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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AmeriFlux FLUXNET-1F US-xRN NEON Oak Ridge National Lab (ORNL)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xRN NEON Oak Ridge National Lab (ORNL). This is the FLUXNET version of the carbon flux data for the site US-xRN NEON Oak Ridge National Lab (ORNL) produced by applying the standard ONEFlux (1F) software. Site Description - Oak Ridge National Laboratory (ORNL) is located at the U.S. Department of Energy's Oak Ridge Reservation in Roane County, Tennessee. The ORNL reservation is situated within the borders of five parallel ridges and valleys to the north of the Clinch River that are part of the Ridge-and-Valley Appalachians physiographic province (Environmental Sciences Division n.d.). The NEON tower site and Walker Branch aquatic site at ORNL are located within the Walker Branch Watershed, a 100 ha area that has served as the site for long-term environmental studies by the Environmental Sciences Division at ORNL, NOAA, and many visiting university researchers.

Network), NEON (National Ecological Observatory [N↗
DOE OSTI2024

The influence of exploration activities of a potential lithium mine to the environment in Western Serbia

The proposed exploitation of the Jadar Valley lithium/borate deposit in Serbia, by the Rio Tinto Corporation, indicates that it would become large-scale processing of boron- and lithium-containing ore. It would be one of the world’s very first lithium mines in populated and agricultural area. The company claims that the envisioned mining will be in accordance with environmental protection requirements. The Jadar Valley deposits have been claimed to cover 90% of Europe’s current lithium needs. Yet, local opposition to the mining has arisen due to potential devastating impacts on groundwater, soil, water usage, biodiversity loss, and waste accumulation. Research drilling by the mining company has already produced environmental damage, with mine water containing high levels of boron leaking from exploratory wells and causing crops to dry out. Furthermore, our investigations reveal substantially elevated downstream concentrations of boron, arsenic, and lithium in nearby rivers as compared to upstream regions. Additionally, here we show that soil samples exhibit repeated breaches of remediation limit values with environmental consequences on both surface and underground waters. With the opening of the mine, problems will be multiplied by the tailings pond, mine wastewater, noise, air pollution, and light pollution, endangering the lives of numerous local communities and destroying their freshwater sources, agricultural land, livestock, and assets.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

NASA's Earth Science Research and Environmental Predictions

NASA Earth Science program began in the 1960s with cloud imaging satellites used for weather observations. A fleet of satellites are now in orbit to investigate the Earth Science System to uncover the connections between land, Oceans and the atmosphere. Satellite systems using an array of active and passive remote sensors are used to search for answers on how is the Earth changing and what are the consequences for life on Earth? The answer to these questions can be used for applications to serve societal needs and contribute to decision support systems for weather, hazard, and air quality predictions and mitigation of adverse effects. Partnerships with operational agencies using NASA's observational capabilities are now being explored. The system of the future will require new technology, data assimilation systems which includes data and models that will be used for forecasts that respond to user needs.

Hilsenrath, E.↗
NASA NTRS1977

Mother, Earth, Father Sky Symposium

A conference was held in which minority aerospace scientists and engineers interacted with the minority community, particularly at the junior high, high school, and college levels. There were two presentations in the biological sciences, two in the physical and environmental sciences, seven in engineering and computer sciences, and nine in aerospace science and engineering. Aerospace technology careers and aerospace activities were discussed as to how they are relevant to minorities and women.

Bowman, B.↗
DOE OSTI2026

Computational Modeling of Atmospheric Processes at Texas Southern University

Texas Southern University (TSU) is strengthening its research program in atmospheric chemistry and physics with a climate science emphasis by leveraging partnerships with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility, Brookhaven National Laboratory (BNL), and the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This RDPP-supported program focuses on secondary organic aerosols (SOAs) and reactive atmospheric species that influence cloud formation, precipitation processes, and radiative forcing. SOAs play a critical role in cloud microphysics and Earth’s energy balance, yet the chemical and physical mechanisms governing SOA–cloud interactions remain a significant source of uncertainty in predictive climate models. Through computational modeling, observational data analysis, and national laboratory collaboration, this program develops a skilled cohort of students trained in atmospheric science, environmental data analysis, and climate-relevant modeling. These research experiences build technical competencies that are transferable to careers in government laboratories, academia, and industry. By engaging students from historically underrepresented communities in high-impact climate research, TSU expands participation in the atmospheric sciences workforce while contributing meaningful scientific insights to DOE-supported ARM research activities. This partnership strengthens national capacity in climate science and supports the development of the next generation of atmospheric researchers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Approximation of ice phenology of Maine lakes using Aqua MODIS surface temperature data

