Abstract The potential for cloud seeding to induce dynamic changes that alter cloud structure beyond basic ice formation processes has remained theoretical. While previous research hypothesized the presence of dynamic responses in seeded clouds, this study presents the first direct observational evidence that seeding can generate buoyant forces strong enough to deepen and deform clouds. In situ aircraft measurements and W‐band radar analysis shows how the buoyant force increased cloud tops by hundreds of meters and induced secondary circulations that altered the cloud and precipitation structure. These dynamic changes triggered additional ice formation and precipitation not captured in current conceptual models. The results demonstrate that dynamic responses can be induced through glaciogenic seeding, representing foundational research that will significantly improve understanding of seeding mechanisms and precipitation formation in commonly seeded clouds.

Abstract. Closed-to-open cell mixed-phase cloud transitions within marine cold air outbreaks subjected to strong turbulent surface fluxes remain poorly understood despite their importance to high-latitude climate. The Cold-Air outbreak Experiment in the Sub-Arctic Region (CAESAR) research aircraft sampled closed-cells with cloud condensation nuclei concentrations surpassing 680 cm-3, decreasing to 90 cm-3 across a transition to open-cells. The aerosol likely originated from Siberian industrial emissions. With fetch, liquid water paths (LWPs) increase from 120 g m-2 to 270 g m-2 and cloud-top effective diameters increase from 10 μm to 16 μm, coincident with more riming. Ice particle number concentrations (Ni) are generally 2 L-1 or less, but exceed ice nucleating particle number concentrations by 100x. As the cloud-top inversion weakens and the boundary layer deepens further, ice precipitation co-exists with lidar-observed surface cold pools, modulated by entrainment events, juxtaposed with surface-based plumes of warm moist air. Open-cells contain isolated LWP peaks surpassing 500 g m-2 collocated with strong updrafts, adjacent to glaciated cloud. Ni surpasses 10 L-1 at cloud temperatures < -15 °C. Precipitation shafts contain abundant large graupel (> 5 mm diameter) with liquid-equivalent precipitation intensities reaching 3 mm hr-1 developing cold pools with virtual potential temperature depressions reaching 1.3 K. Nonetheless, buoyancy fluxes of 200-250 W m-2 prevent sub-cloud decoupling. The updrafts supporting liquid water production occur at the upwind edge of the cold pools. This case expands the observations needed to better understand mixed-phase Arctic cloud processes.

The planetary boundary layer (PBL) is the atmospheric layer closest to Earth’s surface that is directly influenced by surface processes, where exchanges of momentum, heat, mass, and radiation regulate environmental conditions with direct societal relevance. Because the thermodynamic structure and dynamics of the PBL are tightly coupled to surface–atmosphere interactions, accurate characterization of these processes is essential for advancing understanding of Earth system feedbacks. However, despite their importance, significant observational gaps remain in capturing the coupled surface–PBL system across the spatial and temporal scales required for both scientific and operational applications. This perspective paper articulates the central role of surface–atmosphere interactions in PBL science and their importance for advancing multiplatform observing systems. We assess the key surface variables and their required spatiotemporal resolutions needed for accurate PBL characterization, evaluate the capabilities and limitations of current global observing systems and the Program of Record—including space-based, airborne, and ground-based assets—and review emerging technological and scientific efforts aimed at addressing these gaps. Building on this assessment, we argue that advancing toward a comprehensive, surfaceinformed PBL observing system is both a scientific and societal imperative. Such a system would overcome current observational limitations and unlock substantial benefits across a wide range of applications that depend critically on accurate PBL representation, yet remain underrecognized. By synthesizing current knowledge and defining clear observational priorities, this work aims to guide the design of future PBL global observing systems and its integration, as well as to mobilize the scientific community toward coordinated, multi-scale observations of surface–atmosphere interactions, ultimately advancing PBL science and its applications on a global scale. SIGNIFICANCE STATEMENT: The planetary boundary layer (PBL) is the lowest part of the 86

