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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Planetary Boundary-Layer Height (PBLHT) Value-Added Product: Remote-Sensing Retrievals

The planetary boundary layer (PBL) is fundamental to numerous atmospheric processes, including aerosol mixing and transport, cloud evolution, and precipitation formation. A critical parameter in these studies is the PBL height (PBLHT). This vertical depth is essential for characterizing PBL structures in numerical simulations and serves as a primary metric for estimating flux exchanges between the Earth’s surface and the atmosphere. Radiosonde (SONDE) observations provide high-vertical-resolution measurements of temperature and moisture profiles and are widely used to estimate PBLHT (Liu and Liang 2010, Seidel et al. 2010). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s PBLHT value-added product (VAP) for radiosonde measurements, known as PBLHTSONDE, applies three commonly used methods—the Heffter (1980) method, the Liu and Liang (2010) method, and the bulk Richardson number approach (Seibert et al. 2000)—to derive PBLHT. The PBLHTSONDE VAP operates routinely at ARM observatories and mobile facilities, with data available from the ARM Data Center shortly after sounding observations are collected (Sivaraman et al. 2013). However, radiosonde observations are limited by their low temporal resolution. Most stations launch soundings only twice daily, which constrains the ability to investigate and characterize the temporal evolution of the PBL using radiosonde data alone. The use of continuous remote-sensing observations provides high temporal resolution of PBLHT estimates. These observations include aerosol lidars (Dang et al. 2019, Su et al. 2020), Doppler lidar (DL; Tucker et al. 2009, Krishnamurthy et al. 2021), and water vapor and/or temperature lidars and radiometers (Turner et al. 2014). These observations provide valuable data on the PBL’s thermodynamic properties (e.g., water vapor and/or temperature lidars and radiometers), dynamic properties (e.g., DL), and distribution of tracer substances (e.g., aerosol lidars), all of which can be used to estimate PBLHT. ARM developed PBLHT estimates from the micropulse lidar (MPL; PBLHTMPL), Doppler lidar (PBLHTDL), and combined Raman lidar (RL)/atmospheric emitted radiance interferometer (AERI) thermodynamic profiles (PBLHTTHERMO). Each estimate captures different physical characteristics of the boundary layer—aerosol tracers, vertical velocity turbulence, and thermodynamic structure—and exhibits distinct strengths and limitations depending on the PBL regime and time of day. In addition, the ARM ceilometer (CEIL) provides three potential PBLHT candidates derived from the vendor's built-in algorithm. Building on these individual retrievals, ARM developed the PBLHTBEML VAP, which combines the four remote-sensing-based estimates with ancillary meteorological variables using the machine learning approach of Zhang et al. (2025) to produce a best-estimate PBLHT at 10-minute resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part I: Dynamical Downscaling

Abstract New simulations at 12-km grid spacing with the Weather and Research Forecasting (WRF) Model nested in the MPI Earth System Model (ESM) are used to quantify possible changes in wind power generation potential as a result of global warming. Annual capacity factors (CF; measures of electrical power production) computed by applying a power curve to hourly wind speeds at wind turbine hub height from this simulation are also used to illustrate the pitfalls in seeking to infer changes in wind power generation directly from low-spatial-resolution and time-averaged ESM output. WRF-derived CF are evaluated using observed daily CF from operating wind farms. The spatial correlation coefficient between modeled and observed mean CF is 0.65, and the root-mean-square error is 5.4 percentage points. Output from the MPI-WRF Model chain also captures some of the seasonal variability and the probability distribution of daily CF at operating wind farms. Projections of mean annual CF (CF A ) indicate no change to 2050 in the southern Great Plains and Northeast. Interannual variability of CF A increases in the Midwest, and CF A declines by up to 2 percentage points in the northern Great Plains. The probability of wind droughts (extended periods with anomalously low production) and wind bonus periods (high production) remains unchanged over most of the eastern United States. The probability of wind bonus periods exhibits some evidence of higher values over the Midwest in the 2040s, whereas the converse is true over the northern Great Plains. Significance Statement Wind energy is playing an increasingly important role in low-carbon-emission electricity generation. It is a “weather dependent” renewable energy source, and thus changes in the global atmosphere may cause changes in regional wind power production (PP) potential. We use PP data from operating wind farms to demonstrate that regional simulations exhibit skill in capturing actual power production. Projections to the middle of this century indicate that over most of North America east of the Rocky Mountains annual expected PP is largely unchanged, as is the probability of extended periods of anomalously high or low production. Any small declines in annual PP are of much smaller magnitude than changes due to technological innovation over the last two decades.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Retrieval of Cloud Liquid Water Using Microwave Signals from LEO Satellites: A Feasibility Study through Simulations

