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The spatial distribution and magnitude of snowfall resulting from cloud seeding with silver iodide (AgI) is closely linked to atmospheric conditions, seeding operations, and dynamical, thermodynamical, and microphysical processes. Here, microphysical processes leading to ice and snow production are analyzed in orographic clouds for three cloud-seeding events, each with light or no natural precipitation and well-defined, traceable seeding lines. Airborne and ground-based radar observations are linked to in situ cloud and precipitation measurements to determine the spatiotemporal evolution of ice initiation, particle growth, and snow fallout in seeded clouds. These processes and surface snow amounts are explored as particle plumes evolve from varying amounts of AgI released, and within changing environmental conditions, including changes in liquid water content (LWC) along and downwind of the seeding track, wind speed, and shear. More AgI did not necessarily produce more liquid equivalent snowfall (LESnow). The greatest amount of LESnow, largest area covered by snowfall, and highest peak snowfall produced through seeding occurred on the day with the largest and most widespread occurrence of supercooled drizzle, highest wind shear, and greater LWC along and downwind of the seeding track. The day with the least supercooled drizzle and the lowest LWC downwind of the seeding track produced the smallest amount of LESnow through seeding. The stronger the wind was, the farther away the snowfall occurred from the seeding track.

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.

The Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) project aims to study the impacts of cloud seeding on winter orographic clouds. The field campaign took place in Idaho between 7 January and 17 March 2017 and employed a comprehensive suite of instrumentation, including ground-based radars and airborne sensors, to collect in situ and remotely sensed data in and around clouds containing supercooled liquid water before and after seeding with silver iodide aerosol particles. The seeding material was released primarily by an aircraft. It was hypothesized that the dispersal of the seeding material from aircraft would produce zigzag lines of silver iodide as it dispersed downwind. In several cases, unambiguous zigzag lines of reflectivity were detected by radar, and in situ measurements within these lines have been examined to determine the microphysical response of the cloud to seeding. The measurements from SNOWIE aim to address long-standing questions about the efficacy of cloud seeding, starting with documenting the physical chain of events following seeding. The data will also be used to evaluate and improve computer modeling parameterizations, including a new cloud-seeding parameterization designed to further evaluate and quantify the impacts of cloud seeding.

The Wyoming Weather Modification Pilot Project randomized cloud seeding experiment was a crossover statistical experiment conducted over two mountain ranges in eastern Wyoming and lasted for 6 years (2008–13). The goal of the experiment was to determine if cloud seeding of orographic barriers could increase snowfall and snowpack. The experimental design included triply redundant snow gauges deployed in a target–control configuration, covariate snow gauges to account for precipitation variability, and ground-based seeding with silver iodide (AgI). The outcomes of this experiment are evaluated with the statistical–physical experiment design and with ensemble modeling. The root regression ratio (RRR) applied to 118 experimental units provided insufficient statistical evidence (p value of 0.28) to reject the null hypothesis that there was no effect from ground-based cloud seeding. Ensemble modeling estimates of the impact of ground-based seeding provide an alternate evaluation of the 6-yr experiment. The results of the model ensemble approach with and without seeding estimated a mean enhancement of precipitation of 5%, with an inner-quartile range of 3%–7%. Estimating the impact on annual precipitation over these mountain ranges requires results from another study that indicated that approximately 30% of the annual precipitation results from clouds identified as seedable within the seeding experiment. Thus the seeding impact is on the order of 1.5% of the annual precipitation, compared to 1% for the statistical–physical experiment, which was not sufficient to reject the null hypothesis. These results provide an estimate of the impact of ground-based cloud seeding in the Sierra Madre and Medicine Bow Mountains in Wyoming that accounts for uncertainties in both initial conditions and model physics.

Two ground-based and two airborne cloud seeding events between 2003 and 2005 from a trace chemistry field experiment conducted by the Desert Research Institute (DRI) in the Payette river basin of Idaho are simulated by the Weather Research and Forecasting (WRF) model in Large Eddy Simulation (LES) mode with a grid spacing of 667-m using the recently developed Wintertime silver iodide ( AgI ) Seeding Parameterization (WASP, Xue et al., 2013a,b ). The WASP in WRF was specifically modified to simulate the emissions of both AgI and Indium oxide ( In 2 O 3 ) particles from ground- and aircraft-based generators and the associated interactions with hydrometeors. Validations of model results against available observations from soundings and SNOwpack TELemetry (SNOTEL) data show that WRF simulations reasonably capture the dynamics, the thermodynamics, and the precipitation patterns. The comparisons of deposited Ag and In concentrations between model results and observations, and the analyses of seeding effects and AgI seeding efficiencies show that: The simulated Ag mass concentrations inside the snow are similar to observations ranging mostly from 0 to 10 −9 kg kg −1 and have high spatial correlations with observations in ground seeding cases (∼ 80 % ) but lower in airborne seeding (∼ 40 % ). The simulated Ag / In ratios range between 60 and 600 indicating that ice nucleation of AgI particle dominates the scavenging of AgI in incorporating Ag into the snow. The overall simulated seeding effect of the four cases is 6 % increase in precipitation over the LES domain, which is similar to what was inferred from the observations for the entire experiment. The magnitude of the AgI seeding efficiency is one order higher in airborne seeding cases (∼ 10 10 kg kg −1 ) compared to ground seeding cases (∼ 10 9 kg kg −1 ).