Wintertime precipitation in the western United States is essential for water supply, affecting agriculture, ecosystems, local economies, and beyond. Due to increasing concerns over water resources, the Wyoming Water Development Commission (WWDC) has invested in research to assess the potential of glaciogenic cloud seeding to enhance winter precipitation. This study uses the Weather Research and Forecasting Model Weather Modification (WRF-WxMod), within an ensemble modeling framework, to simulate a winter season (2019-20) of aerial cloud seeding over the Medicine Bow and Sierra Madre Ranges in Wyoming and the Never Summer Range in Colorado. Twenty-seven cases of operational cloud seeding were analyzed to quantify precipitation impacts. Ensemble-mean results for the 2019-20 season showed an increase of over 10 mm of liquid-equivalent precipitation at sites in the highest elevations of the target area, with an overall mean of 9478 acre-feet (AF) (ensemble range of 6058-14030 AF) of additional precipitation across the North Platte and Little Snake River basins combined. In addition to investigating the results from the 2019-20 season, a case study from 9 to 10 December 2021 was evaluated in depth, as a "zigzag" signature resulting from a back-and-forth crosswind flight pattern of a seeding aircraft was observed on the Cheyenne NEXRAD, similar to what was observed in the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) field campaign. This unambiguous seeding signature makes this an ideal case to compare WRF-WxMod to observations.

Abstract This study evaluates the ability of CONUS404, a 4-km resolution historical climate reconstruction that uses a coupled atmosphere–land surface model driven by a global reanalysis, to accurately simulate the precipitation, temperature, and snow water equivalent (SWE) across the mountainous western United States by comparing it against a variety of datasets including observations, statistical interpolations, and data assimilation products. The analysis was performed across four subdomains with distinct hydroclimates over the period from 1985 to 2021. CONUS404 cold-season precipitation generally agrees well with gauge-based gridded estimates, with some exceptions. CONUS404 matches observationally based SWE estimates during the early accumulation period but consistently exhibits earlier-peaking, shallower snowpacks with slower late-season ablation rates. CONUS404’s good agreement in terms of seasonal precipitation and SWE during the accumulation period (early in the cold season) suggests that snowfall is not the primary driver of CONUS404’s negative SWE bias that begins to emerge in January. While the average temperatures are a fairly good representation, CONUS404 cannot adequately simulate the full extent of nighttime cold temperatures (minima are warm biased) or daytime warm temperatures (maxima are cold biased), resulting in a significantly reduced daily temperature range. This study cannot fully attribute the cause of the negative SWE bias in CONUS404 in late winter, and further investigation is required. Significance Statement Streamflow in the interior western United States and other midlatitude semiarid mountainous regions strongly depends on cold-season orographic precipitation and seasonal snowpack. Therefore, an accurate, highly resolved description of these fields, particularly over snow-dominated mountains, is essential for high-fidelity, physics-based watershed hydrologic predictions. Here, the accuracy of a 4-km resolution historical climate reconstruction that uses a coupled atmosphere–land surface model is examined. While precipitation is captured rather well, the peak seasonal snowpack in late winter/early spring is considerably less than observations suggest. This discrepancy calls for a better understanding of the surface energy balance and snow ablation rate at snowpack measurement sites.

This study examines the mesoscale structure and evolution of a polar low associated with a marine cold-air Region (CAESAR), the National Science Foundation National Center for Atmospheric Research C-130 aircraft equipped with an array of in situ and remote sensing instrumentation, including profiling radars and lidars, traversed this polar low five times, yielding detailed vertical transects of clouds and precipitation. This polar low was rather shallow and formed in the wake (not at the leading edge) of an MCAO. Observations and output from an operational convection-permitting model reveal that the polar low developed in the lee of an island, Svalbard, under deep northerly flow that roughly aligned with surface-driven baroclinicity. The polar low was marked by a region of surface-driven, mostly open-cellular precipitating convection, and a separate region of deeper stratiform clouds driven by moist-isentropic ascent in an area of suppressed surface heat fluxes. The confluence of a cold air mass from the northeast, only briefly exposed to open water, with a more mature, warmer MCAO air mass with a deeper well-mixed boundary layer previously exposed to high surface heat fluxes over the Fram Strait led to convergent, cyclonically sheared boundaries with enhanced convection. These convergent boundaries emerged as cyclonic potential vorticity streamers generated frictionally by Svalbard's terrain, became more intense by diabatic heating in clouds, and were transported downstream into the polar low.

