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Abstract
The past several years have seen a renewed interest in the importance of low-density riming growth to the development of hailstones. This paper reports on the results of a study that incorporates the physical factors controlling the density of the rime deposit in a two-dimensional, time-dependent numerical cloud model with discretized treatment of the graupel/hail size distribution. Comparisons are made between cases in which the mass-diameter relationship is fixed based on a priori assumed particle densities and cases in which the mass-diameter relationship is allowed to change in accordance with the variable particle density diagnosed from the riming density relationship and past growth history.
Compared to the fixed particle density treatment common to earlier work, ice particles of lower density have enhanced surface and cross-sectional area for particles of equal mass, which in turn, increases the effective ventilation experienced by the particles and their capture volumes, thus allowing enhanced diffusional and accretional growth. The lower density particles also experience reduced sedimentation effects due to reduced fallspeeds. This leads to increased residence time in favorable growth environments for both the low density embryos in the region of the embryo curtain and for medium density particles growing to hail in the more active regions of the cloud.
Abstract
The past several years have seen a renewed interest in the importance of low-density riming growth to the development of hailstones. This paper reports on the results of a study that incorporates the physical factors controlling the density of the rime deposit in a two-dimensional, time-dependent numerical cloud model with discretized treatment of the graupel/hail size distribution. Comparisons are made between cases in which the mass-diameter relationship is fixed based on a priori assumed particle densities and cases in which the mass-diameter relationship is allowed to change in accordance with the variable particle density diagnosed from the riming density relationship and past growth history.
Compared to the fixed particle density treatment common to earlier work, ice particles of lower density have enhanced surface and cross-sectional area for particles of equal mass, which in turn, increases the effective ventilation experienced by the particles and their capture volumes, thus allowing enhanced diffusional and accretional growth. The lower density particles also experience reduced sedimentation effects due to reduced fallspeeds. This leads to increased residence time in favorable growth environments for both the low density embryos in the region of the embryo curtain and for medium density particles growing to hail in the more active regions of the cloud.
Abstract
This paper reports on simulations of a multicellular hailstorm case observed during the 1983 Alberta Hail Project. The field operations on that day concentrated on two successive feeder cells which were subjected to controlled seeding experiments. The fist of these cells received the placebo treatment and the second was seeded with dry ice. The principal tool of this study is a modified version of the two-dimensional, time dependent hail category model described in Part I of this series of papers. It is with this model that hail growth processes are investigated, including the simulated effects of cloud seeding techniques as practiced in Alberta.
The model simulation of the natural case produces a very good replication of the observed storm, particularly the placebo feeder cell. This is evidenced, in particular, by the high degree of fidelity of the observed and modeled radar reflectivity in terms of magnitudes, structure, and evolution. The character of the hailfall at the surface and the scale of the storm are captured nicely by the model, although cloud-top heights are generally too high, particularly for the mature storm system.
Seeding experiments similar to those conducted in the field have also been simulated. These involve seeding the feeder cell early in its active development phase with dry ice (CO2) or silver iodide (AgI) introduced near cloud top. The model simulations of these seeded cases capture some of the observed seeding signatures detected by radar and aircraft. In these model experiments, CO2 seeding produced a stronger response than AgI seeding relative to inhibiting hail formation. For both seeded cases, production of precipitating ice was initially enhanced by the seeding, but retarded slightly in the later stages, the net result being modest increases in surface rainfall, with hail reduced slightly. In general, the model simulations support several subhypotheses of the operational strategy of the Alberta Research Council regarding the earlier formation of ice, snow, and graupel due to seeding.
Abstract
This paper reports on simulations of a multicellular hailstorm case observed during the 1983 Alberta Hail Project. The field operations on that day concentrated on two successive feeder cells which were subjected to controlled seeding experiments. The fist of these cells received the placebo treatment and the second was seeded with dry ice. The principal tool of this study is a modified version of the two-dimensional, time dependent hail category model described in Part I of this series of papers. It is with this model that hail growth processes are investigated, including the simulated effects of cloud seeding techniques as practiced in Alberta.
The model simulation of the natural case produces a very good replication of the observed storm, particularly the placebo feeder cell. This is evidenced, in particular, by the high degree of fidelity of the observed and modeled radar reflectivity in terms of magnitudes, structure, and evolution. The character of the hailfall at the surface and the scale of the storm are captured nicely by the model, although cloud-top heights are generally too high, particularly for the mature storm system.
Seeding experiments similar to those conducted in the field have also been simulated. These involve seeding the feeder cell early in its active development phase with dry ice (CO2) or silver iodide (AgI) introduced near cloud top. The model simulations of these seeded cases capture some of the observed seeding signatures detected by radar and aircraft. In these model experiments, CO2 seeding produced a stronger response than AgI seeding relative to inhibiting hail formation. For both seeded cases, production of precipitating ice was initially enhanced by the seeding, but retarded slightly in the later stages, the net result being modest increases in surface rainfall, with hail reduced slightly. In general, the model simulations support several subhypotheses of the operational strategy of the Alberta Research Council regarding the earlier formation of ice, snow, and graupel due to seeding.
