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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Hailstorm Analyses and Detection Derived from Current and Historical Satellite Data and Convective Environmental Parameters

We seek to demonstrate the extent to which hailstorms can be detected using a combination of geostationary (GEO) visible and infrared metrics of storm intensity and convective environmental parameters from reanalysis. Hailstorm identifications from low-Earth-orbiting (LEO) passive microwave sensors and maximum expected size of hail (MESH) from ground-based radar serve as a proxy for hail events. Data are analyzed for two warm seasons over the contiguous United States (CONUS). A neural network (NN) is trained to predict hailstorm detection dependent on optimal multi-variate weighting of observed and modeled input. The NN results are then applied to a 15-year Meteosat Second Generation climatology over South Africa to depict where hailstorms are most likely to occur. We also explore the impact of GEO imager resolution on our ability to discriminate hailstorms by matching GOES-13 (4 km) and GOES-16 (2 km) storm intensity metrics against hail characteristics using LEO, MESH, and spotter reports over CONUS during 2017, when both satellites were simultaneously imaging. Such analysis allows us to assess the feasibility of assembling a severe storm climate data record back to GOES-8, in the mid-1990’s. Finer spatial resolution of GOES-16 better resolves the updraft characteristics and intensities that are inherently linked to hail formation; however, GOES-13 can be normalized to achieve comparable detection capability. When intelligently combined with model-derived convective environmental parameters, GEO-derived storm intensity metrics enable high-spatial resolution hail risk assessment at hourly intervals throughout the diurnal cycle anywhere around the world and an improved understanding of hailstorms in the climate system.

Kyle F Itterly↗
DOE OSTI2020

Synchrotron infrared nano-spectroscopy and -imaging

Infrared (IR) spectroscopy has evolved into a powerful analytical technique to probe molecular and lattice vibrations, low-energy electronic excitations and correlations, and related collective surface plasmon, phonon, or other polaritonic resonances. In combination with scanning probe microscopy, near-field infrared nano-spectroscopy and -imaging techniques have recently emerged as a frontier in imaging science, enabling the study of complex heterogeneous materials with simultaneous nanoscale spatial resolution and chemical and quantum state spectroscopic specificity. Here, we describe synchrotron infrared nano-spectroscopy (SINS), which takes advantage of the low-noise, broadband, high spectral irradiance, and coherence of synchrotron infrared radiation for near-field infrared measurements across the mid- to far-infrared with nanometer spatial resolution. This powerful combination provides a qualitatively new form of broadband spatio-spectral analysis of nanoscale, mesoscale, and surface phenomena that were previously difficult to study with IR techniques, or even any form of micro-spectroscopy in general. We review the development of SINS, describe its technical implementations, and highlight selected examples representative of the rapidly growing range of applications in physics, chemistry, biology, materials science, geology, and atmospheric and space sciences.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Predicting weather impacts on corn production in a data-limited region using a transfer learning approach

The stability of food supply and prices may depend more on annual changes in yields from year-to-year variability in weather than on longer-term average changes from changing climatic conditions. However, the absence of high-quality data on crop yields at fine spatial resolutions in many regions of the world makes it challenging to statistically model their response to interannual variability in weather patterns. Therefore, there is a need for empirical methods that can project annual crop yield changes even in limited data regions. Here, we propose a transfer learning algorithm that uses high spatial resolution data from one region to project yields in another region with more limited data. The goal of our work is to understand what data types can be beneficial for transferring learning from a source region to a very different target region with more limited data. We utilize Long Short-Term Memory to develop a transfer learning model that is trained on historical county-level corn yield in the United States and predicts district-level corn yield variations in India. Even using smaller amounts of data in India, simulating a data-scarce region, we achieve an average root mean square error of 0.48 bu acre−1 in predicting interannual yield variations. Using Shapley values to interpret results, we explore the contribution of the different weather parameters to interannual yield variability and find a larger influence of precipitation-related variables. Our study demonstrates the usefulness of this method for transferring models of weather impacts on crop yields trained on a data-rich country to one with more limited data. It suggests the potential of applying the transfer learning model to mitigate the need for extensive raw data globally.

Vishwakarma, Srishti [ORNL] (ORCID:000000031674419↗
NASA NTRS1986

Analytical ultrasonics for evaluation of composite materials response. Part 2: Generation and detection

To evaluate the response of composite materials, it is imperative that the input excitation as well as the observed output be well characterized. This characterization ideally should be in terms of displacements as a function of time with high spatial resolution. Additionally, the ability to prescribe these features for the excitation is highly desirable. Various methods for generating and detecting ultrasound in advanced composite materials are examined. Characterization and tailoring of input excitation is considered for contact and noncontact, mechanical, and electromechanical devices. Type of response as well as temporal and spatial resolution of detection methods are discussed as well. Results of investigations at Virginia Tech in application of these techniques to characterizing the response of advanced composites are presented.