A novel method, using low Earth orbit (LEO) satellite microwave communication links for cloud liquid water measurements, is introduced in this paper. The feasibility of this approach is studied through simulations of the retrieval system including a LEO satellite communicating with a group of ground receivers equipped with signal-to-noise ratio (SNR) estimators, a synthetic cloud attenuation field and a tomographic retrieval algorithm. Rectangular and Gaussian basis functions are considered to define the targeted field. Simulation results suggest that the proposed least-squares based retrieval algorithm produces satisfactory outcomes for both types of basis functions. The root-mean-square error of the retrieved field is around 0.2 dB/km, with the range of the reference field as 0 to 2.35 dB/km. It is also confirmed that the partial retrieval of the cloud field is achievable when a limited number of receivers with restricted locations are available. The retrieval outcomes exhibit properties of high resolution and low error, indicating that the proposed approach has great potential for cloud observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

New Measurements of the Lyα Forest Continuum and Effective Optical Depth with LyCAN and DESI Y1 Data

Abstract We present the Ly α Continuum Analysis Network (LyCAN), a convolutional neural network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of 1040–1600 Å based on the red side of the Ly α emission line (1216–1600 Å). We developed synthetic spectra based on a Gaussian mixture model representation of nonnegative matrix factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift ( z < 0.2) Hubble Space Telescope/Cosmic Origins Spectrograph (COS) quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms principal component analysis (PCA) and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of 2.1 ≤ z ≤ 4.2 and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power law of the form τ ( z ) = τ 0 ( 1 + z ) γ to our measurements and find τ 0 = (2.46 ± 0.14) × 10 −3 and γ = 3.62 ± 0.04. Our results show particular agreement with high-resolution, ground-based observations around z = 2, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Grating-Based Imaging-Scattering with Portable Neutron Generator

Company: Adelphi Technology, Inc. Title: Grating-Based Imaging-Scattering with Portable Neutron Generator PI: Dr. Jay Theodore Cremer, Jr. Topic: 26a Statement of the problem or situation that is being addressed. Successful plant growth depends upon an efficient and robust root system. The plant root is part of a larger system of water and microbial flows in the soil system. While much effort has been exerted to develop an imaging system for water, microbes, and roots, the problem is challenging, and no widely accepted imaging method currently exists. The optical solutions use a highly modified soil system. X-ray imaging methods are insensitive to the soft tissues in the presence of sand. Thermal neutron imaging has been often tested, but found inadequate, due to limited access and low image resolution. This project will develop a new strategy for neutron imaging of plant/soil systems. The project will allow long duration experiments in greenhouse environments and increase the image information content to the micron scale. General statement of how this problem is being addressed. Portable, rugged thermal and fast neutron sources are being developed where portable means a two-soldier team can carry the source and power unit to survey rough terrain for explosives. In the past decade, microfabrication of X-ray and thermal/cold neutron optics has opened a new imaging strategy. The standard transmission image is now supplemented with simultaneous acquisition of a phase contrast image and an image revealing scattering features. In materials science, the interferometric neutron scattering image has been used to detect early crack formation in stressed additive manufacturing test samples. The detection requires sensitivity to scattering features at the 1-micron scale. By addition of our proposed grating-optic to Adelphi Technology’s radiographic/tomographic imaging system, which is based on portable thermal neutron source, the resulting thermal neutron scatter image of the plant/soil system, will reveal details at 1-micron. Commercial Applications and Other Benefits Neutron interferometry imaging has greater penetration through large metal components compared to industrial X-ray imaging. The low-cost, large area optics developed for greenhouse applications, combined with the robust, portable neutron generator, can then be marketed as a system for inspection of additive manufactured components. In the aerospace industry, all freshly printed components are validated with X-ray CT. Scheduled maintenance again requires X-ray CT as the ability to predict aerospace component lifetime does not yet exist. Large aerospace components are only partially observed with X-ray imaging. Key Words Neutron radiography/tomography, grating interferometry, thermal neutron generator imaging, plant root and soil imaging, rhizosphere imaging, deployable neutron imaging systems Summary for Members of Congress A rugged, portable source of thermal neutrons is adapted for neutron interferometry imaging with the addition of low-cost, 3D printed optics. The first application of our proposed deployable, compact thermal neutron generator imaging system, using a grating optic, is plant root/soil science in greenhouse settings and agricultural laboratories.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Spectral Induced Polarization-Biogeochemical Relationships for Remediation Amendment Monitoring

