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NASA NTRSDate not supplied

Monte Carlo Simulations for Evaluating the Accuracy of GLM Detection Efficiency and False Alarm Rate Retrievals

The performance of the Geostationary Lightning Mapper has been evaluated through comparison with other satellite lightning sensors and ground-based networks. However, because the performance of these reference sensors is both imperfect and imperfectly known, the true performance of GLM can only be estimated through such a process. In particular, GLM performance metrics such as detection efficiency (DE) and false alarm rate (FAR) retrieved through comparison with reference networks are affected by those networks’ own DE, FAR, and spatiotemporal accuracy, as well as the selected flash matching criteria. This study presents follow-on results from an ongoing analysis that uses a Monte Carlo simulation-based inversion technique to quantify the effect on retrieved GLM performance of a reasonable range of reference network DE, FAR, spatiotemporal accuracy, and the associated geographic patterns of each. These results help quantify and bound the actual performance of GLM and the attendant uncertainties when comparing GLM to imperfect reference networks.

Katrina Virts↗
NASA NTRSDate not supplied

Analyzing Optical Energy Behavior in Tropical Cyclones During Rapid Intensitication

Forecasting rapid intensification (RI) in tropical cyclones is an unpredictable task taken on by forecasters every year. Hurricane Laura made its way through the Gulf of Mexico in August 2020, undergoing RI on August 26, 2020 and strengthening from a category 1 hurricane to a category 4 hurricane in less than 18 hours. The goal of this project was to use data from the Geostationary Lightning Mapper (GLM) aboard the GOES-16 satellite to track lightning over the Western Hemisphere and investigate optical energy during this period of RI. Data was taken from the entire hurricane using a fixed area that captured Laura from 0000-2359 UTC on August 26 and using Python, the sum of the optical energy, average flash extent density (FED), and average flash area were investigated using time series plots to determine if there were any patterns before, during, and after RI. Variations at the beginning and end of RI point to a change in lightning behavior. Along with time series plots, investigating the distribution of values during RI may be a useful in determining if these parameters have any discernable pattern. Applying this methodology to a larger sample of tropical cyclones can provide a better understanding as to how these parameters vary during RI periods.

Kiahna Mollette↗
NASA NTRSDate not supplied

An Analysis of Depolarization Streaks for Anticipating Lightning in Thundersnow

Infrequent lightning events, particularly in stratiform precipitation, present a unique decision-support challenge to National Weather Service (NWS) forecasters and core partners. Anticipating thundersnow events, which are rare compared to warm season lightning, are especially difficult to anticipate due to slanted updrafts within the comma-head region of a mid-latitude cyclone. Researchers and operational forecasters have observed depolarization streaks in differential reflectivity (ZDR) as a result of ice crystal layers prior to thundersnow initiation. These depolarization streaks form as a result of ice crystals aligning themselves with enhancements in the electric field in stratiform precipitation and are associated with ZDR values near zero. During the 7 March 2018 winter storm, a teacher in New Jersey was struck by lightning while dismissing students and depolarization streaks were observed in weather radar observations. Therefore, it is advantageous to examine depolarization streaks in ZDR to determine whether it can be used to anticipate lightning potential in winter-time events. Multiple events will be analyzed using the National Lightning Detection Network (NLDN) and the Geostationary Lightning Mapper (GLM) to determine if thundersnow flashes coincide with ZDR depolarization streaks in weather radars. This study also expands on collaboration between the NWS Huntsville Forecast Office and NASA Short-term Prediction Research and Transition (SPoRT) program to determine how depolarization streaks can be used operationally to anticipate lightning within stratiform regions. Preliminary work has indicated noticeable potential in correlating depolarization streak as a precursor to thundersnow flashes in a variety of geographical regions.

