Abstract. Boundary layer and turbulent characteristics (surface fluxes, turbulent kinetic energy – TKE, turbulent kinetic energy dissipation rate – ϵ), along with synoptic-scale changes in these properties over time, are examined using data collected from 18 research flights made with the CIRPAS Twin Otter Aircraft. Data were collected during the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) at Point Alpha (20∘ S, 72∘ W) in October and November 2008 off the coast of South America. The average boundary layer depth is found to be 1148 m, with 28 % of the boundary layer profiles analyzed displaying decoupling. Analysis of correlation coefficients indicates that as atmospheric pressure decreases, the boundary layer height (zi) increases. As has been shown previously, the increase in zi is accompanied by a decrease in turbulence within the boundary layer. As zi increases, cooling near cloud top cannot sustain mixing over the entire depth of the boundary layer, resulting in less turbulence and boundary layer decoupling. As the latent heat flux (LHF) and sensible heat flux (SHF) increase, zi increases, along with the cloud thickness decreasing with increasing LHF. This suggests that an enhanced LHF results in enhanced entrainment, which acts to thin the cloud layer while deepening the boundary layer. A maximum in TKE on 1 November (both overall average and largest single value measured) is due to sub-cloud precipitation acting to destabilize the sub-cloud layer while acting to stabilize the cloud layer (through evaporation occurring away from the surface, primarily confined between a normalized boundary layer height, z/zi, of 0.40 to 0.60). Enhanced moisture above cloud top from a passing synoptic system also acts to reduce cloud-top cooling, reducing the potential for mixing of the cloud layer. This is observed in both the vertical profiles of the TKE and ϵ, in which it is found that the distributions of turbulence for the sub-cloud and in-cloud layer are completely offset from one another (i.e., the range of turbulent values measured have slight or no overlap for the in-cloud and sub-cloud regions), with the TKE in the sub-cloud layer maximizing for the analysis period, while the TKE in the in-cloud layer is below the average in-cloud value for the analysis period. Measures of vertical velocity variance, TKE, and the buoyancy flux averaged over all 18 flights display a maximum near cloud middle (between normalized in-cloud height, Z*, values of 0.25 and 0.75). A total of 10 of the 18 flights display two peaks in TKE within the cloud layer, one near cloud base and another near cloud top, signifying evaporative and radiational cooling near cloud top and latent heating near cloud base. Decoupled boundary layers tend to have a maximum in turbulence in the sub-cloud layer, with only a single peak in turbulence within the cloud layer.
Abstract. Aerosol–cloud interactions are complex, including albedo and lifetime effects that cause modifications to cloud characteristics. With most cloud–aerosol interactions focused on the previously stated phenomena, there have been no in situ studies that focus explicitly on how aerosols can affect large-scale (centimeters to tens of meters) droplet inhomogeneities within clouds. This research therefore aims to gain a better understanding of how droplet inhomogeneities within cumulus clouds can be influenced by in-cloud droplet location (cloud edge vs. center) and the surrounding environmental aerosol number concentration. The pair-correlation function (PCF) is used to identify the magnitude of droplet inhomogeneity from data collected on board the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft, flown during the 2006 Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS). Time stamps (at 10−4 m spatial resolution) of cloud droplet arrival times were measured by the Artium Flight phase-Doppler interferometer (PDI). Using four complete days of data with 81 non-precipitating cloud penetrations organized into two flights of low-pollution (L1, L2) and high-pollution (H1, H2) data shows enhanced inhomogeneities near cloud edge as compared to cloud center for all four cases. Low-pollution clouds are shown to have enhanced overall inhomogeneity, with flight L2 being solely responsible for this enhanced inhomogeneity. Analysis suggests cloud age plays a larger role in the amount of inhomogeneity experienced than the aerosol number concentration, with dissipating clouds showing increased inhomogeneities as compared to growing or mature clouds. Results using a single, vertically developed cumulus cloud demonstrate enhanced droplet inhomogeneity near cloud top as compared to cloud base.
