Radar variables are commonly used to identify deep convection in thunderstorms. Polarimetric radar provides additional signs of deep convection with columnar regions of increased differential reflectivity (Zdr) and specific differential phase (Kdp). However, the prevalence of polarimetric signals across all trackable storm objects observed by radar is not well understood and is necessary context for understanding the prevalence of polarimetric parameters in deep convection. In this study, we objectively track all thunderstorm objects observed by WSR-88D NEXRAD radar on eight storm days in the southeastern United States. The case days are selected from the Verification of the Origins of Rotation in Tornadoes Experiment-Southeast (VORTEX-SE) and Propagation, Evolution, and Rotation in Linear Storms (PERiLS) field campaigns and encompass a wide range of storm modes, including quasi-linear convective systems, a storm type for which its hazards are notoriously difficult to forecast. Storms are objectively identified and tracked using the open-source analysis tool Tracking and Object-Based Analysis of Clouds (tobac), and over 2800 tracked cells are identified over the eight case days. The tobac provides a feature mask at every time step of a tracked cell. Within each cell shape, we examine the prevalence of Zdr and Kdp columns above the melting level and lightning activity. We find that columns of Zdr are widely prevalent, even in thunderstorms without lightning or any other polarimetric column features, but still meeting the tracking threshold of 30 dBZ. However, intense Kdp columns are related to lightning production}columns with lightning are over 2 times stronger than those without lightning. The microphysical development in the storm leading to electrification and polarimetric column observations is also discussed. SIGNIFICANCE STATEMENT: The purpose of this study is to better understand how prevalent microphysical radar signatures are in the presence of lightning. This is important because thunderstorms electrify via collisions between ice and hydrometeors within the cloud. Cloud electrification is initiated within the mixed-phase region of thunderstorms, where populations of these particles are found in large quantities, and can be observed with polarimetric radar. Our results are a step toward understanding relationships between lightning and what we can observe with radar for all storm types.

The 15 January 2022 eruption of Hunga volcano (Kingdom of Tonga) produced the most lightning ever documented during an explosive eruption to date. This study estimates the mass of erupted tephra that may be structurally or electromagnetically affected by the lightning, based upon lightning peak current, channel length, and ash plume particle concentration. The lightning channels totaled 1.67 million m(3) in volume and contained 548 kg of volcanic ash at a calculated plume concentration of 0.328 g/m(3). From this total, 54.8 kg of ash may display physical evidence in the form of lightning-induced textures, such as lightning-induced volcanic spherules, but this is an insignificant fraction of the total airfall deposit (10(-8)%). However, the total mass of ash exposed to magnetic flux densities exceeding Earth's ambient surface values is 2.24 & times; 10(14) g, corresponding to just over a third (34.9%) of the calculated mass of total airfall (5.21 & times; 10(14) g). This study reveals that even though physical evidence of volcanic lightning may be limited, ash particles will still be affected by the electromagnetic fields generated by the lightning discharge. The extent of these effects will be a function of lightning properties, ash properties, and location of the ash in relation to the discharge channel.