Autumn Millard↗
NASA NTRSDate not supplied

Relating Lightning Flash Size and Energy to Tropical Cyclone Structure and Intensity Change

The number and location of lightning flashes within tropical cyclones (TCs) has proven to be a useful predictor of TC intensity change. Generally, a large number of lightning flashes located within the radius of maximum wind indicates a convective structure favorable for intensification. However, weakening TCs can also exhibit numerous lightning flashes, and rapid intensification can occur in the absence of inner-core lightning. It is thus difficult to interpret what the presence or absence of inner-core lightning might mean for a TC’s future evolution. The Geostationary Lightning Mapper (GLM) offers a new capability to observe not only the number and location of lightning flashes, but also the size and optical energy of those flashes. This presentation describes the application of these new metrics to further understand the relationship between lightning and TC structural and intensity evolution. Evidence is presented that flash size and optical energy reveal more about the convective and kinematic structures relevant to intensity change than an analysis of lightning flash count and location alone. We hypothesize that large, energetic lightning flashes are generated when the TC secondary circulation is strongest, an environment which favors increased generation of ice particles in the eyewall updraft and larger charge separation through outward advection of ice in the upper-level outflow. Conversely, smaller, lower-energy lightning flashes tend to occur in more localized turbulent updrafts, which can be forced by a variety of processes – some of which act to weaken the storm. These hypotheses are supported by numerical simulations of TC convection.

Patrick Duran↗
NASA NTRSDate not supplied

Analyzing the Tropical Cyclone Diurnal Cycle using GPM, TROPICS, and other Spaceborne Observations

Tropical cyclones (TCs) exhibit a distinct diurnal cycle of high clouds and rainfall, marked by an expansion of the TC cirrus canopy during the day and enhanced rainfall overnight. Recent modeling work also has uncovered a diurnal cycle of low-level radial and tangential winds in simulated storms, marked by an expansion of the surface wind field overnight and into the morning, along with increasing maximum wind speed in the eyewall. These results suggest that diurnal changes in radiative heating tendencies not only affect upper-level cirrus clouds and precipitating convection, but also the low-level circulation. This presentation will characterize expansions of the TC rain field using the Global Precipitation Measurement (GPM) Mission’s Integrated Multi-Satellite Retrievals for GPM (IMERG) half-hourly precipitation estimates. The Level 3 IMERG-Final rainfall data are azimuthally averaged about TC center positions in the Atlantic and Eastern Pacific basins, accounting for asymmetries due to vertical wind shear and storm motion. Preliminary results indicate that the TC rain field expands overnight and through the morning, reaching its maximum extent during the afternoon. This evolution is considerably asymmetric, however, with expansion favored downshear of the storm center. The results are broadly consistent with previous work that characterized the TC diurnal cycle using other observations and simulations. A similar analysis is performed using microphysical retrievals from the GPM Goddard Profiling algorithm and lightning data from the Geostationary Lightning Mapper to understand the relationship between the diurnal cycle, ice microphsyics, and lightning. Finally, with the ongoing Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission, we will discuss our plans to leverage TROPICS for enhanced observation of the TC diurnal cycle.

Patrick Duran↗
NASA NTRS2022

A Terrestrial Gamma-ray Flash from the 2022 Hunga Tonga–Hunga Ha’apai Volcanic Eruption

The Hunga Tonga–Hunga Ha’apai submarine volcano recently resumed activity. Violent eruptions on 2022 January 14th and 15th 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 (GLM) 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.

Terrestrial gamma-ray flashes↗
NASA NTRS2022

Chile Wildfires: Utilizing NASA and NOAA Earth Observations to Determine Lightning-ignited Wildfire Risks in Central Chile

In recent years, Central Chile has experienced wildfires of increasing frequency and intensity which threaten natural resources and communities. The Corporación Nacional Forestal (CONAF) responds to wildfires caused by a variety of ignitions, including lightning, but it is difficult to determine the prevalence of lightning-ignited wildfires based solely on ground observations. In collaboration with CONAF and the Embassy of Chile, Agricultural Office, the team used Earth observations to map coincidence of lightning strikes and wildfire ignitions. The Active Fire Product of Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS) identified wildfires as thermal anomalies, which the team compared to the lightning events detected by NOAA’s GOES-16 Geostationary Lightning Mapper (GLM). Next, the team mapped lightning strike frequency and lightning related wildfires across the study area. Finally, the team calculated and mapped a relative estimate of lightning-ignited wildfire vulnerability across the year, fire season (December – March), and off-season (April – November) by summing the following factors: lightning frequency, the Normalized Difference Moisture Index (NDMI) and land surface temperature (LST). These risks were then weighted by fuel availability. Preliminary analysis of the lightning fire relationship showed a spatiotemporal coincidence, primarily in the South-central region of study, near Temuco, and isolated areas on the Andean front. The team identified areas at risk of lightning-induced wildfires, predominantly in the northern third of the study area and along the Andean front. Adjusting the relative weight of risk factors and improving the lightning and fire coincidence map by clustering VIIRS thermal anomalies into fire events could reduce discrepancies and improve risk assessments for future work.