Geophysical tools such as electrical resistivity (ER) can indirectly monitor subsurface changes in response to remedial injections. These methods exhibit relatively low spatial resolution compared to sediment core characterization but are advantageous due to the ability to collect measurements non-intrusively over time across large volumes of the subsurface. Moreover, along with confirmatory groundwater or core sampling, geophysical methods can be used during active biogeochemical remedies to monitor short-term contaminant transformations and mobility, as well as part of an overall strategy for long-term monitoring of subsurface contaminated sites. The use of alternating current spectral induced polarization (SIP) provides significantly more information than conventional geophysical methods like direct current ER. SIP allows for monitoring changes in both solution and surface conductivity by separation of real and imaginary conductivity, respectively, as well as surface capacitance. In principle, SIP can measure indicators of remedy progression such as precipitation reactions that sequester contaminants, potentially providing a better indication of amendment delivery and reactivity as compared to conventional ER methods. However, multiple processes and material properties have overlapping (interacting) electrical responses across a range of frequencies. Hence, the purpose of this scoping study was to evaluate if SIP can be used to monitor (a) amendment delivery and (b) precipitation and reactivity of amendments under consideration at Hanford. SIP measurements were collected in fully saturated columns packed with sand and Hanford formation sediments containing (a) amendments that were highly conductive with significant capacitance (zero valent iron – ZVI, sulfur modified iron – SMI) and (b) amendments that exhibited low electrical conductivity with a small capacitance (calcite, apatite, bismuth). The sand was a quartz material with homogenous particle size that exhibited a relatively low surface conductivity. It was used as a control for comparison with the sediments from the Hanford Site, which have a greater surface conductivity because of their complex mineralogy and heterogeneous particle size distribution and may have complex interactions with amendments. The amendment mass fraction was varied to represent the different stages and subsurface locations associated with the delivery of a remedy. The primary objective was to identify the solution and solid surface changes associated with the delivery amendments and their secondary reactions within the subsurface. The figure below summarizes results for the amendments tested through this project. The SIP phase shift or imaginary conductivity change for the high conductivity amendments was more than 10 times that of the low conductivity amendments, highlighting the relative ease of detection of ZVI and SMI independent of the background signal from sand or Hanford sediments. The ZVI phase shift and imaginary conductivity changes occur primarily at high frequency (> 100 Hz) whereas SMI changes were at low frequency (0.01 to 10 Hz). SIP signals of SMI also increased over time and the maximum shifted to lower frequencies. The low conductivity amendments (calcite, abiotic and biotic apatite, bismuth subnitrate) exhibited relatively small phase and imaginary conductivity changes when added to sediments. The changes were above minimum detection limits (0.5 mrad for phase shift, 0.03 µS/cm for imaginary conductivity) for the highest concentration except for the commercial bismuth material. The lowest amendment concentration that can be detected is likely sediment specific, as minerals in sediments (clays, magnetite, Fe-oxides) have some capacitance and, therefore, exhibit a variable phase shift.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Comparison of greenhouse gas emission estimates from six hydropower reservoirs using modeling versus field surveys

