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NASA NTRS2012

Steps Toward an EOS-Era Aerosol Type Climatology

We still have a way to go to develop a global climatology of aerosol type from the EOS-era satellite data record that currently spans more than 12 years of observations. We have demonstrated the ability to retrieve aerosol type regionally, providing a classification based on the combined constraints on particle size, shape, and single-scattering albedo (SSA) from the MISR instrument. Under good but not necessarily ideal conditions, the MISR data can distinguish three-to-five size bins, two-to-four bins in SSA, and spherical vs. non-spherical particles. However, retrieval sensitivity varies enormously with scene conditions. So, for example, there is less information about aerosol type when the mid-visible aerosol optical depth (AOD) is less that about 0.15 or 0.2, or when the range of scattering angles observed is reduced by solar geometry, even though the quality of the AOD retrieval itself is much less sensitive to these factors. This presentation will review a series of studies aimed at assessing the capabilities, as well as the limitations, of MISR aerosol type retrievals involving wildfire smoke, desert dust, volcanic ash, and urban pollution, in specific cases where suborbital validation data are available. A synthesis of results, planned upgrades to the MISR Standard aerosol algorithm to improve aerosol type retrievals, and steps toward the development of an aerosol type quality flag for the Standard product, will also be covered.

Kahn, Ralph A.↗

DOE OSTI2026

Validation Studies of RELAP5-3D for High-Temperature Gas-Cooled Reactor Analysis Using a Refined RELAP5-3D Model of the High Temperature Test Facility

RELAP5-3D has been used extensively for high-temperature gas-cooled reactor (HTGR) analysis, but such analysis lies outside the validation basis for the code. Oregon State University (OSU) and the United States Department of Energy’s (DOE) Advanced Reactor Technologies (ART) – Gas-cooled reactor campaign worked together to design and operate the High Temperature Test Facility (HTTF) at OSU to provide validation data for prismatic HTGR thermal hydraulics analysis. Work using a previous RELAP5-3D model of HTTF demonstrated the ability to reproduce trends in HTTF data but an inability to reproduce the values measured in multiple experiments within the uncertainty. It was hypothesized that a new model with a finer radial nodalization would perform better for HTTF analysis. In this paper, we present the development of that more refined model and analyze HTTF experiments PG-27 and PG-29, a pressurized (PCC) and depressurized conduction cooldown (DCC) transient. Comparing PG-27 results to experimental data shows a better prediction of steady state and transient temperatures; however, a deeper dive reveals that better transient temperature predictions are a result of better initial conditions. The transient temperature rise in the core is comparable between the two models, but the legacy model predicts temperatures in the reflectors better. The new model demonstrates the ability to predict unique temperatures in each sector of the core during PG-29, capturing the azimuthal asymmetry; however, the temperature predictions still differ from measured temperatures. One hypothesis is that differences between the assumed and actual power distribution leads to the underprediction of the individual block temperatures. These results suggest that gaps and uncertainties in the measured boundary conditions for the HTTF tests do not allow to fully validate RELAP5-3D for prismatic HTGR analyses. The authors suspect that some of the differences between predicted and measured temperatures may be a result of uncertainties associated with HTTF itself rather than RELAP5-3D. We demonstrated improved validation for steady-state analysis, but significantly improved transient performance has yet to be recognized.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1982

Helicopter simulation validation using flight data

A joint NASA/Army effort to perform a systematic ground-based piloted simulation validation assessment is described. The best available mathematical model for the subject helicopter (UH-60A Black Hawk) was programmed for real-time operation. Flight data were obtained to validate the math model, and to develop models for the pilot control strategy while performing mission-type tasks. The validated math model is to be combined with motion and visual systems to perform ground based simulation. Comparisons of the control strategy obtained in flight with that obtained on the simulator are to be used as the basis for assessing the fidelity of the results obtained in the simulator.

