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Abstract Cloud seeding has been widely used for enhancing wintertime snowfall, particularly to augment water resources. This study examines microphysical responses to airborne glaciogenic seeding with silver iodide (AgI) during a specific case from the Seeded and Natural Orographic Wintertime Clouds: Idaho Experiment (SNOWIE) on 11 January 2017. Ground-based and airborne remote sensing and in situ measurements were employed to assess the impact of cloud seeding on cloud properties and precipitation formation. On 11th January, AgI propagated downwind along prevailing winds, and any potential ice and snow particles created from it were identified by ground-based radar as zigzag lines of enhanced reflectivity compared to background reflectivity. As the aircraft flew several times through these seeded clouds, microphysical properties within seeded clouds can be compared to those observed in unseeded clouds. The results indicate that seeded clouds exhibited significantly enhanced ice water content (IWC; reaching up to 0.20 g m⁻³) and precipitating-size (>400μm) ice particle concentrations (>7 L⁻¹) relative to unseeded clouds. Additionally, seeded clouds exhibited a 30% decrease in the mean liquid water content (LWC) and cloud droplet concentrations, indicating efficient glaciation processes influenced by AgI. Precipitating snow development in seeded clouds occurred within 15–40 min following AgI release, marked by a transition from mixed-phase clouds with abundant supercooled liquid water (SLW) to ice clouds, with lidar-measured linear depolarization ratio (LDR) increasing to >0.3. These findings underscore the effectiveness of cloud seeding in enhancing snowfall by facilitating ice initiation and growth. Significance StatementThis study investigates the microphysical response of wintertime orographic clouds to airborne glaciogenic seeding, highlighting its role in enhancing precipitation. By introducing silver iodide (AgI) into clouds with supercooled liquid water, the seeding process facilitates ice particle formation, leading to increased snowfall. Through a detailed analysis of microphysical conditions using advanced in situ and remote sensing instruments, the study reveals enhanced ice water content and efficient conversion of liquid water to ice in seeded clouds. These findings provide critical insights into cloud-seeding efficacy, particularly in regions with abundant supercooled liquid water, offering a scientific foundation for enhancing snowpack in water-scarce mountainous areas. 

Abstract It is not uncommon for layers within the warm conveyor belt in a frontal system to become potentially unstable, releasing elevated convection. The present study examines this destabilization process over complex terrain, and resulting precipitation, with a focus on the surface coupling, orographic ascent, and the initiation and evolution of convective cells. This study uses detailed observations combined with numerical modeling of a baroclinic system passing over the Idaho Central Mountains in the United States on 7 February 2017. The data were collected as part of the Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment (SNOWIE). Specifically, observations from a ground-based scanning X-band radar and an airborne profiling Doppler W-band radar along ~100 km long flight tracks aligned with the wind describe the development and evolution of convective cells above shallow stratiform orographic clouds. Convection-permitting numerical simulations of this event, with an inner domain grid resolution of 0.9 km, capture the emergence and vertical structure of the convective cells. Therefore, they are used to describe the advection of warm, moist air over a retreating warm front, cold air pooling within the Snake River Basin and adjacent valleys, destabilization in a moist layer above this shallow stable layer, and instability release in orographic gravity wave updrafts. In this case, the convective cells topped out near 6 km ASL, and the resulting precipitation fell mostly leeward of the ridge where convection was triggered, on account of strong cross-barrier flow. Sequential convection initiation over terrain ridges and rapid downwind transport led to banded precipitation structures. 

Abstract Cloud seeding of wintertime orographic clouds in the western United States has been attempted to enhance snow production and snowpack. Due to the scarcity of long-term, high-resolution cloud and precipitation observations over complex terrain, few studies have explored variations in orographic snowfall amounts by comparing environmental conditions and cloud characteristics with surface snowfall distribution and quantity. This study analyzes the environmental conditions and cloud characteristics in relation to surface snowfall patterns for the 24 snowfall events observed during the 2017 Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). The investigation aims to understand: 1) What is the influence, if any, of wind, turbulence, and updraft strength on snowfall amounts, rates, and distribution? 2) What is the relationship, if any, of cloud properties and precipitation-forming effectiveness? and 3) Can cloud seeding modify controlling cloud characteristics sufficiently to increase precipitation in otherwise inefficient orographic clouds? The analysis over a 7200-km²observational domain revealed that the accumulated liquid-equivalent snowfall was <0.9 × 10⁷m³and snowfall rates were <0.45 mm h⁻¹for about half of the events. Low snowfall events were characterized by cloud-top temperatures >−20°C, fewer larger droplets, higher liquid water content, and lower ice water content compared to the other events. Cases with minimal background natural snowfall also permitted radar observation of seeding lines. In these cases, cloud seeding was mainly responsible for snowfall. The amount of silver iodide (AgI) released during cloud seeding did not correlate well with snowfall amount and rate. Significance StatementThis study illustrates the complexities of estimating snowfall in wintertime orographic clouds, underscoring the frequent inefficiency of these clouds in generating snowfall—a pivotal concern for regions dependent on snowpack for water resources. By analyzing environmental and cloud characteristics against snowfall patterns during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE), the research provides critical insights into the complexities of precipitation formation. The findings, particularly on the impact of cloud seeding in enhancing snowfall under specific conditions, contribute significantly to our understanding of weather modification techniques. This research not only is vital for advancing scientific knowledge in understanding wintertime mountain cloud systems but also holds profound implications for water resource management, agriculture, and disaster preparedness in snow-dependent regions. 

