Search Results

You are looking at 1 - 7 of 7 items for

  • Author or Editor: R. D. Farley x
  • Refine by Access: All Content x
Clear All Modify Search
R. D. Farley and H. D. Orville

Abstract

This paper is the first in a three part series describing numerical simulations of hailstorms and hailstone growth using a two-dimensional, time-dependent cloud model. In this model. cloud water, cloud ice and rain are treated via standard parameterization technique The precipitating ice field is discretized into 20 logarith-mically spaced size categories which evolve in, and interact with the time-dependent dynamic framework. Ice particles are generated by the freezing of raindrops and via a parameterization of the Bergeron process. Growth of these ice particles is based on wet and dry growth concepts applied to the continuous accretion process.

The model has been used to simulate a severe supercellular hailstorm from the National Hail Research Experiment These simulations include cases assuming various microphysical configurations of the model along with simplified cloud seeding experiments The simulations indicate many areas of agreement between the model results and observation chief among them being the characteristic sloping updraft and moving gust front, the rounded dome cloud top, the radar overhang, and the intense precipitation cascade. The major observed features which were not properly simulated were the persistent bounded weak echo region and the high concentrations of giant hail and associated high radar reflectivity values. The model results have also been compared to and are consistent with aircraft measurements of the thermodynamic structure of the subcloud region, and the basic internal structure of hailstorms.

The model simulations and the storm were prodigious producers of surface rain and hail. The model was unable to simulate the vast amounts of large hail observed for this case, mainly due to depiction of the cloud water caused by embryo generation mechanisms being too efficient, although the two-dimensionality of the model may also limit hail production. Recirculation of hall embryos from the forward overhang back down into the leading edge of the sloping updraft was important to hail production according to both the observations and the model results. The overall effect of the cloud seeding, although dependent on the magnitude and duration of the seeding, was quite similar in all cases. The primary seeding, effect was the creation of more small ice particles, most of which were carried aloft into the anvil. Dynamic effects induced by the seeding were generally insignificant. In all seeded cases the amount of hail at the surface was reduced, although the undesirable response of decreased rainfall also resulted.

Full access
Terry L. Clark and R. D. Farley

Abstract

The Clark nonhydrostatic anelastic code is extended to allow for interactive grid nesting in both two and three spatial dimensions. Tests are presented which investigate the accuracy of three different quadratic interpolation formulae which are used to derive boundary conditions for the fine mesh model. Application of the conservation condition of Kurihara and others is shown to result in significant improvements in the treatment of interactive nesting. A significant improvement in the solutions for interactive versus parasitic nesting is also shown in the context of forced gravity wave flow. This result, for the anelastic system, is in agreement with the earlier results of Phillips and Shukla, who considered the hydrostatic shallow water system of equations.

The interactive nesting model is applied to the simulation of the severe downslope windstorm of 11 January 1972 in Boulder using both two and three spatial dimensions. The three-dimensional simulation results in a gustiness signature in the surface wind speed. The cause of this gustiness is attributed to the development of turbulent eddies in the convectively unstable region of the topographically forced wave. These eddies are transported to the surface by downdrafts formed in the leading edge of the convectively unstable region. A type of periodicity to the wind gustiness signature is then produced by a competition between the two physical processes of wave build up via forced gravity wave dynamics and wave breakdown via convective instability. The actual source/sink terms for the turbulence are still under investigation. Some preliminary comparisons between the two- and three-dimensional windstorm simulations are also presented.

Full access
R. D. Farley and C. S. Chen

Abstract

The Wisner one-dimensional time-dependent model has been modified to allow the condensed water forms to be represented by 52 logarithmically spaced size categories covering a range of just under 2 μm radius to slightly less than 5 mm radius. The size distribution of the water drops was allowed to evolve with time as a result of the physical processes of vertical advection, condensation/evaporation, stochastic coalescence, and drop breakup. Salt seeding was simulated by the introduction of a distribution of raindrop embryos at cloud base for a specified period of time. The raindrop embryo distribution was derived from calculations on the diffusional growth of a distribution of salt particles in the unsaturated air below cloud base. This model was applied to the 23 July 1970 salt seeding case reported by Biswas and Dennis. This “detailed microphysical” study has indicated that salt seeding can be effective in stimulating the warm rain process only if breakup-induced chain reactions result. In order for the chain reaction to develop, high vertical velocities (greater than 10 m s−1) are required. Salt seeding acts mainly as a catalyst in initiating this Langmuir-type chain reaction. Without breakup, salt seeding has little effect other than to allow a few of the big drops to fall out of the model clouds. Breakup acting alone may cause the model clouds to precipitate but much longer periods are required than when seeding and breakup are combined. The effects of salt seeding and breakup-induced chain reactions are also strongly dependent on the dynamics of the model cloud.