Key, D. L.↗

DOE OSTI2022

Modeling Approach to Critical in the Upcoming CERBERUS Experiment

The planned Critical Experiment Reflected By coppEr to betteR Understand Scattering (CERBERUS) seeks to maximize sensitivity to elastic neutron scattering in the intermediate energy region (0.625 eV to 100 keV). It will be performed near the end of FY 2023 at the National Criticality Experiments Research Center (NCERC). Very few International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks are sensitive to copper in this region. Creating a benchmark sensitive in this area will make the Zeus benchmark series, an intermediate benchmark evaluation that uses a copper reflector, more useful for code and nuclear data validation. Approaching criticality in a safe manner is of utmost importance to avoid a criticality accident, which would present a safety concern and could cause damage to equipment. The two rules that are followed closely to ensure that a criticality accident does not occur are the 3/4 rule and the 1/2 rule. The 3/4 rule states that no more than 3/4 of a critical mass can be assembled by hand, and the 1/2 rule states that no more than 1/2 of the material expected to reach criticality, or 1/2 the distance needed to reach criticality, can be added before another measurement of the count rate has been taken. This work will discuss the approach to criticality as modeled in MCNP6® 1 particle transport code with the ENDF/B- VIII.0 cross-section library and the .00c data library.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

A data-driven peridynamic continuum model for upscaling molecular dynamics

Nonlocal models, including peridynamics, often use integral operators that embed lengthscales in their definition. However, the integrands in these operators are difficult to define from the data that are typically available for a given physical system, such as laboratory mechanical property tests. In contrast, molecular dynamics (MD) does not require these integrands, but it suffers from computational limitations in the length and time scales it can address. To combine the strengths of both methods and to obtain a coarse-grained, homogenized continuum model that efficiently and accurately captures materials’ behavior, we propose a learning framework to extract, from MD data, an optimal Linear Peridynamic Solid (LPS) model as a surrogate for MD displacements. To maximize the accuracy of the learnt model we allow the peridynamic influence function to be partially negative, while preserving the well-posedness of the resulting model. To achieve this, we provide sufficient well-posedness conditions for discretized LPS models with sign-changing influence functions and develop a constrained optimization algorithm that minimizes the equation residual while enforcing such solvability conditions. This framework guarantees that the resulting model is mathematically well-posed, physically consistent, and that it generalizes well to settings that are different from the ones used during training. We illustrate the efficacy of the proposed approach with several numerical tests for single layer graphene. Our two-dimensional tests show the robustness of the proposed algorithm on validation data sets that include thermal noise, different domain shapes and external loadings, and discretizations substantially different from the ones used for training.

homogenization↗

NASA NTRS2005

Assessment of the Broadleaf Crops Leaf Area Index Product from the Terra MODIS Instrument

The first significant processing of Terra MODIS data, called Collection 3, covered the period from November 2000 to December 2002. The Collection 3 leaf area index (LAI) and fraction vegetation absorbed photosynthetically active radiation (FPAR) products for broadleaf crops exhibited three anomalies (a) high LAI values during the peak growing season, (b) differences in LAI seasonality between the radiative transfer-based main algorithm and the vegetation index based back-up algorithm, and (c) too few retrievals from the main algorithm during the summer period when the crops are at full flush. The cause of these anomalies is a mismatch between reflectances modeled by the algorithm and MODIS measurements. Therefore, the Look-Up-Tables accompanying the algorithm were revised and implemented in Collection 4 processing. The main algorithm with the revised Look-Up-Tables generated retrievals for over 80% of the pixels with valid data. Retrievals from the back-up algorithm, although few, should be used with caution as they are generated from surface reflectances with high uncertainties.