Abstract Snowpack melting is a crucial water resource for local ecosystems, agriculture, and hydropower in the Intermountain West of the United States. Glaciogenic seeding, a method widely used in mountain regions to enhance precipitation, has been subject to numerous field studies aiming to understand and validate this mechanism. However, investigating precipitation distribution and amounts in mountainous areas is complicated due to the intricate interplay of synoptic circulation patterns and local complex topography. These interactions significantly influence microphysical processes, ultimately affecting the amount and distribution of surface precipitation. To address these challenges, this study leverages Weather Research and Forecasting (WRF) Model simulations, providing high-resolution (900 m), hourly data, spanning the Payette region of Idaho from January to March 2017. We applied the self-organizing map approach to categorize the most representative synoptic circulation patterns and conducted a multiscale analysis to explore their associated environmental conditions and microphysical processes, aiming to assess the cloud seeding potential. The analysis identified four primary synoptic patterns: cold zonal flow (CZF), cold southwesterly flow (CSWF), warm zonal flow (WZF), and warm southwesterly flow (WSWF), constituting 21.3%, 23.1%, 30.0%, and 25.5%, respectively. CSWF and WSWF demonstrated efficiency in generating natural precipitation. These patterns were characterized by abundant supercooled liquid water (SLW) and ice particles, facilitating cloud droplet growth through seeder–feeder processes. On the other hand, CZF exhibited the least SLW and limited potential for cloud seeding, while WZF displayed a lower ice water content but substantial SLW in the diffusion/dendritic growth layer, suggesting a favorable scenario for cloud seeding. Significance StatementUnderstanding snowfall amounts and distribution in the mountains and how it is linked to topography, synoptic flow, and microphysical processes will help in the development of effective strategies for cloud seeding operations, managing runoff, reservoir, and mitigating flood risks, garnering substantial interest from stakeholders and the government agencies. 

Abstract The western United States region, an economic and agricultural powerhouse, is highly dependent on winter snowpack from the mountain west. Coupled with increasing water and renewable electricity demands, the predictability and viability of snowpack resources in a changing climate are becoming increasingly important. In Idaho, specifically, up to 75% of the state’s electricity production comes from hydropower, which is dependent on the timing and volume of spring snowmelt. While we know that 1 April snowpack is declining from SNOTEL observations and is expected to continue to decline as indicated by GCM predictions, our ability to understand the variability of snowfall accumulation and distribution at the regional level is less robust. In this paper, we analyze snowfall events using 0.9-km-resolution WRF simulations to understand the variability of snowfall accumulation and distribution in the mountains of Idaho between 1 October 2016 and 31 April 2017. Various characteristics of snowfall events throughout the season are evaluated, including the spatial coverage, event durations, and snowfall rates, along with the relationship between cloud microphysical variables—particularly liquid and ice water content—on snowfall amounts. Our findings suggest that efficient snowfall conditions—for example, higher levels of elevated supercooled liquid water—can exist throughout the winter season but are more impactful when surface temperatures are near or below freezing. Inefficient snowfall events are common, exceeding 50% of the total snowfall events for the year, with some of those occurring in peak winter. For such events, glaciogenic cloud seeding could make a significant impact on snowpack development and viability in the region. Significance StatementThe purpose and significance of this study is to better understand the variability of snowfall event accumulation and distribution in the Payette Mountains region of Idaho as it relates to the local topography, the drivers of snowfall events, the cloud microphysical properties, and what constitutes an efficient or inefficient snowfall event (i.e., its ability to convert atmospheric liquid water into snowfall). As part of this process, we identify how many snowfall events in a season are inefficient to determine the number of snowfall events in a season that are candidates for enhancement by glaciogenic cloud seeding. 

