A Case Study of Radar Observations and WRF LES Simulations of the Impact of Ground-Based Glaciogenic Seeding on Orographic Clouds and Precipitation. Part II: AgI Dispersion and Seeding Signals Simulated by WRF

Several Weather Research and Forecasting (WRF) Model simulations of natural and seeded clouds have been conducted in non-LES and LES (large-eddy simulation) modes to investigate the seeding impact on wintertime orographic clouds for an actual seeding case on 18 February 2009 in the Medicine Bow Mountains of Wyoming. Part I of this two-part series has shown the capability of WRF LES with 100-m grid spacing to capture the essential environmental conditions by comparing the model results with measurements from a variety of instruments. In this paper, the silver iodide (AgI) dispersion features, the AgI impacts on the turbulent kinetic energy (TKE), the microphysics, and the precipitation are examined in detail using the model data, which leads to five main results. 1) The vertical dispersion of AgI particles is more efficient in cloudy conditions than in clear conditions. 2) The wind shear and the buoyancy are both important TKE production mechanisms in the wintertime PBL over complex terrain in cloudy conditions. The buoyancy-induced eddies are more responsible for the AgI vertical dispersion than the shear-induced eddies are. 3) Seeding has insignificant effects on the cloud dynamics. 4) AgI particles released from the ground-based generators affect the cloud within the boundary layer below 1 km AGL through nucleating extra ice crystals, converting liquid water into ice, depleting more vapor, and generating more precipitation on the ground. The AgI nucleation rate is inversely related to the natural ice nucleation rate. 5) The seeding effects on the ground precipitation are confined within narrow areas. The relative seeding effect ranges between 5% and 20% for the simulations with different grid spacing.

Wave-Induced Boundary Layer Separation in the Lee of the Medicine Bow Mountains. Part II: Numerical Modeling

Mountain waves and rotors in the lee of the Medicine Bow Mountains in southeastern Wyoming are investigated in a two-part paper. Part I by French et al. delivers a detailed observational account of two rotor events: one displays characteristics of a hydraulic jump and the other displays characteristics of a classic lee-wave rotor. In Part II, presented here, results of high-resolution numerical simulations are conveyed and physical processes involved in the formation and dynamical evolution of these two rotor events are examined. The simulation results reveal that the origin of the observed rotors lies in boundary layer separation, induced by wave perturbations whose amplitudes reach maxima at or near the mountain top. An undular hydraulic jump that gave rise to a rotor in one of these events was found to be triggered by midtropospheric wave breaking and an ensuing strong downslope windstorm. Lee waves spawning rotors developed under conditions favoring wave energy trapping at low levels in different phases of these two events. The upstream shift of the boundary layer separation zone, documented to occur over a relatively short period of time in both events, is shown to be the manifestation of a transition in flow regimes, from downslope windstorms to trapped lee waves, in response to a rapid change in the upstream environment, related to the passage of a short-wave synoptic disturbance aloft. The model results also suggest that the secondary obstacles surrounding the Medicine Bow Mountains play a role in the dynamics of wave and rotor events by promoting lee-wave resonance in the complex terrain of southeastern Wyoming.

Wave-Induced Boundary Layer Separation in the Lee of the Medicine Bow Mountains. Part I: Observations*

Two cases of mountain waves, rotors, and the associated turbulence in the lee of the Medicine Bow Mountains in southeastern Wyoming are investigated in a two-part study using aircraft observations and numerical simulations. In Part I, observations from in situ instruments and high-resolution cloud radar on board the University of Wyoming King Air aircraft are presented and analyzed. Measurements from the radar compose the first direct observations of wave-induced boundary layer separation. The data from these two events show some striking similarities but also significant differences. In both cases, rotors were observed; yet one looks like a classical lee-wave rotor, while the other resembles an atmospheric hydraulic jump with midtropospheric gravity wave breaking aloft. High-resolution (30 × 30 m2) dual-Doppler syntheses of the two-dimensional velocity fields in the vertical plane beneath the aircraft reveal the boundary layer separation, the scale and structure of the attendant rotors, and downslope windstorms. In the stronger of the two events, near-surface winds upwind of the boundary layer separation reached 35 m s−1, and vertical winds were in excess of 10 m s−1. Moderate to strong turbulence was observed within and downstream of these regions. In both cases, the rotor extended horizontally 5–10 km and vertically 2–2.5 km. Horizontal vorticity within the rotor zone reached 0.2 s−1. Several subrotors from 500 to 1000 m in diameter were identified inside the main rotor in one of the cases. Part II presents a modeling study and investigates the kinematic structure and the dynamic evolution of these two events.

The Dispersion of Silver Iodide Particles from Ground-Based Generators over Complex Terrain. Part II: WRF Large-Eddy Simulations versus Observations

A numerical modeling study has been conducted to explore the ability of the Weather Research and Forecasting (WRF) model-based large-eddy simulation (LES) with 100-m grid spacing to reproduce silver iodide (AgI) particle dispersion by comparing the model results with measurements made on 16 February 2011 over the Medicine Bow Mountains in Wyoming. Xue et al.'s recently developed AgI cloud-seeding parameterization was applied in this study to simulate AgI release from ground-based generators. Qualitative and quantitative comparisons between the LES results and observed AgI concentrations were conducted. Analyses of turbulent kinetic energy (TKE) features within the planetary boundary layer (PBL) and comparisons between the 100-m LES and simulations with 500-m grid spacing were performed as well. The results showed the following: 1) Despite the moist bias close to the ground and above 4 km AGL, the LES with 100-m grid spacing captured the essential environmental conditions except for a slightly more stable PBL relative to the observed soundings. 2) Wind shear is the dominant TKE production mechanism in wintertime PBL over complex terrain and generates a PBL of about 1000-m depth. The terrain-induced turbulent eddies are primarily responsible for the vertical dispersion of AgI particles. 3) The LES-simulated AgI plumes were shallow and narrow, in agreement with observations. The LES overestimated AgI concentrations close to the ground, which is consistent with the higher static stability in the model than is observed. 4) Non-LES simulations using PBL schemes had difficulty in capturing the shear-dominant turbulent PBL structure over complex terrain in wintertime. Therefore, LES of wintertime orographic clouds with grid spacing close to 500 m or finer are recommended.

An Airborne Profiling Radar Study of the Impact of Glaciogenic Cloud Seeding on Snowfall from Winter Orographic Clouds

Data from an airborne vertically pointing millimeter-wave Doppler radar are used to study the cloud microphysical effect of glaciogenic seeding of cold-season orographic clouds. Fixed flight tracks were flown downstream of ground-based silver iodide (AgI) generators in the Medicine Bow Mountains of Wyoming. Composite data from seven flights, each with a no-seeding period followed by a seeding period, indicate that radar reflectivity was higher near the ground during the seeding periods. Several physical considerations argue in favor of the hypothesis that the increase in near-surface reflectivity is attributed to AgI seeding. While the increase in near-surface reflectivity and thus snowfall rate are statistically significant, caution is warranted in view of the large natural variability of weather conditions and the small size of the dataset.