The impacts of various assumptions of cloud properties represented within a numerical weather prediction model's radiation scheme are demonstrated. In one approach, the model assumed the radiative effective radii of cloud water, cloud ice, and snow were represented by values assigned a priori, whereas a second, “coupled” approach utilized known cloud particle assumptions in the microphysics scheme that evolved during the simulations to diagnose the radii explicitly. This led to differences in simulated infrared (IR) brightness temperatures, radiative fluxes through clouds, and resulting surface temperatures that ultimately affect model-predicted diurnally-driven convection. The combined approach of evaluating simulated versus observed IR brightness temperatures, radiation reaching the ground, and surface temperature forecasts revealed the root model biases better than evaluating any single variable. This study found that the Weather Research and Forecasting (WRF) model predicted less overall clouds than was observed, particularly in the mid‑troposphere, but that properly connecting the assumptions of particle sizes in the microphysics scheme to the radiation scheme resulted in sensible cloud-radiation indirect effects and modest improvements in simulated IR brightness temperature, amount of solar radiation reaching the ground, and surface temperature.

A new microphysics scheme has been developed based on the prediction of bulk particle properties for a single ice-phase category, in contrast to the traditional approach of separating ice into various predefined species (e.g., cloud ice, snow, and graupel). In this paper, the new predicted particle properties (P3) scheme, described in Part I of this series, is tested in three-dimensional simulations using the Weather Research and Forecasting (WRF) Model for two contrasting well-observed cases: a midlatitude squall line and winter orographic precipitation. Results are also compared with simulations using other schemes in WRF. Simulations with P3 can produce a wide variety of particle characteristics despite having only one free ice-phase category. For the squall line, it produces dense, fast-falling, hail-like ice near convective updraft cores and lower-density, slower-falling ice elsewhere. Sensitivity tests show that this is critical for simulating high precipitation rates observed along the leading edge of the storm. In contrast, schemes that represent rimed ice as graupel, with lower fall speeds than hail, produce lower peak precipitation rates and wider, less distinct, and less realistic regions of high convective reflectivity. For the orographic precipitation case, P3 produces areas of relatively fast-falling ice with characteristics of rimed snow and low- to medium-density graupel on the windward slope. This leads to less precipitation on leeward slopes and more on windward slopes compared to the other schemes that produce large amounts of snow relative to graupel (with generally the opposite for schemes with significant graupel relative to snow). Overall, the new scheme produces reasonable results for a reduced computational cost.

Four cloud-seeding cases over southern Idaho during the 2010/11 winter season have been simulated by the Weather Research and Forecasting (WRF) model using the coupled silver iodide (AgI) cloud-seeding scheme that was described in Part I. The seeding effects of both ground-based and airborne seeding as well as the impacts of model physics, seeding rates, location, timing, and cloud properties on seeding effects have been investigated. The results were compared with those from Part I and showed the following: 1) For the four cases tested in this study, control simulations driven by the Real-Time Four Dimensional Data Assimilation (RTFDDA) WRF forecast data generated more realistic atmospheric conditions and precipitation patterns than those driven by the North America Regional Reanalysis data. Sensitivity experiments therefore used the RTFDDA data. 2) Glaciogenic cloud seeding increased orographic precipitation by less than 1% over the simulation domain, including the Snake River basin, and by up to 5% over the target areas. The local values of the relative precipitation enhancement by seeding were ~20%. Most of the enhancement came from vapor depletion. 3) The seeding effect was inversely related to the natural precipitation efficiency but was positively related to seeding rates. 4) Airborne seeding is generally more efficient than ground-based seeding in terms of targeting, but its efficiency depends on local meteorological conditions. 5) The normalized seeding effects ranged from 0.4 to 1.6 under various conditions for a certain seeding event.