As with most aquatic ecosystems, reservoirs play an important role in the global carbon (C) cycle and emit greenhouse gases (GHG) as carbon dioxide (CO 2 ) and methane (CH 4 ). However, GHG emissions from reservoirs are poorly quantified, especially in temperate systems, resulting in high uncertainty. We compared reservoir C emission estimates and uncertainty of diffusive, ebullitive, and degassing pathways in six hydropower reservoirs in the southeastern United States among four data sources: two field-based surveys and two models (including the GHG Reservoir “G-res” Tool). We found that CH 4 diffusion was most similar across data sources (modeled minus observed, bias = - 21 g CO 2-eq m -2 y -1 ) and had low relative uncertainty (coefficient of variation, CV = 0.98). On the other hand, CO 2 diffusion was least consistent across data sources (bias = - 518 g CO 2-eq m -2 y -1 ). Both field surveys indicated strong negative CO 2 diffusion (i.e., CO 2 uptake) at all reservoirs, while G-res estimated positive CO 2 diffusion. By extension, total C emissions showed similar discrepancies, leading to high uncertainty in upscaling and interpreting reservoir source-sink dynamics. Finally, CH 4 ebullition had the highest relative uncertainty (CV = 2.77) due to high variability across sites. We discuss limitations of field surveys and these models, including temperature-based annualization methods, varying definitions of ebullition zones, low sampling resolution, and lack of dynamism. Future field efforts focused on capturing variability in CO 2 diffusion and CH 4 ebullition will be especially valuable in reducing uncertainty and improving models to advance our understanding reservoir GHG emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Accuracy and precision of ESI-Orbitrap-IRMS observations of hours to tens of hours via reservoir injection

Here, orbitrap isotope ratio mass spectrometry (Orbitrap-IRMS) has recently been applied to high-precision, natural-abundance isotope ratio measurements of a diverse range of compounds, including amino acids, oxyanions, fatty acids, and metals. These measurements can characterize many isotope ratios simultaneously at high (≈1.0‰) precision. In a successful experiment, observed precision will track the shot-noise limit and be limited by experimental time. Some isotope ratios, for example those involving 17 O in organic compounds or multiply-substituted (‘clumped’) isotopologues, require experimental times of hours to tens of hours to achieve desired precision, while current sample introduction techniques focus on observations on the order of seconds to tens of minutes. In this study, we characterize Orbitrap-IRMS performance for three long duration measurements (individual acquisitions ≥1 h and as long as 24 h) using an automated reservoir injection system coupled to a Q Exactive HF Orbitrap with an electrospray ionization (ESI) source. First, we characterize long-term intra-measurement stability through a 24-h long measurement of acetone. We report the following isotope ratios and precisions (as acquisition errors, errors on the observed ratio within this measurement (σ AE )): 13 C/ 12 C (σ AE = 0.07‰), 17 O/ 16 O (σ AE = 1.1‰), 18 O/ 16 O (σ AE = 0.3‰), and 13 C 13 C/ 12 C (σ AE = 0.65‰). The σ AE of each tracks the shot noise limit throughout and is limited by the challenging conditions (high resolution and low numbers of ions per scan) required for 17 O/ 16 O measurement in the presence of 13 C via Orbitrap. Second, we characterize inter-measurement stability via a sequence of seven 75-min analyses of perchlorate. We observe the following ratios and acquisition errors: 37 Cl/ 35 Cl (σ AE = 0.09‰); 17 O/ 16 O (σ AE = 1.6‰); 18 O/ 16 O (σ AE = 0.7‰), 37 Cl 17 O/ 35 Cl 16 O (σ AE = 2.7‰), and 37 Cl 18 O/ 35 Cl 16 O (σ AE = 1.2‰). However, we find that inter-measurement drift between acquisitions limits our accuracy and precision for standardized measurements (i.e., error on reported δ values) to ≈1‰ for the 37 Cl/ 35 Cl measurement. Hence, the benefits of low σ AE may not be fully realized. Third, we demonstrate accuracy via sample/standard comparisons of a methionine sample with 13 C enrichment of ≈20‰ relative to a known standard. Using a sequence of seven 60-min analyses, we recover the following isotope ratios and standardized precisions (i.e., error on reported δ values, denoted propagated acquisition errors, σ PAE ): 33 S/ 32 S (σ PAE = 1.0‰), 34 S/ 32 S (σ PAE = 0.7‰), 15 N/ 14 N (σ PAE = 2.1‰), 2 H/ 1 H (σ PAE = 3.2‰), 13 C/ 12 C (σ PAE = 0.4‰), 18 O/ 16 O (σ PAE = 1.6‰), & 13 C 13 C/ 12 C (σ PAE = 2.8‰) with confirmation of accurate results for the known 13 C/ 12 C and 13 C 13 C/ 12 C enrichments. Together, our results demonstrate the viability of Orbitrap-IRMS for long duration measurements of diverse sample types via an automated reservoir injection system. Inter-measurement stability remains a challenge; we expect our methods to be most applicable to extended measurements of hard-to-observe properties, such as 17 O in organics and clumped isotopologues.

