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At least 253 records · Page 14
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NASA NTRS2017

An Overview of the Design and Development of the GOES R-Series Space Segment

The first of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite R-series (GOES-R) satellites was launched in November 2016. GOES-R has been developed by NOAA in partnership with the National Aeronautics and Space Administration (NASA). The satellite represents a quantum leap in the state of the art for geostationary weather satellites by providing data from a suite of six new instruments. All instruments were developed expressly for this mission, and include two Earth-observing instruments (the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM)), two solar-viewing instruments (Solar Ultraviolet Imager (SUVI) and Extreme ultraviolet and X-ray Irradiance Sensors (EXIS)) and two in situ instruments (Space Environment In-Situ Suite (SEISS) and a magnetometer pair). In addition to hosting the instruments, GOES-R also accommodates several communication packages designed to collect and relay data for weather forecasting and emergency management. Accommodating the six instruments and four communication payloads imposed challenging and competing constraints on the satellite, including requirements for extremely stable earth and solar pointing, high-speed and nearly error-free instrument data transmission, and a very quiet electromagnetic background. To meet mission needs, GOES-R employed several technological innovations, including low-thrust rocket engines that allow instrument observations to continue during maneuvers, and the first civilian use of Global Positioning System-based orbit determination in geostationary orbit. This paper will provide a brief overview of the GOES-R satellite and its instruments as well as the developmental challenges involved in accommodating the instruments and communications payloads.

GOES-16↗
NASA NTRS2018

The Deep Space Gateway Lightning Mapper (DLM) - Monitoring Global Change and Thunderstorm Processes Through Observations of Earth's High-Latitude Lightning from Cis-Lunar Orbit

Function: Monitor global change and thunderstorm processes through observations of Earth's high-latitude lightning. This instrument will combine long-lived sampling of individual thunderstorms with long-term observations of lightning at high latitudes: How is global change affecting thunderstorm patterns; How do high-latitude thunderstorms differ from low-latitude? Why is the Gateway the optimal facility for this instrument / research: Expected DSG (Deep Space Gateway) orbits will provide nearly continuous viewing of the Earth's high latitudes (50 degrees latitude and poleward); These regions are not well covered by existing lightning mappers (e.g., Lightning Imaging Sensor / LIS, or Geostationary Lightning Mapper / GLM); Polar, Molniya, Tundra, etc. Earth orbits have significant drawbacks related to continuous coverage and/or stable FOVs (Fields of View).

Climate↗
NASA NTRS2018

Lightning Imaging Sensor on the International Space Station: Assessments and Results from First Year Operations

Over two decades, the NASA Marshall Space Flight Center, the University of Alabama in Huntsville, and their partners have demonstrated the effectiveness and value of space-based lightning observations as a remote sensing tool for Earth science research and applications, and, in the process, established a robust global lightning climatology. The Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) provided global observations of tropical lightning for an impressive 17 years before that mission came to a close in April 2015. Now a space-qualified LIS, built as the flight spare for TRMM, has been installed on the International Space Station (ISS) for a minimum two year mission following its SpaceX launch on February 19, 2017. The LIS, flown as a hosted payload on the Department of Defense Space Test Program-Houston 5 (STP-H5) mission, was delivered to the ISS in the Dragon trunk and robotically installed in an Earth-viewing position on the outside of the ISS. Following successful activation and checkout, LIS has continuously observed the amount, rate, and radiant energy lightning within its field-of-view as it orbits the Earth. Placing LIS on the Space Station provides a great opportunity to not only extend the 17-year TRMM LIS record of tropical lightning measurements but also to expand that coverage to higher latitudes missed by the previous mission. Furthermore, this mission continues the important science focus to better understand the processes which cause lightning, as well as the connections between lightning and subsequent severe weather events. This understanding is a key to improving weather predictions and saving lives and property here in the United States and around the world. The LIS measurements, along with observations from the new Geostationary Lightning Mapper (GLM) operating on NOAA's newest weather satellites, the Geosynchronous Operational Environmental Satellite-16/17 (GOES-16/17), are being used to cross-validate both systems. An especially unique contribution from the ISS platform is the production of real-time lightning data, especially valuable for operational forecasting and warning applications over data sparse regions such as the oceans. Finally, LIS provides simultaneous and complementary observations with other ISS payloads such as the European Space Agency's Atmosphere-Space Interaction Monitor (ASIM) that is exploring the connection between thunderstorms and lightning with terrestrial gamma-ray flashes (TGFs). Leveraging TRMM's well-established processing and data handling assures that LIS data can be quickly delivered to users.