Duke, J. C., Jr.↗
NASA NTRS2007

Solutions Network Formulation Report. Reducing Light Pollution in U.S. Coastal Regions Using the High Sensitivity Cameras on the SAC-C and Aquarius/SAC-D Satellites

Light pollution has significant adverse biological effects on humans, animals, and plants and has resulted in the loss of our ability to view the stars and planets of the universe. Over half of the U.S. population resides in coastal regions where it is no longer possible to see the stars and planets in the night sky. Forty percent of the entire U.S. population is never exposed to conditions dark enough for their eyes to convert to night vision capabilities. In coastal regions, urban lights shine far out to sea where they are augmented by the output from fishing boat, cruise ship and oil platform floodlights. The proposed candidate solution suggests using HSCs (high sensitivity cameras) onboard the SAC-C and Aquarius/SAC-D satellites to quantitatively evaluate light pollution at high spatial resolution. New products modeled after pre-existing, radiance-calibrated, global nighttime lights products would be integrated into a modified Garstang model where elevation, mountain screening, Rayleigh scattering, Mie scattering by aerosols, and atmospheric extinction along light paths and curvature of the Earth would be taken into account. Because the spatial resolution of the HSCs on SAC-C and the future Aquarius/SAC-D missions is greater than that provided by the DMSP (Defense Meteorological Satellite Program) OLS (Operational Linescan System) or VIIRS (Visible/Infrared Imager/Radiometer Suite), it may be possible to obtain more precise light intensity data for analytical DSSs and the subsequent reduction in coastal light pollution.

Andrews, Jane C.↗
DOE OSTI2024

The Electron Spectro-Microscopy (ESM) Beamline at NSLS-II

Photoelectron spectroscopy is a primary tool for the study of the electronic structure of materials and the chemical composition of surfaces. High-resolution angle-resolved photoemission spectroscopy (ARPES) has the unique ability to map the energy bands in momentum space. Furthermore, going beyond the single particle picture, the self-energy corrections caused by correlations in solids can be extracted from the analysis of the emission line shape. The current level of refinement, in terms of energy and angular resolution (ΔE < 1 meV, Δθ < 0.1°), makes the technique sensitive to the lowest energy excitations and the dynamics of electrons, which in turn virtually determine all the macroscopic properties of any system and govern the chemical, electrical, magnetic, and physical processes. Similarly important, X-ray photoelectron microscopy (XPEEM), combined with the low-energy electron microscopy (LEEM), is indispensable in probing the complexity of chemical, structural, electronic and magnetic properties of surfaces and shallow interfaces, with the spatial resolution of few tens of nanometer (nm). The Electron-Spectro-Microscopy beamline (ESM) has been recently commissioned at NSLS-II and is now in operation. The primary spectroscopic technique is photoemission, performed over a wide energy range with control of light polarization and in a variety of flux/resolution conditions. The beamline has two experimental end stations that allow to perform ARPES and XPEEM/LEEM, separately. The ARPES end station focuses on high energy-resolution work, with spot-size of a few microns. The XPEEM/LEEM end station is a full-field microscope (XPEEM) operating either with the synchrotron generated X-rays (XPEEM), or with an internal electron gun (LEEM). Spatial resolution is crucial in studies of newly synthesized complex materials since they are often initially available only as small specimens (typically micron size). Furthermore, chemical inhomogeneities on surfaces are often an integral part of surface chemical processes. Finally, the ESM beamline with X-ray spots of few microns is optimized to study the electronic structure of novel materials with microscopy capabilities.

47 OTHER INSTRUMENTATION↗
NASA NTRS1980

Matched tandem etalon camera - MATEC - and its application to auroral observations

The matched tandem etalon camera employs a Fabry-Perot interferometer (FP) in the photographic mode for the spatial resolution over all angles up to 7 deg from normal. An interference filter and an appropriate field lens isolate a single order of 0.1 A resolution, which is recorded simultaneously at all angles in the field of view by array detection. Thus the resolution and luminosity of the MATEC camera are those of the FP. The MATEC pilot model has a ratio of free spectral range to linewidth of 400 and utilizes intensified photographic detection. In a system applied to auroral measurements the MATEC views a semiconical sky mirror to provide a simulatenous dimension of spatial resolution in the N-S meridian combined with the dimension of spectral resolution. Stellar features and cloud and ground reflections are more easily identified than by any scanning photometer.

