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Abstract The magnitude of water vapor content within the near-storm inflow can either support or deter the storm’s upscale growth and maintenance. However, the heterogeneity of the moisture field near storms remains poorly understood because the operational observation network lacks detail. This observational study illustrates that near-storm inflow water vapor environments are both significantly heterogeneous and different than the far-inflow storm environment. This study also depicts the importance of temporal variation of water vapor mixing ratio (WVMR) to instability during the peak tornadic seasons in the U.S. Southeast and Great Plains regions during the Verification of the Origins of Rotation in Tornadoes Experiment Southeast 2018 (VSE18) campaign and the Targeted Observation by Radar and UAS of Supercells (TORUS) campaign, respectively. VSE18 results suggest that the surface processes control WVMR variation significantly in lower levels, with the highest WVMR mainly located near the surface in inflows in the southeast region. In contrast, TORUS results show more vertically homogeneous WVMR profiles and rather uniform water vapor distribution variation occurring in deep, moist stratified inflows in the Great Plains region. Temporal water vapor variations within 5-min periods could lead to over 1000 J kg −1 CAPE changes in both VSE18 and TORUS, which represent significant potential buoyancy perturbations for storms to intensify or decay. These temporal water vapor and instability evolutions of moving storms remain difficult to capture via radiosondes and fixed in situ or profiling instrumentation, yet may exert a strong impact on storm evolution. This study suggests that improving observations of the variability of near-storm inflow moisture can accurately refine a potential severe weather threat. Significance Statement It has long been recognized that better observations of the planetary boundary layer (PBL) inflow near convective storms are needed to improve severe weather forecasting. The current operational networks essentially do not provide profile measurements of the PBL, except for the sparsely spaced 12-hourly sounding network. More frequent geostationary satellite observations do not provide adequately high vertical resolution in the PBL. This study uses airborne lidar profiler measurements to examine moisture in the inflow region of convective storms in the Great Plains and the southeastern United States during their respective tornadic seasons. Rapid PBL water vapor variations on a ∼5 min time scale can lead to CAPE perturbations exceeding 1000 J kg −1 , representing significant perturbations that could promote storm intensification or decay. Severe thunderstorms may generate high-impact weather phenomena, such as tornadoes, high winds, hail, and heavy rainfall, which have substantial socioeconomic impacts. Ultimately, by contrasting characteristics of the convective storm inflow in the two regions, this study may lead to a more accurate assessment of severe weather threats. 

Abstract Airborne vertically profiling Doppler radar data and output from a ∼1-km-grid-resolution numerical simulation are used to examine how relatively small-scale terrain ridges (∼10–25 km apart and ∼0.5–1.0 km above the surrounding valleys) impact cross-mountain flow, cloud processes, and surface precipitation in deep stratiform precipitation systems. The radar data were collected along fixed flight tracks aligned with the wind, about 100 km long between the Snake River Plain and the Idaho Central Mountains, as part of the 2017 Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment (SNOWIE). Data from repeat flight legs are composited in order to suppress transient features and retain the effect of the underlying terrain. Simulations closely match observed series of terrain-driven deep gravity waves, although the simulated wave amplitude is slightly exaggerated. The deep waves produce pockets of supercooled liquid water in the otherwise ice-dominated clouds (confirmed by flight-level observations and the model) and distort radar-derived hydrometeor trajectories. Snow particles aloft encounter several wave updrafts and downdrafts before reaching the ground. No significant wavelike modulation of radar reflectivity or model ice water content occurs. The model does indicate substantial localized precipitation enhancement (1.8–3.0 times higher than the mean) peaking just downwind of individual ridges, especially those ridges with the most intense wave updrafts, on account of shallow pockets of high liquid water content on the upwind side, leading to the growth of snow and graupel, falling out mostly downwind of the crest. Radar reflectivity values near the surface are complicated by snowmelt, but suggest a more modest enhancement downwind of individual ridges. Significance Statement Mountains in the midlatitude belt and elsewhere receive more precipitation than the surrounding lowlands. The mountain terrain often is complex, and it remains unclear exactly where this precipitation enhancement occurs, because weather radars are challenged by beam blockage and the gauge network is too sparse to capture the precipitation heterogeneity over complex terrain. This study uses airborne profiling radar and high-resolution numerical simulations for four winter storms over a series of ridges in Idaho. One key finding is that while instantaneous airborne radar transects of the cross-mountain flow, vertical drafts, and reflectivity contain much transient small-scale information, time-averaged transects look very much like the model transects. The model indicates substantial surface precipitation enhancement over terrain, peaking over and just downwind of individual ridges. Radar observations suggest less enhancement, but the radar-based assessment is uncertain. The second key conclusion is that, even though orographic gravity waves are felt all the way up into the upper troposphere, the orographic precipitation enhancement is due to processes very close to the terrain. 

