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NASA NTRS2008

Large-Scale Structure of the Molecular Gas in Taurus Revealed by High Spatial Dynamic Range Spectral Line Mapping

Viewgraph topics include: optical image of Taurus; dust extinction in IR has provided a new tool for probing cloud morphology; observations of the gas can contribute critical information on gas temperature, gas column density and distribution, mass, and kinematics; the Taurus molecular cloud complex; average spectra in each mask region; mas 2 data; dealing with mask 1 data; behavior of mask 1 pixels; distribution of CO column densities; conversion to H2 column density; variable CO/H2 ratio with values much less than 10(exp -4) at low N indicated by UV results; histogram of N(H2) distribution; H2 column density distribution in Taurus; cumulative distribution of mass and area; lower CO fractional abundance in mask 0 and 1 regions greatly increases mass determined in the analysis; masses determined with variable X(CO) and including diffuse regions agrees well with the found from L(CO); distribution of young stars as a function of molecular column density; star formation efficiency; star formation rate and gas depletion; and enlarged images of some of the regions with numerous young stars. Additional slides examine the origin of the Taurus molecular cloud, evolution from HI gas, kinematics as a clue to its origin, and its relationship to star formation.

molecular clouds↗

NASA NTRS2011

Marker-Based Hierarchical Segmentation and Classification Approach for Hyperspectral Imagery

The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. First, pixelwise classification is performed and the most reliably classified pixels are selected as markers, with the corresponding class labels. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. The experimental results show that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for hyperspectral image analysis.

Tarabalka, Yuliya↗

NASA NTRS2010

Modulation of Atlantic Aerosols by the Madden-Julian Oscillation

Much like the better-known EI Nino-Southern Oscillation, the Madden-Julian Oscillation (MJO) is a global-scale atmospheric phenomenon. The MJO involves periodic, systematic changes in the distribution of clouds and precipitation over the western Pacific and Indian oceans, along with differences in wind intensity over even more extensive areas, including the north and subtropical Atlantic Ocean. The lead authors of this paper developed a sophisticated mathematical technique for mapping the spatial and temporal behavior of changes in the atmosphere produced by the MJO. In a previous paper, we applied this technique to search for modulation of airborne particle amount in the eastern hemisphere associated with the "wet" (cloudy) vs. "dry" phases of the MJO. The study used primarily AVHRR, MODIS, and TOMS satellite-retrieved aerosol amount, but concluded that other factors, such as cloud contamination of the satellite signals, probably dominated the observed variations. The current paper looks at MJO modulation of desert dust transport eastward across the Atlantic from northern Africa, a region much less subject to systematic cloud contamination than the eastern hemisphere areas studied previously. In this case, a distinct aerosol signal appears, showing that dust is transported westward much more effectively during the MJO phase that favors westward-flowing wind, and such transport is suppressed when the MJO reduces these winds. Aside form the significant achievement in identifying such an effect, the result implies that an important component of global dust transport can be predicted based on the phase of the MJO. As a consequence, the impact of airborne dust on storm development in the Atlantic, and on dust deposition downwind of the desert sources, can also be predicted and more accurately modeled.

Tian, B.↗

NASA NTRS2012

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Tarabalka, Y.↗

NASA NTRS2012

Transmission Electron Microscopy (TEM) Sample Preparation of Si(1-x)Gex in c-Plane Sapphire Substrate

The National Aeronautics and Space Administration-invented X-ray diffraction (XRD) methods, including the total defect density measurement method and the spatial wafer mapping method, have confirmed super hetero epitaxy growth for rhombohedral single crystalline silicon germanium (Si1-xGex) on a c-plane sapphire substrate. However, the XRD method cannot observe the surface morphology or roughness because of the method s limited resolution. Therefore the authors used transmission electron microscopy (TEM) with samples prepared in two ways, the focused ion beam (FIB) method and the tripod method to study the structure between Si1-xGex and sapphire substrate and Si1?xGex itself. The sample preparation for TEM should be as fast as possible so that the sample should contain few or no artifacts induced by the preparation. The standard sample preparation method of mechanical polishing often requires a relatively long ion milling time (several hours), which increases the probability of inducing defects into the sample. The TEM sampling of the Si1-xGex on sapphire is also difficult because of the sapphire s high hardness and mechanical instability. The FIB method and the tripod method eliminate both problems when performing a cross-section TEM sampling of Si1-xGex on c-plane sapphire, which shows the surface morphology, the interface between film and substrate, and the crystal structure of the film. This paper explains the FIB sampling method and the tripod sampling method, and why sampling Si1-xGex, on a sapphire substrate with TEM, is necessary.

