An Improved Trajectory Model to Evaluate the Collection Performance of Snow Gauges

Author:

Colli Matteo1,Rasmussen Roy2,Thériault Julie M.3,Lanza Luca G.1,Baker C. Bruce4,Kochendorfer John4

Affiliation:

1. Department of Civil, Chemical and Environmental Engineering, University of Genoa, and WMO/CIMO Lead Centre “B. Castelli” on Precipitation Intensity, Genoa, Italy

2. National Center for Atmospheric Research,* Boulder, Colorado

3. Department of Earth and Atmospheric Sciences, Université du Québec à Montréal, Montreal, Quebec, Canada

4. Atmospheric Turbulence and Diffusion Division, National Oceanic and Atmospheric Administration, Oak Ridge, Tennessee

Abstract

AbstractRecent studies have used numerical models to estimate the collection efficiency of solid precipitation gauges when exposed to the wind in both shielded and unshielded configurations. The models used computational fluid dynamics (CFD) simulations of the airflow pattern generated by the aerodynamic response to the gauge–shield geometry. These are used as initial conditions to perform Lagrangian tracking of solid precipitation particles. Validation of the results against field observations yielded similarities in the overall behavior, but the model output only approximately reproduced the dependence of the experimental collection efficiency on wind speed. This paper presents an improved snowflake trajectory modeling scheme due to the inclusion of a dynamically determined drag coefficient. The drag coefficient was estimated using the local Reynolds number as derived from CFD simulations within a time-independent Reynolds-averaged Navier–Stokes approach. The proposed dynamic model greatly improves the consistency of results with the field observations recently obtained at the Marshall Field winter precipitation test bed in Boulder, Colorado.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference29 articles.

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3. A general hydrodynamic theory for mixed-phase microphysics. Part I: Drag and fall speeds of hydrometeors;Böhm;Atmos. Res.,1992

4. A statistical and physical description of hydrometeor distributions in Colorado snowstorms using a video disdrometer;Brandes;J. Appl. Meteor. Climatol.,2007

5. Colli, M. , 2014: Assessing the accuracy of precipitation gauges: A CFD approach to model wind induced errors. Ph.D. thesis, University of Genoa, 209 pp., doi:10.13140/RG.2.1.4408.1767.

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