Abstract
The collision-coalescence process of inertial particles in turbulence is held responsible for the quick growth of cloud droplets from ∼15 to ∼50 µm in diameter, but it is not well understood. Turbulence has two effects on cloud droplets: (1) it brings them closer together, preferentially concentrating them in certain parts of the flow, and (2) it sporadically creates high accelerations, causing droplets to detach from the underlying flow. These turbulence-cloud droplet interactions are difficult to study numerically or in the laboratory due to the large range of scales involved in atmospheric turbulence, so in situ measurements are needed. Here, we present a Lagrangian particle tracking (LPT) experimental setup situated close to the summit of Mt. Zugspitze at an altitude of 2650m above the sea level on top of the environmental research station Schneefernerhaus. Clouds naturally occur at this location about a quarter of the time. The LPT experiment probes a volume of ∼40 × 20 × 12mm3, has a spatial resolution of 5 µm and a temporal resolution of 0.1ms, and measures accelerations to within 0.1ms-2. Furthermore, the experiment can slide over a set of rails, driven by a linear motor, to compensate for the mean wind. It can slide up to 7.5ms-1. By doing so, the average residence time of the particles in the measurement volume increases. The mean wind compensation allows us to study various dynamical quantities, such as the velocity autocorrelation, or the dynamics of clustering. Moreover, it is beneficial for particle tracking, in general, since longer particle tracks allow us to apply better filtering to the tracks and thus increase accuracy. We present the radial distribution function, which quantifies clustering, the longitudinal relative velocity distribution, and the Lagrangian velocity autocorrelation, all computed from cloud droplet trajectories.
Highlights
Rain formation in wet clouds proceeds in four phases: activation, condensation, collision–coalescence due to turbulence, and collision–coalescence due to differential settling.1,2 These processes are quite well understood, except for collision–coalescence due to turbulence
We present the radial distribution function, which quantifies clustering, the longitudinal relative velocity distribution, and the Lagrangian velocity autocorrelation, all computed from cloud droplet trajectories
We show that the experimental setup is suitable for measuring various cloud droplet distribution statistics, such as the radial distribution function (RDF) and the fractal dimension
Summary
Rain formation in wet clouds proceeds in four phases: activation, condensation, collision–coalescence due to turbulence, and collision–coalescence due to differential settling. These processes are quite well understood, except for collision–coalescence due to turbulence. To achieve a large range of scales, one has to either scale the experiments up, which is often impossible due to space and/or budget constraints, or decrease the size of the small scales The latter, often implies the use of a larger dissipation rate, which causes the ratio of gravity to characteristic turbulent acceleration, g/ε3/4ν−1/4, to decrease, which, in turn, affects the particles’ settling behavior.. The highest experimentally resolvable Reynolds-number experiments that we know of are performed in the Max Planck Variable Density Turbulence Tunnel at the Max Planck Institute of Dynamics and SelfOrganization in Göttingen, where Taylor Reynolds numbers up to 6000 are reached In these experiments, the Kolmogorov scale η can be as small as 9 μm, which is up to five times smaller than the hot-wires used, so special care is taken to ensure the validity of the results.. We show that the experimental setup is suitable for measuring various cloud droplet distribution statistics, such as the radial distribution function (RDF) and the fractal dimension
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