Kim, Hyun Jung↗

NASA NTRS2014

Myanmar Ecological Forecasting: Utilizing NASA Earth Observations to Monitor, Map, and Analyze Mangrove Forests in Myanmar for Enhanced Conservation

Mangroves supply many essential environmental amenities, such as preventing soil erosion, filtering water pollution, and protecting shorelines from harmful waves, floods, storms and winds. The Mangroves in Myanmar not only provide citizens with a food source, but they also offer firewood, charcoal, and construction materials. The depletion of mangroves is threatening more than the biodiversity however; Myanmar's fiscal livelihood is also in harm's way. Mangroves are valued at $100,000 to $277,000 per square kilometer and if managed in a sustainable fashion, can infuse constant income to the emerging Myanmarese economy. This study analyzed three coastline regions, the Ayeyarwady Delta, Rakhine and Tanintharyi, and mapped the spatial extent of mangrove forest during the dry season in 2000 and 2013. The classifications were derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operation Land Imager (OLI) imagery, as well as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model information. This data was atmospherically corrected, mosaicked, masked and classified in ENVI, followed by ArcGIS to perform raster calculations and create final products. Forest degradation collected from 2000 to 2013 was later used to forecast the density and health of Mangroves in the year 2030. These results were subsequently presented to project partners Dr. Peter Leimgruber and Ellen Aiken at the Smithsonian Conservation Biology Institute in Front Royal, VA. After the presentation of the project to the partners, these organizations formally passed on to the Myanmar Ministry of Environment, Conservation and Forestry for policy makers and forest managers to utilize in order to protect the Myanmar mangrove ecosystem while sustaining a healthy economy.

Weber, Samuel J.↗

NASA NTRS2014

NuSTAR Study of Hard X-ray Morphology and Spectroscopy G21.5-0.9

We present NuSTAR high-energy X-ray observations of the pulsar wind nebula (PWN)/supernova remnant G21.5−0.9. We detect integrated emission from the nebula up to approx. 40 keV, and resolve individual spatial features over a broad X-ray band for the first time. The morphology seen by NuSTAR agrees well with that seen by XMM-Newton and Chandra below 10 keV. At high energies, NuSTAR clearly detects non-thermal emission up to approx. 20 keV that extends along the eastern and northern rim of the supernova shell. The broadband images clearly demonstrate that X-ray emission from the North Spur and Eastern Limb results predominantly from non-thermal processes. We detect a break in the spatially integrated X-ray spectrum at approx. 9 keV that cannot be reproduced by current spectral energy distribution models, implying either a more complex electron injection spectrum or an additional process such as diffusion compared to what has been considered in previous work. We use spatially resolved maps to derive an energy-dependent cooling length scale, E(sup m) is directly proportional to L(E) with m = −0.21 plus or minus 0.01. We find this to be inconsistent with the model for the morphological evolution with energy described by Kennel & Coroniti. This value, along with the observed steepening in power-law index between radio and X-ray, can be quantitatively explained as an energy-loss spectral break in the simple scaling model of Reynolds, assuming particle advection dominates over diffusion. This interpretation requires a substantial departure from spherical magnetohydrodynamic, magnetic-flux-conserving outflow, most plausibly in the form of turbulent magnetic-field amplification.

radiation mechanisms↗

NASA NTRS2015

Is Ice-Rafted Sediment in a North Pole Marine Record Evidence for Perennial Sea-ice Cover?

Ice-rafted sediments of Eurasian and North American origin are found consistently in the upper part (13 Ma BP to present) of the Arctic Coring Expedition (ACEX) ocean core from the Lomonosov Ridge, near the North Pole (approximately 88 degrees N). Based on modern sea-ice drift trajectories and speeds, this has been taken as evidence of the presence of a perennial sea-ice cover in the Arctic Ocean from the middle Miocene onwards. However, other high latitude land and marine records indicate a long-term trend towards cooling broken by periods of extensive warming suggestive of a seasonally ice-free Arctic between the Miocene and the present. We use a coupled sea-ice slab-ocean model including sediment transport tracers to map the spatial distribution of ice-rafted deposits in the Arctic Ocean. We use 6 hourly wind forcing and surface heat fluxes for two different climates: one with a perennial sea-ice cover similar to that of the present day and one with seasonally ice-free conditions, similar to that simulated in future projections. Model results confirm that in the present-day climate, sea ice takes more than 1 year to transport sediment from all its peripheral seas to the North Pole. However, in a warmer climate, sea-ice speeds are significantly faster (for the same wind forcing) and can deposit sediments of Laptev, East Siberian and perhaps also Beaufort Sea origin at the North Pole. This is primarily because of the fact that sea-ice interactions are much weaker with a thinner ice cover and there is less resistance to drift. We conclude that the presence of ice-rafted sediment of Eurasian and North American origin at the North Pole does not imply a perennial sea-ice cover in the Arctic Ocean, reconciling the ACEX ocean core data with other land and marine records.

