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NASA NTRS1999

Towards a Strategy of Remote Sensing of Aerosol Direct and Indirect Radiative Forcing

The role of aerosol forcing remains one of the largest uncertainties in estimating man's impact on the global climate system. One school of thought suggests that remote sensing by satellite sensors will provide the data necessary to narrow these uncertainties. Much effort has gone into the development of new satellite sensors specifically designed to retrieve aerosol loading and some information about the sizes of the aerosols. These next generation remote sensing instruments (EOS-MODIS, EOS-MISR, POLDER, ATSR) will provide unprecedented accuracy in the retrieval of aerosol loading. Although the new generation of sensors has excellent accuracy compared to the heritage instruments of the past, they still have measurement limitations. In clean, pristine regions the absolute magnitude of the uncertainty in the aerosol retrieval becomes comparable in magnitude to the signal itself. If much of the aerosol forcing is occurring at very low magnitudes of aerosol concentrations, satellite remote sensing will miss it. This study attempts to quantify remote sensing limitations due to the accuracy limits of the retrieval algorithms. We use a combination of numerical aerosol transport models, ground-based AERONET data and ISCCP cloud climatology to determine how much of the forcing occurs in regions too clean to determine from satellite retrievals. This study is not an intercomparison of global transport models. It is not an estimation of global aerosol forcing. This study is an exercise to determine whether satellite remote sensing can live up to our high expectations. The results show that while remote sensing will be able to measure a majority of the direct forcing, it will miss roughly half of the indirect forcing.

Remer, L. A.↗

NASA NTRS2000

Uncertainties in Remote Sensing of Aerosol Radiative Forcing

Remer, L.↗

NASA NTRS2006

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. , Over five years of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface s radiative characteristics. However, roughly 30% of the global land surface, on an annual equal-angle basis, is obscured due to persistent and transient cloud cover, while another 207% is obscured due to ephemeral and seasonal snow effects. This precludes the MOD43B3 albedo products from being directly used in some remote sensing and ground-based applications, climate models, and global change research projects. To provide researchers with the requisite spatially complete global snow-free land surface albedo dataset, an ecosystem-dependent temporal interpolation technique was developed to fill missing or lower quality data and snow covered values from the official MOD43B3 dataset with geophysically realistic values. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data.

King, Michael D.↗

DOE OSTI2022

Small Seismic Events in Oklahoma Detected and Located by Machine Learning–Based Models

A complete earthquake catalog is essential to understand earthquake nucleation and fault stress. Following the Gutenberg–Richter law, smaller, unseen seismic events dominate the earthquake catalog and are invaluable for revealing the fault state. The published earthquake catalogs, however, typically miss a significant number of small earthquakes. Part of the reason is due to a limitation of conventional algorithms, which can hardly extract small signals from background noise in a reliable and efficient way. To address this challenge, we utilized a machine learning method and developed new models to detect and locate seismic events. These models are efficient in processing a large amount of seismic data and extracting small seismic events. We applied our method to seismic data in Oklahoma, United States, and detected ~14 times more earthquakes compared with the standard Oklahoma Geological Survey catalog. The rich information contained in the new catalog helps better understand the induced earthquakes in Oklahoma.

58 GEOSCIENCES↗

DOE OSTI2022

Light-field control of real and virtual charge carriers

We report light-driven electronic excitation is a cornerstone for energy and information transfer. In the interaction of intense and ultrafast light fields with solids, electrons may be excited irreversibly, or transiently during illumination only. As the transient electron population cannot be observed after the light pulse is gone, it is referred to as virtual, whereas the population that remains excited is called real. Virtual charge carriers have recently been associated with high-harmonic generation and transient absorption, but photocurrent generation may stem from real as well as virtual charge carriers. However, a link between the generation of the carrier types and their importance for observables of technological relevance is missing. Here we show that real and virtual charge carriers can be excited and disentangled in the optical generation of currents in a gold–graphene–gold heterostructure using few-cycle laser pulses. Depending on the waveform used for photoexcitation, real carriers receive net momentum and propagate to the gold electrodes, whereas virtual carriers generate a polarization response read out at the gold–graphene interfaces. On the basis of these insights, we further demonstrate a proof of concept of a logic gate for future lightwave electronics. Our results offer a direct means to monitor and excite real and virtual charge carriers. Individual control over each type of carrier will markedly increase the integrated-circuit design space and bring petahertz signal processing closer to reality.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

HETDEX Public Source Catalog 1: 220 K Sources Including Over 50 K Ly$α$ Emitters from an Untargeted Wide-area Spectroscopic Survey*