Young, E. R.↗
NASA NTRS1998

Neutral Networks for Subpixel Classification of Multispectral Images

In this work, the implementation and use of AVHRR (Advanced Very High Resolution Radiometer) images for subpixel analysis is studied. The work consists of two parts, the first is making training data, the second is using the training data to design a neural net subpixel analyzer. Most work on subpixel analysis has been done with images with more spectral bands. AVHRR images were chosen because of their easy acquisition, and because the five spectral bands allow investigation into the development of training data. The first step in subpixel analysis is the development of training data. This consists of image to be classified, and the classification of each pixel. In order to do the classification, a high spatial resolution image is typically needed in order to manually create a classified image. It is difficult to have both the image of interest, and a high spatial resolution image of the same area taken at the same time. Thus it was studied whether a subsampled image taken from the image of interest could serve as the training data. Statistical work has been done showing the unusefulness of this approach. In the second part of the analysis, a feedforward neural net was trained and used to classify the AVHRR images. Results of these tests, comparing the neural net with typical statistical based schemes are shown.

Figueroa, Ricardo R.↗
NASA NTRS2004

Revisiting the Interpretation of Thorium Abundances at Hansteen Alpha

Hansteen Alpha is one of the few remaining locations on the Moon thought to be formed by highlands volcanism. Hansteen Alpha is a triangular shaped feature located in the southern portion of Oceanus Procellarum (12 degrees W, 50 degrees S) and its size is approximately 25 km on each side. As described by Hawke et al., there is clear evidence that: 1) Hansteen Alpha was emplaced by extrusive volcanic processes; and 2) it was formed by a viscous lava that should be enriched in Th. However, in the study of Hawke et al. using available Lunar Prospector (LP) Th data, it was concluded that the Hansteen Alpha region was not greatly enriched in Th as would be expected for a highly evolved, viscous lava. It was further concluded based on other compositional data that the magma that formed Hansteen Alpha did not correspond to any known rock type. Here we revisit the interpretation of Th abundances at Hansteen Alpha for a couple of reasons. First, the size of Hansteen Alpha is smaller than the spatial resolution of the LP Gamma-ray Spectrometer (LP-GRS) from which the Th abundances were derived. Therefore, the LP-GRS pixels covering Hansteen Alpha may not truly represent the Th abundance of the Hansteen Alpha feature. Second, recent work has led to a much greater understanding of the Th spatial distribution for small-area features on the lunar surface. In particular, using forward modeling techniques, we have developed the ability to obtain information about Th abundances for features that are at or smaller than the FWHM spatial resolution (approximately [80 square kilometers]) of the LP-GRS data.

Lawrence, D. J.↗
NASA NTRS2018

Assimilation of Satellite Derived Soil Moisture Profiles into a Crop Modeling System for Robust Yield Estimates

Soil Moisture Measurement - Remote Sensing. - Microwave (MW) Remote Sensing: Physically based and quantitative in nature; Based on difference in dielectric constant; Coarse spatial resolution 25-40 km; Shallow SM estimation depth 0-5 cm (approx.); All weather capabilities (e.g. Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) etc.) - Thermal Infrared (TIR) Remote Sensing: Indirect SM retrieval through energy flux estimations; Relatively better spatial resolution 1-10 km; Root-zone moisture retrieval capability; Can not penetrate through clouds, hence data gaps (e.g. Surface Energy Balance Algorithm for Land (SEBAL), Atmospheric Land Exchange Inverse (ALEXI) etc.)

SERVIR↗
NASA NTRSDate not supplied

Atom Probe Tomography and Three-Dimensional Atomic Scale Characterisation of Interplanetary Dust Particles: Inorganic and Organic, Hydrous and Anhydrous Assemblages

Interplanetary dust particles (IDPs)preserve primordial fragments from our Solar System and external stellar systems, sampled from a vast range of dust forming bodies that often display smaller degrees of parent body processing than is seen in meteorites. IDPs preserve some of the smallest astromaterials from our Solar System, many of which are believed to be among the most important materials for studying physical and chemical processing, and formation mechanisms occurring within the interstellar medium (ISM), Solar Nebula and external planetary systems[1]. However, their formation processes and provenance are poorly constrained, owing in part to spatial resolution limitations of traditional analytical techniques. Atom probe tomography (APT) uses a pulsed laser to field-evaporate material at the atomic scale from needle-shaped samples, and time-of-flight spectrometry for 3D reconstruction of element and isotope distribution in samples after data acquisition. This technique has the highest spatial resolution available of any technique used within the geoscience field[2]. However, measuring multi-phase specimens and porous media in APT can be challenging, two primary characteristics of IDPs. Here we present a custom method for APT needle design and the first results of a 3Datomic scale study of interplanetary dust particles, salt crystals and extraterrestrial insoluble and soluble organic matter designed to overcome the challenges of studying IDP-like materials.

