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  1. 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 dBZein as little as 500-m depths due to rapid growth of pristine planar ice crystals. The falling snow removed ∼80% of the SLW content frommore »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.

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  2. Abstract

    As part of the analysis following the Seeded and Natural Orographic Wintertime Storms (SNOWIE) project, the ice water content (IWC) in ice and mixed-phase clouds is retrieved from airborne Wyoming Cloud Radar (WCR) measurements aboard the University of Wyoming King Air (UWKA), which has a suite of integrated in situ IWC, optical array probes, and remote sensing measurements, and it provides a unique dataset for this algorithm development and evaluation. A sensitivity study with different idealized ice particle habits shows that the retrieved IWC with aggregate ice particle habit agrees the best with the in situ measurement, especially in ice or ice-dominated mixed-phase clouds with a correlation coefficient (rr) of 0.91 and a bias of close to 0. For mixed-phase clouds with ice fraction ratio less than 0.8, the variances of IWC estimates increase (rr = 0.76) and the retrieved mean IWC is larger than in situ IWC by a factor of 2. This is found to be related to the uncertainty of in situ measurements, the large cloud inhomogeneity, and the retrieval assumption uncertainty. The simulated reflectivity Ze and IWC relationships assuming three idealized ice particle habits and measured particle size distributions show that hexagonal columns with themore »same Ze have a lower IWC than aggregates, whose Ze–IWC relation is more consistent with the observed WCR Ze and in situ IWC relation in those clouds. The 2D stereo probe (2DS) images also indicate that ice particle habit transition occurs in orographic mixed-phase clouds; hence, the retrieved IWC assuming modified gamma particle size distribution (PSD) of aggregate particles tends to have a greater bias in this kind of clouds.

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  3. 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 areasmore »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.« less
    Free, publicly-accessible full text available April 1, 2023
  4. 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 tomore »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.« less
  5. Abstract 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 themore »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.« less