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István Geresdi, Lulin Xue, and Roy Rasmussen

Abstract

A new version of a bin microphysical scheme implemented into the Weather Research and Forecasting (WRF) Model was used to study the effect of glaciogenic seeding on precipitation formation in orographic clouds. The tracking of silver iodide (AgI) particles inside of water drops allows the proper simulation of the immersion nucleation. The ice formations by deposition, condensational freezing, and contact nucleation of AgI particles are also simulated in the scheme. Cloud formation—both stably stratified and convective—and the spread of AgI particles were simulated by idealized flow over a two-dimensional (2D) bell-shaped mountain. The results of numerical experiments show the following: (i) Only the airborne seeding enhances precipitation in stably stratified layer clouds. Seeding can reduce or enhance precipitation in convective clouds. AgI seeding can significantly affect the spatial distribution of the surface precipitation in orographic clouds. (ii) The positive seeding effect is primarily due to additional diffusional growth of AgI-nucleated ice crystals in layer clouds. In convective clouds, seeding-induced changes of both diffusion and riming processes determine the seeding effect. (iii) The seeding effect is inversely related to the natural precipitation efficiency. (iv) Bulk seeding parameterization is adequate to simulate AgI seeding impacts on wintertime orographic clouds. More uncertainties of ground-seeding effects are found between bulk and bin simulations.

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Lulin Xue, Xia Chu, Roy Rasmussen, Daniel Breed, and Bart Geerts

Abstract

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.

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Guo Zhang, Guangsheng Zhou, Fei Chen, Michael Barlage, and Lulin Xue

Abstract

It is still a daunting challenge for land surface models (LSMs) to correctly represent surface heat exchange for water-limited desert steppe ecosystems. This study aims to improve the ability of the Noah LSM to simulate surface heat fluxes through addressing uncertainties in precipitation forcing conditions, rapidly evolving vegetation properties, soil hydraulic properties (SHPs), and key parameterization schemes. Three years (2008–10) of observed surface heat fluxes and soil temperature over a desert steppe site in Inner Mongolia, China, are used to verify model simulations. The proper seasonal distribution of precipitation, along with more realistic vegetation parameters, can improve the simulation of sensible heat flux (SH) and the seasonal variability of latent heat flux. Correctly representing the low-surface exchange coefficient is crucial for improving SH for short vegetation like this desert steppe site. Relating C zil, the coefficient in the Noah surface exchange coefficient calculation, with canopy height h improves the simulated SH and the diurnal range of soil temperature over the simulation compared with using the default constant C zil. The exponential water stress formulation proposed here for the Jarvis scheme improves the partitioning between soil evaporation and transpiration. It is found that the surface energy fluxes are very sensitive to SHPs. This study highlights the important role of the proper parameter values and appropriate parameterizations for the surface exchange coefficient and water stress function in canopy resistance in capturing the observed surface energy fluxes and soil temperature variations for this desert steppe site.

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Xia Chu, Bart Geerts, Lulin Xue, and Roy Rasmussen

Abstract

This study uses the WRF large-eddy simulation model at 100-m resolution to examine the impact of ground-based glaciogenic seeding on shallow (~2 km deep), cold-based convection producing light snow showers over the Sierra Madre in southern Wyoming on 13 February 2012, as part of the AgI Seeding Cloud Impact Investigation (ASCII). Detailed observations confirm that simulation faithfully captures the orographic flow, convection, and natural snow production, especially on the upwind side. A comparison between treated and control simulations indicates that glaciogenic seeding effectively converts cloud water in convective updrafts to ice and snow in this case, resulting in increased surface precipitation. This comparison further shows that seeding enhances liquid water depletion by vapor deposition, and enhances buoyancy, updraft strength, and cloud-top height. This suggests that the dynamic seeding concept applies, notwithstanding the clouds’ low natural supercooled liquid water content. But the simulated cloud-top-height changes are benign (typically <100 m). This, combined with the fact that most natural and enhanced snow growth occurs in a temperature range in which the Bergeron diffusional growth process is effective, suggests that the modeled snowfall enhancement is largely due to static (microphysical) processes rather than dynamic ones.

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Lulin Xue, Amit Teller, Roy Rasmussen, Istvan Geresdi, and Zaitao Pan

Abstract

This study evaluates the possible impact of aerosol solubility and regeneration on warm-phase orographic clouds and precipitation. The sensitivity evaluation is performed by simulating cloud formation over two identical 2D idealized mountains using a detailed bin microphysical scheme implemented into the Weather Research and Forecasting model (WRF) version 3. The dynamics, thermodynamics, topography, and microphysical pathways were designed to produce precipitating clouds in a linear hydrostatic mountain wave regime. The cloud over the second mountain is affected by regenerated aerosols advected from the cloud over the first mountain. Effects of aerosol solubility and regeneration were investigated with surface relative humidity of 95% and 85% for both clean and polluted background aerosol concentrations.

Among the findings are the following: 1) The total number of cloud drops decreases as the aerosol solubility decreases, and the impacts of aerosol solubility on cloud drops and precipitation are more significant in polluted clouds than in clean clouds. 2) Aerosol regeneration increases cloud drops and reduces the precipitation by 2%–80% in clouds over the second mountain. Regenerated aerosol particles replenish one-third to two-thirds of the missing particles when regeneration is not considered. 3) Different size distributions of regenerated aerosol particles have negligible effect on clouds and precipitation except for polluted clouds with high aerosol solubility. 4) When the solubility of initial aerosol particles decreases with an increasing size of aerosol particles, the modified solubility of regenerated aerosol particles increases precipitation over the second mountain.

