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Abstract This study presents an evaluation of the skill of 12 global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) archive in capturing convective storm parameters over the United States. For the historical reference period 1979–2014, we compare the model-simulated 6-hourly convective available potential energy (CAPE), convective inhibition (CIN), 0–1-km wind shear (S01), and 0–6-km wind shear (S06) to those from two independent reanalysis datasets: ERA5 and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2). To obtain a comprehensive picture, we analyze the parameter distribution, climatological mean, extreme, and thresholded frequency of convective parameters. The analysis reveals significant bias in capturing both magnitude and spatial patterns, which also vary across the seasons. The spatial distribution of means and extremes of the parameters indicates that most models tend to overestimate CAPE, whereas S01 and S06 are underrepresented to varying extents. Additionally, models tend to underestimate extremes in CIN. Comparing the model profiles with rawinsonde profiles indicates that most of the high CAPE models have a warm and moist bias. We also find that the near-surface wind speed is generally underestimated by the models. The intermodel spread is larger for thermodynamic parameters as compared to kinematic parameters. The models generally have a significant positive bias in CAPE over western and eastern regions of the continental United States. More importantly, the bias in the thresholded frequency of all four variables is considerably larger than the bias in the mean, suggesting a nonuniform bias across the distribution. This likely leads to an underrepresentation of favorable severe thunderstorm environments and has the potential to influence dynamical downscaling simulations via initial and boundary conditions. Significance StatementGlobal climate model projections are often used to explore future changes in severe thunderstorm activity. However, climate model outputs often have significant biases, and they can strongly impact the results. In this study, we thoroughly examined biases in convective parameters in 12 models from phase 6 of the Coupled Model Intercomparison Project with respect to two reanalysis datasets. The analysis is performed for North America, covering the period 1979–2014. The study reveals significant biases in convective parameters that differ between models and are tied to the biases in temperature, humidity, and wind profiles. These results provide valuable insight into selecting the right set of models to analyze future changes in severe thunderstorm activity across the North American continent. 

Abstract Cold pools play a range of important roles in quasi-linear convective systems (QLCSs), including maintenance via the development of new convective cells as well as baroclinic generation of horizontal vorticity. Although a number of QLCS cold pools have been characterized in the literature using one or a few sensors, their variability (both internally and across a range of environments) has still not been widely studied. This gap in knowledge extends particularly to high-shear low-CAPE (HSLC) convective environments common to the cool season in the southeastern United States, where the Propagation, Evolution, and Rotation in Linear Storms (PERiLS) field campaign was focused. PERiLS specifically targeted environmental and storm-scale processes in QLCSs, including their cold pools. Our analysis focuses on the heterogeneity and temporal variability of cold pools across short time and spatial scales using numerous surface and sounding observations across five PERiLS QLCSs. The PERiLS cold pools are generally weaker than those previously studied in warm-season, midlatitude QLCSs, likely due to the lower CAPE and higher relative humidity values common to HSLC environments during PERiLS. Nevertheless, the distributions of most PERiLS cold pool variables at least partially overlap with those of previously studied QLCSs. The median PERiLS measurement reveals a cold pool that is ≈2.5 km deep, having a surface temperature decrease of ≈−6°C, and a peak outflow wind gust of ≈13 m s⁻¹. In the spirit of a “cold pool audit,” we present the internal and case-to-case variability of these particularly well-observed QLCSs. Significance StatementEvaporatively cooled air masses (“cold pools”) are created by quasi-linear convective systems (“QLCSs,” also called “squall lines”), and they in turn play important roles in the maintenance and structures of QLCSs. There have been relatively few direct measurements of cold pool variability, especially for the frequently severe QLCSs occurring during the cool season in the southeastern United States. Numerous surface and upper-air measurements from the recent Propagation, Evolution, and Rotation in Linear Storms (“PERiLS”) field experiment are used to document Southeastern QLCS cold pools. The PERiLS cold pools were surprisingly similar to, albeit somewhat weaker than, those found in prior studies of warm-season QLCSs in other regions. 

