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Abstract
Based on numerical experiments in droplet collection with a stochastic model similar to Berry's, a new quantitative definition of autoconversion is discussed. The new formulation of autoconversion is compared with Kessler's and with Berry's. The new formulation has the decisive advantage over Berry's model of being directly compatible with Kessler's accretion model.
Abstract
Based on numerical experiments in droplet collection with a stochastic model similar to Berry's, a new quantitative definition of autoconversion is discussed. The new formulation of autoconversion is compared with Kessler's and with Berry's. The new formulation has the decisive advantage over Berry's model of being directly compatible with Kessler's accretion model.
Abstract
A numerical model of supercooled cumuli is developed and discussed. Water substance in the model is idealized to be partitioned into the five phase components; namely, water vapor, liquid cloud water, liquid rainwater, frozen rainwater, and ice crystals. Continuity equations are developed that predict the distribution of water substance among the five phase components. The cloud dynamic framework consists of a simple one-dimensional Lagrangian model that includes the effects of entrainment. The model is able to operate either as a steady-state model or as a spherical vortex model.
The results of two case study experiments illustrated that the principle action of ice particles nucleated on sublimation nuclei, or by the freezing of cloud droplets in cumulus clouds containing moderate to heavy amounts of supercooled rainwater, is to promote the freezing of supercooled rainwater. On the other hand, clouds containing small amounts of supercooled rainwater are dynamically insensitive to moderate concentrations of ice crystals. In such clouds, extensive riming and vapor deposition growth of crystals in concentrations of several thousand per liter are required before they make significant contributions to the dynamic structure of the cloud.
Finally, it was found that the warm-cloud precipitation process can either invigorate or retard the dynamic behavior of a supercooled cloud, depending upon the height and magnitude of the precipitation process.
Abstract
A numerical model of supercooled cumuli is developed and discussed. Water substance in the model is idealized to be partitioned into the five phase components; namely, water vapor, liquid cloud water, liquid rainwater, frozen rainwater, and ice crystals. Continuity equations are developed that predict the distribution of water substance among the five phase components. The cloud dynamic framework consists of a simple one-dimensional Lagrangian model that includes the effects of entrainment. The model is able to operate either as a steady-state model or as a spherical vortex model.
The results of two case study experiments illustrated that the principle action of ice particles nucleated on sublimation nuclei, or by the freezing of cloud droplets in cumulus clouds containing moderate to heavy amounts of supercooled rainwater, is to promote the freezing of supercooled rainwater. On the other hand, clouds containing small amounts of supercooled rainwater are dynamically insensitive to moderate concentrations of ice crystals. In such clouds, extensive riming and vapor deposition growth of crystals in concentrations of several thousand per liter are required before they make significant contributions to the dynamic structure of the cloud.
Finally, it was found that the warm-cloud precipitation process can either invigorate or retard the dynamic behavior of a supercooled cloud, depending upon the height and magnitude of the precipitation process.
Abstract
This paper utilizes experimental data from a multiple Doppler radar and surface mesoscale network to describe the evolution and structure of a small, isolated, mesoscale convective system over the South Park region of central Colorado. This system evolved from a cluster of convective clouds which eventually transformed to a mature system possessing both stratiform and convective components. The structure of individual precipitating convective clouds comprising the mature system depended on their location (upshear or downshear) relative to the system. Unsteady upshear convective components formed discretely and propagated upshear. In contrast, downshear convective components occupied a greater area, exhibited more steadiness, and propagated downshear.
Doppler analyses indicate that mesoscale updrafts within anvils flanking the convective cores existed relatively early, about 1.5 h after first cloud formation. Mesoscale downdrafts did not appear until ∼3 h after precipitation initiation. The appearance of a mesoscale downdraft was temporally correlated with intensification of the upshear convective region. The analyses suggest a close dependence between upshear convection and the stratiform region in this case. Upshear convection supplied condensate to the stratiform region, while the stratiform region produced mesoscale downdrafts whose outflow boundary helped maintain the upshear convection.