Studies of lake ice phenology have historically relied on limited in situ data. Relatively few observations exist for ice out and fewer still for ice in, both of which are necessary to determine the temporal extent of ice cover. Satellite data provide an opportunity to better document patterns of ice phenology across landscapes and relate them to the climatological drivers behind changing ice phenology. We developed a model, the Cumulative Sum Method (CSM), that uses daytime and nighttime surface temperature observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Earth-observing Aqua satellite to approximate ice in (the onset of ice cover) and ice out from training datasets of 13 and 58 Maine lakes, respectively, during the 2002/2003 through 2017/2018 ice seasons. Ice in was signaled by reaching a threshold of cumulative negative degrees following the first day of the season below 0°C. Ice out was signaled by reaching a threshold of cumulative positive degrees following the first day of the year above 0°C. The comparison of observed and remotely sensed ice-in dates showed relative agreement with a correlation coefficient of 0.71 and a mean absolute error (MAE) of 9.8 days. Ice-out approximations had a correlation coefficient of 0.67 and an MAE of 8.8 days. Lakes smaller in surface area and nearer the Atlantic coast had the greatest error in approximation. Application of the CSM to 20 additional lakes in Maine produced a comparable ice-out MAE of 8.9 days. Ice-out model performance was weaker for the warmest years; there was a larger MAE of 12.0 days when the model was applied to the years 2019–2023 for the original 58 lakes. The development of this model, which utilizes daily satellite data, demonstrates the promise of remote sensing for quantifying ice phenology over short, temporal scales, and wider geographic regions than can be observed in situ, and allows exploration of the influence of surface temperature patterns on the process and timing of ice in and ice out.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Utilizing biochars to stabilize mercury in contaminated floodplain sediment: Implications on mercury remediation

Major weather events contribute to the mobility and remobilization of legacy mercury (Hg) contamination and sequestration within sediments. Remediation using biochar as a soil amendment is a useful technique to immobilize and decrease Hg toxicity. This study explored whether biochar application is effective at stabilizing labile mercury (LaHg) from floodplain sediment. Controlled mesocosms simulating contamination events and flooding conditions were conducted. Floodplain sediment, which experiences annual periodic flooding, was collected. Sediment was spiked with inorganic Hg, applied with different types of biochar, and experienced simulated flooding events. Four types of biochar, pure rice husk (RH), pure peanut hull (PH), sulfur-modified rice husk (SMRH), and sulfur-modified peanut hull (SMPH), were applied at 10 and 40 g/kg rates (i.e., RH 10, RH 40; PH 10, PH 40, SMRH 10, SMRH 40, SMPH 10, SMPH 40). Total Hg, methylmercury, and LaHg concentrations were analyzed by coupling with redox potential measurements. Results indicate that SMRH 10, PH 10, PH 40, SMPH 10, and SMPH 40 successfully remediate Hg by stabilizing and reducing LaHg species from floodplain sediment. However, a high Hg methylation potential was observed with unsulfated and sulfated peanut hulls (PH 10, PH 40, SMPH 10, and SMPH 40), as they tend to create a reducing microenvironment that favors sulfate reduction reactions. Additionally, sulfur-modified biochar tends to promote Hg methylation potential at high application rates (i.e., 40 g/kg). We thus recommend using SMRH at a relatively low application rate (SMRH 10) for the remediation of Hg from floodplain sediment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Root Characteristics Vary with Depth Across Four Lowland Seasonal Tropical Forests

