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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 73 records · Page 4
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DOE OSTI2023

Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model: RegCM

Mitigation of carbonaceous aerosol emissions is expected to provide climate and health co-benefits. The accurate representation of carbonaceous aerosols in climate models is critical for reducing uncertainties in their climate feedback. In this regard, emission fluxes and aerosol life cycle processes are the two primary sources of uncertainties. Here, we demonstrate that the incorporation of a dynamic ageing scheme and emission estimates that are updated for the local sources improves the representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model, RegCM, compared with its default configuration. The respective mean black carbon (BC) and organic carbon (OC) surface concentrations in 2010 are estimated to be 4.25 and 10.35 µg m -3 over the Indo-Gangetic Plain (IGP) in the augmented model. The BC column burden over the polluted IGP is found to be 2.47 mg m -2 , 69.95 % higher than in the default model configuration and much closer to available observations. The anthropogenic aerosol optical depth (AOD) increases by more than 19 % over the IGP due to the model enhancement, also leading to a better agreement with observed AOD. The respective top-of-the-atmosphere, surface, and atmospheric anthropogenic aerosol short-wave radiative forcing are estimated at -0.3, -9.3, and 9.0 W m -2 over the IGP and -0.89, -5.33, and 4.44 W m -2 over Peninsular India (PI). Our results suggest that the combined effect of two modifications leads to maximum improvements in the model performance in regions where emissions play a dominant role.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Present and Future Changes in Land‐Atmosphere Coupling of Water and Energy Over Extratropical Forest Regions

Abstract Couplings between land and the near surface atmosphere are modulated by interactions between soil conditions, vegetation dynamics, turbulent fluxes, and atmospheric properties. How the land‐atmosphere coupling responds to warming and elevated CO 2 are important for understanding the land surface carbon, energy, and water cycles. In this work, we documented this coupled land‐atmosphere network based on observations and the Energy Exascale Earth System Model (E3SM) simulations over extratropical forest ecosystems. We employed a transfer entropy approach and novel network metrics to reveal patterns and strength of the land‐atmosphere coupling under historical conditions and a future high emission scenario (SSP585). We found that, in observations, the present‐day extratropical forest coupling network has high network connectivity (72%–88% of the targeted processes are coupled). E3SM reasonably captured the extratropical forest coupling network (modeled network connectivity was 81%–96%) and predicted that the coupling strength would significantly increase by 28% (±3%) under warming and elevated CO 2 conditions. Furthermore, E3SM factorial coupled experiments suggested that warming enhanced soil nitrogen mineralization favoring plant nitrogen uptake and vegetation growth were responsible for the strengthening future land‐atmosphere coupling. This work provides new metrics to analyze and document complex couplings for coupled earth system processes and highlights the important roles soil nutrient availability and biogeochemistry have on land‐atmosphere coupling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Spectro-Microscopic Investigation of the Aerosol Impact on Hydrological Processes

This project investigated physico-chemical characteristics of atmospheric particles collected during DOE ARM field campaigns and how they are involved in the hydrological cycle. Our efforts were focused on multi-modal chemical imaging and molecular characterization of atmospheric particles and snow samples collected during the Surface-Atmosphere Integrated Field Laboratory (SAIL) campaign and particle samples from the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) campaign.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Shrub Expansion Simulations at Trail Valley Creek Tundra site using E3SM Land Model (ELM) Arctic-focused Version

The warming of the Arctic is causing substantial compositional, structural, and functional changes in tundra vegetation including shrub and densification in parts of the Arctic. Assessing the impact of these changes in vegetation composition on the Arctic’s carbon and energy budgets is important to constrain projected local and global surface-atmosphere exchanges. We conduct a sensitivity analysis of the projected surface energy fluxes, soil carbon pools, and carbon dioxide fluxes (net ecosystem exchange, gross primary production, and ecosystem respiration) between present day and 2100 to different shrub expansion rates and air temperature increases under future emission scenarios (intermediate – RCP4.5, and high – RCP8.5) using the Arctic-focused version of the Energy Exascale Earth System Model (E3SM) Land Model (ELM). We focus on Trail Valley Creek (TVC), a mineral upland tundra site located in the western Canadian Arctic, which is experiencing tall shrub densification and expansion. In this study, we run TVC under two different warming scenarios RCP4.5 and RCP 8.5 and simulate different shrubification rates projected until year 2100. In this repository, we include all the forcing, input, parameters, and output data corresponding to all the simulations performed. flmd.csv includes a detailed description of the datasets files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