Tan, Bin↗

DOE OSTI2025

Over three decades, and counting, of near-surface turbulent flux measurements from the Atmospheric Radiation Measurement (ARM) user facility

Processes mediating the coupling of terrestrial, aquatic, biospheric, and atmospheric systems influence weather, climate, and ecosystem dynamics via transfer of energy, momentum, water, and carbon (or other species). These exchange processes are quantified by measurements of near-surface turbulent fluxes. Understanding processes at these interfaces provides insight toward understanding and predicting current and future states within the Earth system. The Atmospheric Radiation Measurement (ARM) user facility has been conducting measurements of near-surface turbulent fluxes since the early 1990s at long-term fixed locations and shorter-term mobile deployments across the Earth. ARM has utilized two established methods for conducting these measurements: energy balance Bowen ratio (EBBR) and eddy covariance (EC). Primary measurements from the former include sensible and latent heat flux, while the latter also measures fluxes of momentum and carbon (primarily carbon dioxide, with methane fluxes measured at two locations to date). The EBBR systems have been deployed at 22 locations, and, to date, the EC systems have been deployed at over 50 sites, with plans for additional novel site locations in the future. Herein, the history, evolution, and key aspects of these instrument systems are documented, along with information on data quality assurance and post-processing, as well as best use practices. Additionally, three data validation experiments were recently conducted, and their key findings are summarized. Finally, ancillary datasets acquired by ARM, which can contextualize and aid interpretation of the near-surface turbulent flux measurements, are discussed. The datasets described herein include the eddy correlation flux measurement system: 30ECOR (https://doi.org/10.5439/1879993, Sullivan et al., 1997), 30QCECOR (https://doi.org/10.5439/1097546, Gaustad, 2003), ECORSF (https://doi.org/10.5439/1494128, Sullivan et al., 2019a), and associated AmeriFlux and Methane Value-Added Product, AMCMETHANE (https://doi.org/10.5439/1508268, Billesbach, 2011); the energy balance Bowen ratio system: 30EBBR (https://doi.org/10.5439/1023895, Sullivan et al., 1993) and 30BAEBBR (https://doi.org/10.5439/1027268, Gaustad and Xie, 1993); and the carbon dioxide flux measurement system: CO2FLX (https://doi.org/10.5439/1287574, https://doi.org/10.5439/1287575, https://doi.org/10.5439/1287576, Koontz et al., 2015a, b, c; https://doi.org/10.5439/1989774, https://doi.org/10.5439/1989776, https://doi.org/10.5439/1992202, Biraud and Chan, 2002a, b, c). These data can be found by searching the above data stream names at https://adc.arm.gov/discovery/#/results/ (last access: 8 September 2025).

Sullivan, Ryan C. [Argonne National Laboratory (AN↗

NASA NTRSDate not supplied

Verification of TROPOMI NO2 Product Using OMI NO2 algorithm

We evaluated S5P TROPOspheric Monitoring Instrument (TROPOMI) operational nitrogen dioxide (NO2) product by comparing with the NO2 retrievals from Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite. We compared spatially matched NO2 vertical column density (VCD) data from OMI and TROPOMI to identify any discrepancies between the two operational products. We also applied OMI Air-Mass Factor (AMF) algorithm to TROPOMI Slant Column Density (SCD) data (v02.03.01) aiming to create long-term merged NO2 Earth Science Data Record (https://disc.gsfc.nasa.gov/datasets/TROPOMI_MINDS_NO2_1.1/summary ). The algorithm (version 4.0) uses new Geometry-dependent Lambertian Equivalent surface Reflectivity (GLER) product available for each TROPOMI pixel. GLER is pre-calculated using the vector linearized discrete ordinate radiative transfer (VLIDORT) model, which uses as input high-resolution bidirectional reflectance distribution function (BRDF) information from NASA's Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the wind-dependent Cox–Munk wave-facet slope distribution over water, the latter with a contribution from the water-leaving radiance based on MODIS gap-filled in-water chlorophyll-a data. The GLER data, combined with consistently retrieved cloud parameters, provide improved information for the calculation of the scattering weight profiles. Additional AMF improvements result from using high resolution (0.25o latitude x 0.25o longitude) a priori NO2 profile shapes and other auxiliary information from the Global Modeling Initiative (GMI) Replay simulation sampled using S5P orbital simulator. Our TROPOMI_MINDS_NO2 algorithm employs the stratosphere-troposphere separation scheme, de-striping, and surface snow/ice treatment consistently with the latest OMI NO2 re-processing (version 4). We evaluate the TROPOMI_MINDS_NO2 product by comparing with the S5P operational NO2 product as well as with independent NO2 observations from ground-based Pandora and aircraft observations. Our results indicate that the new TROPOMI_MINDS_NO2 retrievals are generally higher than the S5P operational NO2 product over polluted regions and show improved agreement with independent validation data.