Palaeoclimate↗

NASA NTRS2014

Stardust Interstellar Preliminary Examination IV: Scanning Transmission X-Ray Microscopy Analyses of Impact Features in the Stardust Interstellar Dust Collector

We report the quantitative characterization by synchrotron soft X-ray spectroscopy of 31 potential impact features in the aerogel capture medium of the Stardust Interstellar Dust Collector. Samples were analyzed in aerogel by acquiring high spatial resolution maps and high energy-resolution spectra of major rock-forming elements Mg, Al, Si, Fe, and others. We developed diagnostic screening tests to reject spacecraft secondary ejecta and terrestrial contaminants from further consideration as interstellar dust candidates. The results support an extraterrestrial origin for three interstellar candidates: I1043,1,30 (Orion) is a 3 pg particle with Mg-spinel, forsterite, and an iron-bearing phase. I1047,1,34 (Hylabrook) is a 4 pg particle comprising an olivine core surrounded by low-density, amorphous Mg-silicate and amorphous Fe, Cr, and Mn phases. I1003,1,40 (Sorok) has the track morphology of a high-speed impact, but contains no detectable residue that is convincingly distinguishable from the background aerogel. Twenty-two samples with an anthropogenic origin were rejected, including four secondary ejecta from impacts on the Stardust spacecraft aft solar panels, nine ejecta from secondary impacts on the Stardust Sample Return Capsule, and nine contaminants lacking evidence of an impact. Other samples in the collection included I1029,1,6, which contained surviving solar system impactor material. Four samples remained ambiguous: I1006,2,18, I1044,2,32, and I1092,2,38 were too dense for analysis, and we did not detect an intact projectile in I1044,3,33. We detected no radiation effects from the synchrotron soft X-ray analyses; however, we recorded the effects of synchrotron hard X-ray radiation on I1043,1,30 and I1047,1,34.

Dust↗

NASA NTRS2015

Development of Double and Triple-Pulsed 2-micron IPDA Lidars for Column CO2 Measurements

Carbon dioxide (CO2) is an important greenhouse gas that significantly contributes to the carbon cycle and globalradiation budget on Earth. CO2 role on Earth’s climate is complicated due to different interactions with various climatecomponents that include the atmosphere, the biosphere and the hydrosphere. Although extensive worldwide efforts formonitoring atmospheric CO2 through various techniques, including in-situ and passive sensors, are taking place highuncertainties exist in quantifying CO2 sources and sinks. These uncertainties are mainly due to insufficient spatial andtemporal mapping of the gas. Therefore it is required to have more rapid and accurate CO2 monitoring with higheruniform coverage and higher resolution. CO2 DIAL operating in the 2-μm band offer better near-surface CO2measurement sensitivity due to the intrinsically stronger absorption lines. For more than 15 years, NASA LangleyResearch Center (LaRC) contributed in developing several 2-m CO2 DIAL systems and technologies. This paperfocuses on the current development of the airborne double-pulsed and triple-pulsed 2-m CO2 integrated pathdifferential absorption (IPDA) lidar system at NASA LaRC. This includes the IPDA system development andintegration. Results from ground and airborne CO2 IPDA testing will be presented. The potential of scaling suchtechnology to a space mission will be addressed.

Singh, Upendra N.↗

NASA NTRS2017

A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

NeMO=NET↗

NASA NTRS2018

Overview of Primitive Object Volatile Explorer (PrOVE) CubeSat or Smallsat Concept

