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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

AmeriFlux FLUXNET-1F US-PFp SE2 Hardwood-4 CHEESEHEAD 2019

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-PFp SE2 Hardwood-4 CHEESEHEAD 2019. This is the FLUXNET version of the carbon flux data for the site US-PFp SE2 Hardwood-4 CHEESEHEAD 2019 produced by applying the standard ONEFlux (1F) software. Site Description - This tower (32m, trailer-based, telescoping) is located in the southeastern quadrant of the 10 x 10km study domain. It is located in a mixed hardwood forest - black ash and red maple (canopy height: 20 - 24.4 m).

Desai, Ankur↗
DOE OSTI2020

Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator

Abstract. Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, as well as the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, canopy structure, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) by mimicking the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events, splitting the logged forest patch into disturbed and intact patches; determine the survivorship of cohorts in the disturbed patch; and modifying the biomass and necromass (total mass of coarse woody debris and litter) pools following logging. We parameterized the logging module to reproduce a selective logging experiment at the Tapajós National Forest in Brazil and benchmarked model outputs against available field measurements. Our results suggest that the model permits the coexistence of early and late successional functional types and realistically characterizes the seasonality of water and carbon fluxes and stocks, the forest structure and composition, and the ecosystem succession following disturbance. However, the current version of FATES overestimates water stress in the dry season and therefore fails to capture seasonal variation in latent and sensible heat fluxes. Moreover, we observed a bias towards low stem density and leaf area when compared to observations, suggesting that improvements are needed in both carbon allocation and establishment of trees. The effects of logging were assessed by different logging scenarios to represent reduced impact and conventional logging practices, both with high and low logging intensities. The model simulations suggest that in comparison to old-growth forests the logged forests rapidly recover water and energy fluxes in 1 to 3 years. In contrast, the recovery times for carbon stocks, forest structure, and composition are more than 30 years depending on logging practices and intensity. This study lays the foundation to simulate land use change and forest degradation in FATES, which will be an effective tool to directly represent forest management practices and regeneration in the context of Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The impact of forest-controlled snow variability on late-season streamflow varies by climatic region and forest structure

Previous studies have documented how forests influence snow at fine spatial scales, but none have documented the influence that existing forest-snow variability has on streamflow. Here to test how much forest-controlled snow variability influences streamflow, a tiling parameterization based on classifications from high-resolution (1–3 m) vegetation maps was incorporated into the Distributed Hydrology and Soil Vegetation Model (DHSVM). Within each grid cell (90–150 m), the tiling parameterization simulated forest-snow variability with four independently evolving snowpacks. Each tile had unique radiation conditions to represent conditions underneath the canopy, in exposed areas, and along north- and south-facing forest edges. This tiled parameterization was used to test where and when detailed forest-snow modelling should be considered further and where and when the impacts are too small to be worth the effort. To test this, tiled model simulations of streamflow were compared to non-tiled model simulations in the Sierra Nevada, CA, the Jemez Mountains, NM, and the Eastern Cascades, WA. In Tuolumne, CA, the tiled model simulated little difference in grid cell average SWE, and late-season streamflow decreased by only 3%–4% compared to the non-tiled model. In Jemez, NM, the tiled model decreased late-season streamflow by 18% due to increased sublimation. In Chiwawa, WA, the tiled model increased late-season streamflow by 15% due to high shortwave radiation attenuation and less longwave radiation enhancement from the forest. Furthermore, within the Chiwawa, a substantial silvicultural practice was synthetically implemented to increase the north-facing edge's fractional area. This silvicultural experiment, which used the same fractional forest area in all simulations increased late-season streamflow by 35% compared to tiled model simulations that did not represent forest edges. In conclusion, representing forest-SWE variability had an effect on late-season streamflow in some watersheds but not in others based on the fractional area of the forest edges, forest characteristics, and climate conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Airborne LiDAR to Improve Canopy Fuels Mapping for Wildfire Modeling