SAIL Aerosol Vertical Profiles (SAIL-AVP) Field Campaign Report

Aerosols are central to understanding the water cycle within mountainous regions, but a complete understanding of this role cannot be provided without vertically resolved observations, particularly for aerosol-cloud interactions, since we simultaneously need to know aerosol information and meteorology near cloud bases. The goal of SAIL Aerosol Vertical Profiles (SAIL-AVP) was to perform tethered balloon system (TBS) measurements during different seasons to elucidate process-level understanding of the aerosols and associated meteorological conditions within complex mountainous terrain. Measurements were conducted during the deployment of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s second Mobile Facility (AMF2) as part of the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River Watershed of the Upper Colorado River Basin (UCRB) in southwestern Colorado. In mid-latitude continental interior mountain ranges, and especially at SAIL, aerosol vertical profiles and their relationships with meteorology are, almost without exception, inferred from a combination of ground-based and remote-sensing data. These flights provided many more dimensions to aerosol-cloud interactions that are unavailable to those inferential approaches: the TBS collected in situ information in the vertical, optical, chemical, and biological dimensions for aerosol-cloud interactions. Furthermore, the collocation of these flights with longstanding collaborative resources in the region, including the ongoing surface and subsurface hydrologic observations from the DOE’s Watershed Function Science Focus Area (SFA), produced a unique set of atmospheric observations that are complemented by existing land-surface and subsurface (e.g., groundwater) observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

On the estimation of boundary layer heights: a machine learning approach

Abstract. The planetary boundary layer height (zi) is a key parameter used in atmospheric models for estimating the exchange of heat, momentum, and moisture between the surface and the free troposphere. Near-surface atmospheric and subsurface properties (such as soil temperature, relative humidity, etc.) are known to have an impact on zi. Nevertheless, precise relationships between these surface properties and zi are less well known and not easily discernible from the multi-year dataset. Machine learning approaches, such as random forest (RF), which use a multi-regression framework, help to decipher some of the physical processes linking surface-based characteristics to zi. In this study, a 4-year dataset from 2016 to 2019 at the Southern Great Plains site is used to develop and test a machine learning framework for estimating zi. Parameters derived from Doppler lidars are used in combination with over 20 different surface meteorological measurements as inputs to a RF model. The model is trained using radiosonde-derived zi values spanning the period from 2016 through 2018 and then evaluated using data from 2019. Results from 2019 showed significantly better agreement with the radiosonde compared to estimates derived from a thresholding technique using Doppler lidars only. Noteworthy improvements in daytime zi estimates were observed using the RF model, with a 50 % improvement in mean absolute error and an R2 of greater than 85 % compared to the Tucker method zi. We also explore the effect of zi uncertainty on convective velocity scaling and present preliminary comparisons between the RF model and zi estimates derived from atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Land-Surface Temperature Transitions at the Bankhead National Forest (LASTT-BNF) Field Campaign Report

Land surface types that are common in the Southeast United States (e.g., forests, agriculture, urban) can play key roles in the regulation of surface-atmosphere energy exchange and boundary-layer evolution in the region (Hinkle et al. 2024). Heterogeneity in these land-surface types and associated emissivities can drive strong transitions in land surface temperature (LST), which is an important component of the surface energy balance. Within the forested canopy surrounding the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s field deployment at the Bankhead National Forest (BNF) in Alabama main site (M1) (Kuang et al. 2026), the different components of the vegetation and ground surface can create strong gradients in surface temperature that can influence the canopy thermal environment and vegetative function (e.g., stress, transpiration), both of which can have important, yet poorly characterized, controls on lower atmospheric processes (e.g., thermal turbulence, secondary circulations).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

