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  • View in gallery

    Operational cloud-seeding project target areas for enhancement of winter snowpack in the mountains of the western United States in 2015 (colored green). No projects occurred in the states that are colored blue. (Source: North American Weather Modification Council.)

  • View in gallery

    Locations of major research projects in the western United States that were designed to evaluate the feasibility of orographic enhancement of snowpack through cloud seeding over the period 1960–2019.

  • View in gallery

    Examples of (left) WRF-simulated and (right) HYSPLIT-simulated AgI number concentrations using a logarithmic scale [log(m−3)] at three vertical levels: (a) 2500, (b) 3000, and (c) 3500 m MSL. The ground-based AgI generators are at the southern edge of the plume indicated by the stars on the HYSPLIT maps. The WRF maps include terrain contours (1500 and 2500 m) and state lines for Idaho.

  • View in gallery

    Three-dimensional depictions of the topography of the Medicine Bow Range in Wyoming, AgI aerosol number concentration (>100 L−1 for visible plumes), and wind vectors at three levels [~2800 (yellow), ~3600 m (blue), and ~4400 (purple) m MSL] at three times separated by 90 min, shown as a (left) bird’s-eye view from the south and (right) side views from the southeast. (Adapted from Xue et al. (2014).]

  • View in gallery

    Example of seeding lines observed during the 2017 SNOWIE campaign. Shown, from a single pass by the Wyoming King Air, are in situ measured (a) hydrometeor concentration for liquid droplets (blue; from Cloud Droplet Probe) and ice particles (red; only particles >50 μm in diameter, from 2DS probe) and (b) bulk condensed water content for liquid (blue) and ice (red), both from the deep-cone Nevzorov probe. (c) The vertical cross-section of W-band reflectivity during the same pass. The horizontal dotted line is the flight track. The locations of echoes resulting from seeding plumes are highlighted (green line). (d) A time-coincident 0.5° plan-position indicator scan using a ground-based X-band Doppler on Wheels, with the horizontal extent of the echo resulting from the seeding plume also highlighted. Also shown are 2DS probe particle size distributions (e) measured inside the plumes (black) and just upwind of the plumes (blue) and (f) corresponding two-dimensional hydrometeor shadows (left) outside the plumes and (right) inside the plumes.

  • View in gallery

    Monthly time series of accumulative precipitation (mm) for (a) 2001–02, (b) 2003–04, (c) 2005–06, and (d) 2007–08. Solid line is simulated precipitation with the WRF Model at SNOTEL mountain site locations. Dashed lines are SNOTEL measurements, with gray shades representing 1 standard deviation from the average daily precipitation totals at SNOTEL sites. The dots are Parameter–Elevation Regressions on Independent Slopes Model (PRISM) monthly averaged snowfall estimates. [From Rasmussen et al. (2011).]

  • View in gallery

    Schematic of the AgI–cloud interactions that are simulated in the seeding parameterization. [Adapted from Xue et al. (2013a), with additional parameterizations now included in the scheme.]

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Wintertime Orographic Cloud Seeding—A Review

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  • 1 Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois
  • | 2 Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming
  • | 3 Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado
  • | 4 Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado
  • | 5 Idaho Power Company, Boise, Idaho
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Abstract

This paper reviews research conducted over the last six decades to understand and quantify the efficacy of wintertime orographic cloud seeding to increase winter snowpack and water supplies within a mountain basin. The fundamental hypothesis underlying cloud seeding as a method to enhance precipitation from wintertime orographic cloud systems is that a cloud’s natural precipitation efficiency can be enhanced by converting supercooled water to ice upstream and over a mountain range in such a manner that newly created ice particles can grow and fall to the ground as additional snow on a specified target area. The review summarizes the results of physical, statistical, and modeling studies aimed at evaluating this underlying hypothesis, with a focus on results from more recent experiments that take advantage of modern instrumentation and advanced computation capabilities. Recent advances in assessment and operations are also reviewed, and recommendations for future experiments, based on the successes and failures of experiments of the past, are given.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Robert M. Rauber, r-rauber@illinois.edu

Abstract

This paper reviews research conducted over the last six decades to understand and quantify the efficacy of wintertime orographic cloud seeding to increase winter snowpack and water supplies within a mountain basin. The fundamental hypothesis underlying cloud seeding as a method to enhance precipitation from wintertime orographic cloud systems is that a cloud’s natural precipitation efficiency can be enhanced by converting supercooled water to ice upstream and over a mountain range in such a manner that newly created ice particles can grow and fall to the ground as additional snow on a specified target area. The review summarizes the results of physical, statistical, and modeling studies aimed at evaluating this underlying hypothesis, with a focus on results from more recent experiments that take advantage of modern instrumentation and advanced computation capabilities. Recent advances in assessment and operations are also reviewed, and recommendations for future experiments, based on the successes and failures of experiments of the past, are given.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Robert M. Rauber, r-rauber@illinois.edu

1. Introduction

The U.S. population more than doubled from 1950 to 2010 and shifted from rural to urban areas (U.S. Census Bureau 2010). Southern and western states experienced the greatest population increase, resulting in concurrent expansion of public water supply systems. In response to increased demands and limits on water supplies, western communities have sought additional water sources through technologies such as cloud seeding, and/or have instituted water-conservation measures to preserve existing supply (Kenny et al. 2009). Water will become an increasingly scarce resource as populations continue to grow and changes in climate over the coming decades threaten the water volume of snow reservoirs in the western mountains (Mote et al. 2005; Rasmussen et al. 2011).

