Settling velocity of snow with varying morphology and concentration in atmospheric turbulence
Abstract
Here we present the field measurements of snow size and concentration as well as its corresponding settling velocity based on the data collected from multiple deployments at EOLOS Wind Energy Research Field Station at Rosemount, MN, USA. All the deployments were conducted at night, allowing us to implement the in situ large-scale particle image velocimetry (PIV) and particle tracking velocimetry (PTV) to quantify the turbulent flow field and snow particle setting velocity in a sampling area on the order of 10 m as reported by Nemes et al. [J. Fluid Mech. 2017] and Heisel et al. [J. Fluid Mech. 2018]. The general micrometeorological conditions were provided by a 130 m meteorological tower (met-tower) equipped with 4 sonic anemometers and 6 low frequency humidity and temperature sensors at the field site, and the turbulence characteristics were measured using both the met-tower sonics and in situ PIV. In addition, the snow particle size, morphology were captured using digital in-line holography (DIH) and the snow concentration was estimated using both DIH and the particle images from the PIV. The settling velocity of snow particles was captured using in situ PIV or PTV depending on the snow concentration level during each deployment. The turbulence conditions from the available deployments varied by an order of magnitude in the Taylor-scale Reynolds number, covering a range of Stokes number and different cases of snow particle-turbulence interaction phenomenology. The occurrence of large scale clusters allows us to identify Stokes critical conditions, and quantify the spatial variability of settling velocity enhancement as compared to quiescent flow conditions. Such variability is estimated in terms of snow particle velocity and concentration within the sample area of PIV/PTV measurements and corroborated by small scale concentration variability assessed by DIH. The comparison of the two methods provides a very much needed clarification of the range of snow particle sizes detectable by large scale optical imaging, and a better link between snow morphology and settling velocity.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.A51L2860L
- Keywords:
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- 3310 Clouds and cloud feedbacks;
- ATMOSPHERIC PROCESSES;
- 3311 Clouds and aerosols;
- ATMOSPHERIC PROCESSES;
- 3333 Model calibration;
- ATMOSPHERIC PROCESSES;
- 3354 Precipitation;
- ATMOSPHERIC PROCESSES