boundary of a cloud is studied by means of direct numerical simulations that couple the Eulerian description of the turbulent velocity and water vapor fields with a Lagrangian ensemble of cloud water droplets that can grow and shrink by condensation and evaporation, respectively. The focus is on detailed analysis of the relaxation process of the droplet ensemble during the entrainment of subsaturated air, in particular the dependence on turbulence time scales, droplet number density, initial droplet radius and particle inertia. We find that the droplet evolution during the entrainment process is captured best by a phase relaxation time that is based on the droplet number density with respect to the entire simulation domain and the initial droplet radius. Even under conditions favoring homogeneous mixing, the probability density function of supersaturation at droplet locations exhibits initially strong negative skewness, consistent with droplets near the cloud boundary being suddenly mixed into clear air, but rapidly approaches a narrower, symmetric shape. The droplet size distribution, which is initialized as perfectly monodisperse, broadens and also becomes somewhat negatively skewed. Particle inertia and gravitational settling lead to a more rapid initial evaporation, but ultimately only to slight depletion of both tails of the droplet size distribution. The Reynolds number dependence of the mixing process remained weak over the parameter range studied, most probably due to the fact that the inhomogeneous mixing regime could not be fully accessed when phase relaxation times based on global number density are considered.Comment: 17 pages, 10 Postscript figures (figures 3,4,6,7,8 and 10 are in reduced quality), to appear in Theoretical Computational Fluid Dynamic

The clustering instability of inertial particles spatial distribution in turbulent flows

A theory of clustering of inertial particles advected by a turbulent velocity field caused by an instability of their spatial distribution is suggested. The reason for the clustering instability is a combined effect of the particles inertia and a finite correlation time of the velocity field. The crucial parameter for the clustering instability is a size of the particles. The critical size is estimated for a strong clustering (with a finite fraction of particles in clusters) associated with the growth of the mean absolute value of the particles number density and for a weak clustering associated with the growth of the second and higher moments. A new concept of compressibility of the turbulent diffusion tensor caused by a finite correlation time of an incompressible velocity field is introduced. In this model of the velocity field, the field of Lagrangian trajectories is not divergence-free. A mechanism of saturation of the clustering instability associated with the particles collisions in the clusters is suggested. Applications of the analyzed effects to the dynamics of droplets in the turbulent atmosphere are discussed. An estimated nonlinear level of the saturation of the droplets number density in clouds exceeds by the orders of magnitude their mean number density. The critical size of cloud droplets required for clusters formation is more than $20 \mu$m.Comment: REVTeX 4, 15 pages, 2 figures(included), PRE submitte

Detection of small drizzle droplets in a large cloud chamber using ultrahigh-resolution radar

A large convection–cloud chamber has the potential to produce drizzle-sized droplets, thus offering a new opportunity to investigate aerosol–cloud–drizzle interactions at a fundamental level under controlled environmental conditions. One key measurement requirement is the development of methods to detect the low-concentration drizzle drops in such a large cloud chamber. In particular, remote sensing methods may overcome some limitations of in situ methods. Here, the potential of an ultrahigh-resolution radar to detect the radar return signal of a small drizzle droplet against the cloud droplet background signal is investigated. It is found that using a small sampling volume is critical to drizzle detection in a cloud chamber to allow a drizzle drop in the radar sampling volume to dominate over the background cloud droplet signal. For instance, a radar volume of 1 cubic centimeter (cm3) would enable the detection of drizzle embryos with diameter larger than 40 µm. However, the probability of drizzle sampling also decreases as the sample volume reduces, leading to a longer observation time. Thus, the selection of radar volume should consider both the signal power and the drizzle occurrence probability. Finally, observations from the Pi Convection–Cloud Chamber are used to demonstrate the single-drizzle-particle detection concept using small radar volume. The results presented in this study also suggest new applications of ultrahigh-resolution cloud radar for atmospheric sensing.</p

Diffusion of water molecules in amorphous silica

The diffusive penetration of atmospheric water vapor into amorphous silica (a-SiO2) degrades the performance of electronic devices. In this letter, we calculate the range of activation energies for water diffusion in a-SiO2 such that the diffusion time through, for example, a 0.5-m protective layer is on the order of the decadal time scale, as required in typical applications. We find that for all practical purposes, silica composed of n -member rings is impenetrable to water vapor for n ≤ 5 . Thus, we conclude that the distribution of n-member rings in a-SiO2 and, specifically, the n \u3e; 5 fraction is the critical parameter for predicting device performance

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