<p><strong>Abstract.</strong> Aerosol&#8211;cloud interactions are complex, including albedo and lifetime effects that cause modifications to cloud characteristics. With most cloud&#8211;aerosol interactions focused on the previously stated phenomena, there has been no in&#8211;situ studies that focus explicitly on how aerosols can affect droplet clustering within clouds. This research therefore aims to gain a better understanding of how droplet clustering within cumulus clouds can be influenced by in&#8211;cloud droplet location (cloud edge vs. center) and aerosol number concentration. The pair&#8211;correlation function (PCF) is used to identify the magnitude of droplet clustering from data collected onboard the Center for interdisciplinary Remotely&#8211;Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft, flown during the 2006 Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS). Time stamps (at 10<sup>&#8722;4</sup>&#8201;m spatial resolution) of cloud droplet arrival times were measured by the Artium Flight Phase&#8211;Doppler Interferometer (PDI). Using four complete days of data with 81 non&#8211;precipitating cloud penetrations organized into two flights of low (L1, L2) and high (H1, H2) pollution data shows more clustering near cloud edge as compared to cloud center for all four cases. Low pollution clouds are shown to have enhanced overall clustering, with flight L2 being solely responsible for this enhanced clustering. Analysis suggests cloud age plays a larger role in the clustering amount experienced than the aerosol number concentration, with dissipating clouds showing increased clustering as compared to growing or mature clouds. Results using a single, vertically developed cumulus cloud demonstrate more clustering near cloud top as compared to cloud base.</p>
Abstract. Stratocumulus clouds have a significant impact on climate due to their large spatial extent, with areas of enhanced coverage termed stratocumulus decks. How turbulence evolves with time and influences the stratocumulus deck properties however, in particular throughout the vertical profile of the boundary layer, is still lacking through model parameterizations of the small-scale flow. Collecting in situ data to better understand the turbulence and physical processes occuring within the stratocumu- lus deck therefore key to better model parameterizations. Boundary layer and turbulent characteristics, along with synoptic scale changes in these properties over time, are examined using data collected from 14 research flights made with the CIR- PAS Twin Otter Aircraft. Data was collected during the VOMOS Ocean-Cloud-Atmosphere-Land Study-Regional Experiment (VOCALS-REx) at Point Alpha in October and November of 2008 off the cost of South America (20°S, 72°W). Findings show that the influence of a synoptic system on Nov 1st and 2nd brings in a moist layer above the boundary layer, leading to a deepening cloud layer and precipitation during passage, and a large increase in boundary layer height and cloud thinning after passage. The maximum value in turbulent kinetic energy (TKE) was measured on Nov. 1st due to precipitation destabilizing the sub-cloud layer while a minimum occurred on Nov. 2nd after precipitation had ceased due to turbulent mixing overturning the boundary layer and depleting the initial turbulent energy produced from the evaporation of precipitation below cloud base. Turbulent properties averaged over all 14 flights reach a maximum near cloud middle (between normalized in- cloud values of 0.25–0.75), with well mixed boundary layers experiencing two peaks in TKE, one near cloud base due to latent heat release and another near cloud top due to evaporational cooling. Overall, it appears that turbulence measured at Point Alpha is weaker than that measured over the open ocean to the west of Point Alpha, and that measured during other scientific campaigns. Synoptic scale analysis suggests that as the geopotential height decreases, the boundary layer height and entrainment zone thickness increases, accompanied by a decrease of in-cloud and below-cloud turbulence, and vice versa.
It is well known that fluid turbulence can affect cloud droplet motion, leading to droplet clustering, which in turn can impact precipitation formation through influences on collision-coalescence. Previous work suggests that droplet clustering, or preferential concentration, of cloud droplets occurs on the order of the Kolmogorov length-scale (𝜂), with the magnitude of this clustering depending on the Stokes number (St). However, the accuracy of these theories remains largely unquantified for in situ atmospheric clouds. Therefore, data gathered from a weakly turbulent marine stratocumulus (Sc) deck during the Variability of the American Monsoons (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) are used to analyze the spatial statistics of cloud droplets by means of one-dimensional pair correlation functions 𝜂(l). Cloud droplet arrival times were recorded onboard the CIRPAS Twin-Otter aircraft over a two-week analysis period using the Artium Flight phase-Doppler Interferometer. Results from 2431 subsets of droplet arrival data indicate that droplet clustering occurs in 95% of cases from analyzing 𝜂(l), with the magnitude of the clustering becoming significant in the turbulence dissipation range, at a length-scale of ∼ 2𝜂. Analyzing 𝜂(l) as a function of in-cloud normalized height (Z * ) indicates that a maximum in the magnitude of average droplet clustering occurs near the Sc middle, at Z * = 0.47. Droplet clustering and St are also found to be strongly correlated at a statistically significant rate.
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