TROPOMI↗

NASA NTRSDate not supplied

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Random Forest Classification

Mapping the extent of floodwaters following extreme rainfall aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. This study seeks to determine how accurately maps of inundation can be generated from L-band SAR imagery through Random Forest classification. Once the extent of water and inundated vegetation is classified, cleanup operations are performed using fuzzy logic to reduce false detections. Estimates of water extent are then combined with datasets describing the distribution of population, buildings, and roads throughout the domain to evaluate societal impacts. Results from the Hurricane Florence case study will be discussed along with the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander Melancon↗

NASA NTRS2018

Aircraft System Noise Prediction Uncertainty Quantification for a Hybrid Wing Body Subsonic Transport Concept

Aircraft system level noise prediction for advanced, unconventional concepts has undergone significant improvement over the past two decades. The prediction modeling uncertainty must be quantified so that potential benefits of unconventional configurations, which are outside of the range of empirical models, can be reliably assessed. This paper builds on previous work in an effort to improve estimates of element prediction uncertainties where the prediction methodology has been improved, or new experimental validation data are available, to provide an estimate of the system level uncertainty in the prediction process. In general, the uncertainty of the prediction will be strongly dependent on the aircraft configuration as well as which technologies are integrated. While the quantitative uncertainty values contained here are specific to the hybrid wing body design presented, the underlying process is the same regardless of configuration. A refined process for determining the uncertainty for each element of the noise prediction is detailed in this paper. The system level uncertainty in the prediction of the aircraft noise is determined at the three certification points, using a Monte Carlo method. Comparisons with previous work show a reduction of 1 EPNdB in the 95%coverage interval of the cumulative noise level. The largest impediment for continued reduction in uncertainty for the hybrid wing body concept is the need for improved modeling and validation experiments for fan noise, propulsion airframe aeroacoustic effects, and the Krueger flap, which comprise the bulk of the uncertainty in the cumulative certification noise level.

June, Jason C.↗

NASA NTRS2014

Flash Infrared Thermography Contrast Data Analysis Technique

This paper provides information on an IR Contrast technique that involves extracting normalized contrast versus time evolutions from the flash thermography inspection infrared video data. The analysis calculates thermal measurement features from the contrast evolution. In addition, simulation of the contrast evolution is achieved through calibration on measured contrast evolutions from many flat-bottom holes in the subject material. The measurement features and the contrast simulation are used to evaluate flash thermography data in order to characterize delamination-like anomalies. The thermal measurement features relate to the anomaly characteristics. The contrast evolution simulation is matched to the measured contrast evolution over an anomaly to provide an assessment of the anomaly depth and width which correspond to the depth and diameter of the equivalent flat-bottom hole (EFBH) similar to that used as input to the simulation. A similar analysis, in terms of diameter and depth of an equivalent uniform gap (EUG) providing a best match with the measured contrast evolution, is also provided. An edge detection technique called the half-max is used to measure width and length of the anomaly. Results of the half-max width and the EFBH/EUG diameter are compared to evaluate the anomaly. The information provided here is geared towards explaining the IR Contrast technique. Results from a limited amount of validation data on reinforced carbon-carbon (RCC) hardware are included in this paper.