We present the first publicly released catalog of sources obtained from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). HETDEX is an integral field spectroscopic survey designed to measure the Hubble expansion parameter and angular diameter distance at 1.88 < z < 3.52 by using the spatial distribution of more than a million Lyα-emitting galaxies over a total target area of 540 deg 2 . The catalog comes from contiguous fiber spectra coverage of 25 deg 2 of sky from 2017 January through 2020 June, where object detection is performed through two complementary detection methods: one designed to search for line emission and the other a search for continuum emission. The HETDEX public release catalog is dominated by emission-line galaxies and includes 51,863 Ly$α$-emitting galaxy (LAE) identifications and 123,891 [O ii]-emitting galaxies at z < 0.5. Also included in the catalog are 37,916 stars, 5274 low-redshift (z < 0.5) galaxies without emission lines, and 4976 active galactic nuclei. The catalog provides sky coordinates, redshifts, line identifications, classification information, line fluxes, [O ii] and Ly$α$ line luminosities where applicable, and spectra for all identified sources processed by the HETDEX detection pipeline. Extensive testing demonstrates that HETDEX redshifts agree to within Δz < 0.02, 96.1% of the time to those in external spectroscopic catalogs. We measure the photometric counterpart fraction in deep ancillary Hyper Suprime-Cam imaging and find that only 55.5% of the LAE sample has an r-band continuum counterpart down to a limiting magnitude of r ~ 26.2 mag (AB) indicating that an LAE search of similar sensitivity to HETDEX with photometric preselection would miss nearly half of the HETDEX LAE catalog sample. Data access and details about the catalog can be found online at http://hetdex.org/. A copy of the catalogs presented in this work (Version 3.2) is available to download at Zenodo doi:10.5281/zenodo.7448504.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2002

New CERES Data Examined for Evidence of Tropical Iris Feedback

New data products are available from the CERES instrument, a part of the NASA Earth Observing System. The Single Scanner Footprint (SSF) product combines radiative fluxes with extensive information on the cloud conditions in the footprint, which are retrieved using the co-orbiting imager instrument. These data have been analyzed to more accurately define the radiative properties for the various regions of the recently-proposed adaptive infrared Iris. A variety of ways of defining the cloudy moist region were examined. According to CERES, the net radiative flux for the cloudy moist region ranges between 28 and 54 W/m2 depending on the specific definition used. This is in contrast to the value of 123 W/m2 which was somewhat subjectively assigned by LCH. This simple model may miss many feedbacks in the climate system, but it should provide a rough range of the climate variations if the physics of the Iris is correct. There is some question whether the change in cloudy moist area with cloud-weighted SST actually represents a useful quantity, and whether extrapolating it from a regional variation to a global response to warmer climate is appropriate. Regardless, the current results show that the proposed Iris feedback is very much weaker when objectively-determined radiative properties are used in the model.

Chambers, Lin H.↗

NASA NTRS2009

Synthetic Foveal Imaging Technology

Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.

Hoenk, Michael↗

DOE OSTI2024

Air quality impacts from the development of unconventional oil and gas well pads: Air toxics and other volatile organic compounds

Unconventional oil and natural gas development (UOGD) has expanded rapidly across the United States in recent decades and raised concerns about associated air quality impacts. While significant effort has been made to quantify methane emissions, relatively few observations have been made of Volatile Organic Compounds (VOCs), especially during drilling and completion of new wells. Extensive air monitoring during development of several large, multi-well pads in Broomfield, Colorado, in the Denver-Julesburg Basin, provides a novel opportunity to examine changes in local air toxics and other VOC concentrations during well drilling and completions and production. These operations offer an especially useful case to study as several management practices were implemented to reduce emissions (e.g., electrified, grid-powered drill rigs and closed loop fluid handling systems to reduce truck traffic and limit fluid handling on the pad). With simultaneous measurements of methane and 50 VOCs from October 2018 to December 2022 at as many as 19 sites near well pads, in adjacent neighborhoods, and at a more distant reference location, we identify impacts from each phase of well development and production. Use of weekly, time-integrated canisters, a Proton Transfer Reaction Mass Spectrometer (PTR-MS), continuous photoionization detectors (PID) to trigger canister collection upon detection of VOC-rich plumes, and an instrumented vehicle, provided a powerful suite of measurements to characterize both transient plumes and longer-term changes in air quality. Prior to the start of well development, VOC gradients were small across Broomfield. Once drilling commenced, concentrations of oil and gas (O&G) related VOCs, including alkanes and aromatics, increased around active well pads. Concentration increases were clearly apparent during certain operations, including drilling, coil tubing/millout operations, and production tubing installation. Emissions of C 8 –C 10 n-alkanes during drilling operations highlighted the importance of VOC emissions from synthetic drilling mud chosen to reduce odor impacts. More than 90 samples were collected of transient plumes. Using composition measurements, meteorological data, and information about well pad activities, these plumes were connected with specific UOGD operations including drilling, flowback, and production equipment maintenance. The chemical signatures of these plumes differed by operation type (e.g., C 8 –C 10 n-alkanes constituted a larger fraction of measured VOCs in drilling-related plumes). Concentrations of individual, oil and gas-related VOCs in these plumes were often several orders of magnitude higher than in background air, with maximum ethane and benzene concentrations of 79,600 and 819 ppbv, respectively. Because these plumes typically impact a monitoring site for just several minutes, they are easily missed by slower-responding instruments. Study measurements highlight future emission mitigation opportunities during UOGD operations, including better control of emissions from shakers that separate drill cuttings from drilling mud, production separator maintenance operations, and periodic emptying of sand cans during flowback operations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