Full access
R. D. Farley, D. L. Hjermstad, and H. D. Orville

Abstract

This paper illustrates the potential for mesoscale models to depict the distribution of precipitation in orographic situations. The study covers a 4-day time period in April 1995. The domain of the numerical model covers much of western South Dakota and some of eastern Wyoming and is centered on the Black Hills of South Dakota. The 4-day storm period is characterized by changing atmospheric conditions, from primarily rain generation to snowfall production. Observations and climatic data of precipitation are analyzed to compare with model predictions. The model demonstrated the ability to respond appropriately to changing input conditions and produced reasonably accurate simulations of observed precipitation patterns. The model performed well for sufficiently cold, strongly forced conditions but seemed overly sensitive to the accuracy of model assumptions regarding ice initiation for warmer, weakly forced situations.

Full access
Bruce D. Lee, Richard D. Farley, and Mark R. Hjelmfelt

Abstract

A numerical cloud model has been used to simulate convective storm development on 17 July 1987 in northeast Colorado. The study involves the simulation of convergence along atmospheric boundaries and the subsequent development of convection. The model was initialized using observed conditions for this case day from the Convection Initiation and Downburst Experiment (CINDE).

A two-dimensional version of the Clark NCAR nested grid model is employed. Results indicate that convection in boundary line collision cases can be successfully simulated by using actual observed atmospheric data. Gradual deepening of the moisture layer in the convergence zone was shown to destabilize the local atmosphere leading to the initiation of deep convection on this day. The modeled storm approximated the depth and intensity of the observed storms and displayed many of the features of the actual event.

Sensitivity studies revealed that the timing and intensity of convection along boundaries is greatly affected by alterations in cross-line values of boundary-layer moisture or convergence and by variations in the vertical wind-shear profile within and above the boundary layer. Increasing the low-level moisture created a much stronger and taller modeled storm that developed much more rapidly. Variations in boundary-layer convergence were shown to affect the timing and character of the modeled storm. Horizontal vorticity in the boundary layer, associated with low-level vertical wind shear, was important for the production of deep convection. When the two air masses collided, deeper lifting was obtained if the opposing vorticity of the moving boundaries was balanced than if one of the vorticity sources was significantly stronger than the other. A threshold value of shear above the boundary layer was shown to inhibit the convective development of the modeled storm. These sensitivity studies emphasize the importance of considering the mesoscale variability of these key parameters in nowcasting convection.

Full access
Mark R. Hjelmfelt, Richard D. Farley, and Philip C. S. Chen

Abstract

Numerical simulations are conducted to determine the possible effects of air pollution from coal-fired power plants on cloud and precipitation processes in the northern Great Plains. This study can only be considered as preliminary in nature since a complete cloud simulation is not employed and the ice phase is not considered.

Natural and polluted particulate distributions are developed based on observations in the northern Great Plains and of coal-fired power plant effluent. Cloud droplet growth on these distributions is simulated in a condensation model. Results of this model indicate that the number concentration and dispersion coefficient (breadth) of the cloud droplet size distributions are increased by the addition of pollutant particles, especially if these are more hygroscopic than the background nuclei.

Coalescence calculations using the results of the condensation studies as input are also reported. These results indicate that the rate of production of large drops, while being slowed by an increase in the number concentration, is hastened by an increase in the dispersion coefficient. These two effects nearly cancel each other out so that the time required for precipitation development is very nearly the same for cloud droplet distributions initialized on background and polluted particulate distributions. If, however, both distributions have the same dispersion, the polluted case requires a considerably longer time to develop precipitation.

Full access
J. Wang, M. R. Hjelmfelt, W. J. Capehart, and R. D. Farley

Abstract

Numerical simulations of two snowfall events over the Black Hills of South Dakota are made to demonstrate the use and potential of a coupled atmospheric and land surface model. The Coupled Atmospheric–Hydrologic Model System was used to simulate a moderate topographic snowfall event of 10–11 April 1999 and a blizzard event of 18–23 April 2000. These two cases were chosen to provide a contrast of snowfall amounts, locations, and storm dynamics. The model configuration utilized a nested grid with an outer grid of 16-km spacing driven by numerical forecast model data and an inner grid of 4 km centered over the Black Hills region. Simulations for the first case were made with the atmospheric model, the Advanced Regional Prediction System (ARPS) alone, and with ARPS coupled with the National Center for Atmospheric Research Land Surface Model (LSM). Results indicated that the main features of the precipitation pattern were captured by ARPS alone. However, precipitation amounts were greatly overpredicted. ARPS coupled with LSM produced a very similar precipitation pattern, but with precipitation amounts much closer to those observed. The coupled model also permits simulation of the resulting snow cover and snowmelt. Simulated percentage snow melting occurred somewhat more rapidly than that of the observed. Snow–rain discrimination may be taken from the precipitation type falling out of the atmospheric model based on the microphysical parameterization, or by the use of a surface temperature criteria, as used in most large-scale models. The resulting snow accumulation patterns and amounts were nearly identical. The coupled model configuration was used to simulate the second case. In this case the simulated precipitation and snow depth maximum over the eastern Black Hills were biased to the east and north by about 24 km. The resulting spatial correlation of the simulated snowfall and observations was only 0.37. If this bias is removed, the shifted pattern over the Black Hills region has a correlation of 0.68. Snow-melting patterns for 21 and 22 April appeared reasonable, given the spatial bias in the snowfall simulation.

Full access