AE33 Aethalometer Records at RMBL [AMF2] from April 2022 to October 2023

The dataset presents atmospheric mass loadings of black carbon (BC) and brown carbon (BrC), during the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign that took place from 2021 – 2023 in Gothic, CO. A Magee Scientific aethalometer (model AE33) was deployed at the Rocky Mountain Biological Laboratory, 200 m north of AMF2 to monitor mass loadings of optically absorbing aerosols. The instrument inlet was equipped with a BGI SCC 1.829 ambient cyclone with a particle cutoff of 2.5 μm and placed 5 m above ground level. The dataset reports hour-resolved BC mass loadings at 370, 470, 520, 590, 660, 880, and 950 (BC370, BC470, BC 520, BC590, BC660, BC880, BC950 in ng/m3) reported by the instrument built-in algorithm, which calculates mass loadings from the rate of change of the attenuation of light transmitted through the aerosol-laden filter. BC880 is the operationally defined reference of the BC concentration. Hour-resolved absorbance at each wavelength were calculated from their respective mass absorption cross-section in inverse megameters (Mm-1). The absorption Angstrom exponent (AAE) for BrC and BC were calculated for each hour. BrC AAE (AAE_BrC) was calculated from the slope of Log(wavelength) versus Log(absorbance) based on the measurements at 370, 470, and 520 nm. BC AAE (AAE_BrC) was calculated from the slope of Log(wavelength) versus Log(absorbance) based on the measurements at 590, 660, 880, and 950 nm. The aethalometer record spans time periods of 4/5/2022 – 10/3/2022 and 12/8/2022 – 10/9/2023. The ambient CO2 concentration recorded by a Vaisala CARBOCAP carbon dioxide probe GMP343 is also reported in ppm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Integrating Reanalysis and Satellite Cloud Information to Estimate Surface Downward Long-Wave Radiation

The estimation of downward long-wave radiation (DLR) at the surface is very important for the understanding of the Earth’s radiative budget with implications in surface–atmosphere exchanges, climate variability, and global warming. Theoretical radiative transfer and observationally based studies identify the crucial role of clouds in modulating the temporal and spatial variability of DLR. In this study, a new machine learning algorithm that uses multivariate adaptive regression splines (MARS) and the combination of near-surface meteorological data with satellite cloud information is proposed. The new algorithm is compared with the current operational formulation used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Land Surface Analysis (LSA-SAF). Both algorithms use near-surface temperature and dewpoint temperature along with total column water vapor from the latest European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis ERA5 and satellite cloud information from the Meteosat Second Generation. The algorithms are trained and validated using both ECMWF-ERA5 and DLR acquired from 23 ground stations as part of the Baseline Surface Radiation Network (BSRN) and the Atmospheric Radiation Measurement (ARM) user facility. Results show that the MARS algorithm generally improves DLR estimation in comparison with other model estimates, particularly when trained with observations. When considering all the validation data, root mean square errors (RMSEs) of 18.76, 23.55, and 22.08 W·m –2 are obtained for MARS, operational LSA-SAF, and ERA5, respectively. The added value of using the satellite cloud information is accessed by comparing with estimates driven by ERA5 total cloud cover, showing an increase of 17% of the RMSE. The consistency of MARS estimate is also tested against an independent dataset of 52 ground stations (from FLUXNET2015), further supporting the good performance of the proposed model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Field Validation of Cloud Properties Sensor (SAIL Field Campaign Report)

The purpose of the Field Validation of Cloud Properties Sensor – SAIL campaign was to deploy Aerodyne’s extended-wavelength TWST cloud optical properties sensor (TWST-CPS) in an operationally relevant environment with co-located, externally validated sensors. Colocation with The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s deployment of its second Mobile Facility (AMF2) on the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign at Crested Butte, Colorado was ideal because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance over 440-1700 nm and retrieves cloud optical depth (COD), droplet effective radius (Reff), and thermodynamic phase (Phase). Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A low-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Instrument deployment to test robust operations and a new stray-light baffle design, and the continued development of analysis and retrieval algorithms using the data from this deployment, are central technical objectives of Aerodyne Research’s U.S. Department of Energy Small Business Innovative Research Phase 2 contract (DE-SC0020473, Low-cost shortwave spectroradiometer for retrieval of cloud properties).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Field Validation of Cloud Properties Sensor – SAIL Field Campaign Report

The purpose of the Field Validation of Cloud Properties Sensor – SAIL campaign was to deploy Aerodyne’s extended-wavelength TWST cloud optical properties sensor (TWST-CPS) in an operationally relevant environment with co-located, externally validated sensors. Colocation with The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s deployment of its second Mobile Facility (AMF2) on the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign at Crested Butte, Colorado was ideal because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance over 440-1700 nm and retrieves cloud optical depth (COD), droplet effective radius (Reff), and thermodynamic phase (Phase). Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A low-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Instrument deployment to test robust operations and a new stray-light baffle design, and the continued development of analysis and retrieval algorithms using the data from this deployment, are central technical objectives of Aerodyne Research’s U.S. Department of Energy Small Business Innovative Research Phase 2 contract (DE-SC0020473, Low-cost shortwave spectroradiometer for retrieval of cloud properties).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Logarithmic profile of temperature in sheared and unstably stratified atmospheric boundary layers