Abstract This essay is intended to provide stakeholders and news outlets with a plain-language summary of orographic cloud seeding research, new capabilities, and prospects. Specifically, we address the question of whether a widely practiced type of weather modification, glaciogenic seeding of orographic clouds throughout the cold season, can produce an economically useful increase in precipitation over a catchment-scale area. Our objective is to clarify current scientific understanding of how cloud seeding may affect precipitation, in terms that are more accessible than in the peer-reviewed literature. Public confidence that cloud seeding “works” is generally high in regions with operational seeding, notwithstanding decades of scientific reports indicating that the changes in precipitation are uncertain. Randomized seeding experiments have a solid statistical foundation and focus on the outcome, but, in light of the small seeding signal and the naturally noisy nature of precipitation, they generally require too many cases to be affordable, and therefore are discouraged. A complementary method, physical evaluation, examines changes in cloud and precipitation processes when seeding material is injected and yields insights into the most suitable ambient conditions. Recent physical evaluations have established a robust, well-documented scientific basis for glaciogenic seeding of cold-season orographic clouds to enhance precipitation. The challenge of seeding impact assessment remains, but evidence is provided that, thanks to recent significant progress in observational and computational capabilities, the research community is finally on track to be able to provide stakeholders with guidance on the likely quantitative precipitation impact of cloud seeding in their region. We recommend further process-level evaluations combined with highly resolved, well-constrained numerical simulations of seasonal cloud seeding. 

Abstract Properties of frozen hydrometeors in clouds remain difficult to sense remotely. Estimates of number concentration, distribution shape, ice particle density, and ice water content are essential for connecting cloud processes to surface precipitation. Progress has been made with dual-frequency radars, but validation has been difficult because of lack of particle imaging and sizing observations collocated with the radar measurements. Here, data are used from two airborne profiling (up and down) radars, the W-band Wyoming Cloud Radar and the Ka-band Profiling Radar, allowing for Ka–W-band dual-wavelength ratio (DWR) profiles. The aircraft (the University of Wyoming King Air) also carried a suite of in situ cloud and precipitation probes. This arrangement is optimal for relating the “flight-level” DWR (an average from radar gates below and above flight level) to ice particle size distributions measured by in situ optical array probes, as well as bulk properties such as minimum snow particle density and ice water content. This comparison reveals a strong relationship between DWR and the ice particle median-volume diameter. An optimal range of DWR values ensures the highest retrieval confidence, bounded by the radars’ relative calibration and DWR saturation, found here to be about 2.5–7.5 dB. The DWR-defined size distribution shape is used with a Mie scattering model and an experimental mass–diameter relationship to test retrievals of ice particle concentration and ice water content. Comparison with flight-level cloud-probe data indicate good performance, allowing microphysical interpretations for the rest of the vertical radar transects. 

Potential factors affecting the inland penetration and orographic modulation of lake-effect precipitation east of Lake Ontario include the environmental (lake, land, and atmospheric) conditions, mode of the lake-effect system, and orographic processes associated with flow across the downstream Tug Hill Plateau (herein Tug Hill), Black River valley, and Adirondack Mountains (herein Adirondacks). In this study we use data from the KTYX WSR-88D, ERA5 reanalysis, New York State Mesonet, and Ontario Winter Lake-effect Systems (OWLeS) field campaign to examine how these factors influence lake-effect characteristics with emphasis on the region downstream of Tug Hill. During an eight-cool-season (16 November–15 April) study period (2012/13–2019/20), total radar-estimated precipitation during lake-effect periods increased gradually from Lake Ontario to upper Tug Hill and decreased abruptly where the Tug Hill escarpment drops into the Black River valley. The axis of maximum precipitation shifted poleward across the northern Black River valley and into the northwestern Adirondacks. In the western Adirondacks, the heaviest lake-effect snowfall periods featured strong, near-zonal boundary layer flow, a deep boundary layer, and a single precipitation band aligned along the long-lake axis. Airborne profiling radar observations collected during OWLeS IOP10 revealed precipitation enhancement over Tug Hill, spillover and shadowing in the Black River valley where a resonant lee wave was present, and precipitation invigoration over the western Adirondacks. These results illustrate the orographic modulation of inland-penetrating lake-effect systems downstream of Lake Ontario and the factors favoring heavy snowfall over the western Adirondacks.

Inland penetrating lake-effect storms east of Lake Ontario affect remote rural communities, enable a regional winter-sports economy, and contribute to a snowpack that contributes to runoff and flooding during thaws and rain-on-snow events. In this study we illustrate how the region’s three major geographic features—Tug Hill, the Black River valley, and the western Adirondacks—affect the characteristics of lake-effect precipitation, describe the factors contributing to heavy snowfall over the western Adirondacks, and provide an examples of terrain effects in a lake-effect storm observed with a specially instrumented research aircraft.

