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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Direct Radiative Effects of Aerosols at the ARM SGP and TWP Sites (DOE ASR Final Report)

This effort has examined and quantified aerosol direct radiative effects (DREs) and associated uncertainties at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) and Tropical Western Pacific (TWP) sites under both clear and all sky conditions by taking advantage of the advanced ARM long-term comprehensive measurements of aerosol, cloud, radiation, and atmospheric state. This effort has filled the knowledge gap in aerosol DREs at the SGP and TWP under all sky conditions based on the ARM observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Investigating the Impacts of Aqueous-Phase Processing on Organic Aerosol Chemical Climatology Using ARM and ASR Observations

This project improved understanding of how atmospheric aerosol particles form and evolve, with a focus on the role of water-driven (aqueous-phase) chemical reactions in the atmosphere. These processes occur in clouds, fog, and humid air and can significantly change the composition and properties of airborne particles, known as aerosols, which influence air quality and climate. By combining field measurements, laboratory experiments, and advanced analytical techniques, the project identified key chemical signatures that allow scientists to distinguish particles formed through aqueous processes from those formed in the gas phase. Observations from multiple environments, including wildfire smoke, urban regions, and cloud-influenced areas, show that aqueous chemistry is an important pathway for particle formation and aging. The project also developed new measurement approaches using uncrewed aerial systems (UAS) to capture how aerosol composition varies with altitude, providing critical insights into how particles interact with clouds. In addition, new data analysis frameworks were created to better interpret long-term aerosol measurements and improve characterization of particle sources and transformations. These results have been integrated into a global database of aerosol measurements and used to support atmospheric modeling efforts. Overall, the project provides important tools and knowledge to improve predictions of how aerosols affect climate and air quality, particularly through their interactions with radiation and clouds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multiphysics simulation of recent experiments on alkali‐silica reaction expansion in reinforced concrete members

Alkali‐silica reaction (ASR) is an important degradation process that causes volumetric expansion and damage in concrete, and is affected significantly by the local temperature, moisture and stress conditions that often vary across the regions of a structure. Numerical simulation is essential to predict the progression and effects of ASR on the performance of structures. Because of the interactions between thermal and moisture transport and mechanical deformation, it is important for numerical models to represent all these physical phenomena and the coupling between them. Simulations of ASR in reinforced concrete (RC) structures are further complicated by the need to capture interactions between concrete and embedded reinforcing bars. Here, this paper describes the implementation of a scalable, coupled‐physics ASR model for simulating RC structures and assesses the ability of that model to predict ASR‐induced expansion in recent laboratory tests on RC block and beam specimens. These laboratory tests and the simulation approach were selected because of their applicability to RC structural‐scale simulations. This validation study helps builds confidence the ability of this approach to model ASR expansion in large, complex RC structures, which is a current high‐priority need.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Annual Status Report (FY 2024): Performance Assessment for the Integrated Disposal Facility

The purpose of this Annual Summary Report (ASR) for Fiscal Year (FY) 2024 is to evaluate the continued adequacy of the Integrated Disposal Facility (IDF) Performance Assessment (PA) and Disposal Authorization Statement (DAS). This report consolidates relevant monitoring data, modeling analyses, and regulatory reviews to demonstrate a reasonable expectation that the PA objectives and performance measures will be met, as required under DOE O 435.1. The ASR follows the guidance in DOE-STD-5002-2017, which provides a framework for maintaining the validity of the DAS through periodic assessment of facility performance and compliance with waste disposal requirements. The IDF is a near-surface disposal facility designed to receive and permanently dispose of low-level waste (LLW) and mixed low-level waste (MLLW) generated from Hanford Site operations. The facility consists of two double-lined disposal cells equipped with leak detection and leachates recovery systems to ensure environmental protection. Waste planned for disposal includes vitrified low-activity waste (LAW) and solid secondary waste (SSW) from the Hanford Waste Treatment and Immobilization Plant (WTP). At the end of FY 2024, the IDF had not yet received any waste, as it remains in a pre-operational state. Disposal activities will begin with the hot commissioning of the WTP LAW Vitrification Facility using the Direct-Feed Low-Activity Waste (DFLAW) approach in Calendar Year (CY) 2025. This ASR justifies the continued adequacy of the PA and DAS by reviewing key documents and data sources. these sources are listed in Table A-2 in Appendix A.4): The Operating Disposal Authorization Statement (ODAS) for the IDF (DOE-EM, 2021) remains in effect, with no outstanding conditions or key issues affecting its implementation. Based on the comprehensive review of PA analyses, monitoring data, and regulatory compliance activities, this ASR concludes that the IDF remains in compliance with DOE O 435.1, and there is reasonable assurance that the PA performance objectives will be met once disposal operations commence in CY 2025.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Exploring the binding properties and activities of ancestral expansins

