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Uncrewed aircraft system (UAS) observations from the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting (WRF) Model. The impact of assimilating targeted UAS observations in addition to surface observations was compared to that obtained when assimilating surface observations alone using observing system experiments (OSEs) for a terrain-driven flow case and a convection initiation (CI) case observed within Colorado’s San Luis Valley (SLV). The assimilation of UAS observations in addition to surface observations results in a clear increase in skill for both flow regimes over that obtained when assimilating surface observations alone. For the terrain-driven flow case, the UAS observations improved the representation of thermal stratification across the northern SLV, which produced stronger upvalley flow over the eastern half of the SLV that better matched the observations. For the CI case, the UAS observations improved the representation of the pre-convective environment by reducing dry biases across the SLV and over the surrounding terrain. This led to earlier CI and more organized convection over the foothills that spilled outflows into the SLV, ultimately helping to increase low-level convergence and CI there. In addition, the importance of UAS capturing an outflow that originated over the Sangre de Cristo Mountains and triggered CI is discussed. These outflows and subsequent CI were not well captured in the simulation that assimilated surface observations alone. Observations obtained with a fleet of UAS are shown to notably improve high-resolution analyses and short-term predictions of two very different mesogamma-scale weather events.

In this study, we present a climatology of observed cell mergers along the paths of 342 discrete, right-moving supercells and their association with temporal changes in low-level mesocyclone strength (measured using azimuthal shear). Nearly one-half of the examined supercells experience at least one cell merger. The frequency of cell merger occurrence varies somewhat by geographical region and the time of day. No general relationship exists between cell merger occurrence and temporal changes in low-level azimuthal shear; this corroborates prior studies in showing that the outcome of a merger is probably sensitive to storm-scale and environmental details not captured in this study. Interestingly, we find a significant inverse relationship between premerger azimuthal shear and the subsequent temporal evolution of azimuthal shear. In other words, stronger low-level mesocyclones are more likely to weaken after cell mergers and weaker low-level mesocyclones are more likely to strengthen. We also show that shorter-duration cell merger “events” (comprising multiple individual mergers) are more likely to be associated with a steady or weakening low-level mesocyclone whereas longer-duration cell merger events (3–4 individual mergers) are more likely to be associated with a strengthening low-level mesocyclone. These findings suggest what physical processes may influence the outcome of a merger in different scenarios and that the impact of these processes on low-level mesocyclone strength may change depending on storm maturity. We establish a baseline understanding of the supercell–cell merger climatology and highlight areas for future research in how to better anticipate the outcomes of cell mergers. Significance Statement A common assumption in idealized supercell simulations is that the background environment is homogeneous. Cells merging into a primary supercell represent one of many ways in which the environment might be significantly inhomogeneous. This study analyzes the paths of 342 supercells with a particular focus on how cell merger occurrence influences the strength of the low-level mesocyclone. Almost one-half of all supercells experience at least one cell merger. Supercells are more likely to weaken after a cell merger event if the premerger mesocyclone was strong or if the merger event is relatively short, and vice versa for the likelihood for a supercell to strengthen. These findings are important for those interested in short-term predictions of supercell evolution in response to cell mergers and suggest what dynamic processes may play a role in governing these relationships.

Harsh winters and hazards such as blizzards are synonymous with the northern Great Plains of the United States. Studying these events is difficult; the juxtaposition of cold temperatures and high winds makes microphysical observations of both blowing and falling snow challenging. Historically, these observations have been provided by costly hydrometeor imagers that have been deployed for field campaigns or at select observation sites. This has slowed the development and validation of microphysics parameterizations and remote sensing retrievals of various properties. If cheaper, more mobile instrumentation can be developed, this progress can be accelerated. Further, lowering price barriers can make deployment of instrumentation feasible for education and outreach purposes. The Blowing Snow Observations at the University of North Dakota: Education through Research (BLOWN-UNDER) Campaign took place during the winter of 2019/20 to investigate strategies for obtaining microphysical measurements in the harsh North Dakota winter. Student led, the project blended education, outreach, and scientific objectives. While a variety of in situ and remote sensing instruments were deployed for the campaign, the most novel aspect of the project was the development and deployment of OSCRE, the Open Snowflake Camera for Research and Education. Images from this instrument were combined with winter weather educational modules to describe properties of snow to the public, K–12 students, and members of indigenous communities through a tribal outreach program. Along with an educational deployment of a Doppler on Wheels mobile radar, nearly 1,000 individuals were reached during the project.