Abstract
This paper utilizes experimental data from a multiple Doppler radar and surface mesoscale network to describe the evolution and structure of a small, isolated, mesoscale convective system over the South Park region of central Colorado. This system evolved from a cluster of convective clouds which eventually transformed to a mature system possessing both stratiform and convective components. The structure of individual precipitating convective clouds comprising the mature system depended on their location (upshear or downshear) relative to the system. Unsteady upshear convective components formed discretely and propagated upshear. In contrast, downshear convective components occupied a greater area, exhibited more steadiness, and propagated downshear.
Doppler analyses indicate that mesoscale updrafts within anvils flanking the convective cores existed relatively early, about 1.5 h after first cloud formation. Mesoscale downdrafts did not appear until ∼3 h after precipitation initiation. The appearance of a mesoscale downdraft was temporally correlated with intensification of the upshear convective region. The analyses suggest a close dependence between upshear convection and the stratiform region in this case. Upshear convection supplied condensate to the stratiform region, while the stratiform region produced mesoscale downdrafts whose outflow boundary helped maintain the upshear convection.
Abstract
In this paper the authors address one type of severe weather: strong straight-line winds. The case of a mesoscale convective system that developed in eastern Colorado on 12–13 May 1985 was studied. The system formed in the afternoon, was active until early morning, and caused strong winds during the night.
A multiscale nonhydrostatic full physics simulation was performed to formulate a conceptual model of the main airflow branches of the system, and to gain understanding of the physical processes involved in the strong wind generation in this storm. Four telescopically nested grids covering from the synoptic-scale down to cloud-scale circulations were used. A Lagrangian model was employed to follow trajectories of parcels that took part in the updraft and downdraft, and balances of forces were computed along the trajectories.
The strong nocturnal winds were caused by downdrafts reaching the surface and by a dynamically forced horizontal pressure gradient force. The most important branch of the downdraft had an “up–down” trajectory. Parcels originated close to the ground, were lifted up by a strong upward-directed pressure gradient force, and became colder than their surroundings as they ascended in a stable environment. Then, as they went through the precipitation shaft, they sank due to negative buoyancy enhanced by condensate loading. The upward pressure gradient force was partially related to midlevel perturbation vorticity in the storm.
Abstract
In this paper the authors address one type of severe weather: strong straight-line winds. The case of a mesoscale convective system that developed in eastern Colorado on 12–13 May 1985 was studied. The system formed in the afternoon, was active until early morning, and caused strong winds during the night.
A multiscale nonhydrostatic full physics simulation was performed to formulate a conceptual model of the main airflow branches of the system, and to gain understanding of the physical processes involved in the strong wind generation in this storm. Four telescopically nested grids covering from the synoptic-scale down to cloud-scale circulations were used. A Lagrangian model was employed to follow trajectories of parcels that took part in the updraft and downdraft, and balances of forces were computed along the trajectories.
The strong nocturnal winds were caused by downdrafts reaching the surface and by a dynamically forced horizontal pressure gradient force. The most important branch of the downdraft had an “up–down” trajectory. Parcels originated close to the ground, were lifted up by a strong upward-directed pressure gradient force, and became colder than their surroundings as they ascended in a stable environment. Then, as they went through the precipitation shaft, they sank due to negative buoyancy enhanced by condensate loading. The upward pressure gradient force was partially related to midlevel perturbation vorticity in the storm.
Abstract
Vertical divergence of the mountain wave's momentum flux has recently been hypothesized to be an important contribution to the global momentum budget. Wavebreaking theories and envelope orography have been employed to explain the divergence of the momentum flux. Here, cloud-top radiational cooling is shown to locally destabilize the environment and disrupt the propagation of the mountain wave in idealized two-dimensional simulations, thus drastically altering the expected momentum flux profile. Also, simulations of two-dimensional mountain waves indicate that nonlinearities can increase the wave response if the lower layer is decoupled from the flow aloft or decrease the wave response by providing multiple reflection levels for the incident mountain wave. The onset of wavebreaking and the level at which the wave breaks can be influenced by the ambient thermodynamic profile.