Bacterial expansins are non-lytic proteins capable of loosening cellulose networks, offering promising applications in agriculture, biotechnology, and material science. Their ability to disrupt noncovalent interactions in biopolymer matrices such as cellulose and chitin positions them as valuable tools for upgrading abundant natural materials. However, their industrial use remains limited due to their relatively low wall-loosening activity compared to plant expansins. To address this limitation, we applied Ancestral Sequence Resurrection (ASR) to reconstruct and characterize ancient variants of the Bacillus subtilis expansin BsEXLX1. ASR is a powerful evolutionary tool that enables the inference and synthesis of ancestral proteins, allowing researchers to explore functional traits that may have been lost over time. This approach not only provides insights into protein evolution but also facilitates the design of proteins with enhanced properties, such as improved substrate affinity or structural stability. In this study, we combined biochemical and biophysical assays to evaluate the activity and binding behavior of ancestral expansins. Our results reveal that ancestral variants exhibit increased cellulose affinity, reduced binding to acidic polysaccharides, and greater salt resistance. Furthermore, these traits enhance their wall-loosening activity and demonstrate the utility of ASR in engineering surface-active proteins for industrial applications, particularly in biomass processing and cellulose modification.

09 BIOMASS FUELS↗
DOE OSTI2024

Ce- and Ni-Codoped Double PrBaMn 2 O 5 Perovskite as a Ceramic SOFC Anode

This study explores the efficacy of cerium introduction, both on its own and in combination with nickel, into PrBaMn 2 O 5+δ (PBM) structures to enhance solid oxide fuel cell (SOFC) anodes. We synthesized Pr 1–x Ce x BaMn 2 O 5+δ compositions for x values of 0.05 (PrCe5) and 0.1 (PrCe10), as well as a nickel-doped variant (PrCe5Ni), assessing their performance under H 2 – 3% H 2 O reducing conditions pertinent to SOFC anode operations. Our findings reveal that the PrCe5 composition exhibits a thermal expansion coefficient (TEC) that not only improves upon that of the Ce-free counterpart but also aligns closely with the TEC standards of prevalent SOFC electrolytes. A notable advancement was achieved with the application of a 3.5 μm gadoliniadoped ceria (GDC) buffer layer through physical vapor deposition, effectively mitigating chemical interactions between PBM-based anodes and yttria-stabilized zirconia (YSZ) electrolytes, a concern highlighted by in situ neutron diffraction analyses. Electrochemical impedance spectroscopy, conducted over 220 h in a H 2 –3% H 2 O atmosphere at 750 °C, demonstrated that the optimal 3.5 μm thickness of the GDC buffer layer significantly minimizes the area-specific resistance (ASR) degradation rate to 0.002 Ω cm 2 /h, markedly outperforming both thinner (1 μm) and thicker (8 μm) GDC layers, which showed higher degradation rates of 0.15–0.2 Ω cm 2 /h due to the diffusion of Ba ions or delamination. Moreover, cerium doping fosters superior microstructural stability and obviates barium diffusion, thereby suggesting an enhanced durability of the doped anodes over their lifespan. Integrating nickel into the PrCe5 structure halved the ASR to 0.5 Ω cm 2 at 750 °C, situating it well within the ideal performance range for SOFC anodes. Furthermore, the enhancement brought about by simultaneously doping PBM with cerium and nickel, which fundamentally relies on the critical contributions of defect chemistry and crystal structure, highlights the significance of these fields in creating sophisticated materials for energy related applications.