Increasing conflict between wildfire and the built environment has increased the need for more up-to-date and finer resolution canopy fuels data to improve wildfire modeling and associated risk forecasts. The US Forest Service and US Department of the Interior’s LANDFIRE product, which provides 30-m resolution canopy fuels data for the entire US, is one of the most widely used sources of fuels data. However, the last complete mapping effort for LANDFIRE is based on 2016 conditions, and subsequent updates reflect disturbances 1-2 years behind the release year. Airborne systems equipped with Light Detection and Ranging (LiDAR) sensors can be deployed to actively sense canopy structure and estimate canopy fuels data (cover, height, base height, bulk density) at finer resolutions. Canopy base height (CBH) and canopy bulk density (CBD) are difficult to measure both in the field and in LiDAR point clouds. Still, they are important for accurately modeling crown fires, which are often intense and difficult to contain. Additionally, point cloud datasets are large, and calculations require efficient utilization of computational resources. To address these challenges, we are working on an approach that uses openly available National Ecological Observatory Network (NEON) airborne LiDAR data, with calculations processed in the R programming language and parallelized through the lidR package. CBH and CBD are often derived from tree height, diameter at breast height, and species-specific allometries using the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS). We aim to test if airborne LiDAR can estimate CBH and CBD without the use of empirical equations. Reliable estimates of canopy fuels data directly from airborne LiDAR could streamline quick, fine-resolution updates for use in wildfire behavior models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Long-term dynamics of soil, tree stem and ecosystem methane fluxes in a riparian forest

The carbon (C) budgets of riparian forests are sensitive to climatic variability. Therefore, riparian forests are hot spots of C cycling in landscapes. Only a limited number of studies on continuous measurements of methane (CH 4 ) fluxes from riparian forests is available. Here, in this work, we report continuous high-frequency soil and ecosystem (eddy-covariance; EC) measurements of CH 4 fluxes with a quantum cascade laser absorption spectrometer for a 2.5-year period and measurements of CH 4 fluxes from tree stems using manual chambers for a 1.5 year period from a temperate riparian Alnus incana forest. The results demonstrate that the riparian forest is a minor net annual sink of CH 4 consuming 0.24 kg CH 4 -C ha –1 y –1 . Soil water content is the most important determinant of soil, stem, and EC fluxes, followed by soil temperature. There were significant differences in CH 4 fluxes between the wet and dry periods. During the wet period, 83% of CH 4 was emitted from the tree stems while the ecosystem-level emission was equal to the sum of soil and stem emissions. During the dry period, CH 4 was substantially consumed in the soil whereas stem emissions were very low. A significant difference between the EC fluxes and the sum of soil and stem fluxes during the dry period is most likely caused by emission from the canopy whereas at the ecosystem level the forest was a clear CH 4 sink. Our results together with past measurements of CH 4 fluxes in other riparian forests suggest that temperate riparian forests can be long-term CH 4 sinks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Automated Method for Mapping Giant Kelp Canopy Dynamics from UAV

Satellite and aerial imagery have been used extensively for mapping the abundance and distribution of giant kelp ( Macrocystis pyrifera ) in southern California. There is now great potential for using unoccupied aerial vehicles (UAVs) to map kelp canopy at very high resolutions. However, tides and currents have been shown to affect the amount of floating kelp canopy on the water surface, and the impacts of these processes on remotely sensed kelp estimates in this region have not been fully quantified. UAVs were used to map fine-scale changes in canopy area due to tidal height and current speed at kelp forests off the coast of Palos Verdes, CA and Santa Barbara, CA. An automated method for detecting kelp canopy was developed that was 67% accurate using red-green-blue (RGB) UAV imagery and 93% accurate using multispectral UAV imagery across a range of weather, ocean, and illumination conditions. Increases in tidal height of 1 m reduced the amount of floating kelp canopy by 15% in Santa Barbara and by over 30% in Palos Verdes. The effect of current speed on visible kelp canopy was inconclusive, but there was a trend towards lower canopy area with increased current speed. Therefore, while tidal height and current speed can introduce significant variability to estimates of kelp abundance, the magnitude of this variability is site specific. Still, UAVs are a valuable tool for mapping of kelp canopy and can provide greater spatial resolution and temporal coverage than is possible from many satellite sensors. This data can provide insight into the patterns and drivers of high frequency fluctuations in kelp abundance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