This study examines 11 years of lightning-initiated wildfires (LIWs) that burned 10001 acres over the conterminous United States spanning 2010-20 to identify the associated rainfall and land surface characteristics. The U.S. Forest Service database is used to examine LIWs along with Multi-Radar Multi-Sensor 1-km resolution hourly rainfall, a NASA Land Information System observations-driven simulation on a 3-km grid for historical soil moisture, 4-km resolution satellite-derived green vegetation fraction, and 5-km resolution evaporative stress index (ESI) of live vegetation health to examine land surface conditions surrounding LIWs. The study objectives are to quantify antecedent land surface conditions, compare how conditions vary between wildfires reported the same day (immediate) versus smoldering LIWs reported one or more days after ignition (holdover wildfires), and determine rainfall and land surface characteristics that favor LIWs. Composite results indicate that a steady decline in antecedent soil moisture occurred for the 3 months leading up to LIWs, with similar but not as pronounced declines in evaporative demand given by ratios of evapotranspiration (ET) to potential ET (PET) and ET/PET anomalies (ESI). Rain rates were considerably lower at flash locations igniting wildfires compared to noninitiating flash locations (p 5 100%). Additionally, rainfall tended to be highly associated with holdover LIWs than in immediate LIWs. Antecedent soil moisture and ET/PET were incrementally higher preceding holdover wildfires. Shallow soil moisture was modestly drier (wetter) for lightning flashes igniting wildfires (holdover wildfires), deep soil moisture was slightly wetter in LIWs, but few statistically significant differences were found in the ET/PET and ESI results. SIGNIFICANCE STATEMENT: This study examines the importance of antecedent land surface properties in conjunction with rain rates associated with lightning-initiated wildfires in the United States. Steadily declining soil moisture and evaporative stress of live vegetation preceded lightning-initiated wildfires. Rain rates were the most important factors in determining whether lightning will ignite wildfires; however, drier surface soil moisture and slightly wetter deep soil moisture occurred at lightning flash locations that initiated wildfires. Rain rates and soil moisture were notably higher for holdover wildfires that were identified at least a day or more after lightning ignition, whereas vegetation was less stressed on average in holdover wildfires.

An internationally collaborative airborne campaign in July 2023-led by the University of Bergen (Norway) and NASA, with contributions from many other institutions-discovered that thunderstorms near Florida and Central America produce gamma rays far more frequently than previously thought. The campaign was called Airborne Lightning Observatory for Fly's Eye Geostationary Lightning Mapper (GLM) Simulator (FEGS) and Terrestrial Gamma-ray Flashes (TGFs), which shortens to ALOFT. The campaign employed a unique sampling strategy with NASA's high-altitude ER-2 aircraft, equipped with gamma-ray and lightning sensors, flying near ground-based lightning sensors. Real-time updates from instruments, downlinked to mission scientists on the ground, enabled immediate return to thunderstorm cells found to be producing gamma rays. This maximized the observations of radiation created by strong electric fields in clouds and showed how gamma-ray production may be physically linked to the thunderstorm life cycle. ALOFT also sampled storms entirely within the stereo-viewing region of the GLM instruments on GOES-16/GOES-18and performed multiple underflights of the International Space Station Lightning Imaging Sensor (ISS LIS), while using an upgraded FEGS instrument that demonstrated the operational value of observing multiple wavelengths (including ultraviolet) with future spaceborne lightning mappers. In addition, a robust complement of airborne active and passive microwave sensors-including X- and W-band Doppler radars, as well as radiometers spanning 10-684 GHz-sampled some of the most intense convection ever overflown by the ER-2. These observations will benefit planned convection-focused NASA spaceborne missions. ALOFT is an exemplar of a high-risk, high-reward field campaign that achieved results far beyond original expectations. SIGNIFICANCE STATEMENT: Though it has been known for years that thunderstorms sometimes produce gamma rays, the Airborne Lightning Observatory for Fly's Eye Geostationary Lightning Mapper (GLM) Simulator (FEGS) and Terrestrial Gamma-ray Flashes (TGFs) (ALOFT) campaign discovered that this high-energy radiation is ubiquitous and highly dynamic in tropical thunderstorms. As these thunderstorms intensify, strong electric fields generate gamma-ray glows, and within those glows, powerful TGFs often occur. When the storms weaken, the gamma-ray production weakens. This means gamma rays can be an indicator of thunderstorm evolution, like lightning flash rate. Thus, thunderstorm radiation is not just a boutique topic for lightning physicists, but also relevant to forecasters, storm scientists, and those impacted by aviation hazards. Moreover, ALOFT gathered important validation data for spaceborne lightning sensors and sampled some of the most intense convection ever overflown by NASA aircraft.