Koshti, Ajay↗

NASA NTRS2019

Three Red Suns in the Sky: A Transiting, Terrestrial Planet in a Triple M-dwarf System at 6.9 pc

We present the discovery from Transiting Exoplanet Survey Satellite (TESS) data of LTT 1445Ab. At a distance of 6.9 pc, it is the second nearest transiting exoplanet system found to date, and the closest one known for which the primary is an M dwarf. The host stellar system consists of three mid-to-late M dwarfs in a hierarchical configuration, which are blended in one TESS pixel. We use MEarth data and results from the Science Processing Operations Center data validation report to determine that the planet transits the primary star in the system. The planet has a radius of {1.38}_{-0.12}^{+0.13} {R}_{\oplus }, an orbital period of {5.35882}_{-0.00031}^{+0.00030} days, and an equilibrium temperature of {433}_{-27}^{+28} K. With radial velocities from the High Accuracy Radial Velocity Planet Searcher, we place a 3σ upper mass limit of 8.4 {M}_{\oplus } on the planet. LTT 1445Ab provides one of the best opportunities to date for the spectroscopic study of the atmosphere of a terrestrial world. We also present a detailed characterization of the host stellar system. We use high-resolution spectroscopy and imaging to rule out the presence of any other close stellar or brown dwarf companions. Nineteen years of photometric monitoring of A and BC indicate a moderate amount of variability, in agreement with that observed in the TESS light-curve data. We derive a preliminary astrometric orbit for the BC pair that reveals an edge-on and eccentric configuration. The presence of a transiting planet in this system hints that the entire system may be co-planar, implying that the system may have formed from the early fragmentation of an individual protostellar core.

Binaries↗

NASA NTRS2023

Oregon Coast Range Ecological Conservation: Mapping Recent Logging Within Drinking Watersheds of Oregon’s Coastal Range to Support Future Resource Management Policies

Logging operations are widespread across the Oregon Coast Range and conventional logging practices pose a risk of contamination to surface water quality. The NASA DEVELOP Oregon Coast Ecological Conservation team partnered with nonprofit Oregon Wild to quantify the extent of clearcutting and commercial thinning in 80 Coast Range drinking watersheds between 2000 and 2022. This project used all available Landsat data from 1997 through June 2023 in Google Earth Engine. Sensors used include Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, and Landsat 9 Operational Land Imager-2. The Continuous Change Detection and Classification (CCDC) algorithm was used with Landsat observations to identify clearcutting patches. Percent change in summer median Landsat Normalized Difference Vegetation Index (NDVI) images were used to identify areas of forest disturbance including commercial thinning. The team concluded that logging, including both clearcutting and commercial thinning, impacted 31% of forested area in drinking watersheds and the intensity of logging remained consistent from year to year. Clearcutting occurred primarily on private land while commercial thinning occurred primarily on state and federal lands. This study showed that CCDC effectively identifies clearcutting, and percent change in NDVI successfully identifies disturbances including commercial thinning. Key constraints included the lack of field validation data and the inability to attribute disturbances to logging with certainty. Ultimately, this study identified the drinking watersheds and communities most likely to be impacted by logging activity. These results can inform legislation aimed at balancing the commercial and environmental benefits of forestlands.

Logging↗

DOE OSTI2021

Investigating the relation between instantaneous driving decisions and safety critical events in naturalistic driving environment

The availability of large-scale naturalistic driving data provides enormous opportunities for studying relationships between instantaneous driving decisions prior to involvement in safety critical events (SCEs). This study investigates the role of driving instability prior to involvement in SCEs. While past research has studied crash types and their contributing factors, the role of pre-crash behavior in such events has not been explored as extensively. The research demonstrates how measures and analysis of driving volatility can be leading indicators of crashes and contribute to enhancing safety. Highly detailed microscopic data from naturalistic driving are used to provide the analytic framework to rigorously analyze the behavioral dimensions and driving instability that can lead to different types of SCEs such as roadway departures, rear end collisions, and sideswipes. Modeling results reveal a positive association between volatility and involvement in SCEs. Specifically, increases in both lateral and longitudinal volatilities represented by Bollinger bands and vehicular jerk lead to higher likelihoods of involvement in SCEs. Further, driver behavior related factors such as aggressive driving and lane changing also increases the likelihood of involvement in SCEs. Driver distraction, as represented by the duration of secondary tasks, also increases the risk of SCEs. Likewise, traffic flow parameters play a critical role in safety risk. The risk of involvement in SCEs decreases under free flow traffic conditions and increases under unstable traffic flow. Further, the model shows prediction accuracy of 88.1 % and 85.7 % for training and validation data. These results have implications for proactive safety and providing in-vehicle warnings and alerts to prevent the occurrence of such SCEs.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

