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Abstract Properties of 7488 thunderstorms are summarized for June–September 2022 during the Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign Houston, Texas, using polarimetric weather radar and VHF 3D Lightning Mapping Array data. Automated tracking of storms linked each instrument’s measurements to a data-defined, time-evolving storm footprint. Within each storm, the depth and magnitude of episodic columns of radar differential reflectivity and specific differential phase quantified the prevalence of updrafts that activated mixed-phase precipitation pathways. Lightning measurements further distinguished the degree of rimed precipitation formation: the fraction of tracks with lightning varied from day to day and cells with lightning had stronger polarimetric columns. Track-level correlation of the lightning flash rate with radar polarimetric measures had substantial spread, showing that lightning provides an additional signal of mixed-phase precipitation processes that can complement future studies of thermodynamic and aerosol controls on cloud microphysics in the Houston region. 

Abstract The National Science Foundation–sponsored Lake-Effect Electrification (LEE) field campaign intensive observation periods occurred between November and early February 2022–23 across the eastern Lake Ontario region. Project LEE documented, for the first time, the total lightning and electrical charge structures of lake-effect storms and the associated storm environment using a lightning mapping array (LMA), a mobile dual-polarization X-band radar, and balloon-based soundings that measured vertical profiles of temperature, humidity, wind, electric field, and hydrometeor types. LEE also observed abundant wind turbine-initiated lightning, which is climatologically more likely during the winter. The frequent occurrence of intense lake-effect storms and the proximity of a wind farm with nearly 300 turbines each more than 100 m tall to the lee of Lake Ontario provided an ideal laboratory for this study. The field project involved many undergraduate (>20) and graduate students. Some foreseen and unforeseen challenges included clearing the LMA solar panels of snow and continuous operation in low-sunlight conditions, large sonde balloons prematurely popping due to extremely cold conditions, sonde line breaking, recovering probes in deep snow in heavily forested areas, vehicles getting stuck in the snowpack, and an abnormally dry season for parts of the LEE domain. In spite of these difficulties, a dataset was collected in multiple lake-effect snowstorms (11 observation periods) and one extratropical cyclone snowstorm that clarifies the electrical structure of these systems. A key finding was the existence of a near-surface substantial positive charge layer (1 nC m⁻³) near the shoreline during lake-effect thunderstorms. 

Abstract The Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field project deployed two aircraft and ground-based assets in the vicinity of Houston, TX, between 27 May 2022 and 2 July 2022, examining how meteorological conditions, dynamics, and aerosols control the initiation, early growth stage, and evolution of coastal convective clouds. To ensure that airborne and ground-based assets were deployed appropriately, a Forecasting and Nowcasting Team was formed. Daily forecasts guided real-time decision making by assessing synoptic weather conditions, environmental aerosol, and a variety of atmospheric modeling data to assign a probability for meeting specific ESCAPE campaign objectives. During the research flights, a small team of forecasters provided “nowcasting” support by analyzing radar, satellite, and new model data in real time. The nowcasting team proved invaluable to the campaign operation, as sometimes changing environmental conditions affected, for example, the timing of convective initiation. In addition to the success of the forecasting and nowcasting teams, the ESCAPE campaign offered a unique “testbed” opportunity where in-person and virtual support both contributed to campaign objectives. The forecasting and nowcasting teams were each composed of new and experienced forecasters alike, where new forecasters were given invaluable experience that would otherwise be difficult to attain. Both teams received training on forecast models, map analysis, HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) modeling and thermodynamic sounding analysis before the beginning of the campaign. In this article, the ESCAPE forecasting and nowcasting teams reflects on these experiences, providing potentially useful advice for future field campaigns requiring forecasting and nowcasting support in a hybrid virtual/in-person framework. 