SnO 2 -Catalyzed Oxidation in High-Efficiency CdTe Solar Cells

Interfaces at the front of superstrate CdTe-based solar cells are critical to carrier transport, recombination, and device performance, yet determination of the chemical structure of these nanoscale regions has remained elusive. This is partly due to changes that occur at the front interfaces during high temperature growth and substantive changes occurring during postdeposition processing. In addition, these buried interfaces are extremely difficult to access in a way that preserves chemical information. In this work, we use a recently developed thermomechanical cleaving technique paired with X-ray photoelectron spectroscopy to probe oxidation states at the SnO 2 interface of CdTe solar cells. We show that the tin oxide front electrode promotes the formation of nanometer-scale oxides of tellurium and sulfur. Most oxidation occurs during CdCl 2 /O 2 activation. Surprisingly, we show that relatively low-temperature anneals (180-260 degrees C) used to diffuse and activate copper acceptors in a doping/back contact process also cause significant changes in oxidation at the front of the cell, providing a heretofore missing aspect of how back contact processes can modify device transport, recombination, and performance. Device performance is shown to correlate with the extent of tellurium and sulfur oxidation within this nanometer-scale region. Mechanisms responsible for these beneficial effects are proposed.

14 SOLAR ENERGY↗

DOE OSTI2023

Model certainty in cellular network-driven processes with missing data

Mathematical models are often used to explore network-driven cellular processes from a systems perspective. However, a dearth of quantitative data suitable for model calibration leads to models with parameter unidentifiability and questionable predictive power. Here we introduce a combined Bayesian and Machine Learning Measurement Model approach to explore how quantitative and non-quantitative data constrain models of apoptosis execution within a missing data context. We find model prediction accuracy and certainty strongly depend on rigorous data-driven formulations of the measurement, and the size and make-up of the datasets. For instance, two orders of magnitude more ordinal (e.g., immunoblot) data are necessary to achieve accuracy comparable to quantitative (e.g., fluorescence) data for calibration of an apoptosis execution model. Notably, ordinal and nominal (e.g., cell fate observations) non-quantitative data synergize to reduce model uncertainty and improve accuracy. Finally, we demonstrate the potential of a data-driven Measurement Model approach to identify model features that could lead to informative experimental measurements and improve model predictive power.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Soil Water Percolation Flux, April 2017 to March 2019, BR-Ma2, Manaus

Soil water percolation flux measurements derived from six passive wick flux meters across three topographic positions (valley, slope and plateau). Data has been processed to compute the mean for each topographic position where two flux meters were installed at each topographic position. Missing data represented a few percent of the total data set and were filled using two approaches. In the event one of the flux meters malfunctioned, we used data from the other sensor from the same topographic position without averaging. When both sensors were not working, such as during the period from September to October 2017 for the slope and valley and July 2018 for the plateau, data was filled using a nonlinear regression model that was based on local precipitation data and coefficients that were empirically derived for each topographic position. The metadata tab included in the .csv has additional information on locations where the sensors were installed, and other installation/maintenance details. Contact ksolander@lanl.gov if you need to use this dataset for additional information.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomic prediction (GP)↗

DOE OSTI2021

Three-dimensional coherent X-ray diffraction imaging via deep convolutional neural networks

Abstract As a critical component of coherent X-ray diffraction imaging (CDI), phase retrieval has been extensively applied in X-ray structural science to recover the 3D morphological information inside measured particles. Despite meeting all the oversampling requirements of Sayre and Shannon, current phase retrieval approaches still have trouble achieving a unique inversion of experimental data in the presence of noise. Here, we propose to overcome this limitation by incorporating a 3D Machine Learning (ML) model combining (optional) supervised learning with transfer learning. The trained ML model can rapidly provide an immediate result with high accuracy which could benefit real-time experiments, and the predicted result can be further refined with transfer learning. More significantly, the proposed ML model can be used without any prior training to learn the missing phases of an image based on minimization of an appropriate ‘loss function’ alone. We demonstrate significantly improved performance with experimental Bragg CDI data over traditional iterative phase retrieval algorithms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

