Abstract
Profiling airborne radar data and accompanying large-eddy-simulation (LES) modeling are used to examine the impact of ground-based glaciogenic seeding on cloud and precipitation in a shallow stratiform orographic winter storm. This storm occurred on 18 February 2009 over amountain in Wyoming. The numerical simulations use the Weather Research and Forecasting (WRF)Model in LES mode with horizontal grid spacings of 300 and 100min a domain covering the entire mountain range, and a glaciogenic seeding parameterization coupled with the Thompson microphysics scheme. A series of non-LES simulations at 900-m resolution, each with different initial/boundary conditions, is validated against sounding, cloud, and precipitation data. The LES runs then are driven by the most representative 900-m non-LES simulation. The 100-m LES results compare reasonably well to the vertical-plane radar data. The modeled vertical-motion field reveals a turbulent boundary layer and gravity waves above this layer, as observed. The stormstructure also validates well, but themodel storm thins andweakensmore rapidly than is observed. Radar reflectivity frequency-by-altitude diagrams suggest a positive seeding effect, but time- and space-matched model reflectivity diagrams only confirm this in a relative sense, in comparison with the trend in the control region upwind of seeding generators, and not in an absolute sense. A model sensitivity run shows that in this case natural storm weakening dwarfs the seeding effect, which does enhance snow mass and snowfall. Since the kinematic and microphysical structure of the storm is simulated well, future Part II of this study will examine how glaciogenic seeding impacts clouds and precipitation processes within the LES.
| Original language | English |
|---|---|
| Pages (from-to) | 2264-2286 |
| Number of pages | 23 |
| Journal | Journal of Applied Meteorology and Climatology |
| Volume | 53 |
| Issue number | 10 |
| DOIs | |
| State | Published - 2014 |
Keywords
- Cloud parameterizations
- Cloud resolving models
- Clouds
- Weather modification
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