25 ENERGY STORAGE↗
DOE OSTI2024

NSA Site Science: Use of ARM Observations from Northern Alaska to Evaluate and Improve Prediction Capabilities

The Arctic is warming at a rate nearly double that of the rest of the planet, leading to profound changes in atmospheric, oceanic, and ice processes. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility has played a significant role in Arctic research, operating observatories in Alaska's North Slope for over 25 years. These observatories provide a rich, and wide-reaching dataset that offers insight into atmospheric processes in northern Alaska. This report details the results of a nine-year research project (2015–2024) supported by the DOE Atmospheric Systems Research (ASR) program, that leverages data from ARM’s deployment of observing facilities at Utqiaġvik (known as the North Slope of Alaska, or NSA, site) and Oliktok Point, Alaska. The project was conducted in two phases: - Phase 1 (2015–2019): Focused on understanding key atmospheric processes at Oliktok Point, including cloud formation, high-latitude precipitation, aerosol-cloud interactions, and cloud properties. - Phase 2 (2019–2024): Extended the research to the broader North Slope region, using data from both Oliktok Point and Utqiaġvik. Topics explored included surface energy budgets, atmospheric stability, ice nucleation processes, and microphysics in Arctic clouds. The project resulted in numerous research products, including 50 peer-reviewed publications and dissertations, 169 presentations, and 10 data products. These products cover a variety of topics, including: - Cloud Macro- and Microphysical Properties: Arctic clouds play a crucial role in energy transfer, and accurate representation in models is critical. The study explored cloud transitions, ice crystal shapes, and dual-wavelength radar data to understand ice crystal habits and size distributions. - Aerosol Properties and Processes: The team examined aerosol sources in the Arctic, including industrial emissions and natural sources. Observations showed significant spatial gradients in aerosol concentrations due to human activities and wildfire smoke. The influence of aerosols on cloud formation and the surface energy budget was also assessed. - Aerosol-Cloud Interactions: Research revealed that aerosols might suppress cloud ice production, affecting cloud radiative forcing and precipitation. The impact of local industrial emissions on cloud properties was also investigated. - Contextualizing the North Slope of Alaska in the context of the broader Arctic: To understand broader trends, the project evaluated large-scale circulation patterns and the influence of weather systems on the Arctic. Studies indicated that large-scale processes play a significant role in temperature patterns and the timing of snowmelt. - Advancing ARM Observational and Modeling Capabilities: The project developed new radar data products and advanced measurement techniques, including clutter mitigation and drizzle detection. Uncrewed aerial systems (UAS) and tethered balloon systems (TBS) were deployed to gather detailed atmospheric data. Additionally, the project supported 10 early career scientists, providing training and mentorship to undergraduate interns, graduate students, postdoctoral researchers, and early career researchers. These efforts contributed to the advancement of ARM research capabilities and fostered a new generation of scientists skilled in Arctic atmospheric research. Ultimately, this ASR-supported project has provided valuable insights into Arctic atmospheric processes and their broader climate implications. Recommendations for future work include continuing support for long-term observing at Arctic locations to foster additional research, further exploration of aerosol-cloud interactions and the potential impacts of enhanced industrialization of the Arctic, and expanded use of uncrewed systems to gather data in this remote and harsh environment. Additionally, the data products developed by this work, and the data products developed through the ARM infrastructure, leave a treasure-trove of additional information that should be explored for many years to come to gain additional insight into physical processes in the Arctic atmosphere that drive the rapid changes occurring in at high latitudes and their global impact.