Across the western United States during winter, precipitation falls as snow over higher elevations along coastal ranges, and at nearly all elevations over interior mountain ranges. The ensuing snowmelt in spring and summer then provides annual water supplies. As early as the 1950s, following the discoveries of Schaefer and Vonnegut concerning cloud seeding (Schaefer 1946; Vonnegut 1947), water resource managers recognized that seeding wintertime orographic cloud systems had the potential to increase water supplies in arid regions. Increasing winter snowpack through seeding was envisioned as a means to enhance the natural snow reservoir that supplies water to drainage basins throughout the melt season. Indeed, the demand for water drove pioneering scientists in the 1950s to develop projects to evaluate the scientific basis for weather modification as a tool to increase water supplies. The early studies of orographic cloud seeding, which progressed to include elaborate field investigations in the 1970s and 1980s, made some progress in understanding the conditions under which cloud seeding could enhance precipitation, but were unable to clearly establish the magnitude of that enhancement. In its 2003 report, the National Research Council (NRC 2003) stated that “there still is no convincing scientific proof of the efficacy of intentional weather modification efforts.” Despite this uncertainty, operational winter orographic weather modification has continued in most western states of the United States (Fig. 1) and in other arid regions, a direct result of the increasing need for water, and the large potential cost benefit for production of additional water by cloud seeding.

Fig. 1.
Fig. 1.

Operational cloud-seeding project target areas for enhancement of winter snowpack in the mountains of the western United States in 2015 (colored green). No projects occurred in the states that are colored blue. (Source: North American Weather Modification Council.)

Citation: Journal of Applied Meteorology and Climatology 58, 10; 10.1175/JAMC-D-18-0341.1

The fundamental hypothesis underlying cloud seeding as a method to enhance precipitation from wintertime orographic cloud systems is that a cloud’s natural precipitation efficiency can be enhanced by converting supercooled water to ice upstream and over a mountain range in such a manner that newly created ice particles can grow and fall to the ground as additional snow on a specified target area. Orographic clouds, in this context, refers to cloud systems over mountain ranges, whether isolated or components of frontal systems within extratropical cyclones. This static-seeding hypothesis has its roots in the physical principle that the equilibrium vapor pressure with respect to ice is less than that with respect to liquid water at the same subfreezing temperature. Thus, at temperatures below 0°C, a water-saturated cloud (relative humidity with respect to water RHw = 100%) will be supersaturated with respect to ice at a rate of about 1% per degree Celsius of supercooling (Pruppacher and Klett 2010). The consequence is that in an initially water-saturated cloud containing supercooled water, ice particles grow rapidly to precipitation size, whereas small and nonprecipitating supercooled cloud droplets are either growing in an updraft or evaporating, providing moisture for ice growth. Alfred Wegener first proposed this diffusional growth process for liquid-saturated clouds (Wegener 1911). It was later explained theoretically and demonstrated experimentally by T. Bergeron and W. Findeisen (Bergeron 1935; Findeisen 1938).

Scientific evaluation of the static-seeding hypothesis has been attempted over the last half century in a number of projects (Fig. 2) using observational process-oriented studies to understand natural cloud structure and effects of cloud seeding, statistical comparisons of surface precipitation between treated and untreated events, and numerical models to simulate both natural and seeded clouds. Past reviews at least partially focused on orographic weather systems and/or weather modification research to modify those cloud systems include those of Smith (1979), Elliott (1986), Rangno (1986), Reynolds (1988), Orville (1996), Bruintjes (1999), Long (2001), Garstang et al. (2005), Huggins (2008), Tessendorf et al. (2015), Reynolds (2015), Gultepe (2015), and Haupt et al. (2019). This paper provides a systematic assessment of our current understanding of the effectiveness of wintertime cloud seeding to enhance mountain snowpack, drawing extensively on results from recent studies not available to authors of past reviews, with a focus on results from new and advanced instrumentation, improved understanding of cloud dynamical and microphysical processes, and more sophisticated numerical modeling technologies. We note that many instrumentation platforms have been deployed in efforts to evaluate cloud seeding. It is beyond the scope of this paper to review their uses, accuracy, and effectiveness. The reader is referred to the American Meteorological Society monograph Ice Formation and Evolution in Clouds and Precipitation: Measurement and Modeling Challenges (McFarquhar et al. 2017) for a concise summary of issues related to measurements of ice and snow in clouds and to articles by Rasmussen et al. (2012), Gultepe et al. (2016) and Kochendorfer et al. (2017) for surface measurements of snow