Here we describe the Primitive Object Volatile Explorer (PrOVE), a smallsat mission concept to study the surface structure and volatile inventory of comets in their perihelion passage phase when volatile activity is near peak. CubeSat infrastructure imposes limits on propulsion systems, which are compounded by sensitivity to the spacecraft disposal state from the launch platform and potential launch delays. We propose circumventing launch platform complications by using waypoints in space to park a deep space SmallSat or CubeSat while awaiting the opportunity to enter a trajectory to flyby a suitable target. In our Planetary Science Deep Space SmallSat Studies (PSDS3) project, we investigated scientific goals, waypoint options, potential concept of operations (ConOps) for periodic and new comets, spacecraft bus infrastructure requirements, launch platforms, and mission operations and phases. Our payload would include two low-risk instruments: a visible image (VisCAM) for 5-10 m resolution surface maps; and a highly versatile multispectral Comet CAMera (ComCAM) will measure 1) H2O, CO2, CO, and organics non-thermal fluorescence signatures in the 2-5 μm MWIR, and 2) 7-10 and 8-14 μm thermal (LWIR) emission. This payload would return unique data not obtainable from ground-based telescopes and complement data from Earth-orbiting observatories. Thus, the PrOVE mission would (1) acquire visible surface maps, (2) investigate chemical heterogeneity of a comet nucleus by quantifying volatile species abundance and changes with solar insolation, (3) map the spatial distribution of volatiles and determine any variations, and (4) determine the frequency and distribution of outbursts.

Clark, Pamela S.↗

NASA NTRS2018

The HR 4796A Debris System: Discovery of Extensive Exo-Ring Dust Material

The optically and IR-bright and starlight-scattering HR 4796A ringlike debris disk is one of the most- (and best-) studied exoplanetary debris systems. The presence of a yet-undetected planet has been inferred (or suggested) from the narrow width and inner/outer truncation radii of its r = 1farcs05 (77 au) debris ring. We present new, highly sensitive Hubble Space Telescope (HST) visible-light images of the HR 4796A circumstellar debris system and its environment over a very wide range of stellocentric angles from 0farcs32 (23 au) to ≈15'' (1100 au). These very high-contrast images were obtained with the Space Telescope Imaging Spectrograph (STIS) using six-roll PSF template–subtracted coronagraphy suppressing the primary light of HR 4796A, with three image-plane occulters, and simultaneously subtracting the background light from its close angular proximity M2.5V companion. The resulting images unambiguously reveal the debris ring embedded within a much larger, morphologically complex, and biaxially asymmetric exo-ring scattering structure. These images at visible wavelengths are sensitive to and map the spatial distribution, brightness, and radial surface density of micron-size particles over 5 dex in surface brightness. These particles in the exo-ring environment may be unbound from the system and interacting with the local ISM. Herein, we present a new morphological and photometric view of the larger-than-prior-seen HR 4796A exoplanetary debris system with sensitivity to small particles at stellocentric distances an order of magnitude greater than has previously been observed.

starlight-scattering HR 4796A↗

NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over 60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

NASA NTRSDate not supplied

Expanding NeMO-Net Machine Learning Capabilities for Citizen Science

NASA NeMO-Net, the neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive citizen science video game, released this April, for desktop and iOS devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using diver photomosaic imagery, the UAV enabled NASA FluidCam instrument, and satellite datasets. To date, the application has had over 40,000 downloads and over60,000 unique coral reef classifications, each filtered through a user-based rating and expert evaluation system. We also present results from NeMO-Net’s convolutional neural network (CNN) models used to semantically segment 2D satellite imagery as well as projections of 3D coral reconstructions using user input data as training datasets. Fusing datasets using machine learning from multiple remote sensing platforms presents novel methodologies for assessing the health of coral ecosystems, which are critically endangered by a changing climate. In partnering with Mission Blue, the National Oceanic and Atmospheric Administration (NOAA), and the Living Oceans Foundation (LOF), NeMO-Net leverages an international consortium of subject matter experts to provide both proper training for citizen scientists and the generation of a labeled datasets to ingest into machine learning algorithms for global coral reef identification.

NeMO-Net↗

NASA NTRS2020

Wildfire Smoke Particle Properties and Evolution, From Space-Based Multi-Angle Imaging II: The Williams Flats Fire during the FIREX-AQ Campaign