Abstract. There is a continuously increasing need for reliable feature detection and tracking tools based on objective analysis principles for use with meteorological data. Many tools have been developed over the previous 2 decades that attempt to address this need but most have limitations on the type of data they can be used with, feature computational and/or memory expenses that make them unwieldy with larger datasets, or require some form of data reduction prior to use that limits the tool's utility. The Tracking and Object-Based Analysis of Clouds (tobac) Python package is a modular, open-source tool that improves on the overall generality and utility of past tools. A number of scientific improvements (three spatial dimensions, splits and mergers of features, an internal spectral filtering tool) and procedural enhancements (increased computational efficiency, internal regridding of data, and treatments for periodic boundary conditions) have been included in tobac as a part of the tobac v1.5 update. These improvements have made tobac one of the most robust, powerful, and flexible identification and tracking tools in our field to date and expand its potential use in other fields. Future plans for tobac v2 are also discussed. 

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 MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis capabilities of GEMPAK (and similar software tools) into a modern computing paradigm. MetPy strives to employ best practices in its development, including software tests, continuous integration, and automated publishing of web-based documentation. As such, MetPy represents a sustainable, long-term project that fills a need for the meteorological community. MetPy’s development is substantially driven by its user community, both through feedback on a variety of open, public forums like Stack Overflow, and through code contributions facilitated by the GitHub collaborative software development platform. MetPy has recently seen the release of version 1.0, with robust functionality for analyzing and visualizing meteorological datasets. While previous versions of MetPy have already seen extensive use, the 1.0 release represents a significant milestone in terms of completeness and a commitment to long-term support for the programming interfaces. This article provides an overview of MetPy’s suite of capabilities, including its use of labeled arrays and physical unit information as its core data model, unit-aware calculations, cross sections, skew T and GEMPAK-like plotting, station model plots, and support for parsing a variety of meteorological data formats. The general road map for future planned development for MetPy is also discussed. 

Three-dimensional radio and optical mapping reveals that streamers of jets can extend from cloud top to the ionosphere. 

Abstract Previous studies of lightning detection by radar mostly consisted of observations with reflector‐antenna systems yielding slow volume scan times. Phased array radars offer much faster scan times that are likely to capture echoes from propagating lightning channels. Rapidly updated range‐height indicator scans were used to observe severe storms that occurred in central Oklahoma with the fully digital S‐band Horus PAR to examine echoes from lightning plasma. Numerous lightning echoes were observed during the sampling period in good spatial and temporal agreement with lightning mapping array detections of very high frequency radiation sources. Statistically, they result in increased horizontal reflectivity factor, deviations in radial velocity and spectrum width, highly variable differential reflectivity and differential phase, and decreases in correlation coefficient. Results presented also highlight the capability of phased array radars to better observe lightning compared to current radars, and aid in the study of storm electrification and lightning physics. 

Abstract Convective clouds play an important role in the Earth’s climate system and are a known source of extreme weather. Gaps in our understanding of convective vertical motions, microphysics, and precipitation across a full range of aerosol and meteorological regimes continue to limit our ability to predict the occurrence and intensity of these cloud systems. Towards improving predictability, the National Science Foundation (NSF) sponsored a large field experiment entitled “Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE).” ESCAPE took place between 30 May - 30 Sept. 2022 in the vicinity of Houston, TX because this area frequently experiences isolated deep convection that interacts with the region's mesoscale circulations and its range of aerosol conditions. ESCAPE focused on collecting observations of isolated deep convection through innovative sampling, and on developing novel analysis techniques. This included the deployment of two research aircraft, the National Research Council of Canada Convair-580 and the Stratton Park Engineering Company Learjet, which combined conducted 24 research flights from 30 May to 17 June. On the ground, three mobile X-band radars, and one mobile Doppler lidar truck equipped with soundings, were deployed from 30 May to 28 June. From 1 August to 30 Sept. 2022, a dual-polarization C-band radar was deployed and operated using a novel, multi-sensor agile adaptive sampling strategy to track the entire lifecycle of isolated convective clouds. Analysis of the ESCAPE observations has already yielded preliminary findings on how aerosols and environmental conditions impact the convective life cycle.