Christopher Matechik↗
NASA NTRSDate not supplied

Relating Lightning Activity to the Convective Evolution of Pre-Genesis Tropical Disturbances

Lightning and environmental characteristics are analyzed for National Hurricane Center (NHC) invest disturbances. For 2019-2021, Atlantic NHC invest tracks are grouped into disturbances that eventually developed into tropical cyclones (TCs) and ones that did not. Data from the NASA/NOAA Geostationary Lightning Mapper (GLM) is used to quantify potential differences in total optical energy, flash extent density, and flash area between the groups. To provide environmental context to the lightning results, vertical profiles from the NOAA Unique Combined Atmospheric Processing System (NUCAPS) dataset will be investigated. Specifically, the profiles will provide insight into the temperature and moisture structure of the invests. In addition to the composite analysis, interesting cases of tropical cyclogenesis will be examined in further detail. Overall, this work seeks to further our understanding of lightning properties and convective environments in tropical cyclogenesis.

Justin W Whitaker↗
NASA NTRSDate not supplied

Bayesian Analysis of the Detection Performance of the Lightning Imaging Sensors

Identical Lightning Imaging Sensors aboard the Tropical Rainfall Measuring Mission satellite (TRMM LIS, 1998-2015) and International Space Station (ISS LIS, 2017-present) have collectively provided over two decades of lightning observations over the global tropics, with ISS LIS extending coverage into the mid-latitudes. Quantifying the detection performance of both LIS sensors is a necessary step toward generating a LIS climatological record and accurately combining LIS data with lightning detections from other sensors and networks. We compare lightning observations from both LIS sensors with reference sources including the Geostationary Lightning Mapper (GLM) and ground-based networks operated by Earth Networks (the Earth Networks Total Lightning Network [ENTLN] and Earth Networks Global Lightning Network [ENGLN]) and Vaisala (the National Lightning Detection Network [NLDN] and Global Lightning Dataset [GLD360]). Instead of a relative detection efficiency (RDE) approach that involves assuming perfect performance of the reference sensor, we employ a Bayesian approach to estimate the upper limit of the absolute detection efficiency (ADE) of each sensor being analyzed. The results of this Bayesian analysis illustrate the geographical pattern of ADE as well as its diurnal cycle and yearly evolution, reflecting the growth of the reference networks over time.

Katrina Virts↗
NASA NTRSDate not supplied

Operational Evaluation of NASA SPoRT Lightning Safety Applications for Impact Based Decision Support Services

The NWS Office in Huntsville is tasked with monitoring and predicting the threat for lightning within its County Warning Area. These impact-based decision support services (IDSS) are provided routinely for aviation operations, irregularly for large-scale, outdoor events, and can have varying safety requirements, such as proximity to location and duration. Lightning monitoring and prediction can require the rapid synthesis of a plethora of data, so products that make this process more efficient and effective are sought by the operational community. The Huntsville NWS Office benefits from close collaboration with the NASA SPoRT Center, which is developing several products to address these operational challenges in concentrated R2O/O2R efforts. One example of this is the StopLight product, which uses Geostationary Lightning Mapper (GLM) flash extent density (FED) to provide an easy-to-interpret visual aid of lightning occurring within the last 30 minutes. The StopLight product shows both the age and location of the last lightning flash within each GLM pixel, which can be particularly useful for IDSS with determining when to resume activities or operations that have been shut down due to lightning. This presentation highlights results of collaboration between NASA SPoRT and NWS Huntsville, including testing of the Stoplight product, and additional experimental products in development. A brief summary of the lightning products are provided while the main focus will discuss product evaluation and forecaster perspective during real-time weather watch activities to support aviation operations and events where IDSS was necessary.

