The Simulation of Cloud Seeding Effects using Numerical Cloud Models

Authors

  • Harold D Orville Institute of Atmospheric Sciences South Dakota School of Mines and Technology Rapid City, South Dakota
  • Richard D Farley Institute of Atmospheric Sciences South Dakota School of Mines and Technology Rapid City, South Dakota
  • Fred J Kopp Institute of Atmospheric Sciences South Dakota School of Mines and Technology Rapid City, South Dakota

DOI:

https://doi.org/10.54782/jwm.v23i1.319

Abstract

One of the technological and scientific developments helping to quantify cloud results is cloud models which, in some instances, require nearly as much computing power as the larger scale climate and general circulation models of the atmosphere. Cloud seeding simulations have been conducted in multi-dimensional, time-dependent cloud models over the past 10 to 15 years, and are increasing in frequency now as computers are more able to handle the task. This presentation will review some of the results obtained. The cloud models are sets of nonlinear partial differential quations, representing the conservation of mass, momentum, and energy. All phases of water are considered. The models treat all types of clouds, from severe convection with hail to gentle upslope motion stratus clouds with snow and light rain, on to non-precipitating clouds. The ice processes are emphasized in both field operations and modeling. Cloud seeding is simulated by changing the initiation and number of ice crystals in the cloud. The most realistic way to make this change is via the simulation of seeding agents, such as silver iodide or solid carbon dioxide, and their interactions with supercooled liquid water and water vapor. The results of the modeling have indicated support for the basic hypotheses of cloud seeding and have shown quantitatively the signals to be expected from the seeding.

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Section

Scientific Papers

How to Cite

The Simulation of Cloud Seeding Effects using Numerical Cloud Models. (1991). The Journal of Weather Modification, 23(1), 17-26. https://doi.org/10.54782/jwm.v23i1.319