Uncrewed aircraft system (UAS) observations collected during the 2018 Lower Atmospheric Process Studies at Elevation—a Remotely Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting Model using an ensemble Kalman filter. The benefit of UAS observations was assessed for a terrain-driven (drainage and upvalley) flow event that occurred within Colorado’s San Luis Valley (SLV) using independent observations. The analysis and prediction of the strength, depth, and horizontal extent of drainage flow from the Saguache Canyon and the subsequent transition to upvalley and up-canyon flow were improved relative to that obtained both without data assimilation (benchmark) and when only surface observations were assimilated. Assimilation of UAS observations greatly improved the analyses of vertical variations in temperature, relative humidity, and winds at multiple locations in the northern portion of the SLV, with reductions in both bias and the root-mean-square error of roughly 40% for each variable relative to the benchmark run. Despite these noted improvements, some biases remain that were tied to measurement error and/or the impact of the boundary layer parameterization on vertically spreading the observations, both of which require further exploration. The results presented here highlight how observations obtained with a fleet of profiling UAS improve limited-area, high-resolution analyses and short-term forecasts in complex terrain.

Because unmanned aircraft systems (UAS) offer new perspectives on the atmosphere, their use in atmospheric science is expanding rapidly. In support of this growth, the International Society for Atmospheric Research Using Remotely-Piloted Aircraft (ISARRA) has been developed and has convened annual meetings and “flight weeks.” The 2018 flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE), involved a 1-week deployment to Colorado’s San Luis Valley. Between 14 and 20 July 2018 over 100 students, scientists, engineers, pilots, and outreach coordinators conducted an intensive field operation using unmanned aircraft and ground-based assets to develop datasets, community, and capabilities. In addition to a coordinated “Community Day” which offered a chance for groups to share their aircraft and science with the San Luis Valley community, LAPSE-RATE participants conducted nearly 1,300 research flights totaling over 250 flight hours. The measurements collected have been used to advance capabilities (instrumentation, platforms, sampling techniques, and modeling tools), conduct a detailed system intercomparison study, develop new collaborations, and foster community support for the use of UAS in atmospheric science.

Obtaining quality air temperature measurements in complex mesoscale environments, such as thunderstorms or frontal zones, is problematic, and particularly challenging from a moving platform. For some time mobile weather platforms known as Mobile Mesonets (MMs) have used custom aspirated temperature shields. The original design was known as the “J-Tube”, which addresses some but not all of the unique problems associated with mobile temperature measurements. For VORTEX-2 2009, a second, well documented shield, the R.M. Young (RMY) 43408 was included but was also found to have certain shortcomings in some severe weather environments. Between the end of VORTEX2 2009 and the start of VORTEX2 2010, a third and new shield called the “U-tube” was designed, tested and installed.Reported here are the results of efforts to better characterize the J-Tube, RMY 43408, and the U-Tube. Several tests designed to isolate key aspects of a radiation shield’s performance, such as performance in rain, high solar radiation, varying wind conditions, and general response time were completed. A period of intercomparison between the three shields during the 2010 season of VORTEX 2 is also used to highlight each shield being used in “real world” conditions. Results indicate that the U-Tube has several significant advantages over the J-tube and 43408 in terms of aspiration rate, sampling efficiency, performance during rain, variable winds, and high solar radiation periods, as well as response time. Given these results, the U-tube should be utilized for mobile observations going forward.

While Hurricane Harvey will best be remembered for record rainfall that led to widespread flooding in southeastern Texas and western Louisiana, the storm also produced some of the most extreme wind speeds ever to be captured by an adaptive mesonet at landfall. This paper describes the unique tools and the strategy used by the Digital Hurricane Consortium (DHC), an ad hoc group of atmospheric scientists and wind engineers, to intercept and collect high-resolution measurements of Harvey’s inner core and eyewall as it passed over Aransas Bay into mainland Texas. The DHC successfully deployed more than 25 observational assets, leading to an unprecedented view of the boundary layer and winds aloft in the eyewall of a major hurricane at landfall. Analysis of anemometric measurements and mobile radar data during heavy convection shows the kinematic structure of the hurricane at landfall and the suspected influence of circulations aloft on surface winds and extreme surface gusts. Evidence of mesoscale vortices in the interior of the eyewall is also presented. Finally, the paper reports on an atmospheric sounding in the inner eyewall that produced an exceptionally large and potentially record value of precipitable water content for observed soundings in the continental United States.