 

Abstract In Part II, two classes of vertical motions, fixed (associated with vertically propagating gravity waves tied to flow over topography) and transient (associated primarily with vertical wind shear and conditional instability within passing weather systems), were diagnosed over the Payette River basin of Idaho during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). This paper compares vertical motions retrieved from airborne Doppler radial velocity measurements with those from a 900-m-resolution model simulation to determine the impact of transient vertical motions on trajectories of ice particles initiated by airborne cloud seeding. An orographic forcing index, developed to compare vertical motion fields retrieved from the radar with the model, showed that fixed vertical motions were well resolved by the model while transient vertical motions were not. Particle trajectories were calculated for 75 cross-sectional pairs, each differing only by the observed and modeled vertical motion field. Wind fields and particle terminal velocities were otherwise identical in both trajectories so that the impact of transient vertical circulations on particle trajectories could be isolated. In 66.7% of flight-leg pairs, the distance traveled by particles in the model and observations differed by less than 5 km with transient features having minimal impact. In 9.3% of the pairs, model and observation trajectories landed within the ideal target seeding elevation range (>2000 m), whereas, in 77.3% of the pairs, both trajectories landed below the ideal target elevation. Particles in the observations and model descended into valleys on the mountains’ lee sides in 94.2% of cases in which particles traveled less than 37 km. 

Abstract Kelvin-Helmholtz (KH) waves are a frequent source of turbulence in stratiform precipitation systems over mountainous terrain. KH waves introduce large eddies into otherwise laminar flow, with updrafts and downdrafts generating small-scale turbulence. When they occur in-cloud, such dynamics influence microphysical processes that impact precipitation growth and fallout. Part I of this paper used dual-Doppler, 2D wind and reflectivity measurements from an airborne cloud radar to demonstrate the occurrence of KH waves in stratiform orographic precipitation systems and identified four mechanisms for triggering KH waves. In Part II, we use similar observations to explore the effects of KH wave updrafts and turbulence on cloud microphysics. Measurements within KH wave updrafts reveal the production of liquid water in otherwise ice-dominated clouds, which can contribute to snow generation or enhancement via depositional and accretional growth. Fallstreaks beneath KH waves contain higher ice water content, composed of larger and more numerous ice particles, suggesting that KH waves and associated turbulence may also increase ice nucleation. A Large-Eddy Simulation (LES), designed to model the microphysical response to the KH wave eddies in mixed phase cloud, shows that depositional and accretional growth can be enhanced in KH waves, resulting in more precipitation when compared to a baseline simulation. While sublimation and evaporation occur in KH downdrafts, persistent supersaturation with respect to ice allows for net increase in ice mass. These modeling results and observations suggest that KH waves embedded in mixed-phase stratiform clouds may increase precipitation, although the quantitative impact remains uncertain. 

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 This observational study documents the consequences of a collision between two converging shallow atmospheric boundaries over the central Great Plains on the evening of 7 June 2015. This study uses data from a profiling airborne Raman lidar (the Compact Raman Lidar, or CRL) and other airborne and ground-based data collected during the Plains Elevated Convection At Night (PECAN) field campaign to investigate the collision between a weak cold front and the outflow from a MCS. The collision between these boundaries led to the lofting of high-CAPE, low-CIN air, resulting in deep convection, as well as an undular bore. Both boundaries behaved as density currents prior to collision. Because the MCS outflow boundary was denser and less deep than the cold-frontal airmass, the bore propagated over the latter. This bore was tracked by the CRL for about three hours as it traveled north over the shallow cold-frontal surface and evolved into a soliton. This case study is unique by using the high temporal and spatial resolution of airborne Raman lidar measurements to describe the thermodynamic structure of interacting boundaries and a resulting bore. 

Abstract A dry-air intrusion induced by the tropopause folding split the deep cloud into two layers resulting in a shallow orographic cloud with a supercooled liquid cloud top at around −15°C and an ice cloud above it on 19 January 2017 during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). The airborne AgI seeding of this case was simulated by the WRF Weather Modification (WRF-WxMod) Model with different configurations. Simulations at different grid spacing, driven by different reanalysis data, using different model physics were conducted to explore the ability of WRF-WxMod to capture the properties of natural and seeded clouds. The detailed model–observation comparisons show that the simulation driven by ERA5 data, using Thompson–Eidhammer microphysics with 30% of the CCN climatology, best captured the observed cloud structure and supercooled liquid water properties. The ability of the model to correctly capture the wind field was critical for successful simulation of the seeding plume locations. The seeding plume features and ice number concentrations within them from the large-eddy simulations (LES) are in better agreement with observations than non-LES runs mostly due to weaker AgI dispersion associated with the finer grid spacing. Seeding effects on precipitation amount and impacted areas from LES seeding simulations agreed well with radar-derived values. This study shows that WRF-WxMod is able to simulate and quantify observed features of natural and seeded clouds given that critical observations are available to validate the model. Observation-constrained seeding ensemble simulations are proposed to quantify the AgI seeding impacts on wintertime orographic clouds. Significance Statement Recent observational work has demonstrated that the impact of airborne glaciogenic seeding of orographic supercooled liquid clouds is detectable and can be quantified in terms of the extra ground precipitation. This study aims, for the first time, to simulate this seeding impact for one well-observed case. The stakes are high: if the model performs well in this case, then seasonal simulations can be conducted with appropriate configurations after validations against observations, to determine the impact of a seeding program on the seasonal mountain snowpack and runoff, with more fidelity than ever. High–resolution weather simulations inherently carry uncertainty. Within the envelope of this uncertainty, the model compares very well to the field observations.