A Robust Event Diagnostics Platform: Integrating Tensor Analytics and Machine Learning into Real-time Grid Monitoring

The objective of this project is to develop a robust event diagnostics (RED) platform by integrating state-of-the-art tensor analytics and machine learning into real-time grid monitoring. The proposed platform can effectively analyze and discover the information hiding within the provided PMU data for effective real-time grid monitoring. The proposed RED platform provides a set of robust diagnostics tools for grid operation and management, including 1) data quality assessment, 2) data completion, 3) event detection, and 4) robust event classification. All the functionalities of the RED platform can help the operator to make informed decisions and respond in a timely manner. The developed RED platform will serve as an innovative advisory tool to reliably identify key events and discover new insights about the events and grid characteristics in the PMU data, and contribute to the efficient, safe, reliable operation and design of the nation’s electric system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties

Connecting a material's surface chemistry with its electrocatalytic performance is one of the major questions in analytical electrochemistry. This is especially important in many sensor applications where analytes from complex media need to be measured. Unfortunately, today this connection is still largely missing except perhaps for the most simple ideal model systems. Here we present an approach that can be used to obtain insights about this missing connection and apply it to the case of carbon nanomaterials. In this paper we show that by combining advanced computational techniques augmented by machine learning methods with x-ray absorption spectroscopy (XAS) and electrochemical measurements, it is possible to obtain a deeper understanding of the correlation between local surface chemistry and electrochemical performance. As a test case we show how by computationally assessing the growth of amorphous carbon (a-C) thin films at the atomic level, we can create computational structural motifs that may in turn be used to deconvolute the XAS data from the real samples resulting in local chemical information. Then, by carrying out electrochemical measurements on the same samples from which x-ray spectra were measured and that were further characterized computationally, it is possible to gain insight into the interplay between the local surface chemistry and electrochemical performance. To demonstrate this methodology, we proceed as follows: after assessing the basic electrochemical properties of a-C films, we investigate the effect of short HNO 3 treatment on the sensitivity of these electrodes towards an inner sphere redox probe dopamine to gain knowledge about the influence of altered surface chemistry to observed electrochemical performance. Overall, these results pave the way towards a more general assessment of electrocatalysis in different systems and provide the first steps towards data driven tailoring of electrode surfaces to gain optimal performance in a given application.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Quantitative measurements of dislocations in metals for advancing predictive simulations

LLNL applications require scientists to predict how materials evolve under various thermomechanical conditions. While this is achieved through physics-based simulations, uncertainty in the predictions of mechanical properties remains a serious challenge that limits the predictive capabilities of models because we lack methods to compare predictions of atomic-scale defects (dislocations) with experimental measurements. High energy X-ray diffraction (HEXRD) is the most relevant technique that can provide the necessary statistical information on dislocations. However, this technique is not yet quantitative because we lack a precise understanding of the relationship between X-ray diffraction patterns and the underlying material dislocation content and arrangements. To address this need, we used our novel computational X-ray diffraction method to simulate the effect of dislocations on the diffraction patterns. We compared virtual and experimental diffraction patterns. Results allowed us to clearly establish the relationship between X-ray diffraction patterns and the underlying dislocation structures, proving that it is feasible to quantitatively measure dislocation statistics with HEXRD. This project delivered a method that can provide the missing piece to LLNL’s mechanical property simulations in advanced metals by obtaining experimentally long-needed quantitative dislocation data, which could fully enable predictive capabilities.

36 MATERIALS SCIENCE↗

NASA NTRS2000

Mars Scout: Micromissions to Investigate Martian Environments

Environments can be local, regional, or global. They can include one or more geological, morphological, climatological, and biological types. An environment also represents all the interactions that take place in the identified boundaries. Current planned missions to Mars in the Surveyor Program assume a good knowledge of the Martian environment that we do not have because it cannot be obtained only from orbit. There is a missing step between orbital data and the complex Surveyor missions to be landed that needs to be filled. The Ames/IRSPS Scout Mission Concept originally proposed in February 1999 filled this gap by landing a series of small (less than 10 kgs. each) scout missions. The Mars Environment Scout Mission Concept is being developed to explore the possibility of sending a series of small, simple, and inexpensive stations to the surface of Mars. The objective(s) would be to document either: (a) the environmental diversity of Mars, (b) a specific Martian environment, and/or (c) a region of interest. This type of mission will provide critical information about environments that is currently not available, and could also be used as precursors helping the design, preparation, and planning of more complex future missions to come.

Cabrol, N. A.↗