Members of the international community developing unmanned aircraft for atmospheric research conducted a highly successful coordinated flight week in Colorado during the summer of 2018 to collect measurements, develop capabilities, and enhance community in the field. publishedVersion

Radiosonde observations are used the world over to provide critical upper-air observations of the lower atmosphere. These observations are susceptible to errors that must be mitigated or avoided when identified. One source of error not previously addressed is radiosonde icing in winter storms, which can affect forecasts, warning operations, and model initialization. Under certain conditions, ice can form on the radiosonde, leading to decreased response times and incorrect readings. Evidence of radiosonde icing is presented for a winter storm event in Norman, Oklahoma, on 24 November 2013. A special sounding that included a particle imager probe and a GoPro camera was flown into the system producing ice pellets. While the iced-over temperature sensor showed no evidence of an elevated melting layer (ML), complementary Particle Size, Image, and Velocity (PASIV) probe and polarimetric radar observations provide clear evidence that an ML was indeed present. Radiosonde icing can occur while passing through a layer of supercooled drops, such as frequently found in a subfreezing layer that often lies below the ML in winter storms. Events that have warmer/deeper MLs would likely melt any ice present off the radiosonde, minimizing radiosonde icing and allowing the ML to be detected. This paper discusses the hypothesis that the absence of an ML in the radiosonde data presented here is more likely to occur in winter storms that produce ice pellets, which tend to have cooler/shallower MLs. Where sounding data do appear to be compromised by icing, polarimetric radar data might be used to identify MLs for nowcasting purposes and numerical model initialization.

Results are presented from an intercomparison of temperature, humidity, and wind velocity sensors of the Tempest unmanned aircraft system (UAS) and the National Severe Storms Laboratory (NSSL) mobile mesonet (NSSL-MM). Contemporaneous evaluation of sensor performance was facilitated by mounting the Tempest wing with attached sensors to the NSSL-MM instrument rack such that the Tempest and NSSL-MM sensors could collect observations within a nearly identical airstream. This intercomparison was complemented by wind tunnel simulations designed to evaluate the impact of the mobile mesonet vehicle on the observed wind velocity.The intercomparison revealed strong correspondence between the temperature and relative humidity (RH) data collected by the Tempest and the NSSL-MM with differences generally within sensor accuracies. Larger RH differences were noted in the presence of heavy precipitation; however, despite the exposure of the Tempest temperature and humidity sensor to the airstream, there was no evidence of wet bulbing within precipitation. Wind tunnel simulations revealed that the simulated winds at the location of the NSSL-MM wind monitor were ~4% larger than the expected winds due to the acceleration of the flow over the vehicle. Simulated vertical velocity exceeded 1 m s−1 for tunnel inlet speeds typical of a vehicle moving at highway speeds. However, the theoretical noncosine reduction in winds that should result from the impact of vertical velocity on the laterally mounted wind monitor was found to be negligible across the simulations. Comparison of the simulated and observed results indicates a close correspondence, provided the crosswind component of the flow is small.

The Mesoscale Predictability Experiment (MPEX) was a field campaign conducted 15 May through 15 June 2013 within the Great Plains region of the United States. One of the research foci of MPEX regarded the upscaling effects of deep convective storms on their environment, and how these feed back to the convective-scale dynamics and predictability. Balloon-borne GPS radiosondes, or “upsondes,” were used to sample such environmental feedbacks. Two of the upsonde teams employed dual-frequency sounding systems that allowed for upsonde observations at intervals as fast as 15 min. Because these dual-frequency systems also had the capacity for full mobility during sonde reception, highly adaptive and rapid storm-relative sampling of the convectively modified environment was possible. This article documents the mobile sounding capabilities and unique sampling strategies employed during MPEX.

A balloonborne instrument known as the Particle Size, Image, and Velocity (PASIV) probe has been developed at the National Severe Storms Laboratory to provide in situ microphysical measurements in storms. These observations represent a critical need of microphysics observations for use in lightning studies, cloud microphysics simulations, and dual-polarization radar validation. The instrument weighs approximately 2.72 kg and consists of a high-definition (HD) video camera, a camera viewing chamber, and a modified Particle Size and Velocity (Parsivel) laser disdrometer mounted above the camera viewing chamber. Precipitation particles fall through the Parsivel sampling area and then into the camera viewing chamber, effectively allowing both devices to sample the same particles. The data are collected on board for analysis after retrieval. Taken together, these two instruments are capable of providing a vertical profile of the size, shape, velocity, orientation, and composition of particles along the balloon path within severe weather.The PASIV probe has been deployed across several types of weather environments, including thunderstorms, supercells, and winter storms. Initial results from two cases in the Deep Convective Clouds and Chemistry Experiment are shown that demonstrate the ability of the instrument to obtain high-spatiotemporal- resolution observations of the particle size distributions within convection.