A silver iodide (AgI) cloud-seeding parameterization has been implemented into the Thompson microphysics scheme of the Weather Research and Forecasting model to investigate glaciogenic cloud-seeding effects. The sensitivity of the parameterization to meteorological conditions, cloud properties, and seeding rates was examined by simulating two-dimensional idealized moist flow over a bell-shaped mountain. The results verified that this parameterization can reasonably simulate the physical processes of cloud seeding with the limitations of the constant cloud droplet concentration assumed in the scheme and the two-dimensional model setup. The results showed the following: 1) Deposition was the dominant nucleation mode of AgI from simulated aircraft seeding, whereas immersion freezing was the most active mode for ground-based seeding. Deposition and condensation freezing were also important for ground-based seeding. Contact freezing was the weakest nucleation mode for both ground-based and airborne seeding. 2) Diffusion and riming on AgI-nucleated ice crystals depleted vapor and liquid water, resulting in more ice-phase precipitation on the ground for all of the seeding cases relative to the control cases. Most of the enhancement came from vapor depletion. The relative enhancement by seeding ranged from 0.3% to 429% under various conditions. 3) The maximum local AgI activation ratio was 60% under optimum conditions. Under most seeding conditions, however, this ratio was between 0.02% and 2% in orographic clouds. 4) The seeding effect was inversely related to the natural precipitation efficiency but was positively related to seeding rates. 5) Ground-based seeding enhanced precipitation on the lee side of the mountain, whereas airborne seeding from lower flight tracks enhanced precipitation on the windward side of the mountain.

This paper describes idealized simulations of a squall line observed on 20 June 2007, in central Oklahoma. Results are compared with measurements from dual-polarization radar and surface disdrometer. The baseline model configuration qualitatively reproduces key storm features, but underpredicts precipitation rates and generally overpredicts median volume raindrop diameter. The sensitivity of model simulations to parameterization of raindrop breakup is tested under different low-level (0–2.5 km) environmental vertical wind shears. Storm characteristics exhibit considerable sensitivity to the parameterization of breakup, especially for moderate (0.0048 s−1) shear. Simulations with more efficient breakup tend to have higher domain-mean precipitation rates under both moderate and higher (0.0064 s−1) shear, despite the smaller mean drop size and hence lower mass-weighted fall speed and higher evaporation rate for a given rainwater content. In these runs, higher evaporation leads to stronger cold pools, faster propagation, larger storm size, greater updraft mass flux (but weaker convective updrafts at mid- and upper levels), and greater total condensation that compensates for the increased evaporation to give more surface precipitation. The impact of drop breakup on mass-weighted fall speed is also important and leads to a nonmonotonic response of storm characteristics (surface precipitation, cold pool strength, etc.) to changes in breakup efficiency under moderate wind shear. In contrast, the response is generally monotonic at higher wind shear. Interactions between drop breakup, convective dynamics, cold pool intensity, and low-level environmental wind shear are also described in the context of “Rotunno–Klemp–Weisman (RKW) theory,” which addresses how density currents evolve in sheared environments.

As a response to extreme water shortages in southeast Queensland, Australia, brought about by reduced rainfall and increasing population, the Queensland government decided to explore the potential for cloud seeding to enhance rainfall. The Queensland Cloud Seeding Research Program (QCSRP) was conducted in the southeast Queensland region near Brisbane during the 2008/09 wet seasons. In addition to conducting an initial exploratory, randomized (statistical) cloud seeding study, multiparameter radar measurements and in situ aircraft microphysical data were collected. This comprehensive set of observational platforms was designed to improve the physical understanding of the effects of both ambient aerosols and seeding material on precipitation formation in southeast Queensland clouds. This focus on gaining physical understanding, along with the unique combination of modern observational platforms utilized in the program, set it apart from previous cloud seeding research programs. The overarching goals of the ...

During the Queensland Cloud Seeding Research Program, the “CP2” polarimetric radar parameter differential radar reflectivity Zdr was used to examine the raindrop size evolution in both maritime and continental clouds. The focus of this paper is to examine the natural variability of the drop size distribution. The primary finding is that there are two basic raindrop size evolutions, one associated with continental air masses characterized by relatively high aerosol concentrations and long air trajectories over land and the other associated with maritime air masses with lower aerosol concentrations. The size evolution difference is during the growth stage of the radar echoes. The differential radar reflectivity in the growing continental clouds is dominated by large raindrops, whereas in the maritime clouds differential reflectivity is dominated by small raindrops and drizzle. The drop size evolution in many of the maritime air masses was very similar to those observed in the maritime air of the Caribbean Sea observed with the NCAR S-band polarimetric radar (S-Pol) during the Rain in Cumulus over the Ocean (RICO) experiment. Because the tops of the Queensland continental clouds ascended almost 2 times as fast as the maritime ones in their growth stage, both dynamical and aerosol factors may be important for the systematic difference in drop size evolution. Recommendations are advanced for future field programs to understand better the causes for the observed variability in drop size evolution. Also, considering the natural variability in drop size evolution, comments are provided on conducting and evaluating cloud seeding experiments.