The Airborne Lighting Observatory for FEGS and TGFs (ALOFT) is equipped with a comprehensive set of instruments on-board a NASA ER-2 research aircraft for observing Terrestrial Gamma-ray Flashes (TGFs) and gamma-ray glows from thunderclouds. The ER-2 research aircraft flew at about 20 km altitude, above thunderstorms, from July 1st to July 30th, 2023, for a total flight time of about 60 hours. The onboard instrument suite comprised several X/gamma-ray detectors, which spanned a dynamic range of four orders of magnitude in flux and covered the entire energy spectrum associated with the gamma-ray transients. During the campaign, we observed over 130 short gamma-ray transients, along with hundreds of gamma-ray glows. Several of these detections consisted of thousands of photon counts, allowing precise and unprecedented spectral analyses. In this study, we present a comprehensive spectral analysis of various events using a forward modeling technique and Monte-Carlo simulations. This approach enables us to constrain the source characteristics of these events, including their source energy spectrum, production altitude and offset, spatial extension, and the brightness (fluence) of the source RREA electrons.

The ALOFT campaign targeted aircraft measurements of terrestrial gamma-ray flashes (TGFs) through NASA ER-2 overflights of strong thunderstorms. We report here the analysis of glow-terminating TGFs (GT-TGFs) that occur at the end of some gamma-ray glows. GT-TGFs were generated by most of the observed storms during the campaign and were prolifically generated by two specific storms that were particularly active in gamma ray production. One unique feature of GT-TGFs is that they always occur within several tens of microseconds of a narrow bipolar event (NBE). The characteristics of GT-TGFs and the associated NBE radio emissions will be described in detail.

During the Airborne Lightning Observatory for FEGS and TGFs (ALOFT) campaign in July 2023, the International Space Station (ISS), at an altitude of approximately 410 km, passed over the same region as covered by ALOFT within a short time period on the 24th of July. The ALOFT campaign, which carried gamma-ray detectors, photometers, and instruments for characterizing the electrical activity and the cloud environment, flew at an altitude of approximately 20 km and covered thunderstorms over the Gulf of Mexico and Caribbean during its 60 flight hours. The Atmosphere-Space Interactions Monitor (ASIM) is mounted on the ISS, with its Modular X- and Gamma-ray Sensor (MXGS) designed for observing TGFs. During the ISS overpass, ALOFT observed six TGFs within less than two minutes that were all within the field of view of the ASIM instrument. However, none of the TGFs were detected by ASIM. Here we present the six TGFs observed by ALOFT during the ISS overpass and discuss their source properties. The ASIM non-detection provides a strong upper limit on the TGF fluence.

The Airborne Lightning Observatory for FEGS and TGFs (ALOFT) was a field campaign targeted at Terrestrial Gamma-ray Flashes (TGFs) and gamma-ray glows from thunderclouds. The campaign was successfully carried out during July 2023, for a total of 60 flight hours in the Gulf of Mexico and the Caribbean. The scientific payload was flown on a NASA ER-2 research aircraft, capable to fly at 20 km altitude above thunderclouds. The payload included a suite of gamma-ray detectors spanning four orders of magnitude dynamic range in flux, and a complete suite of instruments for the characterisation of the electrical and optical activity, and the thundercloud environment. A key asset of the mission was the real-time downlink of gamma-ray count rates, which enabled the immediate identification of gamma-ray glowing regions. The pilot was then instructed to turn and pass over the same glowing region to explore its spatial extension and duration. ALOFT resulted in the detection of hundreds of gamma-ray glows, anticipating a revolution in our understanding of the phenomenon. Thunderclouds were observed to glow for hours and over several thousands of square kilometers, making glows a much more pervasive phenomenon than previously reported. Glows show significant time variability from seconds down to millisecond time scale, suggesting a relation to short transients such as TGFs more complex than previously thought. Glows are observed in association with the overpass of active convective cores, 20-25 km in size, yet their time variability and intensity modulation suggest a more complex spatial structure. These observations challenge the current view of glows as quasi-stationary phenomena related to relatively stable electrification conditions. The observed glows show highly dynamic temporal and spatial structures and are closely related to the development phases of active thunderclouds. These observations call for a rethinking of the assumptions at the basis of current modeling efforts.