Fine roots are key to ecosystem-scale nutrient, carbon (C), and water cycling, yet our understanding of fine root trait variation within and among tropical forests, one of Earth’s most C-rich ecosystems, is limited. We characterized root biomass, morphology, nutrient content, and arbuscular mycorrhizal fungal (AMF) colonization to 1.2 m depths across four distinct lowland Panamanian forests, and related root characteristics to soil C stocks. We hypothesized that: (H1) Fine root characteristics vary consistently with depth across seasonal tropical forests, with deeper roots exhibiting more exploratory traits, such as for deep water acquisition; (H2) fine root characteristics vary among tropical forests mainly in surface soils, where resource availability also varies. Here we found consistent variation with depth across the four forests, including decreased root biomass, root tissue density, and AMF, and increased specific root length. Among the forests, there was variation in some fine root characteristics, including greater surface root biomass and lower SRL in the wettest forest, and smaller fine root diameter in the driest forest. We also found that root characteristics were related to total soil C stocks, which were positively related to root biomass and negatively related to specific root length. These results indicate emergent properties of root variation with depth across tropical forests, and show site-scale variation in surface root characteristics. Future work could explore the flexibility in root characteristics under changing conditions such as drought.

13C NMR↗
DOE OSTI2026

Impact of Forest Canopy Structure on Buoyant Plume Dynamics During Wildland Fires

Heterogeneous forest canopies can generate complex turbulent structures, but in the presence of a fire plume, these interactions are not fully understood. This study investigates the influence of forest canopy heterogeneity on buoyant plume dynamics resulting from surface thermal anomalies representing wildland fires, utilizing Large Eddy Simulation (LES). The Parallelized Large-Eddy Simulation Model (PALM) was employed to simulate six canopy configurations: no canopy, homogeneous canopy, external plume-edge canopy, internal plume-edge canopy, 100 m gap canopy, and 200 m gap canopy. Each configuration was analyzed with and without a static surface heat flux patch of 5000 W ∙ m -2 , resulting in a resting buoyant plume. Simulations were conducted under three crosswind speeds: 0, 5, and 10 m ∙ s -1 . Results show that canopy structure significantly modifies plume behavior, mean flow, and turbulent kinetic energy (TKE) budgets. Plume updraft speed and tilt varied with canopy configuration and crosswind speed. Horizontal pressure gradients associated with plume-atmosphere interaction were modified based on the canopy configuration, resulting in varying crosswind speed reductions at the plume region. Strong momentum absorption was observed above the canopy for the crosswind cases, with the greatest enhancement in the gap canopies. Momentum injection from below the canopy due to the heat source was also observed, resulting in plume structure modulation based on canopy configuration. TKE was found to be the largest in the gap canopy configurations. TKE budget analysis revealed that buoyant production dominated over shear production. At the center of the heat patch, the gap canopy configurations showed enhanced buoyancy within the gap. These results improve our knowledge of fire-canopy-atmosphere interactions that can inform fire models on the impacts of canopy heterogeneity on plume dynamics and ember ejections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

An Evaluation of Dynamical Downscaling Methods Used to Project Regional Climate Change

In the past decade, dynamical downscaling using “pseudo-global-warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)-simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic-scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large-scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic-scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Large‐Scale Statistically Meaningful Patterns (LSMPs) Associated With Precipitation Extremes Over Northern California

Abstract We analyze large‐scale statistically meaningful patterns (LSMPs) that precede extreme precipitation (PEx) events over Northern California (NorCal). We find LSMPs by applying k‐means clustering to the two leading principal components of daily 500 hPa geopotential height anomalies two days before the onset, from October to March during 1948–2015. Statistical significance testing based on Monte Carlo simulations suggests a minimum of four statistically distinguished LSMP clusters. The four LSMP clusters are characterized as Northwest continental negative height anomaly, Eastward positive “Pacific‐North American Pattern (PNA),” Westward negative “PNA,” and Prominent Alaskan ridge. These four clusters, shown in multiple variables, evolve very differently and have differing links to the Arctic and tropical Pacific regions. Using binary forecast skill measures and a new copula‐based framework for predicting PEx events, we find LSMP indices that are useful predictors of NorCal PEx events, with moisture‐based variables being the best predictors of PEx events at least 6 days before the onset, and the lower atmospheric variables being better than their upper atmospheric counterparts any day in advance tested. To ensure statistical rigor, the LSMPs analyzed here (with the modified acronym) include local tests of both significance and consistency, which are not always featured in the literature on large‐scale meteorological patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Examining the Robustness of Weakened Orographic Influence on Precipitation in Downscaled Climate Projections Over the Western US