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Xia Chu, Lulin Xue, Bart Geerts, Roy Rasmussen, and Daniel Breed

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 a mountain in Wyoming. The numerical simulations use the Weather Research and Forecasting (WRF) Model in LES mode with horizontal grid spacings of 300 and 100 m in 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 storm structure also validates well, but the model storm thins and weakens more 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.

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Xia Chu, Bart Geerts, Lulin Xue, and Binod Pokharel

Abstract

The impact of glaciogenic seeding on precipitation remains uncertain, mainly because of the noisy nature of precipitation. Operational seeding programs often target cold-season orographic clouds because of their abundance of supercooled liquid water. Such clouds are complicated because of common natural seeding from above (seeder–feeder effect) or from below (blowing snow). Here, observations, mainly from a profiling airborne Doppler radar, and numerical simulations are used to examine the impact of glaciogenic seeding on a very shallow (<1 km), largely blocked cloud that is not naturally seeded from aloft or from below. This cloud has limited but persistent supercooled liquid water, a cloud-base (top) temperature of −12°C (−16°C), and produces only very light snowfall naturally. A Weather Research and Forecasting Model large-eddy simulation at 100-m resolution captures the observed upstream stability and wind profiles and reproduces the essential characteristics of the orographic flow, cloud, and precipitation. Both observations and simulations indicate that seeding locally increases radar (or computed) reflectivity in the target area, even after removal of the natural trend between these two periods in a nearby control region. A model sensitivity run suggests that seeding effectively glaciates the mostly liquid cloud and substantially increases snowfall within the seeding plume. This is due to a dramatic increase in the number of ice particles and not to their size. The increased ice particle concentration facilitates snow growth by vapor deposition in a cloud the temperature range of which is conducive to the Bergeron process.

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István Geresdi, Lulin Xue, Noémi Sarkadi, and Roy Rasmussen

Abstract

The University of Pécs and NCAR Bin (UPNB) microphysical scheme was implemented into the mesoscale Weather Research and Forecast (WRF) Model that was used to study the impact of silver iodide (AgI) seeding on precipitation formation in winter orographic clouds. Four different experimental units were chosen from the Wyoming Weather Modification Pilot Project to simulate the seeding effect. The results of the numerical experiments show the following: (i) Comparisons with the soundings, snow gauges, and microwave radiometer data indicate that the three-dimensional simulations with detailed microphysics reasonably represent both the dynamics and the microphysics of real clouds. (ii) The dispersion of the AgI particles from the simulated ground-based seeding was effective because of turbulent mixing. (iii) In the investigated cases (surface temperature is less than 0°C), surface precipitation and precipitation efficiency show low susceptibility to the concentrations of cloud condensation nuclei and natural ice nucleating particles. (iv) If the available liquid water content promotes the enhancement of the number of snowflakes by diffusional growth, the surface precipitation can be increased by more than 5%. A novel parameter relevant to orographic clouds, horizontally integrated liquid water path (LWP), was evaluated to find the relation between seeding efficiency and liquid water content. The impact of seeding is negligible if the horizontal LWP is less than 0.1 mm and is apparent if the horizontal LWP is larger than 1 mm, as based on the cases investigated in this study.

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Sarah A. Tessendorf, Kyoko Ikeda, Courtney Weeks, Roy Rasmussen, Jamie Wolff, and Lulin Xue

Abstract

This paper presents an evaluation of the precipitation patterns and seedability of orographic clouds in Wyoming using SNOTEL precipitation data and a high-resolution multiyear model simulation over an 8-yr period. A key part of assessing the potential for cloud seeding is to understand the natural precipitation patterns and how often atmospheric conditions and clouds meet cloud-seeding criteria. The analysis shows that high-resolution model simulations are useful tools for studying patterns of orographic precipitation and establishing the seedability of clouds by providing information that is either missed by or not available from current observational networks. This study indicates that the ground-based seeding potential in some mountain ranges in Wyoming is limited by flow blocking and/or prevailing winds that were not normal to the barrier to produce upslope flow. Airborne seeding generally had the most potential for all of the mountain ranges that were studied.

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Lulin Xue, Amit Teller, Roy Rasmussen, Istvan Geresdi, Zaitao Pan, and Xiaodong Liu

Abstract

A detailed bin aerosol-microphysics scheme has been implemented into the Weather Research and Forecast Model to investigate the effects of aerosol solubility and regeneration on mixed-phase orographic clouds and precipitation. Two-dimensional simulations of idealized moist flow over two identical bell-shaped mountains were carried out using different combinations of aerosol regeneration, solubility, loading, ice nucleation parameterizations, and humidity. The results showed the following. 1) Pollution and regenerated aerosols suppress the riming process in mixed-phase clouds by narrowing the drop spectrum. In general, the lower the aerosol solubility, the broader the drop spectrum and thus the higher the riming rate. When the solubility of initial aerosol increases with an increasing size of aerosol particles, the modified solubility of regenerated aerosols reduces precipitation. 2) The qualitative effects of aerosol solubility and regeneration on mixed-phase orographic clouds and precipitation are not affected by different ice nucleation parameterizations. 3) The impacts of aerosol properties on rain are similar in both warm- and mixed-phase clouds. Aerosols exert weaker impact on snow and stronger impact on graupel compared to rain as graupel production is strongly affected by riming. 4) Precipitation of both warm- and mixed-phase clouds is most sensitive to aerosol regeneration, then to aerosol solubility, and last to modified solubility of regenerated aerosol; however, the precipitation amount is mainly controlled by humidity and aerosol loading.

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