Abstract
A two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the “bulk water” microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron process and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outside the cloud. The melting of hail and snow are included in the model. Wet and dry growth of hail and shedding of rain from hail are simulated.
The simulations show that the inclusion of snow has improved the realism of the results compared to a model without snow. The formation of virga from cloud anvils is now modeled. Addition of the snow field has resulted in the inclusion of more diverse and physically sound mechanisms for initiating the hail field, yielding greater potential for distinguishing dominant embryo types characteristically different from warm- and cold-based clouds.
Abstract
A two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the “bulk water” microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron process and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outside the cloud. The melting of hail and snow are included in the model. Wet and dry growth of hail and shedding of rain from hail are simulated.
The simulations show that the inclusion of snow has improved the realism of the results compared to a model without snow. The formation of virga from cloud anvils is now modeled. Addition of the snow field has resulted in the inclusion of more diverse and physically sound mechanisms for initiating the hail field, yielding greater potential for distinguishing dominant embryo types characteristically different from warm- and cold-based clouds.
Abstract
Studies have been conducted to determine the cloud seeding potential of stratiform type clouds using a two-dimensional, time-dependent cloud model. An atmospheric sounding from Villanubla, Spain, in February 1980, was used to initialize the model. The model is designed to allow mesoscale convergence in the lower levels and divergence in the upper levels, which results in a stratiform-type cloud in this Spanish situation.
The seeding of clouds using either dry ice or silver iodide has been tested and rather surprising results are indicated. The silver iodide seeding simulations produce strong dynamic responses in the model clouds, even with small amounts of supercooled liquid available and a few natural ice crystals per liter in the cloud. These effects occur in a nearly moist adiabatic layer as well as in a convectively unstable layer.
The effects appear to be due to the heat released as the liquid freezes and the cloudy environment switches from liquid saturation to ice saturation. Cloud vertical motions of a few to several m s−1 are produced in the seeded cloud region. Vertical motions of 10 to 20 cm s−1 exist in comparable regions of the unseeded cloud. Precipitation is strongly affected. Consequently, this heat release is much more significant in terms of the overall energetics of the cloud than has been evident in our seeding simulation conducted in pure convective situations with much stronger updrafts.
The tests of the dry ice seeding indicate small effects, but this is largely due to the rapid fall of the dry ice pellets through the cloud and to the short time period available for the seeding to take effect.
Abstract
Studies have been conducted to determine the cloud seeding potential of stratiform type clouds using a two-dimensional, time-dependent cloud model. An atmospheric sounding from Villanubla, Spain, in February 1980, was used to initialize the model. The model is designed to allow mesoscale convergence in the lower levels and divergence in the upper levels, which results in a stratiform-type cloud in this Spanish situation.
The seeding of clouds using either dry ice or silver iodide has been tested and rather surprising results are indicated. The silver iodide seeding simulations produce strong dynamic responses in the model clouds, even with small amounts of supercooled liquid available and a few natural ice crystals per liter in the cloud. These effects occur in a nearly moist adiabatic layer as well as in a convectively unstable layer.
The effects appear to be due to the heat released as the liquid freezes and the cloudy environment switches from liquid saturation to ice saturation. Cloud vertical motions of a few to several m s−1 are produced in the seeded cloud region. Vertical motions of 10 to 20 cm s−1 exist in comparable regions of the unseeded cloud. Precipitation is strongly affected. Consequently, this heat release is much more significant in terms of the overall energetics of the cloud than has been evident in our seeding simulation conducted in pure convective situations with much stronger updrafts.
The tests of the dry ice seeding indicate small effects, but this is largely due to the rapid fall of the dry ice pellets through the cloud and to the short time period available for the seeding to take effect.
Abstract
A two-dimensional time-dependent cloud model which covers a region 19.2 km × 19.2 km in the x and z directions with 200 m grid intervals, has been used to simulate silver iodide (AgI) seeding effects on strong convective clouds. The model is a set of conservation equations for momentum, energy and mass (air and water contents). One extra conservation equation is applied to trace the seeding agent which advects and diffuses along the flow field and interacts with the supercooled cloud fields. Contact and deposition nucleation are simulated. Only inertial impact and Brownian collection are considered as possible mechanisms for contact nucleation. Most of the AgI particles work as deposition or sorption nuclei in this study.
Three different soundings are tested. Most of the effort is used in testing sounding H1, from Miles City, Montana, 29 July 1975. Seeding at a different place (see H1/P1), at a different time (case H1/T1), and with different amounts of AgI (cases H1/M1 and H1/M2) are simulated. The effects of natural ice nuclei are also tested (cases H1/N2, H1/N3 and H1/S3). The model results show a “time window” for the icing process in natural (unseeded) cases. This time window is related to the concentration of the natural ice nuclei and the flow pattern. Concerning seeding effects, this study shows the potential to augment precipitation by AgI seeding. This potential is closely related to the dispersion of the proper amount of seeding agent into the proper region and at the proper time to obtain optimum effects.