This study addresses the kinematic, microphysical, and electrical evolution of an isolated convective storm observed on 3 June 2000 during the Severe Thunderstorm Electrification and Precipitation Study field campaign. Doppler-derived vertical velocities, radar reflectivity, hydrometeor classifications from polarimetric radar, and Lightning Mapping Array (LMA) charge structures are examined over a nearly 3-h period. This storm, characterized as a low-precipitation supercell, produced modest amounts of hail, determined by fuzzy-logic hydrometeor classification as mostly small (

This study discusses radar and lightning observations of two multicellular storms observed during the Severe Thunderstorm Electrification and Precipitation Study. The Lightning Mapping Array data indicated that the charge structure of the 19 June 2000 storm was consistent with a normal polarity tripole, while the 22 June 2000 storm exhibited an overall inverted tripolar charge structure. The 19 June storm consisted of weaker convection and produced little to no hail and moderate total flash rates peaking between 80 and 120 min−1. The cells in the 22 June 2000 storm were much more vigorous, exhibited strong, broad updrafts, and produced large quantities of hail, as well as extraordinary total flash rates as high as 500 min−1. The National Lightning Detection Network (NLDN) indicated that the 19 June storm produced mostly negative cloud-to-ground (CG) lightning, while the 22 June storm produced predominantly positive CG lightning, peaking at 10 min−1 just after two cells merged. However, the Los Alamos Sferic Array indicated that many of the positive CG strokes reported by the NLDN in the 22 June storm were intracloud discharges known as narrow bipolar events. Negative CG lightning was also observed in the 22 June storm, but typically came to ground beneath an inverted dipole in the storm anvil.

This second part of a two-part study examines the lightning and charge structure evolution of the 29 June 2000 tornadic supercell observed during the Severe Thunderstorm Electrification and Precipitation Study (STEPS). Data from the National Lightning Detection Network and the New Mexico Tech Lightning Mapping Array (LMA) are used to quantify the total and cloud-to-ground (CG) flash rates. Additionally, the LMA data are used to infer gross charge structure and to determine the origin locations and charge regions involved in the CG flashes. The total flash rate reached nearly 300 min−1 and was well correlated with radar-inferred updraft and graupel echo volumes. Intracloud flashes accounted for 95%–100% of the total lightning activity during any given minute. Nearly 90% of the CG flashes delivered a positive charge to ground (+CGs). The charge structure during the first 20 min of this storm consisted of a midlevel negative charge overlying lower positive charge with no evidence of an upper positive charge. The charge structure in the later (severe) phase was more complex but maintained what could be roughly described as an inverted tripole, dominated by a deep midlevel (5–9 km MSL) region of positive charge. The storm produced only two CG flashes (both positive) in the first 2 h of lightning activity, both of which occurred during a brief surge in updraft and hail production. Frequent +CG flashes began nearly coincident with dramatic increases in storm updraft, hail production, total flash rate, and the formation of an F1 tornado. The +CG flashes tended to cluster in or just downwind of the heaviest precipitation, which usually contained hail. The +CG flashes all originated between 5 and 9 km MSL, centered at 6.8 km (−10°C), and tapped LMA-inferred positive charge both in the precipitation core and (more often) in weaker reflectivity extending downwind. All but one of the −CG flashes originated from >9 km MSL and tended to strike near the precipitation core.