space-based lightning↗
NASA NTRS2018

Early Results from the RELAMPAGO Lightning Mapping Array

RELAMPAGO (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations) is a National Science Foundation (NSF) field campaign to understand intense and severe convection in central Argentina, near the Sierras de Cordoba mountain range. In order to address RELAMPAGO science goals, as well as to assist with ground validation of the Geostationary Lightning Mapper (GLM) instrument on the GOES-16/17 satellites, NASA Marshall Space Flight Center (MSFC) has installed an 11-station Lightning Mapping Array (LMA) in this region. The LMA supported the Enhanced Observing Period (EOP) of RELAMPAGO, and then is continuing operations until mid-to-late April 2019.

Lang, Timothy↗
NASA NTRS2019

Assessing Reliability of NDE Flaw Detection Using Smaller Number of Demonstration Data Points

The paper provides an engineering analysis approach for assessing reliability of NDE flaw detection using smaller number of demonstration data points. It explores dependence of probability of detection (POD), probability of false positive (POF), on contrast-to-noise ratio, and net decision threshold-to-noise ratio in a simulated data; and draws some generically applicable inferences to devise the approach. ASTM nondestructive evaluation standards provide requirements on signal-to-noise ratio and/or contrast-to-noise ratio in order to provide reliable flaw detection and limit false positive calls. POD analysis of inspection test data results in an estimated flaw size, denoted by 𝑎90/95. This flaw size has 90% POD and minimum 95% confidence. POF is also estimated in the analysis. POD demonstration requires specimens with flaws of known size. In many situations, it is very expensive to produce the large number of flaws required for the POD analysis. In some situations, only real flaws can truly represent the flaws for demonstration. Real flaws of correct size and location in part configuration specimen may be difficult to produce, if not impossible. Here, an engineering analysis approach is devised using simulation to assess reliability of NDE technique when a limited number of flaws are available for demonstration. In this simulation, a technique is considered reliable, if it provides flaw detectability size equal to or better than the theoretical 𝑎90𝑡ℎ used in simulation and also provides a POF less than or equal to a chosen value. The paper uses simulated signal response versus flaw size data to devise the approach. Linear correlation is used between the signal response data and flaw size. POD software mh1823 uses generalized linear model (GLM) in POD analysis after transforming the flaw size and signal response, if needed, using logarithm. Therefore, this approach is in agreement with the linear signal correlation used in mh1823. Using the POD analysis of data, generic conditions on contrast-to-noise ratio and net decision threshold-to-noise ratio are derived for reliable flaw detection. In order to assess technique reliability using the engineering approach, signal response-to-flaw size correlation about the flaw size of concern is needed. In addition, measurement of noise is also needed. If the technique meets the above requirements, assumption of linear signal-to-flaw size correlation and conditions on noise, then the technique can be assessed using this analysis as it fits the underlying POD model used here. The approach is conservative and is designed to provide a larger flaw size compared to the POD approach. Such NDE technique assessment approach, although, not as rigorous as POD, can be cost effective if the larger flaw size can be tolerated. Typically, this is a situation for all quality control NDE inspections. Here, an NDE technique needs to be reliable and 𝑎90/95 is not estimated, but the assessed flaw size is assumed to be larger than the unknown a90 due to conservative factors or margins. Applicability of the approach for assessing reliability of flaw detection in x-ray radiography and 2D imaging in general is also explored.

Koshti, Ajay M.↗
NASA NTRS2019

The WRF Lightning Forecasting Algorithm: Sensitivities to Microphysics and Boundary Layer Physics Schemes

As with WRF model simulated convection in general, LFA output is sensitive to cloud and PBL physics. WRF convection is also sensitive to model initialization uncertainties and unresolved errors.  Large sensitivity exists in HRRR-like Thompson microphysics and PBL, for which original LFA calibration constant needs to be multiplied by 1.13 to give proper FRD amplitudes. Thompson microphysics scheme also shows poorest correlations relative to reference data, suggesting low predictability of HRRR LFA output. Need to validate HRRR LFA against GLM observations.