Observations from recent field campaigns investigating glaciogenic cloud seeding demonstrate the process of silver iodide (AgI) dispersion through ice nucleation, crystal growth, then enhanced snowfall at the surface. These observations, combined with numerical simulations, were used to quantify seeding’s impact on enhancing precipitation in targeted regions. With the microphysical chain of events established, fundamental knowledge gaps remain on the mechanisms by which seeding modifies the cloud dynamics, structure, and precipitation enhancement. This study presents the first direct observational evidence that glaciogenic seeding generates buoyant forces in wintertime orographic clouds that elevate cloud tops and secondary circulations that alter the cloud structure. In this study, we analyze dynamic responses induced from seeding in the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) and CLOUDLAB field campaigns. The SNOWIE cases occurred in the Payette mountains in presence of widespread supercooled liquid conditions and low natural ice number concentrations. Ground-based X-band radars tracked the development and evolution of cloud and precipitation from five seeding legs. Distinct cells, directly attributable to airborne seeding, developed from smaller weaker echoes (10 dBZ) at the natural cloud top and rapidly intensified to produce precipitation with echoes >30 dBZ. The key observed processes were dynamic responses induced by the latent heat released from seeding that led to enhancing cloud top by 350 m compared to the natural cloud. An airborne W-band Dual-Doppler cross-section illustrates the detailed dynamic structure for one cell consisting of a central updraft, divergence near cloud top, and toroidal circulations along its periphery in an observed moist-neutral environment. In situ measurements show distinct microphysical regimes in the elevated cloud top, with seeding generated ice number concentrations up to 580 L-1. A WRF-WxMod ensemble shows the evolution of dynamic responses, the microphysical characteristics, and precipitation enhancement up to 200 km downwind of release. We combine these results with preliminary observations from the 2025-2026 CLOUDLAB field campaign that further investigate the roles each step in a dynamic response has on seeded cloud microphysical properties. We show the evolution of seeded cloud from Ka-band cloud radars, combined with in-situ measurements from a holographic imager, to show dynamic response impact on microphysical structure and cloud properties.

Precipitation enhancement over complex terrain is predominantly driven by quasi-stationary, terrain-tied vertical motions, making their variability a critical factor in shaping precipitation distributions and accumulation. This study quantifies the dominant modes of terrain-tied vertical motion variability over the Payette River basin of Idaho. Principal component analysis is applied to a seasonal simulation spanning November 2016-April 2017, which encompassed the Seeded and Natural Orographic Wintertime Clouds: the Idaho Experiment (SNOWIE) field campaign (January-March 2017). The first mode, accounting for more than 20% of the variance in vertical motion, captures ridge-tied updrafts and represents the primary pattern of terrain-induced ascent. The second mode (8%) reflects how synoptic-scale variations modulate updraft orientation, distinguishing between north-south and east-west ridgelines. The third mode (6%) isolates variability in updraft width and magnitude. These three dominant modes of variability, which explain over one-third of the vertical velocity variance in the seasonal simulation, strongly influence the distribution of supercooled liquid water (SLW) and precipitation over the terrain. Results show that the dominant modes of vertical motion variability were consistent with patterns commonly observed during SNOWIE research flights. Additionally, we quantified vertical motion, SLW, and precipitation means as a function of phase space between the modes, demonstrating that enhanced SLW and precipitation occurred when quasi-stationary waves were present over the terrain.

Part I of this study demonstrated how terrain-induced gravity waves triggered elevated convection, with tops up to 6-7 km above sea level, in a potentially unstable layer during a winter storm event over the Idaho Central Mountains on 7 February 2017. Herein, this case is explored further with a large-eddy simulation (LES) at 100-m grid spacing to examine the detailed structure and evolution of convective cells emergent from shallow stratiform clouds, their interaction with complex terrain, and the resulting precipitation processes. The 100-m LES produced fine-scale precipitation structures similar in depth and width to radar observations, with vertical velocity distributions and cloud microphysical properties matching airborne observations. The 100-m LES confirmed the role of vertically propagating gravity waves over the highest terrain ridges in providing the initial lift necessary to release potential instability. Unlike coarser-resolution simulations, the 100-m LES produced clusters of convective towers,-2 km wide, roughly matching observations, although they were more regularly spaced than observed. Cospectral analysis of these towers confirms their convective nature. The small-scale convective updrafts, locally exceeding 2 ms-1 and mostly within the-10 degrees to-20 degrees C temperature zone, enabled snow particles to grow rapidly through depositional growth and riming, and a significant fraction of the simulated precipitation fell as graupel, according to the LES model. Precipitation from this emergent convection occurred primarily in the lee of the main terrain ridge on account of the strong flow above mountain top level. Cumulatively, the LES produced 18% more precipitation than non-LES models in this case. SIGNIFICANCE STATEMENT: This study advances our understanding of cold-season precipitation processes over complex terrain. The key physical mechanisms identified herein are gravity wave-driven potential instability release, multiscale interactions between terrain and convection, and enhanced mixed-phase precipitation growth. This study demonstrates that large-eddy simulations with a grid spacing of-100 m are needed to properly capture the observed small convective towers and the snowfall they produce over and downwind of mountain ridges. In this case study, the large-eddy simulations (<= 300-m grid spacing) produced slightly more precipitation than less-resolved convection-permitting simulations with parameterized eddy exchanges. A more systematic analysis of precipitation from small-scale convection in winter storms is warranted since orographic precipitation has important implications for water resource management in the western United States.

