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William R. Cotton

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William R. Cotton

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In this paper, testing, implementation, and evolution of both static and dynamic seeding concepts are reviewed. A brief review of both waterspray and hygroscopic seeding is first presented. This is followed by reviews of static seeding of stable orographic clouds and supercooled cumuli. We conclude with a review of dynamic seeding concepts with particular focus on the Florida studies.

It is concluded that it is encouraging that our testing procedures have evolved from single-response-variable “blackbox” experiments to randomized experiments that attempt to test a number of components in the hypothesized chain of physical responses to seeding. It is cautioned, however, that changes in the seeding strategy to optimize detection of a physical response (in any of the intermediate links in the hypothesized chain of responses) can have an adverse effect upon rainfall on the ground.

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William R. Cotton

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A one-dimensional time-dependent cumulus model is developed and discussed. Data predicted by the model along with a bulk entrainment model are compared with a case study observation and Warner's mean profile of Q/QA. While a great deal of the discrepancy between observed and predicted data can he attributed to the transient nature of convection, the consistent pattern of overprediction of such cloud properties as Q/QA and vertical velocity is indeed disturbing. It is concluded that neither the entrainment model nor the scalar nonlinear eddy viscosity model can adequately treat the general problem of turbulent transport in convective clouds. There is, however, sufficient evidence suggesting the models can he of practical value if their use is limited to dynamically active clouds and, in the case of the entrainment model, to a restricted portion of the cloud cycle life. Furthermore, there is little doubt that the entrainment coefficient is not a universal constant while the universality of the mixing length coefficients in the eddy viscosity models is still in question.

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William R. Cotton

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A review of convective cloud modeling spanning the period from the days of the NOAA Experimental Meteorology Laboratory (EML) in the late 1960s to 2000 is presented. The intent is to illustrate the evolution of cloud models from the one-dimensional parcel-type models to the current generation of three-dimensional convective storm models and cloud ensemble models. Moreover, it is shown that Dr. Joanne Simpson played a pivotal role in the evolution of cloud models from the very first models to current generation cloud ensemble models. It is also shown that the first concept of the Regional Atmospheric Modeling System (RAMS) began while Drs. Cotton and Pielke worked under Dr. Simpson's supervision at EML. It is then illustrated how far cloud modeling has come with recent applications of RAMS to atmospheric research and numerical weather prediction. The chapter concludes with an outline of the major limitations of current generation convective cloud models.

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WILLIAM R. COTTON

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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.

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William R. Cotton

This review is begun with a brief summary of the current status of our understanding of the physics of precipitation in warm clouds. The impact of warm-cloud precipitation processes on the evolution of the ice phase in supercooled clouds also is discussed.

This is followed by a review of experimental attempts to modify the microstructure of warm clouds. Modeling studies of warm cloud modification and observational studies of inadvertent warm cloud modification also are drawn upon to further elucidate the physics of warm cloud modification. The hypotheses, and evidence, for dynamic modification of warm clouds are then discussed. A few brief comments on modeling of warm cloud processes also are given. These comments are intended to serve as a warning to the non-modeler to be very cautious in taking the results of the modeling studies at face value. Finally, the review is concluded with specific recommendations regarding the current status of warm cloud modification, and future directions for the scientist and the weather modification practitioner.

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WILLIAM R. COTTON

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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.

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Johannes Verlinde and William R. Cotton

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Observations collected during the Oklahoma–Kansas PRE-STORM experiment are used to document the evolution and structure of a mesoscale vortex couplet that developed in the mesoscale convective system that occurred on 16–17 June 1985. The evolution of the circulations was captured by dual-Doppler radar observations for 1.4 hours. This allowed an evaluation of the various terms of the vertical vorticity equation, which give insight into the mechanisms that are important in the generation of the circulations. The primary mechanism responsible for the formation of the observed vortices was the interaction of the larger-scale flow with low level momentum transported to higher levels by multiple convective updrafts. As a consequence vertical shear of the horizontal wind was important to initial vorticity production. The vorticity generated in this manner was subsequently increased in strength due to middle level convergence. When the convection weakened and dissipated, the primary source of vorticity was removed, and because this was an unbalanced circulation on a scale less than the Rossby radius of deformation, the vortex broke up and spun down. Comparisons are made with other documented cases, and differences and similarities are pointed out. It is hypothesized that this circulation is a common kind in precipitating mesoscale systems, which has hitherto largely been undetected because its size is too large to be easily observed in a Doppler radar network set up to study thunderstorms, yet too small to be detected by standard sounding networks or most research sounding networks.

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Gad Levy and William R. Cotton

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Nine clouds are simulated by perturbing Florida Area Cumulus Experiment (FACE) field soundings employing the Colorado State University cloud model. After a cloud similar in size to the one observed is initiated, glaciation is simulated in experiments designed to study the mechanisms by which glaciation is communicated to the subcloud boundary layer. Numerical model results show that the vertical pressure mechanism consisting of hydrostatic and dynamic pressure gradient force and “pressure buoyancy” is present, as is the downdraft mechanism, but they are secondary to loading, temperature buoyancy, water vapor buoyancy and the horizontal dynamic forces on the scale of a single deep convective cloud. The communication mechanism that has the most sustained and coherent influence upon the subcloud layer is the settling and evaporation of precipitation. A clear implication of this study to weather modification is that for dynamic seeding to have a significant influence upon the upscale growth of a cloud system, artificially triggered explosive growth of relatively weak convective towers must also be aimed at a carefully designed increase in the rainfall from those clouds.

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William R. Cotton and Albert Boulanger

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Using the one-dimensional cumulus model developed by Cotton, predictions of the effects of seeding cumulus clouds were performed during the month of July 1973 as part of the Experimental Meteorology Laboratory's Florida Area Cumulus Experiment 1973 experiment. In Part I we compared seedability predictions with the Miami 1200 GMT soundings and soundings taken over the center of the experimental area (Central Site) at 1400 GMT. It was found that substantial differences between the two predictions occurred on a number of days in spite of the fact that the soundings are separated in time by only 2 h and in space by only 110 km.

In this paper we compare seedability predictions with the MIA 1200 GMT soundings and the CS 1800 GMT soundings. The CS 1800 GMT soundings were assumed to be representative of conditions over the experimental area during the period of operation of the experiment. We found that the predictions with the MIA 1200 GMT soundings were, on the average, more representative of conditions over the center of the experimental area during the period of operation of the experiment than were the predictions with the CS 1400 GMT soundings. The results of this study indicate that the choice of a sounding site and sounding time to be used for prediction of seeding effects over an experimental area must be carefully considered in the design of the experiment.

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