ProtoDUNE Vertical Drift needs a selective triggering algorithm. The detector sits on Earth's surface, so cosmic activity dominates its data. Our goal in this paper is to trigger on neutrino events more robustly than the current deployed Analog-to-Digital Converter Simple Window (ADCSW) model and, eventually, search for signals of Beyond Standard Model (BSM) physics at DUNE as our ultimate North Star objective. As a step towards this goal, we evaluate a Wasserstein Normalized Autoencoder (WNAE) on simulated collection-plane only windows of shape $1\times10\times10$ where Neutrinos act as our BSM-proxy and Cosmic-ray Muons serve as our learned background. The network parameters are fitted using only cosmic-ray muon events as background in order to maintain an unsupervised pipeline. Training uses finite-step Langevin $x^-$ samples, positive-sample reconstruction energy, and an empirical sliced $2$-Wasserstein objective to learn a normalized Boltzmann energy model. We then calibrate on a nominal $5\,\mathrm{Hz}$ operating threshold calculated from cosmic validation data. Both WNAE and ADCSW accept 311 of 194,083 held-out cosmic background events at this $5\,\mathrm{Hz}$ threshold. We found that WNAE accepts 9,677 of 34,634 neutrino-proxy events $(27.9\pm0.24)\%$, compared with 10,076 $(29.1\pm0.24)\%$ for ADCSW, an observed WNAE-minus-ADCSW difference of $-1.15\%$. At another nominal $2\,\mathrm{Hz}$ target threshold, the corresponding efficiencies are $(20.5\pm0.22)\%$ and $(22.6\pm0.22)\%$, respectively. Of the WNAE-selected neutrino proxies at $5\,\mathrm{Hz}$, $(20.8\pm0.4)\%$ of the classified neutrino-proxy events are unique to WNAE, where the uncertainty is an absolute binomial standard error of $0.4\%$.

Zheng, Jake [U. Chicago (main)] (ORCID:00090002189↗

DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

Zheng, Jake [Chicago U.] (ORCID:0009000218901379)↗

NASA NTRSDate not supplied

NASA Earth Systems Digital Twins (ESDT)