Abstract
Vertical divergence of the mountain wave's momentum flux has recently been hypothesized to be an important contribution to the global momentum budget. Wavebreaking theories and envelope orography have been employed to explain the divergence of the momentum flux. Here, cloud-top radiational cooling is shown to locally destabilize the environment and disrupt the propagation of the mountain wave in idealized two-dimensional simulations, thus drastically altering the expected momentum flux profile. Also, simulations of two-dimensional mountain waves indicate that nonlinearities can increase the wave response if the lower layer is decoupled from the flow aloft or decrease the wave response by providing multiple reflection levels for the incident mountain wave. The onset of wavebreaking and the level at which the wave breaks can be influenced by the ambient thermodynamic profile.
Abstract
The interaction of topographically induced thermally and mechanically driven diurnal flow regimes in the lee of the Rockies is shown to lead to the growth of a mesoscale convective system (MCS). An organic MCS observed during the 1977 combined South Park Area Cumulus Experiment and High Plains Experiment is numerically simulated with a two-dimensional nonhydrostatic cloud model covering spatial scales of 1000 km. In this numerical investigation,mesoγ-, mesoβ- and mesoα-scales of motion are represented simultaneously. As a result, interesting features of cloud-mesoscale interaction are predicted that cannot be represented in cloud parameterization frameworks. Based on the results of this simulation, a six-stage conceptual model of orogenic development is given.
Abstract
The interaction of topographically induced thermally and mechanically driven diurnal flow regimes in the lee of the Rockies is shown to lead to the growth of a mesoscale convective system (MCS). An organic MCS observed during the 1977 combined South Park Area Cumulus Experiment and High Plains Experiment is numerically simulated with a two-dimensional nonhydrostatic cloud model covering spatial scales of 1000 km. In this numerical investigation,mesoγ-, mesoβ- and mesoα-scales of motion are represented simultaneously. As a result, interesting features of cloud-mesoscale interaction are predicted that cannot be represented in cloud parameterization frameworks. Based on the results of this simulation, a six-stage conceptual model of orogenic development is given.
Abstract
A detailed analysis of the dynamics and thermodynamics responsible for the structure, growth and propagation of an orogenic mesoscale convective system simulated in two dimensions is made. The process of scale interaction is addressed through Fourier analysis and Reynolds averaging analysis of representative predicted variables, diabatic forcing and momentum acceleration terms. Additional dynamical analysis is accomplished through sensitivity experiments in which Coriolis, diabatic heating and ambient airflow are varied.
The general conclusion is that the simulated orogenic development is a geostrophic adjustment process to convective heating which is itself modulated and maintained by orographically induced flow systems. The heating scales range over a nearly continuous spectrum ranging from 10–250 km. The heating occurs in response to primary advective gravity modes. The larger-scale gravity-wave disturbances modulate the smaller scales by organizing mean upward vertical motion patterns. The largest gravity-wave modes are modulated by constraints of the slope flow circulation, namely a phasing of an advective mode with a localized break in the plains inversion.
The simulated growth to mesoα-scale proportions occurs from the horizontal expansion of the disturbance through interaction with the mountain-plains scale slope flow circulation. Similar to upscale two-dimensional turbulence cascade, the mountain plains solenoid deforms thermal patterns, increasing their scale. As the scale reaches mesoα-scale proportions, geostrophic adjustment frequencies are sufficient to allow the thermal fields to persist. Implications to the problem of cumulus parameterization and limitations of the two-dimensional framework of this numerical study are discussed.
Abstract
A detailed analysis of the dynamics and thermodynamics responsible for the structure, growth and propagation of an orogenic mesoscale convective system simulated in two dimensions is made. The process of scale interaction is addressed through Fourier analysis and Reynolds averaging analysis of representative predicted variables, diabatic forcing and momentum acceleration terms. Additional dynamical analysis is accomplished through sensitivity experiments in which Coriolis, diabatic heating and ambient airflow are varied.