58 GEOSCIENCES↗
DOE OSTI2020

Distinguishing Mesoscale Polar Order (Unidirectional vs Bidirectional) of Cellulose Microfibrils in Plant Cell Walls Using Sum Frequency Generation Spectroscopy

Cellulose in plant cell walls are synthesized as crystalline microfibrils with diameters of 3–4 nm and lengths of around 1–10 μm. These microfibrils are known to be the backbone of cell walls, and their multiscale three-dimensional organization plays a critical role in cell wall functions including plant growth and recalcitrance to degradation. The mesoscale organization of microfibrils over a 1–100 nm range in cell walls is challenging to resolve because most characterization techniques investigating this length scale suffer from low spatial resolution, sample preparation artifacts, or inaccessibility of specific cell types. Here, we report a sum frequency generation (SFG) study determining the mesoscale polarity of cellulose microfibrils in intact plant cell walls. SFG is a nonlinear optical spectroscopy technique sensitive to the molecular-to-mesoscale order of noncentrosymmetric domains in amorphous matrices. However, the quantitative theoretical model to unravel the effect of polarity in packing of noncentrosymmetric domains on SFG spectral features has remained unresolved. In this work, we show how the phase synchronization principle of the SFG process is used to predict the relative intensities of vibrational modes with different polar angles from the noncentrosymmetric domain axis. Applying this model calculation for the first time and employing SFG microscopy, we found that cellulose microfibrils in certain xylem cell walls are deposited unidirectionally (or biased in one direction) instead of the bidirectional polarity which was believed to be dominant in plant cell walls from volume-averaged characterizations of macroscopic samples. Here, with this advancement in SFG analysis, one can now determine the relative polarity of noncentrosymmetric domains such as crystalline biopolymers interspersed in amorphous polymer matrices, which will open opportunities to study new questions that have not been conceived in the past.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Feeling the Strain: Quantifying Ligand Deformation in Photosynthesis

Structural distortion of protein-bound ligands can play a critical role in enzyme function by tuning the electronic and chemical properties of the ligand molecule. However, quantifying these effects is difficult due to the limited resolution of protein structures and the difficulty of generating accurate structural restrains for non-protein ligands. Here, we seek to quantify these effects through a statistical analysis of ligand distortion in Chlorophyll (Chl) proteins (CP), where ring deformation is thought to play a role in energy and electron transfer. To assess the accuracy of ring-deformation estimates from available structural data, we take advantage of the C 2 symmetry of Photosystem II (PSII), comparing ring-deformation estimates for equivalent sites both within and between 113 distinct X-ray and Cryogenic electron microscopy (CryoEM) PSII structures. Significantly, we find that several deformation modes exhibit considerable variability in predictions, even for equivalent monomers, down to 2 Å resolution, to an extent that probably prevents their utilization in optical calculations. We further find that refinement restrains play a critical role in determining deformation values to resolution as low as 2 Å. However, for those modes that are well-resolved in the structural data, ring deformation in PSII is strongly conserved across all species tested, from cyanobacteria to algae. Furthermore, these results highlight both the opportunities and limitations inherent in the structure-based analysis of the bioenergetic and optical properties of CPs and other protein-ligand complexes.