N D Nevill↗
NASA NTRS1988

Concentration, temperature, and density in a hydrogen-air flame by excimer-induced Raman scattering

Single-pulse, vibrational Raman scattering (VRS) is an attractive laser diagnostic for the study of supersonic hydrogen-air combustion. The VRS technique gives a complete thermodynamic description of the gas mixture at a point in the reacting flow. Single-pulse, vibrational Raman scattering can simultaneously provide independent measurements of density, temperature, and concentration of each major species (H2, H2O, O2 and N2) in a hydrogen/air turbulent combustor. Also the pressure can be calculated using the ideal gas law. However, single-pulse VRS systems in current use for measurement of turbulent combustion have a number of shortcomings when applied to supersonic flows: (1) slow repetition rate (1 to 5 Hz), (2) poor spatial resolution (0.5x0.3x0.3 cu mm), and (3) marginal time resolution. Most of these shortcomings are due to the use of visible wavelength flash-lamp pumped dye lasers. The advent of UV excimer laser allows the possibility of dramatic improvements in the single-pulse, vibrational Raman scattering. The excimer based VRS probe will greatly improve repetition rate (100 to 500 Hz), spatial resolution (0.1x0.1x0.1 cu mm) and time resolution (30ns). These improvements result from the lower divergence of the UV excimer, higher repetition rate, and the increased Raman cross-sections (15 to 20 times higher) at ultra-violet (UV) wavelengths. With this increased capability, single-pulse vibrational Raman scattering promises to be an ideal non-intrusive probe for the study of hypersonic propulsion flows.

Wehrmeyer, Joseph A.↗
NASA NTRS2007

Summary of Terra and Aqua MODIS On-orbit Calibration and Characterization Results

The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's EOS Terra spacecraft has been in operation for more than seven years since its launch in December 1999 and the MODIS onboard Aqua spacecraft has been in operation for more than 4.5 years since its launch in May 2002. Compared to its heritage sensors, such as AVHRR, CZCS, SeaWiFS, HIRS, and Landsat TM, the MODIS instrument was developed with improved spectral and spatial resolutions, and temporal scale or global coverage frequency. The two MODIS instruments are nearly identical with each collecting data in 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.2jm and 16 thermal emissive bands (TEB) from 3.7 to 4.4 microns. MODIS makes the Earth view observations with a scan angle range of +/-55 degree relative to instrument nadir and at three nadir spatial resolutions: 0.25km for bands 1-2.05km for bands 3-7, and 1km for bands 8-36, thus enabling complete global coverage of the Earth in less than 2 days. Both Terra and Aqua MODIS observations have been routinely used to generate a broad range of science data products that are widely distributed and extensively applied for the studies of the Earth's land, oceans, and atmosphere and for the monitoring of climate and environmental changes. It is obvious that the MODIS science data product quality strongly relies on sensor on-orbit performance and its capability of continuously tracking sensor response changes over time. Because of this, each MODIS was built with a comprehensive set of on-board calibrators (OBC) that include a solar diffuser (SD) for the RSB calibration, a blackbody (BB) for the TEB calibration, and a spectro-radiometric calibration assembly (SRCA) for the spatial (RSB and TEB) and spectral (RSB only) characterization. Most importantly, extensive and dedicated sensor calibration and characterization efforts have been constantly made by the MODIS Characterization Support Team (MCST) at NASA/GSFC. In this presentation, we will provide an overview of MODIS sensor operations since 1aunh and the onorbit calibration and characterization methodologies with emphasis on the differences between Terra and Aqua MODIS characteristics. We will summarize both Terra and Aqua MODIS onorbit calibration and characterization results, including their RSB and TEB detector noise characterization, the sensor response changes, and the corrections to the optics degradation. In addition to radiometric calibration performance, we will illustrate both sensors' spectral and spatial characterization results in terms of their band-to-band registrations and spectral band center wavelength shifts.