The general conclusion is that the simulated orogenic development is a geostrophic adjustment process to convective heating which is itself modulated and maintained by orographically induced flow systems. The heating scales range over a nearly continuous spectrum ranging from 10–250 km. The heating occurs in response to primary advective gravity modes. The larger-scale gravity-wave disturbances modulate the smaller scales by organizing mean upward vertical motion patterns. The largest gravity-wave modes are modulated by constraints of the slope flow circulation, namely a phasing of an advective mode with a localized break in the plains inversion.
The simulated growth to mesoα-scale proportions occurs from the horizontal expansion of the disturbance through interaction with the mountain-plains scale slope flow circulation. Similar to upscale two-dimensional turbulence cascade, the mountain plains solenoid deforms thermal patterns, increasing their scale. As the scale reaches mesoα-scale proportions, geostrophic adjustment frequencies are sufficient to allow the thermal fields to persist. Implications to the problem of cumulus parameterization and limitations of the two-dimensional framework of this numerical study are discussed.
Abstract
The mesoscale convective complex (MCC) is a common and particularly well-organized class of meso-&α scale storm systems over the central United States. As observed by infrared (IR) satellite, the typical MCC's 10–12 h evolution displays a fairly consistent sequence of events, including the monotonic areal expansion of its anvil from its formation to its maximum size, followed by the monotonic shrinkage of the colder cloud top areas as the system weakens and dissipates. Primarily within the growth phase of this cycle, a characteristic IR signature reflects the MCC in its most intense, mesoconvective stage, which lasts ∼4 h and during which the coldest cloud top area reaches its largest extent.
Hourly precipitation data have been analyzed for 122 MCC cases that were selected from June–August 1977–83 and screened to insure a reasonable conformity with the typical IR life cycle. On average. these systems produced a rainfall volume of 3.46 km 3 during their life cycle, over an area of 3.20×105km2and at an average depth of 10.8 mm. Relative to a normalized, IR-defined life cycle, the averaged trends of hourly rainfall area, intensity, and volume all have well-defined growth/ decay cycles, but with significantly staggered maxima. Average rainfall intensity (R), and the proportion of measurable reports due to convective intensifies, attain maxima early in the life cycle. Hourly rainfall volumes (ν) are more symmetrically distributed in time, with the maximum occurring near the largest anvil size (based on −54°C IR threshold). Active rainfall area (A) continues to increase until ∼1 h after maximum anvil size. The IR-defined, intense mesoconvective stage corresponds to that portion of the life cycle from maximum R to maximum A, and is so termed because of the large areal extent and volumetric rate of convective precipitation intensities. A large area of stratiform precipitation is generated during this stage; it persists and becomes increasingly dominant as convective activity subsides during the latter stages of the life cycle. Averaged mappings of the precipitation data show that throughout the MCC life cycle, the heaviest rainfall tends to be displaced 50–100 km south of the cloud-shield centroid, while the stratiform pattern tends to be more MCC-centered.
A statistical analysis of these precipitation characteristics, derived individually for each case, provides an estimate of the natural interstorm variability for typical summertime MCCS. A comparison of various composite subsets of the sample reveals several interesting tendencies: 1) smaller, less-organized systems tended to be “drier” than similar-sized but better-organized MCCS; 2) large systems were "rainier” than smaller ones through much of the life cycle, not only in terms of A and V, as expected, but also in terms of R; 3) large systems tended to be “rdnice” in the eastern part of the sample domain than in the western part, but this was not so for small systems; and 4) the eastern systems: both large and small, had a more coherent and intense core of heavy precipitation through their life cycle than the western systems.