58 GEOSCIENCES↗
DOE OSTI2026

Annual Summary Report (FY 2025) Performance Assessment for the Integrated Disposal Facility

The purpose of this Annual Summary Report (ASR) for fiscal year (FY) 2025 is to evaluate the continued adequacy of the Integrated Disposal Facility (IDF) Performance Assessment (PA) and Disposal Authorization Statement (DAS). This report consolidates relevant monitoring data, modeling analyses, and regulatory reviews to demonstrate a reasonable expectation that the PA objectives and performance measures will be met, as required under DOE O 435.1, Radioactive Waste Management. The ASR follows the guidance in DOE-STD-5002-2017, Disposal Authorization Statement and Tank Closure Documentation, which provides a framework for maintaining the validity of the DAS through periodic assessment of facility performance and compliance with waste disposal requirements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Atmospheric System Research Workshop Report: New Directions in Atmospheric Ice Processes Research

Atmospheric ice processes are critical for precipitation production, cloud dynamics, and radiative properties and contribute to uncertainties in Earth’s energy budget and hydrological cycle, yet they remain poorly understood. To address this, ASR convened a 2.5-day workshop with 28 experts in laboratory measurements, field observations, and cloud modeling. The primary goal was to identify key knowledge gaps and prioritize future directions in atmospheric ice processes research. The outcomes of this workshop are expected to inform ASR and prompt improvements in cloud and Earth system models (ESMs) by advancing the fundamental understanding of ice processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Annual Summary Report (FY 2025) Composite Analysis for Low-Level Waste Disposal in the Central Plateau of the Hanford Site

In accordance with DOE M 435.1-1, Radioactive Waste Management Manual, requirements, the U.S. Department of Energy (DOE) Hanford Field Office (HFO) prepared this Annual Summary Report (ASR) for fiscal year (FY) 2025 for the Hanford Site Composite Analysis (CA) reported in DOE/RL-2019-52, Composite Analysis for Low-Level Waste Disposal in the Hanford Site Central Plateau (FY 2020) (hereinafter referred to as the Hanford Site Composite Analysis). The preparation of this ASR follows the technical specifications provided in DOE-STD-5002-2017, Disposal Authorization Statement and Tank Closure Documentation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Bipolar Membrane Electrodialyzers as Flexible Demand Response Resources: Co-Optimization of Cost Savings and Product Formation

Bipolar membrane electro dialyzers (BPMED) are widely used for chemical production and processing, including in the emerging ocean alkalinity enhancement (OAE) industry. In this paper, we explore the potential of BPMED devices as flexible electrochemical loads within power system operations. Using a multi-objective optimization framework, we evaluate BPMED operation across 24-hour and monthly horizons to examine how dispatch strategies respond to electricity price and grid conditions. Simulation results show that altering the relative weights of the choices in the objective function strongly shape the operating patterns, with cost-focused strategies that suppress the operation during peak prices. Furthermore, we propose alternative formulations that optimize operations to achieve both cost savings and alignment with periods of lower grid-side carbon intensity (CI), as low grid-side CI is key to maximize OAE efficiency. Additionally, a detailed sensitivity analysis highlights the importance of device properties, where low area-specific resistance (ASR) of membrane and high current efficiency (CE) are observed to jointly unlock cost-effective operation. However, even modest shunt efficiency losses are observed to erode performance and decrease system value. Importantly, the analysis demonstrates that BPMED can serve as a controllable and flexible demand response resource, shifting load to support multiple grid-side objectives, including (but not limited to) renewable integration, alleviate peak demand, and provide co-benefits for system reliability. These findings underscore BPMED’s dual role as a process technology and a grid-supporting asset, pointing to promising pathways for operational optimization of multiple objectives.