Ski resorts across the western U.S. are challenged by global warming, with fewer days of sufficient natural snow during the season and more frequent weather conditions unsuitable for artificial snowmaking early in the season. While this applies to all ski resorts, the magnitude of snow security reduction varies widely. Regional Earth system simulations of sufficient resolution to capture the weather and seasonal snowpack at ski areas in the Rocky Mountain region demonstrate that in the next few decades, high-elevation places, and those historically receiving more snowfall, will be impacted less, while those resorts that currently have relatively low snow security will suffer more. Even though resorts in the Colorado Rockies will experience more warming in the next few decades than ski areas closer to the Pacific coast, they generally are less at risk, including a smaller decrease in the ski season length and in snowmaking potential, and fewer rain-on-snow events.

In the western United States, the recent mega-drought and impacts of climate change have resulted in an interest in cloud seeding to enhance water supplies. Studies and field campaigns focused on cloud seeding across the West have quantified the effect on precipitation generation through the release of silver iodide, and these effects can be studied in simulations using WRF-WxMod (R), a modeling capability based on the WRF model that includes a cloud-seeding parameterization. Here, we use a 36-member ensemble of WRF-WxMod simulations to force a spatially distributed hydrological model, WRF-Hydro, to study how simulated cloud seeding impacts hydrology in the North Platte and Little Snake River basins of Wyoming during the 2020 water year. WRF-Hydro is configured with a 1-km land surface model, Noah-MP, with the terrain routing grid run at 250 m. Compared to observations, WRF-Hydro shows good performance with an average Kling Gupta Efficiency = 0.80. Over the 2020 water year, snow water equivalent increases by 10 mm over target mountain ranges due to simulated cloud seeding and streamflow increases by 6,921 acre-ft over the entire domain. A water budget analysis shows that increases in ensemble mean precipitation due to simulated cloud seeding result in 78% diverted to increasing streamflow, 21% increasing soil moisture, and 8% going toward evapotranspiration. Such information is critical for water managers looking into the efficacy of cloud seeding to enhance their water resources amidst climate change.

Abstract. Models are universally challenged to accurately predict the coupled microphysical, turbulent and radiative processes within widespread, long-lived marine cold-air outbreak (CAO) cloud fields, which leads to biases and uncertainties in atmospheric predictions over all time scales. Here we assemble a suite of ground-based and satellite measurements to initialize and constrain large-eddy simulations (LES) of cloud field evolution with distance downwind from the marginal ice zone during a strong, highly supercooled and convective CAO observed during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). Detailed LES results are compared with large-scale models run in single-column model (SCM) mode, providing an observation-constrained framework for large-scale model evaluation and future improvements. All models reproduce rapid cloud formation off the ice edge, and a monotonic ascent of downwind cloud-top heights that is well correlated with time-integrated surface heat fluxes. LES generally reproduce domain-mean observational targets using a modest test domain (25 x 25 km2), and a larger domain (125 x 125 km2) enables better reproducing the observed growth of convective cell sizes. In realistic mixed-phase LES compared with liquid-only simulations, ice processes lead to thinner, broken cloud decks and substantially reduced cloud radiative effects on top-of-atmosphere longwave fluxes. By contrast, mixed-phase SCM simulations generally underpredict the impact of ice on radiative fluxes, primarily owing to insufficient reduction of cloud cover. Results indicate that cellular cloud structure is qualitatively captured by LES, and thus LES could provide guidance to improvement of large-scale model physics schemes. Follow-on work will extend these results to larger domains, apply objective analysis of mesoscale structure, and include prognostic aerosol properties for droplet and heterogeneous ice formation.

Observation networks established in complex mountain landscapes promise to address critical gaps in understanding of socio-hydrological systems and their process interactions operating at local to regional scales. Knowledge of vulnerabilities and risks founded on observed biophysical and socioeconomic conditions and responses is required to represent realistic scenarios in model simulations of climate change impacts on managed water resources. Socio-hydrological observatories often lack design coordination that consequently constrains the ability to link processes and detect feedbacks across scales and domain boundaries. The goal of the 5-year (2022-2027) project WyACT (Wyoming Anticipating Climate Transitions) is to build adaptive capacity in headwater mountain communities in the Greater Yellowstone Area of of the Rocky Mountains founded on observations, simulation modeling, and driven stakeholder needs and participation. A key feature of WyACT is the development, from the ground up, of a regional observatory network that explicitly coordinates observations of socioeconomic, hydrological, and ecological responses to climate-driven stressors. WY-SEaSON (Wyoming Socio-Environmental Systems Observatory Network) will quantify and monitor the range of responses of snowpack and soil moisture, streamflow, aquatic ecosystems, vegetation stress and fire risk, economic risk perception, and preferred adaptation pathways to a changing climate in a key headwaters region that feeds three major river drainages in western North America. This presentation highlights the structure of WY-SEaSON including the operating principles, goals, mission, and design with examples of emerging and integrated observations.