Kristopher White↗
NASA NTRSDate not supplied

The Convective Nature of the Tropical Cyclone Lifecycle via GLM and GPM Observations

This study examines the convective nature of the tropical cyclone (TC) lifecycle from tropical storm through extratropical transition. We analyze lightning observations collected from the Geostationary Lightning Mapper (GLM) on the GOES-16 satellite in combination with coincident passive microwave and Ku-band radar observations collected from Global Precipitation Measurement (GPM) mission satellites. A unique aspect of this study, which spans the Atlantic basin hurricane seasons 2018-2020, is that it provides the first known total lightning observations in TCs throughout their extratropical (ET) transition. Analysis of Tropical Storm (TS), Category 1-2 hurricanes (CAT12), Category 3-5 hurricanes (CAT35), and ET time periods, which are grouped by storm-motion and shear-relative characteristics, show that lightning maxima generally occur regimes of down-motion (up-shear), consistent (inconsistent) with previous studies. Further analysis also breaks down time periods by geographic location (e.g., land, coast, ocean) and shear strength; shifting lightning patterns are observed with increasing shear. The lightning maxima are also generally collocated with minima in 37-GHz brightness temperature observations, which is indicative of precipitation-sized ice. DPR Ku-band reflectivity profiles from the GPM Precipitation Feature (PF) database exhibit distinct differences in depth and intensity for electrically active PFs vs those that are not. On average, PFs defined by a rain rate threshold are larger for hurricane strength ITPs (CAT12, CAT35) as compared to either TS or ET ITPs. This indicates that during the hurricane strength ITPs, PFs may be capturing the entire, symmetric rain shield.

hurricane↗
NASA NTRSDate not supplied

Lightning Flash Behavior and Convective Characteristics in Hurricanes Florence (2018), Dorian (2019), and Laura (2020)

Lightning is a useful tool in forecasting and understanding the behavior of tropical cyclones (TCs). Flash extent density (FED) has been found to be indicative of strength and intensification in TCs, but optical energy is a newer parameter that has not been studied intensively. This presentation analyzes the relationship between convective characteristics, such as updraft speed and updraft size, and Geostationary Lightning Mapper (GLM) optical energy, flash area, and FED in Hurricanes Florence (2018) and Laura (2020). The maximum optical energy values were analyzed for each minute from the innermost 100 kilometers of the eye to determine if there was a relationship between optical energy, flash area, updraft behavior, and intensification. Microwave imagery and tail-doppler radar (TDR) were examined during rapid increases in flash energy to connect updraft size and strength to these spikes. Early results show an increase in size of a moderate updraft occurring just prior to an increase in lightning optical energy and TC intensity, while smaller updrafts coincide with a decrease in intensity or little to no change in intensity. Continuing work aims to investigate the role of moderate updraft size in lightning behavior and TC intensity.

Kiahna Mollette↗
NASA NTRSDate not supplied

Predicting Lightning Initiation using Deep Learning

Lightning occurrence presents safety challenges to people and property. The main challenge with lightning safety is that the majority of guidance is reactive. In other words, lightning has to have already occurred nearby before a person will respond and take shelter. Further, most injuries or fatalities occur as the storm approaches, or as it's moving away, when rainfall may not be present at the time of the flash. Thus, this project develops a physically-based deep learning model to produce lightning probabilities out to 15 minutes. The deep learning model combines a Convolutional Neural Network (CNN) with a Long Short-Term Memory (LSTM) network to capture both the spatial and temporal evolution of storms to predict the probability that lightning initiation will occur in the next 15 minutes. The model combines radar reflectivity, correlation coefficient and differential reflectivity to inferred storm hydrometer type and precipitation phase, which aids in the identification of electrification processes. The model is trained with data from the Geostationary Lightning Mapper (GLM), which is a near infrared sensor onboard the GOES-R series of satellites that measures optical brightness from lightning. This presentation will provide an overview of the project.