Assessing local climate change impacts often requires downscaling coarse global climate model (GCM) output to finer resolution. Two main approaches exist: dynamical downscaling using high-resolution regional climate models, and statistical downscaling based on historical relationships between large-scale and local variables. In a recent analysis of five dynamically downscaled simulations over the western United States, Koszuta et al. (2024, https://doi.org/10.1029/2023gl107298) found that warming weakens orographic influence on winter precipitation, damping increases on windward slopes and amplifying them in rain-shadowed regions. Here we show that this effect is robust across seasons and multiple dynamically downscaled ensembles, and is more pronounced at higher model resolutions. However, it is absent in projections from a widely used statistical model (LOCA2), even when trained on high-resolution future simulations (LOCA2-Hybrid). This highlights a key limitation of many statistical downscaling methods: their preservation of parent GCM trends, which usually fail to capture emergent changes in orographic precipitation patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Climatology of Cloud‐Land‐Surface Coupling Across Different ARM Sites

Land-atmosphere interactions play a critical role in the evolution and formation of low-level clouds. The different states of coupling between low-level clouds and the surface are uncertain, primarily over continental regions, where complex thermodynamics complicates their investigation. This study uses observations from the Atmospheric Radiation Measurement User Facility to explore cloud-surface coupling and perform a climatological analysis of this interaction in five countries across three continents. The results reveal consistent coupling thresholds and average percentages across the five sites, with coupled clouds accounting for 66% of the cases and decoupled clouds for 34%. Thermodynamic and dynamic evaluations show distinct differences between coupled and decoupled clouds. Coupled clouds are characterized by humid environments, in which vertical motions connect the surface and lower atmosphere to the cloud base, conditions that favor the formation of boundary layer clouds. Decoupled clouds prefer to occur in a drier and colder environment with vertical motions inside the boundary layer being detached from the cloud base, under which boundary layer clouds are hard to form. Coupled clouds peak during warmer hours and seasons, and vice versa for decoupled clouds. This study underscores the complexity of cloud-land-surface interactions and paves the way for further investigations into cloud formation and evolution under different atmospheric environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluating E3SM Global Storm‐Resolving Model Simulations of Deep Convection: Insights From DP‐SCREAM During TRACER

Global Storm-Resolving Models (GSRMs) are becoming increasingly vital for advancing climate modeling and improving the prediction of extreme weather events. Houston, a coastal region frequently affected by deep convective storms, offers an ideal setting to evaluate the ability of GSRMs to simulate deep convection. This study assesses the performance of the Doubly Periodic Simple Cloud-Resolving E3SM (Energy Exascale Earth System Model) Atmosphere Model (DP-SCREAM) using observations from the TRacking Aerosol Convection interactions ExpeRiment (TRACER) campaign. DP-SCREAM effectively reproduces the diurnal cycles of clouds and precipitation, demonstrating much greater skill than the E3SM single column model. The DP-SCREAM is demonstrated to be applicable to coastal regions, partially due to the forcing data sets already capturing the influence of breezes. DP-SCREAM also replicates biases persistent in the global version of SCREAM: the underrepresentation of boundary layer shallow clouds, a lack of mid-level congestus clouds, and the popcorn convection, characterized by small and disorganized convective cells generating the strongest precipitation. To investigate these issues, two sensitivity experiments were conducted: increasing the mixing length and scaling up the buoyancy flux within the Simplified Higher Order Closure scheme. Increasing the mixing length improved mid-level congestus representation and reduced unrealistic early morning fog occurrence. Enhancing buoyancy flux only marginally improved the bias of underproduced big convective cells. In conclusion, an additional resolution sensitivity test at 0.5 km grid spacing demonstrated that a refined horizontal resolution alone is insufficient to resolve these biases.

54 ENVIRONMENTAL SCIENCES↗