Twenty-six years of lightning data were paired with over 68 000 lightning-initiated wildfire (LIW) reports to understand lightning flash characteristics responsible for ignition in between 1995 and 2020. Results indicate that 92% of LIW were started by negative cloud-to-ground (CG) lightning flashes and 57% were single stroke flashes. Moreover, 62% of LIW reports did not have a positive CG within 10 km of the start location, contrary to the science literature's suggestion that positive CG flashes are a dominant fire-starting mechanism. Nearly 1=3 of wildfire events were holdovers, meaning 1 or more days elapsed between lightning occurrence and fire report. However, fires that were reported less than a day after lightning occurrence statistically burned more acreage. Peak current was not found to be a statistically significant delineator between fire starters and non-fire starters for negative CGs but was for positive CGs. Results highlighted the need for reassessing the role of positive CG lightning and subsequently long-continuing current in wildfire ignition started by lightning. One potential outcome of this study's results is the development of real-time tools to identify ignition potential during lightning events to aid in fire mitigation efforts.

The 10-12 April 2019 thundersnow (i.e., lightning within snowfall) outbreak was examined via ground- and space-based lightning observations and was simulated using a numerical weather prediction model with an explicit electrification parameterization. When compared to observations, the simulation propagated the synoptic snowband two to six hours faster while also exaggerating the 3-D reflectivity structure. Throughout the event, the simulation produced 1,733 thundersnow flashes which was less than what was observed by ground- and space-based lightning sensors. In general, simulated thundersnow flashes were spatially offset from the largest reflectivities within the synoptic snowband and tended to occur within elevated convection that traversed isentropically along the top of mid-level frontogenesis. These simulated thundersnow flashes were associated with a tripole charge structure with ice/snow hydrometeors contributing most to the main negative charge region. Both simulated and observed thundersnow flashes initiated in conditionally unstable environments. Lastly, a conceptual model was developed to explain the spatial separation between the largest reflectivities in the snowband and the occurrence of thundersnow. It is hypothesized that the spatial offset of thundersnow initiation from the reflectivity cores within the synoptic snowband arose from a thermal circulation-induced by mid-level frontogenesis-that advects positively charged ice/snow hydrometeors toward the surface and creates a nearly homogeneous vertical charge structure. The 10-12 April 2019 thundersnow event was examined using lightning observations and a numerical simulation. Both observed and simulated thundersnow flashes occurred in slightly unstable environments in the presence of small ice pellets in elevated convection. The charge on the ice and snow hydrometeors slightly offset the charge on the small ice pellets in the cloud structure. Simulated thundersnow flashes also occurred away from the heaviest snowfall rates at the surface. This is a result of a vertical air circulation in the environment that transports positively charged ice/snow hydrometeors downward and prevents thundersnow from occurring in the heaviest surface snowfall rates. Model simulated lightning within snowfall (i.e., thundersnow) was compared to ground- and space-based lightning observations Thundersnow flashes were initiated in elevated convection that traversed isentropically and were spatially offset from the synoptic snowband A conceptual model was developed to explain why thundersnow was spatially offset from the largest reflectivity cores within the snowband

Measurable water quality parameters (e.g., potential of hydrogen, electrical conductivity) are crucial factors in determining the health and viability of coastal fisheries. In particular, shellfish farms (e.g., oysters) are susceptible to changes in water quality. Farmers are often faced with the choice of relying on publicly-available data or investing in expensive commercial monitoring buoys. By gaining accurate real-time localized knowledge of process conditions, effective control methods can then be implemented to maintain optimal process conditions for improved performance and support data-driven decision making. This project focuses on the integration and testing of modern Internet-of-Things (IoT) technologies, open-source software and instrumentation, and automated data collection. The produced water quality measurement (WQM) device consists of a cost-effective PVC frame to support an Arduino-based data collection system. The data collection system monitors and collects seven water quality metrics (i.e., dissolved oxygen, electrical conductivity, oxidation reduction potential, potential of hydrogen, total dissolved solids, temperature, and turbidity). An LTE connection is used to relay the collected metrics and buoy location. The MQTT protocol is used to transmit the data, and a PC receives and translates the data into human-readable graphs and measures. An open-source user interface, developed in Python, allows the user to view time series plots of the data, see a go/no-go status regarding pre-defined process control limits, and view the location of the buoy on a map. This work focuses on the physical construction and testing of the device components and systems to support preparation for future field deployment.

