3 resultados para cloud droplet number concentration

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As the formative agents of cloud droplets, aerosols play an undeniably important role in the development of clouds and precipitation. Few meteorological models have been developed or adapted to simulate aerosols and their contribution to cloud and precipitation processes. The Weather Research and Forecasting model (WRF) has recently been coupled with an atmospheric chemistry suite and is jointly referred to as WRF-Chem, allowing atmospheric chemistry and meteorology to influence each other’s evolution within a mesoscale modeling framework. Provided that the model physics are robust, this framework allows the feedbacks between aerosol chemistry, cloud physics, and dynamics to be investigated. This study focuses on the effects of aerosols on meteorology, specifically, the interaction of aerosol chemical species with microphysical processes represented within the framework of the WRF-Chem. Aerosols are represented by eight size bins using the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) sectional parameterization, which is linked to the Purdue Lin bulk microphysics scheme. The aim of this study is to examine the sensitivity of deep convective precipitation modeled by the 2D WRF-Chem to varying aerosol number concentration and aerosol type. A systematic study has been performed regarding the effects of aerosols on parameters such as total precipitation, updraft/downdraft speed, distribution of hydrometeor species, and organizational features, within idealized maritime and continental thermodynamic environments. Initial results were obtained using WRFv3.0.1, and a second series of tests were run using WRFv3.2 after several changes to the activation, autoconversion, and Lin et al. microphysics schemes added by the WRF community, as well as the implementation of prescribed vertical levels by the author. The results of WRFv3.2 runs contrasted starkly with WRFv3.0.1 runs. The WRFv3.0.1 runs produced a propagating system resembling a developing squall line, whereas the WRFv3.2 runs did not. The response of total precipitation, updraft/downdraft speeds, and system organization to increasing aerosol concentrations were opposite between runs with different versions of WRF. Results of the WRFv3.2 runs, however, were in better agreement in timing and magnitude of vertical velocity and hydrometeor content with a WRFv3.0.1 run using single-moment Lin et al. microphysics, than WRFv3.0.1 runs with chemistry. One result consistent throughout all simulations was an inhibition in warm-rain processes due to enhanced aerosol concentrations, which resulted in a delay of precipitation onset that ranged from 2-3 minutes in WRFv3.2 runs, and up to 15 minutes in WRFv.3.0.1 runs. This result was not observed in a previous study by Ntelekos et al. (2009) using the WRF-Chem, perhaps due to their use of coarser horizontal and vertical resolution within their experiment. The changes to microphysical processes such as activation and autoconversion from WRFv3.0.1 to WRFv3.2, along with changes in the packing of vertical levels, had more impact than the varying aerosol concentrations even though the range of aerosol tested was greater than that observed in field studies. In order to take full advantage of the input of aerosols now offered by the chemistry module in WRF, the author recommends that a fully double-moment microphysics scheme be linked, rather than the limited double-moment Lin et al. scheme that currently exists. With this modification, the WRF-Chem will be a powerful tool for studying aerosol-cloud interactions and allow comparison of results with other studies using more modern and complex microphysical parameterizations.

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In-situ observations on the size and shape of particles in arctic cirrus are less common than those in mid-latitude and tropical cirrus with considerable uncertainty about the contributions of small ice crystals (maximum dimension D<50 µm) to the mass and radiative properties that impact radiative forcing. In situ measurements of small ice crystals in arctic cirrus were made during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in April 2008 during transits of the National Research Council of Canada Convair-580 between Fairbanks and Barrow, Alaska and during Mixed Phase Arctic Cloud Experiment (MPACE) in October 2004 with the University of North Dakota (UND) Citation over Barrow, Alaska. Concentrations of small ice crystals with D < 50 μm from a Cloud and Aerosol Spectrometer (CAS), a Cloud Droplet Probe (CDP), a Forward Scattering Spectrometer Probe (FSSP), and a two-dimensional stereo probe (2DS) were compared as functions of the concentrations of crystals with D > 100 μm measured by a Cloud Imaging Probe (CIP) and two-dimensional stereo probe (2DS) in order to assess whether the shattering of large ice crystals on protruding components of different probes artificially amplified measurements of small ice crystal concentrations. The dependence of the probe comparison on other variables as CIP N>100 (number concentrations greater than diameter D>100 μm),temperature, relative humidity respect to ice (RHice), dominant habit from the Cloud Particle Imager (CPI), aircraft roll, pitch, true air speed and angle of attack was examined to understand potential causes of discrepancies between probe concentrations. Data collected by these probes were also compared against the data collected by a CAS, CDP and CIP during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) and by a CAS and 2DS during the Tropical Composition, Cloud and Climate Coupling (TC4) missions. During ISDAC, the CAS and FSSP both overestimated measurements of small ice crystals compared to both the CDP and 2DS by 1-2 orders of magnitude. Further, the amount of overestimation increased with the concentrations from the CIP2 (N>100 > 0.1 L-1). There was an unexplained discrepancy in concentrations of small crystals between the CDP and 2DS during ISDAC. In addition, there was a strong dependence on RHice of the average ratios of the N3-50, CAS/N3-50,CDP, N3-50, FSSP096/N3-50,CDP, N3-50, CAS/N3-50,FSSP096, N10-50, CDP/N3-50,2DS, N10-50, FSSP096/N10-50,2DS. Continued studies are needed to understand the discrepancy of these probes.

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Simulations of droplet dispersion behind cylinder wakes and downstream of icing tunnel spray bars were conducted. In both cases, a range of droplet sizes were investigated numerically with a Lagrangian particle trajectory approach while the turbulent air flow was investigated with a hybrid Reynolds-Averaged Navier-Stokes/Large-Eddy Simulations approach scheme. In the first study, droplets were injected downstream of a cylinder at sub-critical conditions (i.e. with laminar boundary layer separation). A stochastic continuous random walk (CRW) turbulence model was used to capture the effects of sub-grid turbulence. Small inertia droplets (characterized by small Stokes numbers) were affected by both the large-scale and small-scale vortex structures and closely followed the air flow, while exhibiting a dispersion consistent with that of a scalar flow field. Droplets with intermediate Stokes numbers were centrifuged by the vortices to the outer edges of the wake, yielding an increased dispersion. Large Stokes number droplets were found to be less responsive to the vortex structures and exhibited the least dispersion. Particle concentration was also correlated with vorticity distribution which yielded preferential bias effects as a function of different particle sizes. This trend was qualitatively similar to results seen in homogenous isotropic turbulence, though the influence of particle inertia was less pronounced for the cylinder wake case. A similar study was completed for droplet dispersion within the Icing Research Tunnel (IRT) at the NASA Glenn Research Center, where it is important to obtain a nearly uniform liquid water content (LWC) distribution in the test section (to recreate atmospheric icing conditions).. For this goal, droplets are diffused by the mean and turbulent flow generated from the nozzle air jets, from the upstream spray bars, and from the vertical strut wakes. To understand the influence of these three components, a set of simulations was conducted with a sequential inclusion of these components. Firstly, a jet in an otherwise quiescent airflow was simulated to capture the impact of the air jet on flow turbulence and droplet distribution, and the predictions compared well with experimental results. The effects of the spray bar wake and vertical strut wake were then included with two more simulation conditions, for which it was found that the air jets were the primary driving force for droplet dispersion, i.e. that the spray bar and vertical strut wake effects were secondary.