Abstract Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the U.S., but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear System (PERiLS) project was the first observational study of tornadoes associated with QLCSs ever undertaken. Participants were drawn from more than 10 universities, laboratories, and institutes, with over 100 students participating in field activities. The PERiLS field phases spanned two years, late winters and early springs of 2022 and 2023, to increase the probability of intercepting significant tornadic QLCS events in a range of large-scale and local environments. The field phases of PERiLS collected data in nine tornadic and nontornadic QLCSs with unprecedented detail and diversity of measurements. The design and execution of the PERiLS field phase and preliminary data and ongoing analyses are shown. 

Abstract The current study identifies and quantifies various mechanisms of entrainment, and their diluting effects, in the developing and mature stages of a simulated supercell thunderstorm. The two stages, differentiated by the lack or presence of a rotating updraft, are shown to entrain air by different, but related mechanisms that result from the strong vertical wind shear of the environment. The greatest entrainment rates in the developing stage result from the asymmetric overturning of large eddies near cloud top on the down-shear side. These rates are greater than those published in the literature for cumuli developing in environments lacking strong shear. Although the entrainment rate increases exponentially in time throughout the developing stage, successive cloud turrets help to replenish some of the lost buoyancy and condensate, allowing the nascent storm to develop further. During the mature stage, the greatest entrainment rates occur via “ribbons” of horizontal vorticity wrapping around the rotating updraft that ascend in time. The smaller width of the ribbons in comparison to the wider storm core limits their dilutive effects. Passive tracers placed in the low-level air ingested by the mature storm indicate that on average 20% of the core contains some undiluted air ingested from below the storm base, unaffected by any entrainment mechanism. 

Abstract The Flexible Array of Radars and Mesonets (FARM) Facility is an extensive mobile/quickly-deployable (MQD) multiple-Doppler radar and in-situ instrumentation network. The FARM includes four radars: two 3-cm dual-polarization, dual-frequency (DPDF), Doppler On Wheels DOW6/DOW7, the Rapid-Scan DOW (RSDOW), and a quickly-deployable (QD) DPDF 5-cm COW C-band On Wheels (COW). The FARM includes 3 mobile mesonet (MM) vehicles with 3.5-m masts, an array of rugged QD weather stations (PODNET), QD weather stations deployed on infrastructure such as light/power poles (POLENET), four disdrometers, six MQD upper air sounding systems and a Mobile Operations and Repair Center (MORC). The FARM serves a wide variety of research/educational uses. Components have deployed to >30 projects during 1995-2020 in the USA, Europe, and South America, obtaining pioneering observations of a myriad of small spatial and temporal scale phenomena including tornadoes, hurricanes, lake-effect snow storms, aircraft-affecting turbulence, convection initiation, microbursts, intense precipitation, boundary-layer structures and evolution, airborne hazardous substances, coastal storms, wildfires and wildfire suppression efforts, weather modification effects, and mountain/alpine winds and precipitation. The radars and other FARM systems support innovative educational efforts, deploying >40 times to universities/colleges, providing hands-on access to cutting-edge instrumentation for their students. The FARM provides integrated multiple radar, mesonet, sounding, and related capabilities enabling diverse and robust coordinated sampling of three-dimensional vector winds, precipitation, and thermodynamics increasingly central to a wide range of mesoscale research. Planned innovations include S-band On Wheels NETwork (SOWNET) and Bistatic Adaptable Radar Network (BARN), offering more qualitative improvements to the field project observational paradigm, providing broad, flexible, and inexpensive 10-cm radar coverage and vector windfield measurements. 

Abstract During the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations-Cloud, Aerosol, and Complex Terrain Interactions (RELAMPAGO-CACTI) field experiments in 2018–19, an unprecedented number of balloon-borne soundings were collected in Argentina. Radiosondes were launched from both fixed and mobile platforms, yielding 2712 soundings during the period 15 October 2018–30 April 2019. Approximately 20% of these soundings were collected by highly mobile platforms, strategically positioned for each intensive observing period, and launching approximately once per hour. The combination of fixed and mobile soundings capture both the overall conditions characterizing the RELAMPAGO-CACTI campaign, as well as the detailed evolution of environments supporting the initiation and upscale growth of deep convective storms, including some that produced hazardous hail and heavy rainfall. Episodes of frequent convection were characterized by sufficient quantities of moisture and instability for deep convection, along with deep-layer vertical wind shear supportive of organized or rotating storms. A total of 11 soundings showed most unstable convective available potential energy (MUCAPE) exceeding 6000 J kg −1 , comparable to the extreme instability observed in other parts of the world with intense deep convection. Parameters used to diagnose severe-storm potential showed that conditions were often favorable for supercells and severe hail, but not for tornadoes, primarily because of insufficient low-level wind shear. High-frequency soundings also revealed the structure and evolution of the boundary layer leading up to convection initiation, convectively generated cold pools, the South American low-level jet (SALLJ), and elevated nocturnal convection. This sounding dataset will enable improved understanding and prediction of convective storms and their surroundings in subtropical South America, as well as comparisons with other heavily studied regions such as the central United States that have not previously been possible. 