weather prediction↗
NASA NTRSDate not supplied

TPSAS-NF1676L-32581-DND

The GOES-R series satellites are collecting observations of severe storms at unprecedented detail. Nearly every day, GOES-16/17 collects ABI visible and infrared (IR) imagery of storms at 1-minute or better resolution. When paired with GLM data, these ABI “Mesoscale Domain Sector” (MDS) observations allow us to infer processes that are occurring within storm updrafts and cloud tops via wind flows, temperature, visible texture, and lightning-generated radiances that can be detected using automated algorithms. Prior to the GOES-R series, GOES-8 to -15 observations were relatively coarse which limited their utility in severe storm forecasting after a storm became mature. GOES-R MDS data provides a new opportunity to determine how satellite-derived products could contribute to our understanding and detection of severe storms. This poster highlights recent research on severe storms supported by the NASA Weather and Atmospheric Dynamics Focus Area.

Kristopher Bedka↗
NASA NTRS2020

SEASONAL VARIATION IN THE MEASUREMENT OF GOES-16 ABI CHANNEL-TO-CHANNEL REGISTRATION

An Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) was developed to assess the US Geostationary Operational Environmental Satellite R-series (GOES-R) Advanced Baseline Imager (ABI) and Geostationary Lighting Mapper (GLM) INR performance.Channel-to-channel registration (CCR) is one of the five INR performance metricsproduced by IPATS. A seasonal variationis observed in the CCR assessment in north-south direction when one or both channels are reflective. However, indirect CCR, calculated as the difference of NAV measurements between two channels, does not presentthe similar seasonal variation. The phenomenon of the seasonal variationcoincides with the annual change of the subsolar point location. The amplitude of the seasonal variation is related tothe length and the direction of the shadow. DirectCCR, measured by IPATSdirectly,performs better than indirect CCR when both channels are visible wavelengthsor emissivechannels. For all other channel paircombinations, the assessment of indirect CCR is more accurate.

Bin Tan↗
NASA NTRSDate not supplied

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗
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 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

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

Advances in Entry Modeling for Impact Risk Assessment

A summary of recent advancements in the detailed modeling of asteroid atmospheric entry processes made through NASA’s Asteroid Threat Assessment Project (ATAP) is presented. Understanding, and accurately modeling these processes and their associated uncertainties is critical to predicting all downstream impact effects, such as blast wave and thermal damage footprints. Furthermore, there is (perhaps thankfully) a dearth of empirical data for large impactors of the kind that would pose a threat to human populations, on which to anchor and/or validate models used in risk assessments. Therefore, we must rely heavily on detailed theoretical and numerical modeling to develop robust assessments for decision makers. To that end, ATAP has made some significant progress in advancing the capabilities in this area. Two areas in particular are highlighted in the present work: meteoroid ablation mechanisms, and bolide luminosity. The first research area – meteoroid ablation mechanisms – has focused on performing novel high-enthalpy wind tunnel experiments on meteorites and meteorite analogs, and utilizing the resulting data to develop high-fidelity models for impactor mass loss at scale. These efforts have resulted in several insights. Of note, these data suggest a differential vaporization process where volatiles are liberated preferentially when the asteroidal material is subject to high heat, while refractory components remain in the molten layer on the surface. A numerical model has been developed which considers this phenomena, and its effect on the bulk impactors effective heat of ablation is examined. The second research thrust that is discussed is focused on accurate modeling of impactor radiation phenomena. While another submission to the conference will discuss the application of our approach to thermal ground damage modeling, here, we present an overview of our extensive efforts to utilize available ground- and space-based observations of large bolides (~1m diameter, and above) to inform and validate our detailed modeling approaches. These methods have been shown to accurately reconstruct the detailed spectra for the Benesov bolide, as well as approximate the burn footprint for the Tunguska event. Recent effort has focused on reconciling light curve data from multiple sources (all-sky camera networks, GLM, US government sensors), using our validated model, and providing a calibrated model for luminous efficiency which can then be utilized to infer impactor properties such as shape, mass, and composition. This work will be demonstrated through an exemplar case study focusing on a large bolide event with observational data (e.g. Chelyabinsk, Flensburg, etc.). Finally, our team’s assessment on the current maturity of atmospheric entry models, and priorities for future research will be provided.

ATAP↗