- NSF-PAR ID:
- Date Published:
- Journal Name:
- Journal of Applied Meteorology and Climatology
- Page Range / eLocation ID:
- 909 to 934
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract On 7 February 2020, precipitation within the comma-head region of an extratropical cyclone was sampled remotely and in situ by two research aircraft, providing a vertical cross section of microphysical observations and fine-scale radar measurements. The sampled region was stratified vertically by distinct temperature layers and horizontally into a stratiform region on the west side, and a region of elevated convection on the east side. In the stratiform region, precipitation formed near cloud top as side-plane, polycrystalline, and platelike particles. These habits occurred through cloud depth, implying that the cloud-top region was the primary source of particles. Almost no supercooled water was present. The ice water content within the stratiform region showed an overall increase with depth between the aircraft flight levels, while the total number concentration slightly decreased, consistent with growth by vapor deposition and aggregation. In the convective region, new particle habits were observed within each temperature-defined layer along with detectable amounts of supercooled water, implying that ice particle formation occurred in several layers. Total number concentration decreased from cloud top to the −8°C level, consistent with particle aggregation. At temperatures > −8°C, ice particle concentrations in some regions increased to >100 L −1 , suggesting secondary ice production occurred at lower altitudes. WSR-88D reflectivity composites during the sampling period showed a weak, loosely organized banded feature. The band, evident on earlier flight legs, was consistent with enhanced vertical motion associated with frontogenesis, and at least partial melting of ice particles near the surface. A conceptual model of precipitation growth processes within the comma head is presented. Significance Statement Snowstorms over the northeast United States have major impacts on travel, power availability, and commerce. The processes by which snow forms in winter storms over this region are complex and their snowfall totals are hard to forecast accurately because of a poor understanding of the microphysical processes within the clouds composing the storms. This paper presents a case study from the NASA IMPACTS field campaign that involved two aircraft sampling the storm simultaneously with radars, and probes that measure the microphysical properties within the storm. The paper examines how variations in stability and frontal structure influence the microphysical evolution of ice particles as they fall from cloud top to the surface within the storm.more » « less
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.more » « less
This study presents the first numerical simulations of seeded clouds over the Snowy Mountains of Australia. WRF-WxMod, a novel glaciogenic cloud-seeding model, was utilized to simulate the cloud response to winter orographic seeding under various meteorological conditions. Three cases during the 2018 seeding periods were selected for model evaluation, coinciding with an intensive ground-based measurement campaign. The campaign data were used for model validation and evaluation. Comparisons between simulations and observations demonstrate that the model realistically represents cloud structures, liquid water path, and precipitation. Sensitivity tests were performed to pinpoint key uncertainties in simulating natural and seeded clouds and precipitation processes. They also shed light on the complex interplay between various physical parameters/processes and their interaction with large-scale meteorology. Our study found that in unseeded scenarios, the warm and cold biases in different initialization datasets can heavily influence the intensity and phase of natural precipitation. Secondary ice production via Hallett–Mossop processes exerts a secondary influence. On the other hand, the seeding impacts are primarily sensitive to aerosol conditions and the natural ice nucleation process. Both factors alter the supercooled liquid water availability and the precipitation phase, consequently impacting the silver iodide (AgI) nucleation rate. Furthermore, model sensitivities were inconsistent across cases, indicating that no single model configuration optimally represents all three cases. This highlights the necessity of employing an ensemble approach for a more comprehensive and accurate assessment of the seeding impact.
Winter orographic cloud seeding has been conducted for decades over the Snowy Mountains of Australia for securing water resources. However, this study is the first to perform cloud-seeding simulation for a robust, event-based seeding impact evaluation. A state-of-the-art cloud-seeding model (WRF-WxMod) was used to simulate the cloud seeding and quantified its impact on the region. The Southern Hemisphere, due to low aerosol emissions and highly pristine cloud conditions, has distinctly different cloud microphysical characteristics than the Northern Hemisphere, where WRF-WxMod has been successfully applied in a few regions over the United States. The results showed that WRF-WxMod could accurately capture the clouds and precipitation in both the natural and seeded conditions.
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.more » « less
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.
The 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.