Xiong, X.↗
NASA NTRS2006

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Quattrochi, Dale A.↗
DOE OSTI2025

Multiscale investigation of thermomechanical and compositional developments in Ni alloy 718 under laser processing

Laser processing has been widely employed in various applications due to its exceptional spatial resolution. However, the rapid temperature gradients generated in localized areas present significant challenges for experimental characterization using conventional instruments. To characterize Ni alloy 718 during laser processing, we employed in-situ synchrotron X-ray diffraction with a high-speed detector, a method particularly well-suited for probing processes with high temporal and spatial resolution. Through a series of in-situ experiments, we investigated the local variations in the evolution of microstructures and thermomechanical behaviors within a keyhole mode melt pool. The in situ macroscopic thermomechanical behaviors were quantified using an empirical model derived from diffraction patterns, with experimental results showing reasonable agreement with finite element analysis. Various laser parameters were tested to assess their influences on the residual strains in the melt pools. The results revealed that the residual strain in the keyhole mode melt pool is relatively insensitive to variations in the parameters and is smaller than that in the melt pool created under conduction mode laser scanning. Additionally, we analyzed the shapes of individual diffraction spots, providing insights into the plastic behaviors and compositional developments in the resolidified alloy. The analysis confirmed that compositional variations in a dendritic microstructure manifest as asymmetric broadening of the diffraction spots.

Ni alloy 718↗
NASA NTRS2008

Electron Precipitation Parameters and Ionospheric Conductances Inferred from Auroral Images Acquired by the Visible Imaging Systems (VIS) on the Polar Spacecraft

The Visible Imaging System (VIS) on the polar spacecraft provided time sequences of auroral images at multiple wavelengths that yield information of auroral dynamics on a global scale with a spatial resolution of - 20 km and temporal resolution of approx. 1 minute. Time sequences of VIS images in which the aurora was highly dynamic are used to infer global maps for the electron precipitation parameters, energy flux and characteristic energies, and ionospheric conductances. The maps are inferred from the corresponding VIS images using an auroral model (Lumerzheim et al., 1987). The temporal and spatial resolution of the VIS inferred patterns are unprecedented. The inferred patterns are highly structured and vary significantly on a time scale of less than 5 minutes. These patterns can be very beneficial for global physics-based numerical models for the high-latitude ionosphere which previously had to rely on statistical models for the electron precipitation and ionospheric conductance.

Sigwarth, John B.↗
DOE OSTI2023

A confocal laser-induced fluorescence diagnostic with an annular laser beam

Here, in this work, we report an annular beam confocal laser-induced fluorescence (LIF) configuration, which allows for high spatial resolution measurements of plasma properties in plasma setups and sources with limited optical access. The proposed LIF configuration utilizes the annular laser beam generated by a pair of diffractive axicons. The LIF signal is collected along the main optical axis within the ring region. It is shown experimentally that at a focal distance of 300 mm, a spatial resolution of ~5.3 mm can be achieved. Using geometric optics estimations, we showed that ~1 mm resolution at the same focal distance could potentially be achieved by modifying laser beam parameters. This approaches the localization accuracy of conventional LIF collection methods (with crossing laser beam injection and fluorescence collection optical paths). Measurements of the ion velocity distribution function in an argon plasma using both the confocal LIF with an annular laser beam and conventional LIF demonstrate a satisfactory agreement. The proposed LIF setup has potential applications for diagnostics in various plasma processing equipment and plasma sources, such as hollow cathodes, microplasmas, electric propulsion, etc.

47 OTHER INSTRUMENTATION↗
NASA NTRS1998

Thermal Characteristics of Urban Landscapes

Although satellite data are very useful for analysis of the urban heat island effect at a coarse scale, they do not lend themselves to developing a better understanding of which surfaces across the city contribute or drive the development of the urban heat island effect. Analysis of thermal energy responses for specific or discrete surfaces typical of the urban landscape (e.g., asphalt, building rooftops, vegetation) requires measurements at a very fine spatial scale (i.e., less than 15 m) to adequately resolve these surfaces and their attendant thermal energy regimes. Additionally, very fine scale spatial resolution thermal infrared data, such as that obtained from aircraft, are very useful for demonstrating to planning officials, policy makers, and the general populace the benefits of the urban forest. These benefits include mitigating the urban heat island effect, making cities more aesthetically pleasing and more habitable environments, and aid in overall cooling of the community. High spatial resolution thermal data are required to quantify how artificial surfaces within the city contribute to an increase in urban heating and the benefit of cool surfaces (e.g., surface coatings that reflect much of the incoming solar radiation as opposed to absorbing it thereby lowering urban temperatures). The TRN (thermal response number) is a technique using aircraft remotely sensed surface temperatures to quantify the thermal response of urban surfaces. The TRN was used to quantify the thermal response of various urban surface types ranging from completely vegetated surfaces to asphalt and concrete parking lots for Huntsville, AL.

Luvall, Jeffrey C.↗