Abstract
The mesoscale convective complex (MCC) is a common and particularly well-organized class of meso-&α scale storm systems over the central United States. As observed by infrared (IR) satellite, the typical MCC's 10–12 h evolution displays a fairly consistent sequence of events, including the monotonic areal expansion of its anvil from its formation to its maximum size, followed by the monotonic shrinkage of the colder cloud top areas as the system weakens and dissipates. Primarily within the growth phase of this cycle, a characteristic IR signature reflects the MCC in its most intense, mesoconvective stage, which lasts ∼4 h and during which the coldest cloud top area reaches its largest extent.
Hourly precipitation data have been analyzed for 122 MCC cases that were selected from June–August 1977–83 and screened to insure a reasonable conformity with the typical IR life cycle. On average. these systems produced a rainfall volume of 3.46 km 3 during their life cycle, over an area of 3.20×105km2and at an average depth of 10.8 mm. Relative to a normalized, IR-defined life cycle, the averaged trends of hourly rainfall area, intensity, and volume all have well-defined growth/ decay cycles, but with significantly staggered maxima. Average rainfall intensity (R), and the proportion of measurable reports due to convective intensifies, attain maxima early in the life cycle. Hourly rainfall volumes (ν) are more symmetrically distributed in time, with the maximum occurring near the largest anvil size (based on −54°C IR threshold). Active rainfall area (A) continues to increase until ∼1 h after maximum anvil size. The IR-defined, intense mesoconvective stage corresponds to that portion of the life cycle from maximum R to maximum A, and is so termed because of the large areal extent and volumetric rate of convective precipitation intensities. A large area of stratiform precipitation is generated during this stage; it persists and becomes increasingly dominant as convective activity subsides during the latter stages of the life cycle. Averaged mappings of the precipitation data show that throughout the MCC life cycle, the heaviest rainfall tends to be displaced 50–100 km south of the cloud-shield centroid, while the stratiform pattern tends to be more MCC-centered.
A statistical analysis of these precipitation characteristics, derived individually for each case, provides an estimate of the natural interstorm variability for typical summertime MCCS. A comparison of various composite subsets of the sample reveals several interesting tendencies: 1) smaller, less-organized systems tended to be “drier” than similar-sized but better-organized MCCS; 2) large systems were "rainier” than smaller ones through much of the life cycle, not only in terms of A and V, as expected, but also in terms of R; 3) large systems tended to be “rdnice” in the eastern part of the sample domain than in the western part, but this was not so for small systems; and 4) the eastern systems: both large and small, had a more coherent and intense core of heavy precipitation through their life cycle than the western systems.
Abstract
A variety of meso-β-scale (20–200 km, <6 h) temporal and spatial characteristics associated with the life-cycle of the meso-α-scale (200–2000 km, >6 h) convective complex (MCC) are described. The analysis is based on a typical episode of MCCs in the central United States. Thunderstorms in the MCC are generally well-organized into meso-β-scale convective features. The larger MCCs are typically preceded by several of these meso-β convective clusters or bands, which tend to be aligned along linear meso-α-scale features such as the eastern slope of the Rockies or thermodynamic discontinuities evident in hourly surface or satellite data. The intense development of these larger systems involves the growth, merger and interaction of those meso-β convective feature located nearest the intersection of the meso-α axes along which they are aligned. Throughout the mature phase of the MCC, multiple meso-β convective components may persist within the more uniform meso-α cloud shield as expanding regions of stratiform anvil precipitation develop. The decay of the system is marked by the weakening and difluent propagation of its meso-β convective components. Hourly precipitation data reveal a characteristic precipitation life-cycle in relation to the MCC's satellite appearance. These typical meso-β-scale characteristics offer potential tools for the short-range forecasting of MCCs and their hydrological consequences.