Andrew T White↗
NASA NTRSDate not supplied

End-user Assessment of the NASA SPoRT GLM Stoplight Product

National Weather Service (NWS) offices monitor and forecast the threat for lightning within their County Warning Areas for various impact-based decision support services (IDSS). These forecasts are provided routinely for aviation operations, but irregularly for large-scale, outdoor events, which typically have varying safety requirements with regards to lightning. Lightning monitoring and forecasting can require synthesizing a plethora of data, so products that make this process more efficient and effective are sought by the operational community. The NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop several products to address these operational challenges during the lifecycle of lightning activity, and conduct evaluations in concentrated (Research-to-Operations/Operations-to-Research) efforts. The product evaluated for this study is the Geostationary Lightning Mapper (GLM) Stoplight product, which addresses lightning safety specifically with regards to lightning recency and cessation. The GLM Stoplight product displays the spatial extent of lightning and uses color-coded pixels to show the recency of lightning in 10-minute increments. This presentation highlights results from an assessment of the GLM Stoplight product by select NWS offices, as well as emergency managers, that took place over a 5-week period from May 1st to June 2nd. Feedback was collected on the GLM Stoplight product and on a new and interactive lightning viewer, which allowed participants to tailor visualization of the product based on their location and desired application. Results will help NASA SPoRT gain a better understanding of how forecasters and emergency managers use lightning data for safety applications. In addition, the assessment will inform research on any necessary modifications to this and future lightning products to assist end users.

Kelley Murphy↗
NASA NTRSDate not supplied

GOES-16 GLM Observations for National Climate Assessments

The heating of air by a lightning discharge, followed by rapid cooling, leads to the production of lightning nitrogen oxides (“LNO x ” for brevity, where NO x = NO + NO 2 ). The LNO x are important trace gases because they control the concentration of the greenhouse gas ozone (O 3 ) and the highly reactive hydroxyl radicals (OH). In fact, LNO x are the most important source of NO x in the upper troposphere at tropical and subtropical latitudes, and climate is most sensitive to O 3 in the upper troposphere. Since lightning indirectly influences the Earth's climate, it is a key variable to monitor in National Climate Assessment (NCA) studies. In this work, GOES-16 Geostationary Lightning Mapper (GLM) flash counts and flash optical properties (i.e., optical energy, optical area, …) that are linked to LNO x production are examined in detail for the continental United States analysis region, and are compared with ground-based National Lightning Detection Network (NLDN) observations.

Lightning↗
NASA NTRSDate not supplied

Analysis of Ground-Based Observations of TLES From Spritacular Project Database

Spritacular is a citizen science project that was launched in October of 2022. It provides a space for anyone to submit their transient luminous event (TLE) images along with observational information, i.e. time, geographic location, direction, camera setup. Along with submissions, one can also help identify different types of TLEs in the images submitted. Since its inception hundreds of images have been submitted to the project database by its users. Not only does the database itself provide a record of observations, but these submissions allow for scientists with access to a wider array of observational platforms to obtain a better understanding of TLE’s without having to chase or hunt for them. Citizen science databases come with pros and cons when dealing with observational science and trying to work across different platforms. Using this database, over one hundred sprites were found to have accurate pointing and adequate temporal resolution to attempt to match both ground based (National Lightning Detection Network [NLDN]) and satellite based (Geostationary Lightning Mapper [GLM]) sensors. A statistical analysis of these TLE properties as well as a discussion about the implications these measurements have on the hunt for TLEs both in current space based observational platforms such as the Atmosphere-Space Interaction Monitor (ASIM), International Space Station Lightning Imaging Sensor (ISS-LIS), and GLM or legacy satellite instruments such as the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite will be presented.