Bhattacharya, Saptarshi (ORCID:0000000308902060)↗
DOE OSTI2025

Infiltrated electrodes for metal supported solid oxide electrolysis cells

Metal-supported solid oxide cells (MSOCs) are an alternative to conventional solid oxide cells (SOCs) based on ceramic cermets, offering lower material costs and higher operational flexibility. In this study symmetric MSOCs with infiltrated electrodes are explored for steam electrolysis operation to understand the underlying operation and degradation principles and suggest a direction for future MSOCs development. Two different fuel electrode backbones are used: an electronically-conductive lanthanum strontium co-doped iron nickel titanate (LSFNT) infiltrated with cerium-gadolinium oxide (CGO), or an ionic conductive zirconia based backbone (10ScYSZ) infiltrated with Ni:CGO. At the oxygen side, the backbone is 10ScYSZ, which is infiltrated with lanthanum-strontium co-doped cobalt oxide (LSC), or praseodymium oxide as cobalt-free alternative for comparison. This study suggests that the backbone electronic conductivity is key for good electrochemical performance as well as for boosting cell durability. Highly electronically conductive nanoparticles, especially nickel, were observed to irreversibly agglomerate driven by thermal conditions, whereas CGO proved to be a very stable electrocatalyst. At the fuel side, CGO (LSFNT) electrode showed lower ASR and degradation rate than Ni:CGO(ScYSZ) configuration with measured values of 0.50 Ω cm2 and 11 %/1000 h (at 0.60 A/cm2), and 0.70 Ω cm2 and 26 %/1000 h (at 0.50 A/cm2) at 1.30 V, respectively (700 °C, 50 % steam in hydrogen at the fuel side and air at the oxygen electrode side, LSC(ScYSZ) oxygen electrode).

25 ENERGY STORAGE↗
DOE OSTI2025

Overcoming the Conductance versus Crossover Trade-off in State-of-the-Art Proton Exchange Fuel-Cell Membranes by Incorporating Atomically Thin Chemical Vapor Deposition Graphene

Permeance–selectivity trade-offs are inherent to polymeric membranes. In fuel cells, thinner proton exchange membranes (PEMs) could enable higher proton conductance and increased power density with lower area-specific resistance (ASR), smaller ohmic losses, and lower ionomer cost. However, reducing thickness is accompanied by an increase in undesired species crossover harming performance and long-term efficiency. Here, we show that incorporating atomically thin monolayer graphene synthesized via scalable chemical vapor deposition (CVD) and tunable defect density into PEMs (Nafion, ~5–25 μm thick) can allow for reduced H 2 crossover (~34–78% of Nafion of a similar thickness) while maintaining adequate areal proton conductance for applications (>4 S cm –2 ). In contrast to most prior work using >50 μm symmetric Nafion sandwich structures, we elucidate the interplay of graphene defect density and Nafion proton transport resistance on the performance of Nafion|graphene composite membranes and find high-quality low-defect density CVD graphene (G) supported on Nafion 211 (~25 μm); i.e., N211|G has a high areal proton conductance (~6.1 S cm –2 ) and the lowest H 2 crossover (~0.7 mA cm –2 ). Fully functional centimeter-scale N211|G fuel-cell membranes demonstrate performance comparable to that of state-of-the-art Nafion N211 at room temperature as well as standard operating conditions (~80 °C, ~150–250 kPa-abs) with H 2 /air (power density ~0.57–0.63 W cm –2 ) and H 2 /O 2 feed (power density ~1.4–1.62 W cm –2 ) and markedly reduced H 2 crossover (~53–57%).

25 ENERGY STORAGE↗
DOE OSTI2024

ARM Metadata Entry and Data Upload Manual

The ARM Metadata Entry and Data Upload Tool, Online Metadata Editor (OME), makes it easy to describe ARM, ASR, and externally funded data products in a standardized way and enables these metadata records and uploaded data to be searchable in the ARM Data Discovery tool. The metadata records provide context for the data and facilitates the discovery and (re)use of the data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Convective Boundary-Layer Spatial Heterogeneity Experiment Field Campaign Report

Earth system models (ESMs) require accurate heat, mass, and momentum exchanges between components, which requires accurate observations and modeling of the atmospheric boundary layer. Over the land, the daytime convective atmospheric boundary layer (CBL, also called the convective mixing layer) develops and evolves daily, driven by solar surface heating. Doppler lidar (DL) measurements of vertical velocities provide an effective way to document the diurnal cycle of CBL (Chu et al. 2023). With the support of the U.S. Department of Energy (DOE) Atmospheric Research (ASR) program, we studied convective mixing-layer heights (MLH) across multiple DOE Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory sites based on DL measurements.

54 ENVIRONMENTAL SCIENCES↗