14 SOLAR ENERGY↗
DOE OSTI2025

Enhanced Neutron and γ-Ray Detection via 6 Li Substitution in Undoped and Tl-Doped Zero-Dimensional Perovskite Cs 3 Cu 2 I 5 Scintillators

Radiation detectors are crucial in a wide variety of research and commercial applications, such as oil and gas exploration, medical imaging, nuclear nonproliferation, and homeland security. Neutron and gamma-ray detectors are fundamental components in portal monitors at ports and border crossings, bolstering national security against radiological threats. This study presents a dual-mode scintillator, undoped and Tl-doped 6 Li-Cs 3 Cu 2 I 5 , and demonstrates its potential as a promising material for simultaneous thermal neutron and gamma-ray detection. We explore the Bridgman growth of both undoped and thallium doped Li → Cu and Li → Cs substitutional systems with various Li doping levels and assess their impact on scintillation properties. Under 662 keV gamma-ray excitation, the undoped crystals had light yields up to 35,900 ph/MeV, with energy resolutions down to 4.5%. The Tl-doped crystals performed better than the undoped crystals with light yields peaking at 65,900 ph/MeV and energy resolutions as low as 3.5%. When exposed to a moderated 252 Cf excitation source, our crystals had light yields between 102,900 and 167,200 photons per thermal neutron capture, with a full energy thermal neutron peak reaching 3 MeV in gamma equivalent energy. Pulse shape discrimination studies reveal well-separated gamma and neutron events, resulting in Figure-Of-Merit (FOM) as high as 3.7. Furthermore, these findings highlight the potential of Li-doped Cs 3 Cu 2 I 5 as a viable candidate for next-generation dual-mode scintillators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Understanding Subsurface Fracture Evolution Dynamics Using Time‐Lapse Full Waveform Inversion of Continuous Active‐Source Seismic Monitoring Data

Abstract Predicting the behavior, geometry, and flow properties of subsurface fractures remains a challenging problem. Seismic models that can characterize fractures usually suffer from low spatiotemporal resolution. Here, we develop a correlative double‐difference time‐lapse full waveform inversion of continuous active source seismic monitoring data for determining high‐spatiotemporal‐resolution time‐lapse V p models of in‐situ fracture evolution at a shallow contamination site in Wyoming, USA. Assisted by rock physics modeling, we find that (a) rapidly increasing pore pressure initializes and grows the fracture, increasing the porosity slightly (from ∼13.7% to ∼14.6%) in the tight clay formation, thus decreasing V p (∼50 m/s); (b) the fluid injection continues decreasing V p , likely through the introduction of gas bubbles in the injectate; and (c) final V p reductions reach over ∼150 m/s due to a posited ∼4.5% gas saturation. Our results demonstrate that high‐resolution V p changes are indicative of mechanical and fluid changes within the fracture zone during hydrofracturing.

58 GEOSCIENCES↗
DOE OSTI2024

Machine Learning Classification Strategy to Improve Streamflow Estimates in Diverse River Basins in the Colorado River Basin

Streamflow in the Colorado River Basin (CRB) is significantly altered by human activities including land use/cover alterations, reservoir operation, irrigation, and water exports. Climate is also highly varied across the CRB which contains snowpack-dominated watersheds and arid, precipitation-dominated basins. Recently, machine learning methods have improved the generalizability and accuracy of streamflow models. Previous successes with LSTM modeling have primarily focused on unimpacted basins, and few studies have included human impacted systems in either regional or single-basin modeling. We demonstrate that the diverse hydrological behavior of river basins in the CRB are too difficult to model with a single, regional model. We propose a method to delineate catchments into categories based on the level of predictability, hydrological characteristics, and the level of human influence. Lastly, we model streamflow in each category with climate and anthropogenic proxy data sets and use feature importance methods to assess whether model performance improves with additional relevant data. Overall, land use cover data at a low temporal resolution was not sufficient to capture the irregular patterns of reservoir releases, demonstrating the importance of having high-resolution reservoir release data sets at a global scale. On the other hand, the classification approach reduced the complexity of the data and has the potential to improve streamflow forecasts in human-altered regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Hayward Fault Creep From Coda Wave Interferometry