This is a two-part study that addresses the kinematic, microphysical, and electrical aspects of a severe storm that occurred in western Kansas on 29 June 2000 observed during the Severe Thunderstorm Electrification and Precipitation Study (STEPS) field campaign. In this first part, polarimetric and Doppler radar data are used along with a simple particle growth model to examine the evolution of the kinematic and microphysical properties of the storm from its earliest developing phase through its mature and dissipating phases. During its severe stage, the storm exhibited frequent positive cloud-to-ground lightning strikes, very large (∼5 cm) hail, and a tornado. Doppler-derived winds, radar reflectivity, and hydrometeor classifications from the polarimetric data over a nearly 4-h period are presented. It is shown that updraft velocity and vertical vorticity had to reach magnitudes of at least 10 m s−1 and 10−2 s−1 and occupy major portions of the storm before it could produce most of the observed severe storm characteristics. Furthermore, the establishment of cyclonic horizontal flow around the right flank of the updraft core was essential for hail production. Most of the largest hail grew from near millimeter-sized particles that originated in the mid- to upper-level stagnation region that resulted from obstacle-like flow of environmental air around the divergent outflow from the upper part of the updraft. These recycling embryonic particles descended around the right flank of the updraft core and reentered the updraft, intermingling with other smaller particles that had grown from cloud base along the main low-level updraft stream.

The primary objective of this study was to estimate the percentage of U.S. tornadoes that are spawned annually by squall lines and bow echoes, or quasi-linear convective systems (QLCSs). This was achieved by examining radar reflectivity images for every tornado event recorded during 1998–2000 in the contiguous United States. Based on these images, the type of storm associated with each tornado was classified as cell, QLCS, or other. Of the 3828 tornadoes in the database, 79% were produced by cells, 18% were produced by QLCSs, and the remaining 3% were produced by other storm types, primarily rainbands of landfallen tropical cyclones. Geographically, these percentages as well as those based on tornado days exhibited wide variations. For example, 50% of the tornado days in Indiana were associated with QLCSs. In an examination of other tornado attributes, statistically more weak (F1) and fewer strong (F2–F3) tornadoes were associated with QLCSs than with cells. QLCS tornadoes were more probable during the winter months than were cells. And finally, QLCS tornadoes displayed a comparatively higher and statistically significant tendency to occur during the late night/early morning hours. Further analysis revealed a disproportional decrease in F0–F1 events during this time of day, which led the authors to propose that many (perhaps as many as 12% of the total) weak QLCSs tornadoes were not reported.

This chapter focuses on the lightning and charge structure observed in supercells; a particular class of severe thunderstorms that are typically responsible for producing the most violent hailstorms and tornadoes. The chapter reviews common supercell features, the classification of supercells based on structural and visual characteristics, as well as the microphysics of supercells related to hail growth and electrification. A summary of observed flash rates, lightning polarity, and charge structure within supercells is also presented, along with descriptions of a few case studies as examples. Specific attention has been given to recent observations of anomalous positive cloud-to-ground lightning and inverted charge structures. Though this behavior is not exclusive to supercells, it has typically been observed in strong and/or severe storms that often meet supercell criteria.

Following up on an almost thirty year long history of International Cloud Modeling Workshops, that started out with a meeting in Irsee, Germany in 1985, the 8th International Cloud Modeling Workshop was held in July 2012 in Warsaw, Poland. The workshop, hosted by the Institute of Geophysics at the University of Warsaw, was organized by Szymon Malinowski and his local team of students and co-chaired by Wojciech Grabowski (NCAR/MMM) and Andreas Muhlbauer (University of Washington). International Cloud Modeling Workshops have been held traditionally every four years typically during the week before the International Conference on Clouds and Precipitation (ICCP) . Rooted in the World Meteorological Organization’s (WMO) weather modification program, the core objectives of the Cloud Modeling Workshop have been centered at the numerical modeling of clouds, cloud microphysics, and the interactions between cloud microphysics and cloud dynamics. In particular, the goal of the workshop is to provide insight into the pertinent problems of today’s state-of-the-art of cloud modeling and to identify key deficiencies in the microphysical representation of clouds in numerical models and cloud parameterizations. In recent years, the workshop has increasingly shifted the focus toward modeling the interactions between aerosols and clouds and provided case studies to investigatemore » both the effects of aerosols on clouds and precipitation as well as the impact of cloud and precipitation processes on aerosols. This time, about 60 (?) scientists from about 10 (?) different countries participated in the workshop and contributed with discussions, oral and poster presentations to the workshop’s plenary and breakout sessions. Several case leaders contributed to the workshop by setting up five observationally-based case studies covering a wide range of cloud types, namely, marine stratocumulus, mid-latitude squall lines, mid-latitude cirrus clouds, Arctic stratus and winter-time orographic clouds and precipitation. Interested readers are encouraged to visit the workshop website at http://www.atmos.washington.edu/~andreasm/workshop2012/ and browse through the list of case studies. The web page also provides a detailed list of participants and the workshop agenda. Aside from contributed oral and poster presentations during the workshop’s plenary sessions, parallel breakout sessions focused on presentations and discussions of the individual cases. A short summary and science highlights from each of the cases is presented below.« less