The impact of buoyancy on the mean velocity, temperature, and scalar concentration profiles in the lower atmosphere is typically investigated within the framework of Monin-Obukhov similarity theory (MOST). MOST is the theoretical foundation for parametrizing surface-atmosphere exchanges in nearly all weather, climate, and hydrological models.According to MOST, the classic logarithmic profiles of mean velocity and temperature break down as the buoyancy effects become important. However, recent studies on turbulent Rayleigh-Bénard convection and natural convection along vertical walls suggest that the mean temperature in the near-surface region still follows a logarithmic profile.Motivated by these new results, we study the mean potential temperature profile in sheared and unstably stratified atmospheric boundary layers using direct numerical simulations and field observations. We find that the mean potential temperature profile remains logarithmic across a wide range of stability parameters, which characterizes the relative importance of buoyancy versus shear effects. Compared to MOST, our results suggest that the buoyancy force does not modify the logarithmic nature of the mean potential temperature profile, but instead modulates its slope, which is no longer universal and differs from 1/κ,whereκisthe von Kármán constant. Furthermore, this study provides another perspective on scalar turbulence in the atmospheric boundary layer

58 GEOSCIENCES↗
DOE OSTI2023

Coast-Urban-Rural Atmospheric Gradient Experiment

Accurately representing the climate and weather variability within cities and providing well-tested representations of the impacts of urban systems on the atmospheric environment are challenges for current earth system models (ESMs). Field data for testing and developing these models are critical to addressing these limitations. The Atmospheric Radiation Measurement (ARM) user facility will support a field campaign aimed at understanding how different surface-atmosphere interactions around a city are influencing its climate. The Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) is expected to operate from December 2024 to November 2025 in and around Baltimore, Maryland. With its aging infrastructure, growing susceptibility to heat and flooding, and ongoing issues with air and water pollution, Baltimore is characteristic of many large industrial cities in the Eastern United States. ARM, a U.S. Department of Energy (DOE) Office of Science user facility, plans to deploy one of its three mobile observatories at Morgan State University’s Clifton Park site in downtown Baltimore. Ancillary ARM sites are also planned for rural Maryland, northwest of the city; and to the southern end of Kent Island in Chesapeake Bay. Data from CoURAGE will complement measurements from the Baltimore Social-Environmental Collaborative (BSEC), one of four DOE Urban Integrated Field Laboratories that will operate in cities across the United States to study urban climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Observed Land Surface Influence on Atmospheric Heat and Moisture Profiles During Interstorms

Land-atmospheric (L-A) feedbacks have historically been studied using models whose structure and parameterizations influence outcomes and insights. The representation of L-A feedbacks based on observations alone remains an ongoing challenge for understanding boundary layer development and precipitation. To address this gap, we use ground-based passive remote sensing and in-situ observations to present an analysis of the atmosphere during 103 interstorm soil moisture drydown events spanning nine warm seasons (2016–2024) in the U.S. Southern Great Plains region. By separating events based on local L-A coupling signals and characterizing the profiles of atmospheric heat and moisture to surface energy flux behavior, we investigate the physical mechanisms linking land surface processes to boundary layer development. We find that during interstorm drydowns, the atmospheric column follows a consistent pattern: moisture increases within the boundary layer, peaks near its top, and declines rapidly above, while warming occurs through the depth. Drydowns that shift toward evaporation produce stronger and deeper thermodynamic responses than cases dominated by sensible heating, which are weaker and shallower. Additionally, moisture is accumulated faster within the boundary layer during shorter drydowns, with longer drydowns representing slower, moisture-limited growth. Drydowns with wetter initial soil moisture will sustain stronger moistening within and above the boundary layer, accelerating buoyancy growth and convective potential toward the next storm. These results provide observational evidence linking surface flux evolution to boundary layer thermodynamics and offer a process-level benchmark for evaluating coupled L-A representations in models and demonstrating the influence of soil moisture on short-term weather forecasting skill.