Understanding creep is essential for assessing seismic hazards along the creeping Hayward Fault, which threatens the San Francisco area. Current 1-D monitoring methods, like creepmeters and theodolites, provide limited measurements with low spatial resolution. InSAR offers higher 2-D spatial sampling but lower temporal resolution. We introduce a novel method using coda wave interferometry (CWI) to monitor creep in 2-D with high resolution. By calculating changes in ambient seismic noise travel times, we relate these measurements to creep offsets, bridging the gap between existing methods. Applied to seismic data from 2021 around the Hayward Fault, our CWI-derived offsets aligned with creepmeter measurements, revealing continuous and episodic creep. A 2-D regionalization identified a spatial boundary between these regimes, corroborating previous findings. This approach could enhance seismic monitoring and improve understanding of fault mechanics and earthquake risks.

Luckie, Thomas William [Sandia National Laboratori↗
DOE OSTI2022

Development of an operando characterization stage for multi-modal synchrotron x-ray experiments

It is widely accepted that micro- and nanoscale inhomogeneities govern the performance of many thin-film solar cell absorbers. These inhomogeneities yield material properties (e.g., composition, structure, and charge collection) that are challenging to correlate across length scales and measurement modalities. The challenge is compounded if a correlation is sought during device operation or in conditions that mimic aging under particular stressors (e.g., heat and electrical bias). Correlative approaches, particularly those based on synchrotron x-ray sources, are powerful since they can access several material properties in different modes (e.g., fluorescence, diffraction, and absorption) with minimal sample preparation. Small-scale laboratory x-ray instruments have begun to offer multi-modality but are typically limited by low x-ray photon flux, low spatial resolution, or specific sample sizes. To overcome these limitations, a characterization stage was developed to enable multi-scale, multi-modal operando measurements of industrially relevant photovoltaic devices. The stage offers compatibility across synchrotron x-ray facilities, enabling correlation between nanoscale x-ray fluorescence microscopy, microscale x-ray diffraction microscopy, and x-ray beam induced current microscopy, among others. Furthermore, the stage can accommodate device sizes up to 25 × 25 mm 2 , offering access to multiple regions of interest and increasing the statistical significance of correlated properties. The stage materials can sustain humid and non-oxidizing atmospheres, and temperature ranges encountered by photovoltaic devices in operational environments (e.g., from 25 to 100 °C). As a case study, we discuss the functionality of the stage by studying Se-alloyed CdTe photovoltaic devices aged in the stage between 25 and 100 °C.

14 SOLAR ENERGY↗
DOE OSTI2022

Probing multiscale dissolution dynamics in natural rocks through microfluidics and compositional analysis

Mineral dissolution significantly impacts many geological systems. Carbon released by diagenesis, carbon sequestration, and acid injection are examples where geochemical reactions, fluid flow, and solute transport are strongly coupled. The complexity in these systems involves interplay between various mechanisms that operate at timescales ranging from microseconds to years. Current experimental techniques characterize dissolution processes using static images that are acquired with long measurement times and/or low spatial resolution. These limitations prevent direct observation of how dissolution reactions progress within an intact rock with spatially heterogeneous mineralogy and morphology. We utilize microfluidic cells embedded with thin rock samples to visualize dissolution with significant temporal resolution (100 ms) in a large observation window (3 × 3 mm). Here we injected acidic fluid into eight shale samples ranging from 8 to 86 wt % carbonate. The pre- and postreaction microstructures are characterized at the scale of pores (0.1 to 1 µm) and fractures (1 to 1,000 µm). We observe that nonreactive particle exposure, fracture morphology, and loss of rock strength are strongly dependent on both the relative volume of reactive grains and their distribution. Time-resolved images of the rock unveil the spatiotemporal dynamics of dissolution, including two-phase flow effects in real time and illustrate the changes in the fracture interface across the range of compositions. Moreover, the dynamical data provide an approach for characterizing reactivity parameters of natural heterogeneous samples when porous media effects are not negligible. The platform and workflow provide real-time characterization of geochemical reactions and inform various subsurface engineering processes.

58 GEOSCIENCES↗