Abstract On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water‐rich plume at least 58 km high. Using a combination of satellite‐ and ground‐based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min−1) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co‐located with an internal gravity wave traveling >80 m s−1 in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high‐current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 109 kg s−1), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma‐water interaction at the submarine vent.

Two nor'easter events—sampled during the NASA Investigation of Microphysics and Precipitation for Atlantic Coast‐Threatening Snowstorms (IMPACTS) field campaign—were examined to characterize the microphysics in relation to the underlying electrification processes within wintertime stratiform regions. A theoretical model was developed to determine whether accretion or diffusion growth regimes were preferential during periods of greatest electrification. Model simulation with electrification parameterization was used to provide supplemental context to the physical processes of in‐cloud microphysics and electrification. The strongest electric fields (i.e., ∼80 V m −1 at 20 km) during the 2020 NASA IMPACTS deployment was associated with large non‐rimed ice crystals colliding with each other. During the 29–30 January 2022 science flight, the NASA P‐3 microphysical probe data demonstrated that non‐inductive charging was possible off the coastline of Cape Cod, Massachusetts. Later in the science flight, when the NASA P‐3 and ER‐2 were coordinating with each other, measured electric fields consistently were less than 8 V m −1 and electrification was subdued owing to reduced concentrations of graupel and large ice hydrometeors. Altogether, the in‐situ observations provide evidence for the non‐riming collisional charging mechanism and demonstrates that graupel and supercooled liquid water may not be necessary for weak electrification within wintertime stratiform regions. Model output from simulation of both events suggested that the main synoptic snowbands were associated with elevated hydrometeor snow charge density and electric fields.

This dataset contains lightning and volcanic plume data for the eruption of Hunga Volcano in Tonga from 13–15 January 2022. The dataset consists of two files. The first is a spreadsheet containing four tabs: (1) Ground-based flashes, which include lightning flashes from combined ground-based networks from 13–15 January 2022; (2) Ground-based rates, which include flash rates and pulse rates in one-minute bins from 13–15 January 2022 using the combined networks; (3) Optical GLM flashes & rates, which include GLM flashes and per-minute rates from 15 January 2022; and (4) Volcanic plume dimensions, which include maximum plume heights and umbrella radii through time on 15 January 2022. The second file is a Google Earth KMZ file of umbrella cloud areas outlined from stereoscopic cloud height retrievals from 04:17–07:07 UTC on 15 January 2022. Refer to journal article "Lightning rings and gravity waves: Insights into the giant eruption plume from Tonga’s Hunga Volcano on 15 January 2022" published in Geophysical Research Letters for further details about data processing.

Hail and damaging winds are two threats associated with intense and severe thunderstorms that traverse the Midwest and Great Plains during the primary growing season. In certain severe thunderstorm events, large swaths of agricultural crops are impacted, allowing the damage to be viewed from multiple satellite remote sensing platforms. Previ-ous studies have focused on analyzing individual hail and wind damage swaths (HWDSs) using satellite remote sensing, but these swaths have never been officially archived or documented. This lack of documentation has made it difficult to an-alyze the spatial extent and temporal frequency of HWDSs from year to year. This study utilizes daily true color imagery from MODIS aboard NASA's Terra and Aqua satellites and daily local storm reports from the Storm Prediction Center to build a database of HWDSs occurring in the months of May-August, for years 2000-20. This database identified 1646 HWDSs in 12 states throughout the Midwest and Great Plains, confirmed through a combination of archived severe weather warnings, radar information, and official storm reports. For each entry in the HWDS database, a geospatial outline is provided along with the most likely date of first visible damage from MODIS imagery as well as the physical characteris-tics and time of occurrence estimated from available warnings. This study also provides a summary of the radar characteris-tics for a portion of the database. This database will further the understanding of severe weather damage by hail and wind to agriculture to help understand the frequency of these events and assist in mapping the impacted areas.SIGNIFICANCE STATEMENT: Hail and wind damage swaths (HWDSs) frequently occur during the primary grow-ing season throughout the Midwest and Great Plains but are not yet officially documented or tracked like other severe weather impacts (e.g., tornadoes and derechos). This study describes the creation of a 21-yr HWDS event database us-ing archived daily storm reports and daily true color satellite imagery. Once the database was completed and underwent quality checks, the research team identified spatial and temporal trends from the confirmed swaths.

