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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.