Abstract This paper examines the controls on supercooled liquid water content (SLWC) and drop number concentrations (N_t,CDP) over the Payette River basin during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) campaign. During SNOWIE, 27.4% of 1-Hz in situ cloud droplet probe samples were in an environment containing supercooled liquid water (SLW). The interquartile range of SLWC, when present, was found to be 0.02–0.18 g m⁻³and 13.3–37.2 cm⁻³forN_t,CDP, with the most extreme values reaching 0.40–1.75 g m⁻³and 150–320 cm⁻³in isolated regions of convection and strong shear-induced turbulence. SLWC andN_t,CDPdistributions are shown to be directly related to cloud-top temperature and ice particle concentrations, consistent with past research over other mountain ranges. Two classes of vertical motions were analyzed as potential controls on SLWC andN_t,CDP, the first forced by the orography and fixed in space relative to the topography (stationary waves) and the second transient, triggered by vertical shear and instability within passing synoptic-scale cyclones. SLWC occurrence and magnitudes, andN_t,CDPassociated with fixed updrafts were found to be normally distributed about ridgelines when SLW was present. SLW was more likely to form at low altitudes near the terrain slope associated with fixed waves due to higher mixing ratios and larger vertical air parcel displacements at low altitudes. When considering transient updrafts, SLWC andN_t,CDPappear more uniformly distributed over the flight track with little discernable terrain dependence as a result of time and spatially varying updrafts associated with passing weather systems. The implications for cloud seeding over the basin are discussed. 

Abstract Kelvin–Helmholtz instability (KH) waves have been broadly shown to affect the growth of hydrometeors within a region of falling precipitation, but formation and growth from KH waves at cloud top needs further attention. Here, we present detailed observations of cloud-top KH waves that produced a snow plume that extended to the surface. Airborne transects of cloud radar aligned with range height indicator scans from ground-based precipitation radar track the progression and intensity of the KH wave kinetics and precipitation. In situ cloud probes and surface disdrometer measurements are used to quantify the impact of the snow plume on the composition of an underlying supercooled liquid water (SLW) cloud and the snowfall observed at the surface. KH wavelengths of 1.5 km consisted of ∼750-m-wide up- and downdrafts. A distinct fluctus region appeared as a wave-breaking cloud top where the fastest updraft was observed to exceed 5 m s⁻¹. Relatively weaker updrafts of 0.5–1.5 m s⁻¹beneath the fluctus and partially overlapping the dendritic growth zone were associated with steep gradients in reflectivity of −5 to 20 dBZ_ein as little as 500-m depths due to rapid growth of pristine planar ice crystals. The falling snow removed ∼80% of the SLW content from the underlying cloud and led to a twofold increase in surface liquid equivalent snowfall rate from 0.6 to 1.3 mm h⁻¹. This paper presents the first known study of cloud-top KH waves producing snowfall with observations of increased snowfall rates at the surface. 

Doppler spectra are derived from vertical radar scans (89° elevation) by analyzing the in-phase (I) and quadrature (Q) components of the returned signal. The I/Q time-series data are divided into range gates, and a Fast Fourier Transform (FFT) is applied to convert the data from the time domain to the frequency domain. This reveals Doppler frequency shifts caused by moving scatterers, producing spectra that show the distribution of power across velocities. We corrected the data for the influence of the horizontal wind since the scans were not perfectly vertical and removed returns from ground-clutter. The frequency of data collection was based on DOW7 scanning and data are usually sampled every 4-6 minutes. The data are in netCDF format. 

Doppler spectra are derived from vertical radar scans (89° elevation) by analyzing the in-phase (I) and quadrature (Q) components of the returned signal. The I/Q time-series data are divided into range gates, and a Fast Fourier Transform (FFT) is applied to convert the data from the time domain to the frequency domain. This reveals Doppler frequency shifts caused by moving scatterers, producing spectra that show the distribution of power across velocities. We corrected the data for the influence of the horizontal wind since the scans were not perfectly vertical and removed returns from ground-clutter. The frequency of data collection was based on DOW6 scanning and data are usually sampled every 4-6 minutes. The data are in netCDF format. 

The dataset consists of vertical profiles of horizontal winds derived from radar Plan Position Indicator (PPI) scans conducted at a 17° elevation angle. In cases where 17° data were unavailable, the highest available elevation angle was utilized. The wind profiles were obtained using the Vertical Azimuth Display (VAD) technique, which involves measuring the radial velocity of targets at various azimuth angles and applying a least square fitting procedure to extract the horizontal wind speed and direction as a function of altitude. This method assumes that the wind field is horizontally homogeneous over the radar sampling volume. For more details on the VAD technique, refer to Browning and Wexler (1968).