Zhang, M. S. [Massachusetts Inst. of Technology (M↗
DOE OSTI2025

SAIL Radar b1 Data Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed the second ARM Mobile Facility (AMF2) near Crested Butte, Colorado for the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign. The SAIL campaign occurred from September 1, 2021, to June 15 2023. To study the water cycle in the East River Watershed, ARM deployed a vertically pointing Ka-band ARM Zenith radar (KAZR) and a scanning X-band precipitation radar managed by Colorado State University (CSU XPRECIP), as shown in Figure 1.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Advanced nanoscale characterization of aluminum nanoparticles with modified surface morphology via atmospheric helium and carbon monoxide plasmas

Aluminum nanoparticles (nAl) have the potential as energetic additives in explosive/propellant formulations. Scalable methodologies must be pursued to mitigate the inactive amorphous alumina shell surrounding the active aluminum (Al) core with modified surface morphology and chemistry for increased combustion effects. This work explores the feasibility of making reactive core/shell nAl with thinned oxide shells and modified surface coatings via a two-step atmospheric plasma surface treatment process in a custom dielectric barrier discharge plasma reactor. The commercial nAl of nominal average size similar to 40-60nm was first treated with helium (He) followed by He/carbon monoxide (CO) plasmas for different durations. The resultant samples were characterized via high-resolution transmission electron microscopy (HRTEM) and Fourier transform IR (FTIR) spectra. HRTEM images revealed sporadic patchy gamma -alumina deposits on particle surfaces and in gaps among particles for all samples, suggesting the non-uniform plasma effects of the He/CO glow. Nanoscale chemical analyses via scanning transmission electron microscopy elemental mapping and x-ray energy dispersive spectroscopy were further performed. Although no carbon-associated structure appeared in electron energy loss spectroscopy (EELS) spectra, the presence of carbonaceous materials was confirmed as a thin dispersive layer evenly distributed on the nAl surface suggesting either its amorphous nature or is present at a level insufficient to generate satisfactory EELS spectra. The trend of intensity profiles for key elements acquired by drawing lines across a single particle on the elemental maps confirmed that carbonaceous materials only existed on the surface and they were most likely carboxylates that increased with increased He/CO treatment duration, as evident by FTIR results. Finally, this work demonstrated the success of atmospheric plasma-treated reactive nAl with comprehensively characterized surface features via advanced microscopy and spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Surface temperatures reveal the patterns of vegetation water stress and their environmental drivers across the tropical Americas

Vegetation is a key component in the global carbon cycle as it stores ~450 GtC as biomass, and removes about a third of anthropogenic CO2 emissions. However, in some regions, the rate of plant carbon uptake is beginning to slow, largely because of water stress. Here, we develop a new observation-based methodology to diagnose vegetation water stress and link it to environmental drivers. We used the ratio of remotely sensed land surface to near surface atmospheric temperatures (LST/Tair) to represent vegetation water stress, and built regression tree models (random forests) to assess the relationship between LST/Tair and the main environmental drivers of surface energy fluxes in the tropical Americas. We further determined ecosystem traits associated with water stress and surface energy partitioning, pinpointed critical thresholds for water stress, and quantified changes in ecosystem carbon uptake associated with crossing these critical thresholds. Additionally, we found that the top drivers of LST/Tair, explaining over a quarter of its local variability in the study region, are (1) radiation, in 58% of the study region; (2) water supply from precipitation, in 30% of the study region; and (3) atmospheric water demand from vapor pressure deficits (VPD), in 22% of the study region. Regions in which LST/Tair variation is driven by radiation are located in regions of high aboveground biomass or at high elevations, while regions in which LST/Tair is driven by water supply from precipitation or atmospheric demand tend to have low species richness. Carbon uptake by photosynthesis can be reduced by up to 80% in water-limited regions when critical thresholds for precipitation and air dryness are exceeded simultaneously, that is, as compound events. Our results demonstrate that vegetation structure and diversity can be important for regulating surface energy and carbon fluxes over tropical regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Seasonal Dependent Impact of Ice Cloud Longwave Scattering on the Polar Climate

Most climate models neglect cloud longwave (LW) scattering because scattering is considered negligible compared to strong LW absorption by clouds and greenhouse gases. While this rationale is valid for simulating extrapolar regions, it is questionable for the polar regions, where the atmosphere is dry and hence has weak absorption, and ice clouds that have strong scattering capability frequently occur. Using the slab-ocean Community Earth System Model, we show that ice cloud LW scattering can warm winter surface air temperature by 0.8–1.8 K in the Arctic and 1.3–1.9 K in the Antarctic, while this warming becomes much weaker in polar summer. Such scattering effect cannot be correctly assessed when sea surface temperature and sea ice are prescribed as this effect is manifested through a surface-atmosphere coupling. Furthermore, cloud LW scattering is a necessity for the correct simulation of polar climate and surface radiation budget, especially in the winter.

54 ENVIRONMENTAL SCIENCES↗