Abstract
A variety of meso-β-scale (20–200 km, <6 h) temporal and spatial characteristics associated with the life-cycle of the meso-α-scale (200–2000 km, >6 h) convective complex (MCC) are described. The analysis is based on a typical episode of MCCs in the central United States. Thunderstorms in the MCC are generally well-organized into meso-β-scale convective features. The larger MCCs are typically preceded by several of these meso-β convective clusters or bands, which tend to be aligned along linear meso-α-scale features such as the eastern slope of the Rockies or thermodynamic discontinuities evident in hourly surface or satellite data. The intense development of these larger systems involves the growth, merger and interaction of those meso-β convective feature located nearest the intersection of the meso-α axes along which they are aligned. Throughout the mature phase of the MCC, multiple meso-β convective components may persist within the more uniform meso-α cloud shield as expanding regions of stratiform anvil precipitation develop. The decay of the system is marked by the weakening and difluent propagation of its meso-β convective components. Hourly precipitation data reveal a characteristic precipitation life-cycle in relation to the MCC's satellite appearance. These typical meso-β-scale characteristics offer potential tools for the short-range forecasting of MCCs and their hydrological consequences.
Abstract
Rapid advances in the quality and quantity of atmospheric observations have placed a demand for the development of techniques to assimilate these data sources into numerical forecasting models. Four-dimensional variational assimilation is a promising technique that has been applied to atmospheric and oceanic dynamical models, and to the retrieval of three-dimensional wind fields from single-Doppler radar observations.
This study investigates the feasibility of using space–time variational assimilation for a complex discontinuous numerical model including cloud physics. Two test models were developed: a one-dimensional and a two-dimensional liquid physics kinematic microphysical model. These models were used in identical-twin experiments, with observations taken intermittently. Small random errors were introduced into the observations. The retrieval runs were initialized with a large perturbation of the observation run initial conditions.
The models were able to retrieve the original initial conditions to a satisfactory degree when observations of all the model prognostic variables were used. Greater overdetermination of the degrees of freedom (the initial condition being retrieved) resulted in greater improvement of the errors in the observations of the initial conditions but at a rapid increase in computational cost. Experiments where only some of the prognostic variables were observed also improved the initial conditions, but at a greater cost. To substantially improve the first guess of the field not observed, some spot observations are needed.
The proper scaling of the variables was found to be important for the rate of convergence. This study suggests that scaling factors related to the error variance of the observations give good convergence rates.
To show how this technique can be used when observations are general functions of the prognostic variables of the model (e.g., reflectivity or liquid water path), a form is derived that shows that this can be accomplished. This is considered to be an advantage of this technique over other assimilation techniques, since it is particularly suitable to remote-sensing systems where only integral parameters or derivatives of model prognostic variables are observed.
Abstract
Rapid advances in the quality and quantity of atmospheric observations have placed a demand for the development of techniques to assimilate these data sources into numerical forecasting models. Four-dimensional variational assimilation is a promising technique that has been applied to atmospheric and oceanic dynamical models, and to the retrieval of three-dimensional wind fields from single-Doppler radar observations.
This study investigates the feasibility of using space–time variational assimilation for a complex discontinuous numerical model including cloud physics. Two test models were developed: a one-dimensional and a two-dimensional liquid physics kinematic microphysical model. These models were used in identical-twin experiments, with observations taken intermittently. Small random errors were introduced into the observations. The retrieval runs were initialized with a large perturbation of the observation run initial conditions.
The models were able to retrieve the original initial conditions to a satisfactory degree when observations of all the model prognostic variables were used. Greater overdetermination of the degrees of freedom (the initial condition being retrieved) resulted in greater improvement of the errors in the observations of the initial conditions but at a rapid increase in computational cost. Experiments where only some of the prognostic variables were observed also improved the initial conditions, but at a greater cost. To substantially improve the first guess of the field not observed, some spot observations are needed.
The proper scaling of the variables was found to be important for the rate of convergence. This study suggests that scaling factors related to the error variance of the observations give good convergence rates.
To show how this technique can be used when observations are general functions of the prognostic variables of the model (e.g., reflectivity or liquid water path), a form is derived that shows that this can be accomplished. This is considered to be an advantage of this technique over other assimilation techniques, since it is particularly suitable to remote-sensing systems where only integral parameters or derivatives of model prognostic variables are observed.