"Similarly to artificial intelligence, which is now revolutionizing many aspects of our daily lives, Earth system digital twin technologies have the potential to revolutionize the way Earth Science research will be conducted in the future, and how results and knowledge from this research will provide information to support decision making and yield impactful societal benefits. An Earth System Digital Twin or ESDT is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system as accurately and timely as possible; second, allows for computing forecasts of future states under nominal assumptions and based on the current replica; and third, offers the capability to investigate many hypothetical scenarios under varying impact assumptions. In other words, an ESDT provides the integrated What-Now, What-Next, and What-If pictures of the Earth or Earth system, by continuously ingesting newly observed data and by leveraging multiple interconnected models, machine learning as well advanced computing and visualization capabilities. Digital twins have been developed in engineering since 2002, but the interest in digital twins for the Earth domain is more recent and stems from the convergence of several developments: - The huge amount of diverse data that has now been collected continuously for more than 50 years, and that is becoming more and more difficult to access, understand, and utilize. - At the same time, because of climate change and its impacts the information produced by all of this data is becoming of interest to many new non-traditional users for analyzing and predicting various phenomena. - Because of advances in computational and visualization capabilities and the parallel unprecedented development of machine learning (ML), extracting relevant information from these large amounts of data and running complex models faster has become possible. As a result, it is becoming necessary and possible to build intuitive and interactive frameworks that will enable users with various skill levels and/or organizational hierarchy levels to easily access large amounts of targeted information along with the relevant tools and models (Earth system and human activity models), to support them in analyzing and visualizing this information, to help them understand interactions among models, to visualize the potential outcomes of various impacts, and to support decision or policy making. The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. With all these interests at stake, the challenges of building optimal digital twins are many and complex. The first challenge is to determine if a Digital Twin should be global or local, and multi-domain or thematic. For example, some domains such as Climate or Weather will require a global Digital Twin or Digital Twin capabilities while science areas such as Biodiversity might be more local. We can also envision that multiple thematic ESDTs, e.g., Air Quality, Wildfires, Hydrology could be federated or provide input to other ESDTs, either on a regional level or to a more global ESDT. Overall, we can imagine a future “web” of Digital Twins co-existing in a hierarchy or in a network, and capable of being connected or federated depending on the needs. This last point brings up the very important challenge of interoperability, including standards and protocols that will need to be built into these systems from the beginning. Each individual digital twin would have full flexibility in internal construction but would need standards-based interfaces (input and output) or hooks to make it compatible with others. Another challenge when building digital twins will be to decide how to organize each digital replica. Based on the applications targeted by the DT under implementation, various amounts and types of raw data, Analysis Ready Data (ARD) and information will need to be incorporated. Depending on the required latencies and needs of the users, various solutions can be considered, including Data Cubes, Data Lakes, pointers, or computing information on demand. We envision that each ESDT will choose a solution adapted to its specific objectives. Another important challenge is the type(s) of visualization that will be used, as well as the level of interactivity and refresh rate that will be required. Again, this will depend on the objectives of the ESDT, but also on the various users’ needs. In most cases, several types of visualizations and human interfaces will need to be offered depending on the projected users of that system. In parallel to the challenges highlighted above, there are also many tools and technologies that will need to be developed or improved for all types of digital twins. Among those are improved machine learning technologies, for example providing explainability, but also ML techniques for causality and providing a better integration of physics models. Additionally, reliable uncertainty quantification methods will be needed for all ESDT components, from validating data fusion and assimilation to assessing the accuracy of ML models and weighing the values of decisions supported by those systems. This presentation introduces the ESDT concept, presents several ESDT use cases, and a proposed ESDT architecture framework, as well as various technologies being developed by the Advanced Information Systems Technology (AIST) Program."

Earth Science Remote Sensing; Information Systems↗

DOE OSTI2022

WUS256: An Adjoint Waveform Tomography Model of the Crust and Upper Mantle of the Western United States for Improved Waveform Simulations

Abstract We report a new model (WUS256) of radially anisotropic seismic wavespeeds of the crust and upper mantle of the western United States (WUS) obtained from adjoint waveform tomography for the purpose of improving synthetic waveform fits to observed data. WUS256 is based on inversion of over 94,000 waveforms from 72 earthquakes recorded by nearly 3,400 stations. We started with the SPiRaL global model (Simmons et al., 2021, https://doi.org/10.1093/gji/ggab277 ) and waveforms in the period band of 50–120 s. We followed a conservative multiscale inversion approach with eight stages and 256 total inversion iterations which enabled monotonic misfit reduction to 20‐s minimum‐period waves. WUS256 relied on time‐frequency (TF) phase misfits and a trust region limited memory Broyden–Fletcher–Goldfarb–Shanno (L‐BFGS) optimization. Hessian‐vector products were used to qualitatively assess model resolution. Results indicate that WUS256 has good coverage of the continental regions to depths of about 150 km and is able to resolve features on lateral scales of about 200 km. We quantify waveform fits by the reduction in TF and normalized amplitude difference misfits between WUS256 and the SPiRaL starting model. WUS256 significantly improves waveform fits with misfit reduction 64% for both inversion and validation data sets compared to the SPiRaL starting model and shows even better fits compared to other models. Waveform fits illustrate that WUS256 reproduces body‐waves, fundamental mode surface waves as well as late arriving dispersed and/or scattered short period surface waves. The improvement in waveform fit indicates that WUS256 can be used to reproduce path effects on regional complete waveforms and moment tensor inversions.

58 GEOSCIENCES↗