Applied Cloud Physics

Investigating Precipitation Formation in Winter Storms

Water resources in the western U.S. primarily comes from winter snowpack. In response to increasing demand and limits on supplies, western communities have instituted water-conservation measures to preserve existing supply and/or sought additional water sources through technologies such as cloud seeding. Water will become an increasingly scarce resource as the population continues to grow and the climate changes over the coming decades (Rasmussen et al. 2011). Reduction of water supplies impacts nearly all aspects of western U.S. society, including drinking water, hydropower, irrigation, and tourism.  The recent report by the U.S. Bureau of Reclamation (20xx) highlights these western water issues, and also outlines approaches to further conserve and develop water in the west, including the use of cloud seeding. 

It is not surprising then that many western states have sought to augment water using operational cloud seeding programs.  These programs are based on glaciogenic cloud seeding with either silver iodide (AgI) or liquid propane.  The concept is that some wintertime clouds contain liquid water at subfreezing temperatures, or supercooled liquid water (SLW), that has not participated in the precipitation process due to the lack of effective ice nuclei at relatively warm subfreezing temperatures (typically -5 to -15 °C).  Cloud seeding can provide artificial ice nuclei that can convert these supercooled liquid drops to ice crystals that rapidly grow to snowflake sizes and fall out.  

To date, the effectiveness of glaciogenic cloud seeding with AgI has not been scientifically verified.  HAP scientists have been requested by various state entities to perform a scientifica evaluation of the potential for orographic seeding.  This has led to active work in Wyoming and Idaho.  

Measuring snow

Solid precipitation (i.e. snow, ice) is one of the more complex parameters to be observed and measured by automatic sensors. The measurement of precipitation has been the subject of numerous studies, but there has limited coordinated assessments of the ability and reliability of automatic sensors to accurately measure solid precipitation. The WMO Solid Precipitation Measurement Intercomparison Experiment (SPICE) focuses on measuring precipitation amount, precipitation intensity, and precipitation type (liquid, solid, mixed), over various time periods (minutes, hours, days, season) as well as snow on the ground (snow depth).


  • Department of Water Resources Studies
  • Idaho Power Company
  • Queensland Government
  • State of Wyoming Water Development Commission (WWDC)
  • University of Witwatersrand
  • Weather Modification, Inc.
  • World Meteorological Organization (WMO)
  • Wyoming Water Development Commission


Representative Projects

  • Bighorn Mountains: Performed a feasibility study to assess the potential for cloud seeding in the Bighorn Mountains in north-central Wyoming

  • Feasibility Study for Rainfall Enhancement - UAE

  • Idaho Power Project: Partnered with the Idaho Power Project to assess the effectiveness of cloud seeding using ground generators and aircraft tracks.

  • Solid Precipitation Intercomparison Experiment - SPICE : The WMO Solid Precipitation Intercomparison Experiment (WMO-SPICE) project studied the performance of modern automated sensors used to measure solid precipitation.

  • Southeast Queensland Cloud Seeding Research Program (CSRP): The Southeast Queensland Cloud Seeding Research Program (CSRP) was implemented to assess the feasibility of precipitation enhancement via cloud seeding

  • Wyoming Weather Modification Pilot Project: Implemented an orographic cloud-seeding program in three Wyoming target areas to evaluate the feasibility and effectiveness of cloud seeding

Search through all publications in NCAR's OpenSky Library.

Tessendorf, S. A., and Coauthors, 2019: Transformational approach to winter orographic weather modification research: The SNOWIE Project. Bull. Amer. Meteor. Soc., 100, 71–92,

Robert M. Rauber, Bart Geerts, Lulin Xue, Jeffrey French, Katja Friedrich, Roy M. Rasmussen, Sarah A. Tessendorf, Derek R. Blestrud, Melvin L. Kunkel, and Shaun Parkinson. (2019) Wintertime Orographic Cloud Seeding—A Review. Journal of Applied Meteorology and Climatology 58:10, 2117-2140.Rasmussen, R. M., and Coauthors, 2018: Evaluation of the Wyoming Weather Modification Pilot Project (WWMPP) using two approaches: Traditional statistics and ensemble modeling. Journal of Applied Meteorology and Climatology, 57, 2639-2660, doi:10.1175/JAMC-D-17-0335.1.

Rasmussen, R. M., and Coauthors, 2018: Evaluation of the Wyoming Weather Modification Pilot Project (WWMPP) using two approaches: Traditional statistics and ensemble modeling. Journal of Applied Meteorology and Climatology, 57, 2639-2660, doi:10.1175/JAMC-D-17-0335.1.

Monaghan, A. J., M. P. Clark, M. P. Barlage, A. J. Newman, L. Xue, J. R. Arnold, and R. M. Rasmussen, 2018: High-resolution historical climate simulations over Alaska. Journal of Applied Meteorology and Climatology, 57, 709-731, doi:10.1175/JAMC-D-17-0161.1.

French, J. R., and Coauthors, 2018: Precipitation formation from orographic cloud seeding. Proceedings of the National Academy of Sciences, 115, 1168-1173, doi:10.1073/pnas.1716995115.

Xue, L., and Coauthors, 2017: Idealized simulations of a squall line from the MC3E field campaign applying three bin microphysics schemes: Dynamic and thermodynamic structure. Monthly Weather Review, 145, 4789-4812, doi:10.1175/MWR-D-16-0385.1.

Keeler, J. M., R. M. Rauber, B. F. Jewett, G. M. McFarquhar, R. M. Rasmussen, L. Xue, C. Liu, and G. Thompson, 2017: Dynamics of cloud-top generating cells in winter cyclones. Part III: Shear and convective organization. Journal of the Atmospheric Sciences, 74, 2879-2897, doi:10.1175/JAS-D-16-0314.1.

Xue, L., and Coauthors, 2017: WRF Large-eddy Simulations of chemical tracer deposition and seeding effect over complex terrain from ground- and aircraft-based AgI  generators. Atmospheric Research, 190, 89-103, doi:10.1016/j.atmosres.2017.02.013.

Geresdi, I., L. Xue, and R. Rasmussen, 2017: Evaluation of orographic cloud seeding using a bin microphysics scheme: Two-dimensional approach. Journal of Applied Meteorology and Climatology, 56, 1443-1462, doi:10.1175/JAMC-D-16-0045.1.

Applied Cloud Physics