T. Daniel Walker↗
NASA NTRSDate not supplied

Evaluation of Present and Future Spaceborne Lightning Observations During the ALOFT Campaign

The ALOFT1 campaign took place during July 2023. The NASA ER-2 high-altitude aircraft was based in Tampa, Florida, and flew approximately 60 hours sampling tropical and sub-tropical thunderstorms that were mostly contained within the common fields of view of GLM4-16 and GLM-18. In addition, multiple underflights of the ISS LIS5 instrument occurred. The FEGS2 and LIP6 instrument suite on the ER-2 provided a combination of multispectral optical, slow and fast electric field change, and three-dimensional electric field measurements of lightning and thunderstorms. Notably, in addition to the 777-nm band used by GLM and LIS, FEGS also observed at 337 nm, 500 nm, 868 nm, wideband visible-to-infrared, and shortwave infrared. A spectrometer that spanned most major lightning bands from the ultraviolet to infrared was included. Observations of gamma-ray production by thunderstorms were also collected during ALOFT. Thus, the lightning-observing suite on the ER-2 during ALOFT provides an unprecedented suborbital dataset for direct optical-to-optical and indirect radio-to-optical validation of existing spaceborne lightning sensors like GLM and LIS. In addition, the multispectral observations from FEGS enables evaluation of current and future spaceborne lightning-observing concepts. For example, the 337-nm channel is relevant to both existing missions like ASIM7 as well as future concepts like the CubeSpark mission currently being formulated by NASA. Complementary to LIS, the ISS also carries the STP-H88 payload, which features microwave radiometers covering 18-182 GHz, while the ER-2 carried radiometers covering 10-684 GHz, enabling evaluation of spaceborne passive microwave measurements that are complementary to the lightning observations. 1. Airborne Lightning Observatory for FEGS2 and TGFs3 2. Fly’s Eye GLM4 Simulator 3. Terrestrial Gamma-ray Flashes 4. Geostationary Lightning Mapper 5. International Space Station Lightning Imaging Sensor 6. Lightning Instrument Package 7. Atmosphere-Space Interactions Monitor 8. 8th Space Test Program – Houston mission

Timothy Lang↗
NASA NTRSDate not supplied

Maintaining the Continuity of the Global Climate Data Record of Lightning from Space

Lightning is a natural hazard, an indicator of changes in convective storm behavior across multiple spatial and temporal scales, and a major influence on climate-affecting chemicals such as ozone and methane. Lightning also has substantial impacts on the near-space environment. As such, the World Meteorological Organization (WMO) has designated lightning as an Essential Climate Variable (ECV); that is, a measurement that is really important for understanding Earth’s climate. Spaceborne lightning observations are the gold standard for measuring global lightning, as the detection efficiency is more spatially uniform compared to ground-based lightning measurements. In addition, spaceborne is the only practical method for measuring total lightning (i.e., both intracloud and cloud-to-ground) at the global scale, as ground-based networks have limited ability to detect intracloud lightning at long distances (e.g., over oceans, far from land-based sensors). Since 1995, with only a two-year gap (2015-2017), lightning has been observed globally using a combination of Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) instruments. However, the year 2023 is the planned end for the International Space Station (ISS) LIS mission, and there is no designated low-Earth orbit (LEO) successor yet identified. Since 2017, geostationary (GEO) observations of lightning have become increasingly available. These include the U.S. Geostationary Lightning Mappers (GLMs), China’s Lightning Mapping Imager (LMI), and Europe’s Lightning Imager (LI). While GEO provides continuous, quasi-hemispheric coverage of lightning and thunderstorms, there are current gaps preventing global coverage, particularly in portions of Asia and the western Pacific, as well as high-latitude regions. Moreover, integration of the GEO constellation into a Climate Data Record (CDR) of lightning is a major challenge only recently begun to be addressed by the WMO. Furthermore, recent work has demonstrated some deficiencies in the global record of lightning from space. For example, small lightning flashes are very common in severe weather, but are difficult to observe using the present set of spaceborne lightning imagers. Moreover, some types of lightning are best observed using frequencies other than the commonly used near-infrared (777-nm), including ultraviolet and the radio spectrum. Finally, it is not possible to assess the vertical distribution of lightning globally, even though this measurement is highly relevant to thunderstorm behavior as well as lightning’s effects on greenhouse gases and the near-space environment. This presentation will provide a current assessment of lightning measurements from space, will identify significant current and future gaps in these observations, and will evaluate potential solutions for improving the overall CDR of global lightning.

Timothy Lang↗