Although the characteristics of biomass burning events and the ambient ecosystem determine emitted smoke composition, the conditions that modulate the partitioning of black carbon (BC) and brown carbon (BrC) formation are not well understood, nor are the spatial or temporal frequency of factors driving smoke particle evolution, such as hydration, coagulation, and oxidation, all of which impact smoke radiative forcing. In situ data from surface observation sites and aircraft field campaigns offer deep insight into the optical, chemical, and microphysical traits of biomass burning (BB) smoke aerosols, such as single scattering albedo (SSA) and size distribution, but cannot by themselves provide robust statistical characterization of both emitted and evolved particles. Data from the NASA Earth Observing System’s Multi-Angle Imaging SpectroRadiometer (MISR) instrument can provide at least a partial picture of BB particle properties and their evolution downwind, once properly validated. Here we use in situ data from the joint NOAA/NASA 2019 Fire Influence on Regional to Global Environments Experiment-Air Quality (FIREX-AQ) field campaign to assess the strengths and limitations of MISR-derived constraints on particle size, shape, light-absorption, and its spectral slope, as well as plume height and associated wind vectors. Based on the satellite observations, we also offer inferences about aging mechanisms effecting downwind particle evolution, such as gravitational settling, oxidation, secondary particle formation, and the combination of particle aggregation and condensational growth. This work builds upon our previous study, adding confidence to our interpretation of the remote-sensing data based on an expanded suite of in situ measurements for validation. The satellite and in situ measurements offer similar characterizations of particle property evolution as a function of smoke age for the 06 August Williams Flats Fire, and most of the key differences in particle size and absorption can be attributed to differences in sampling and changes in the plume geometry between sampling times. Whereas the aircraft data provide validation for the MISR retrievals, the satellite data offer a spatially continuous mapping of particle properties over the plume, which helps identify trends in particle property downwind evolution that are ambiguous in the sparsely sampled aircraft transects. The MISR data record is more than two decades long, offering future opportunities to study regional wildfire plume behavior statistically, where aircraft data are limited or entirely lacking.

biomass burning↗

NASA NTRS2018

Overview of Primitive Volatile Explorer (PrOVE) Cubesat or Smallsat Concept

Here we describe the Primitive Object Volatile Explorer (PrOVE), a smallsat mission concept to study the surface structure and volatile inventory of comets in their perihelion passage phase when volatile activity is near peak. CubeSat infrastructure imposes limits on propulsion systems, which are compounded by sensitivity to the spacecraft disposal state from the launch platform and potential launch delays. We propose circumventing launch platform complications by using waypoints in space to park a deep space SmallSat or CubeSat while awaiting the opportunity to enter a trajectory to flyby a suitable target. In our Planetary Science Deep Space SmallSat Studies (PSDS3) project, we investigated scientific goals, waypoint options, potential concept of operations (ConOps) for periodic and new comets, spacecraft bus infrastructure requirements, launch platforms, and mission operations and phases. Our payload would include two low-risk instruments: a visible image (VisCAM) for 5-10 m resolution surface maps; and a highly versatile multispectral Comet CAMera (ComCAM) will measure 1) H2O, CO2, CO, and organics non-thermal fluorescence signatures in the 2-5 µm MWIR, and 2) 7-10 and 8-14 µm thermal (LWIR) emission. This payload would return unique data not obtainable from ground-based telescopes and complement data from Earth-orbiting observatories. Thus, the PrOVE mission would (1) acquire visible surface maps, (2) investigate chemical heterogeneity of a comet nucleus by quantifying volatile species abundance and changes with solar insolation, (3) map the spatial distribution of volatiles and determine any variations, and (4) determine the frequency and distribution of outbursts.

Zucherman, Aaron↗

NASA NTRSDate not supplied

Applications and Performance of a Lightning Risk Assessment using Geostationary Lightning Mapper (GLM) Data

Lightning is a hazard globally, particularly in lesser-developed countries. Cloud-to-ground lightning strikes are a threat to human safety, motivating a desire to monitor location-based lightning risk to mitigate harm. A lightning risk assessment for human safety was created that uses a combination of probabilistic risk calculation and spatial lightning mapping data to produce a risk magnitude. This risk magnitude evolves with time and changing conditions and is compared to tolerability thresholds in order to evaluate safety. The risk assessment using lightning mapping array (LMA) flash extent density (FED) data was found to perform comparatively (with respect to issuing lightning warnings) to a more standard method of monitoring lightning safety where National Lightning Detection Network (NLDN) flashes were monitored within a 5 nautical mile radius of a location of interest. This research investigates the replacement of LMA FED with FED from the Geostationary Lightning Mapper (GLM) within the risk assessment framework. Using GLM FED would allow for risk to be calculated outside of LMA domains and anywhere within the GLM field of view, including areas outside of the United States (US). A few applications of the risk method with GLM FED are shown and discussed for locations both in and outside of the US. Additionally, the performance of the risk method is compared based on the type of lightning input source (LMA vs GLM). The end goal of this work is to provide forecasters and end users with a tool to help monitor lightning risk in decision support scenarios.

Kelley Murphy↗