Deep convective transport of gaseous precursors to ozone (O₃) and aerosols to the upper troposphere is affected by liquid phase and mixed‐phase scavenging, entrainment of free tropospheric air and aqueous chemistry. The contributions of these processes are examined using aircraft measurements obtained in storm inflow and outflow during the 2012 Deep Convective Clouds and Chemistry (DC3) experiment combined with high‐resolution (dx≤3 km) WRF‐Chem simulations of a severe storm, an air mass storm, and a mesoscale convective system (MCS). The simulation results for the MCS suggest that formaldehyde (CH₂O) is not retained in ice when cloud water freezes, in agreement with previous studies of the severe storm. By analyzing WRF‐Chem trajectories, the effects of scavenging, entrainment, and aqueous chemistry on outflow mixing ratios of CH₂O, methyl hydroperoxide (CH₃OOH), and hydrogen peroxide (H₂O₂) are quantified. Liquid phase microphysical scavenging was the dominant process reducing CH₂O and H₂O₂ outflow mixing ratios in all three storms. Aqueous chemistry did not significantly affect outflow mixing ratios of all three species. In the severe storm and MCS, the higher than expected reductions in CH₃OOH mixing ratios in the storm cores were primarily due to entrainment of low‐background CH₃OOH. In the air mass storm, lower CH₃OOH and H₂O₂ scavenging efficiencies (SEs) than in the MCS were partly due to entrainment of higher background CH₃OOH and H₂O₂. Overestimated rain and hail production in WRF‐Chem reduces the confidence in ice retention fraction values determined for the peroxides and CH₂O.

A mobile Shared Mobile Atmospheric Research and Teaching (SMART) radar was deployed in Hurricane Harvey and coordinated with the Corpus Christi, TX, WSR‐88D radar to retrieve airflow during landfall. Aerodynamic surface roughness estimates and a logarithmic wind profile assumption were used to project the 500‐m radar‐derived maximum wind field to near the surface. The logarithmic wind assumption was justified using radiosonde soundings taken within the storm, while the radar wind estimates were validated against an array of StickNets. For the data examined here, the radar projections had root‐mean‐squared error of 3.9 m/s and a high bias of 2.3 m/s. Mesovorticies in Harvey's eyewall produced the strongest radar‐observed winds. Given the wind analysis, Harvey was, at most, a Category 3 hurricane (50–58 m/s sustained winds) at landfall. This study demonstrates the utility of integrated remote and in situ observations in deriving spatiotemporal maps of wind maxima during hurricane landfalls.

A series of vertical cross sections taken through a small mesoscale convective system observed over Florida by the dual‐polarimetric SMART radar were combined with VHF radiation source locations from a lightning mapping array (LMA) to examine the lightning channel propagation paths relative to the radar‐observed ice alignment signatures associated with regions of negative specific differential phase (K_DP). Additionally, charge layers inferred from analysis of LMA sources were related to the ice alignment signature. It was found that intracloud flashes initiated near the upper zero‐K_DP boundary surrounding the negative K_DP region. The zero‐K_DP boundary also delineated the propagation path of the lightning channel with the negative leaders following the upper boundary and positive leaders following the lower boundary. Very few LMA sources were found in the negative K_DP region. We conclude that rapid dual‐polarimetric radar observations can diagnose strong electric fields and may help identify surrounding regions of charge.

Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the United States, but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear Storms (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 2 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.

This article describes a unique ground‐based weather radar dataset collected during the landfall of Hurricane Harvey (2017) along the United States Gulf Coast, documents the wind retrievals conducted with this dataset, and reports on the location of the archive of the data and wind retrievals so that others may gain access and use of these data. Datasets from C‐band dual‐polarimetric Shared Mobile Atmospheric Research and Teaching (SMART) radar and the United States National Weather Service WSR‐88D in Corpus Christi, Texas, are presented, along with dual‐Doppler analyses before and during Harvey's landfall on the United States Gulf Coast. The quality assurance and dual‐Doppler wind synthesis procedures are detailed. Nearly 8 hr of dual‐Doppler wind analyses were constructed, providing an unprecedented dataset for use in understanding hurricane dynamics at landfall and validating numerical simulations of Hurricane Harvey. In addition, raw, dual‐polarization data not used in the dual‐Doppler syntheses, but included in each radar dataset, are also summarized.

A ground-based C-band Shared Mobile Atmospheric Research and Teaching (SMART) polarimetric radar and the National Weather Service WSR-88D radar near Wilmington, North Carolina simultaneously observed Hurricane Florence (2018) as it made landfall as a category 1 hurricane. The slow translation of Florence allowed for more than 30 hr of data collection before, during and after the tropical cyclone came ashore. Nearly 26 hr of three-dimensional wind retrievals every 6–10 min were constructed from the radar observations, providing an unprecedented view of the evolution of rainbands, the inner core and the eyewall of Hurricane Florence. This article describes the radar data, the procedures used for automated quality control, data processing and the wind retrievals that have been constructed. The location of the data and wind retrieval archive is given. These data can be used to study the dynamics and rainfall of Hurricane Florence, to quantify the impact of winds on the natural and built environment, to validate numerical simulations of the tropical cyclone, and as an educational resource for courses in radar and tropical meteorology.