Abstract
A two-dimensional time-dependent cloud model which covers a region 19.2 km × 19.2 km in the x and z directions with 200 m grid intervals, has been used to simulate silver iodide (AgI) seeding effects on strong convective clouds. The model is a set of conservation equations for momentum, energy and mass (air and water contents). One extra conservation equation is applied to trace the seeding agent which advects and diffuses along the flow field and interacts with the supercooled cloud fields. Contact and deposition nucleation are simulated. Only inertial impact and Brownian collection are considered as possible mechanisms for contact nucleation. Most of the AgI particles work as deposition or sorption nuclei in this study.
Three different soundings are tested. Most of the effort is used in testing sounding H1, from Miles City, Montana, 29 July 1975. Seeding at a different place (see H1/P1), at a different time (case H1/T1), and with different amounts of AgI (cases H1/M1 and H1/M2) are simulated. The effects of natural ice nuclei are also tested (cases H1/N2, H1/N3 and H1/S3). The model results show a “time window” for the icing process in natural (unseeded) cases. This time window is related to the concentration of the natural ice nuclei and the flow pattern. Concerning seeding effects, this study shows the potential to augment precipitation by AgI seeding. This potential is closely related to the dispersion of the proper amount of seeding agent into the proper region and at the proper time to obtain optimum effects.
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.
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.
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.
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.
Abstract
The application of a two-dimensional, time-dependent cloud model to describe the effects of dry ice cloud seeding is demonstrated. A conservation equation and associated auxiliary equations for the mixing ratio of dry ice (CO2) are presented. The importance of identical time steps in both seeded and unseeded cases is discussed.
Small convective clouds are seeded at about the −10°C level and the seeding agent (CO2) traced as it falls through the cloud creating a mass of cloud ice in its trail. The cloud ice transforms to snow and the snow to graupel/hail which then melts into rain as it falls below the zero degree isotherm level. Precipitation starts about 6 min earlier in the seeded cloud and the timing of the rain fallout affects the interaction with a second cell. Approximately 20% more rain falls from the seeded cell in a very light shower.
Abstract
The application of a two-dimensional, time-dependent cloud model to describe the effects of dry ice cloud seeding is demonstrated. A conservation equation and associated auxiliary equations for the mixing ratio of dry ice (CO2) are presented. The importance of identical time steps in both seeded and unseeded cases is discussed.
Small convective clouds are seeded at about the −10°C level and the seeding agent (CO2) traced as it falls through the cloud creating a mass of cloud ice in its trail. The cloud ice transforms to snow and the snow to graupel/hail which then melts into rain as it falls below the zero degree isotherm level. Precipitation starts about 6 min earlier in the seeded cloud and the timing of the rain fallout affects the interaction with a second cell. Approximately 20% more rain falls from the seeded cell in a very light shower.
Abstract
No abstract available.
Abstract
No abstract available.
Abstract
Observations made by the T-28 armored research aircraft, radar, and other data sources were used to study an eastern Moutana hailstorm that developed on 1 August 1981 during the Cooperative Convective Precipitation Experiment season. The storm featured a wide, persistent, vertically oriented updraft with speeds exceeding 35 m s−1. Hailstones of over 5 cm diameter were collected at the ground, while the T-28 encountered hail up to about 2.5 cm diameter. Them was no evidence of feeder cells or a weak echo region.
The IAS two-dimensional, time-dependent “bulk water” model was run on this case, using a sounding from this day. Some areas of agreement between the simulation and observations include the maximum updraft speed, cloud top height, presence of a rounded cloud dome, and maximum radar reflectivity. The simulation failed to properly model the width and orientation of the updraft, as well as its long lifetime.
The IAS hail category model was also run on this case. This model features 20 categories of ice particles, which aid in exploring the complexities of hailstone growth. This simulation was dynamically similar to the bulk water simulation. The model predictions of ice particle concentrations agreed fairly well with those observed, and the shedding of drops during the wet growth of had was a significant source of had embryos.
Abstract
Observations made by the T-28 armored research aircraft, radar, and other data sources were used to study an eastern Moutana hailstorm that developed on 1 August 1981 during the Cooperative Convective Precipitation Experiment season. The storm featured a wide, persistent, vertically oriented updraft with speeds exceeding 35 m s−1. Hailstones of over 5 cm diameter were collected at the ground, while the T-28 encountered hail up to about 2.5 cm diameter. Them was no evidence of feeder cells or a weak echo region.
The IAS two-dimensional, time-dependent “bulk water” model was run on this case, using a sounding from this day. Some areas of agreement between the simulation and observations include the maximum updraft speed, cloud top height, presence of a rounded cloud dome, and maximum radar reflectivity. The simulation failed to properly model the width and orientation of the updraft, as well as its long lifetime.
The IAS hail category model was also run on this case. This model features 20 categories of ice particles, which aid in exploring the complexities of hailstone growth. This simulation was dynamically similar to the bulk water simulation. The model predictions of ice particle concentrations agreed fairly well with those observed, and the shedding of drops during the wet growth of had was a significant source of had embryos.