This study investigates the impacts of climate change on precipitation and snowpack in the interior western United States (IWUS) using two sets of convection-permitting Weather Research and Forecasting model simulations. One simulation represents the ~1990 climate, and another represents an ~2050 climate using a pseudo-global warming approach. Climate perturbations for the future climate are given by the CMIP5 ensemble-mean global climate models under the high-end emission scenario. The study analyzes the projected changes in spatial patterns of seasonal precipitation and snowpack, with particular emphasis on the effects of elevation on orographic precipitation and snowpack changes in four key mountain ranges: the Montana Rockies, Greater Yellowstone area, Wasatch Range, and Colorado Rockies. The IWUS simulations reveal an increase in annual precipitation across the majority of the IWUS in this warmer climate, driven by more frequent heavy to extreme precipitation events. Winter precipitation is projected to increase across the domain, while summer precipitation is expected to decrease, particularly in the High Plains. Snow-to-precipitation ratios and snow water equivalent are expected to decrease, especially at lower elevations, while snowpack melt is projected to occur earlier by up to 26 days in the ~2050 climate, highlighting significant impacts on regional water resources and hydrological management.

In the spring of 2024, the US National Science Foundation sponsored the Cold-Air outbrEaks in the Sub-Arctic Region (CAESAR) aircraft campaign, with the simple goal of characterizing cold-air outbreak (CAO) clouds coming off of the Arctic sea ice as comprehensively as possible. A strength of the CAESAR strategy is a comprehensive aerosol, cloud and remote sensing instrumentation suite and early development of a close connection to modeling spanning a range of scales, in part by building on prior DOE-sponsored activity through the Cold-Air Outbreaks in the Marine Boundary Layer (COMBLE) campaign. The higher-level motivation for CAESAR is to better understand how clouds participate and feedback upon the changing Arctic. New technologies, improved data integration and modeling frameworks that are increasingly comparable to the observations hold promise that both the numerical weather prediction and global modeling of the super-cooled liquid, mixed-phase and ice clouds can be improved through the focus provided by the field campaign. In this presentation we provide an overview of the NCAR C-130 aircraft campaign, and its approach to the problem of improving understanding of the cold-air outbreak cloud evolution, microphysical processes including their relationship to aerosol, and cloud mesoscale organization including the development of CAO clouds into polar lows. Initial highlights will be included.

Ice nucleating particles (INPs) initiate ice formation, affecting the liquid versus ice distribution and radiative properties of clouds. INPs have been measured around the Arctic, but few INP concentration measurements have been reported for air during movement south out of central Arctic pack ice regions during cold air outbreaks (CAOs). We analyzed cases of transports connecting the Central Arctic location of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to the near sea ice edge in Svalbard and across ice-free ocean to the Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) site at Andenes, Norway, during the 2019–2020 Arctic winter. Aerosol surface area concentration measurements during CAOs indicate a switch from primarily accumulation mode at MOSAiC toward marine coarse mode (from sea spray emissions) at COMBLE. INP concentrations were independent of aerosol surface area or volume over the pack ice in MOSAiC in winter. At Svalbard, INPs related best to supermicron aerosol surface area and supermicron volume. At the COMBLE site, INPs related best with total aerosol surface area and total aerosol volume. In 5 of 6 case studies analyzed, INP concentrations increased in association with the transition to a dominance of sea spray aerosols. The INPs at COMBLE had a unique INP concentration mode near −18°C and higher ice nucleation active site densities (e.g., INPs per surface area) compared to those previously reported for other open ocean regions dominated by marine aerosols. While the INP sources in this case appear to be from oceanic emissions from shallower oceans under turbid water conditions, attribution solely to sea spray aerosols versus mixing down of free tropospheric aerosols by CAO clouds remains as a future topic. These studies provide a basis for parameterization of INPs for numerical modeling studies of CAO cloud systems.

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-km(2) observational domain revealed that the accumulated liquid-equivalent snowfall was G0.9 x 10(7) m(3) and snowfall rates were G0.45 mm h(-1) for about half of the events. Low snowfall events were characterized by cloud-top temperatures >-20 degrees 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.