Orographic deep convection (DC) initiation and rapid evolution from supercells to mesoscale convective systems (MCS) are common near the Sierras de Cόrdoba, Argentina, which was the focal point of the Remote Sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. This study used an idealized numerical model with elongated north-south terrain similar to that of the Sierras de Cόrdoba to address how variations in terrain height affected the environment and convective morphology. Simulations used a thermodynamic profile from a RELAMPAGO event that featured both supercell and MCS storm modes. Results revealed that DC initiated earlier in simulations with higher terrain, owing both to stronger upslope flows and standing mountain waves. All simulations resulted in supercell formation, with higher terrain supercells initiating closer to the terrain peak and moving slower off the terrain. Higher terrain simulations displayed increases in both low-level and deep-layer wind shear along the eastern slopes of the terrain that were related to the enhanced upslope flows, supporting stronger and wider supercell updrafts/downdrafts and a wider swath of heavy rainfall. Deeper and stronger cold pools from these wider and stronger higher terrain supercells led to surging outflow that reduced convective available potential energy accessible to deep convective updrafts, resulting in quicker supercell demise off the terrain. Lower terrain supercells moved quickly off the terrain, merged with weaker convective cells, and resulted in a quasi-organized MCS. These results demonstrate that terrain-induced flow modification may lead to substantial local variations in convective morphology. 

Abstract On 10 November 2018, during the RELAMPAGO field campaign in Argentina, South America, a thunderstorm with supercell characteristics was observed by an array of mobile observing instruments, including three Doppler on Wheels radars. In contrast to the archetypal supercell described in the Glossary of Meteorology, the updraft rotation in this storm was rather short lived (~25 min), causing some initial doubt as to whether this indeed was a supercell. However, retrieved 3D winds from dual-Doppler radar scans were used to document a high spatial correspondence between midlevel vertical velocity and vertical vorticity in this storm, thus providing evidence to support the supercell categorization. Additional data collected within the RELAMPAGO domain revealed other storms with this behavior, which appears to be attributable in part to effects of the local terrain. Specifically, the IOP4 supercell and other short-duration supercell cases presented had storm motions that were nearly perpendicular to the long axis of the Sierras de Córdoba Mountains; a long-duration supercell case, on the other hand, had a storm motion nearly parallel to these mountains. Sounding observations as well as model simulations indicate that a mountain-perpendicular storm motion results in a relatively short storm residence time within the narrow zone of terrain-enhanced vertical wind shear. Such a motion and short residence time would limit the upward tilting, by the left-moving supercell updraft, of the storm-relative, antistreamwise horizontal vorticity associated with anabatic flow near complex terrain. 

Abstract The pseudo‐global‐warming (PGW) methodology provides an efficient means to investigate the response of a weather or climate event under an imposed climate change signal. In the traditional PGW implementation, this signal is represented through climate‐change “deltas” constructed using monthly averages of global climate model (GCM) output over decadal or longer periods during the past and future. The implications of alternative formulations of such deltas were explored herein. Diurnally varying (DV) deltas were compared to the time‐constant (TC) deltas used in the traditional PGW implementation; this was done to test the potential effect of future changes in the diurnal cycles of temperature, humidity, and winds. Deltas created using 10‐year averages were compared to those using 30‐year averages, to examine the effects of the time‐averaging period in the delta construction. Finally, the common practice of additionally averaging across multiple GCMs to form a composite delta was also considered. Using simulations of three different historical convective storm events, it was shown that each of these PGW delta formulations results in differences in simulation metrics such as total accumulated rainfall, and convective intensity, but major and/or unambiguous differences were not always found. It is recommended that users of the PGW approach carefully consider all implications of delta formulation on their particular problem.