Underground stormwater infrastructure, such as culverts, present a significant maintenance challenge for municipal agencies due to aging, urbanization, and economic pressures. Decision support via machine learning regarding the most effective renewal, replacement, and maintenance, dependable condition prediction can alleviate this burden. In contrast to conventional mathematical models, machine learning-based models generally offer better performance when processing large datasets with missing or “noisy” data. A novel data-driven approach for predicting culvert conditions based on existing data inventory is proposed in this paper using an artificial neural network with a synthetic minority oversampling technique to address imbalanced datasets. Preliminary results show the viability of the proposed machine learning framework for use with this work’s application.

Abstract The Hunga Tonga–Hunga Ha'apai submarine volcano recently resumed activity. Violent eruptions on 14th and 15th January 2022 launched a tall ash plume that produced extremely high lightning rates. Here we report a terrestrial gamma‐ray flash (TGF) that was produced by the volcanic lightning and observed from space by the Fermi Gamma‐ray Burst Monitor (GBM). Observations by radio lightning networks and especially by the Geostationary Lightning Mapper show that the only lightning close enough to produce a TGF detectable by Fermi GBM was from the volcano's plume. With the observing duration of Fermi, observing a single TGF is consistent with the hypothesis that the volcanic lightning of this eruption produced TGFs at the average rate of thunderstorm lightning. The observation of a strong TGF from space also indicates that the electric field was oriented so as to accelerate electrons upward.

The catastrophic derecho that occurred on 10 August 2020 across the midwestern United States caused billions of dollars of damage to both urban and rural infrastructure as well as agricultural crops, most notably across the state of Iowa. This paper documents the complex evolution of the derecho through the use of low-Earth-orbit passive-microwave imager and GOES-16 satellite-derived products complemented by products derived from NEXRAD weather radar observations. Additional satellite sensors including optical imagers and synthetic aperture radar (SAR) were used to observe impacts to the power grid and agriculture in Iowa. SAR improved the identification and quantification of damaged corn and soybeans, as compared to true-color composites and normalized difference vegetation index (NDVI). A statistical approach to identify damaged corn and soybean crops from SAR was created with estimates of 1.97 million acres of damaged corn and 1.40 million acres of damaged soybeans in the state of Iowa. The damage estimates generated by this study were comparable to estimates produced by others after the derecho, including two commercial agricultural companies.

Relationships between lightning flashes and thunderstorm kinematics and microphysics are important for applications such as nowcasting of convective intensity. These relationships are influenced by cloud electrification structures and have been shown to vary in anomalously electrified thunderstorms. This study addresses transitional relationships between active charge structure and lightning flash location in the context of kinematic and microphysical updraft characteristics during the development of an anomalously electrified supercell thunderstorm in the Tennessee Valley on 10 April 2009. The initial charge structure within the updraft was characterized as an anomalous dipole in which positive charge was inferred in regions of precipitation ice (i.e., graupel and hail) and negative charge was inferred in regions of cloud ice (i.e., aggregates and ice crystals). During subsequent development of the anomalous charge structure, additional minor charge layers as well as evidence of increasing horizontal complexity were observed. Microphysical and kinematic characteristics of the charge structure also evolved to include increasing observations of negative charge in precipitation ice regions, indicating the emergence of more prominent normal charging alongside dominant anomalous charging. Simultaneously, lightning flash initiation locations were also increasingly observed in regions of faster updrafts and stronger horizontal gradients in updraft speed. It is suggested that continuous variability in charging behavior over mesogamma spatial scales influenced the evolution of lightning flash locations with respect to the updraft structure. Further work is necessary to determine how this variability may impact lightning flash relationships, including lightning flash rate, with bulk microphysical and kinematic characteristics and related applications.