TTP - WREF 3D Sonic Anemometer Tower D / Raw Data

Tower D is one of four subcanopy towers that were installed in the WREF canopy across a transect distance of 200m. Tower D had one CSAT3-3D sonic mounted at a height of 2.7 m a.g.l. The sonic is facing 290 degrees. The towers were installed to observe flow just above the forest floor and to identify any advection flows in the canopy. These data were also part of a larger ICOS project looking at forest flow coupling/decoupling with tower sites in Italy and Czech Republic.

17 WIND ENERGY↗
DOE OSTI2025

TTP - WREF 3D Sonic Anemometer Tower C / Raw Data

Tower C is one of four subcanopy towers that were installed in the WREF canopy across a transect distance of 200m. Tower C had one CSAT3-3D sonic mounted at a height of 2.7 m a.g.l. The sonic is facing 270 degrees. The towers were installed to observe flow just above the forest floor and to identify any advection flows in the canopy. These data were also part of a larger ICOS project looking at forest flow coupling/decoupling with tower sites in Italy and Czech Republic.

17 WIND ENERGY↗
DOE OSTI2022

Boosts in leaf-level photosynthetic capacity aid Pinus ponderosa recovery from wildfire

Forests mitigate climate change by sequestering massive amounts of carbon, but recent increases in wildfire activity are threatening carbon storage. Currently, our understanding of wildfire impacts on forest resilience and the mechanisms controlling post-fire recovery remains unresolved due to a lack of empirical data on mature trees in natural settings. Here, we quantify the physiological mechanisms controlling carbon uptake immediately following wildfire in mature individuals of ponderosa pine (Pinus ponderosa), a wide-spread and canopy-dominant tree species in fire-prone forests. While photosynthetic capacity was lower in burned than unburned trees due to an overall depletion of resources, we show that within the burned trees, photosynthetic capacity increases with the severity of damage. Our data reveal that boosts in the efficiency of carbon uptake at the leaf-level may compensate for whole-tree damage, including the loss of leaf area and roots. We further show that heightened photosynthetic capacity in remaining needles on burned trees may be linked with reduced water stress and leaf nitrogen content, providing pivotal information about post-fire physiological processes. Our results have implications for Earth system modeling efforts because measurements of species-level physiological parameters are used in models to predict ecosystem and landscape-level carbon trajectories. Finally, current land management practices do not account for physiological resilience and recovery of severely burned trees. Our results suggest premature harvest may remove individuals that may otherwise survive, irrevocably altering forest carbon balance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Adjustments to the law of the wall above an Amazon forest explained by a spectral link

Modification to the law of the wall represented by a dimensionless correction function ϕ RSL (z/h) is derived using atmospheric turbulence measurements collected at two sites in the Amazon in near-neutral stratification, where z is the distance from the forest floor and h is the mean canopy height. The sites are the Amazon Tall Tower Observatory for z/h∈ [1,2.3] and the Green Ocean Amazon (GoAmazon) site for z/h∈ [1,1.4]. Here, a link between the vertical velocity spectrum E ww (k) (k is the longitudinal wavenumber) and ϕ RSL is then established using a co-spectral budget (CSB) model interpreted by the moving-equilibrium hypothesis. The key finding is that ϕ RSL is determined by the ratio of two turbulent viscosities and is given as ν t,BL /ν t,RSL, where ν t,RSL = (1/A)∫$^{∞}_{0}$ τ(k)E ww (k)dk, ν t,BL = k v (z−d)u * , τ(k) is a scale-dependent decorrelation time scale between velocity components, A = C R /(1−C I ) = 4.5 is predicted from the Rotta constant C R = 1.8, and the isotropization of production constant C I = 3/5 given by rapid distortion theory, k v is the von Kármán constant, u * is the friction velocity at the canopy top, and d is the zero-plane displacement. Because the transfer of energy across scales is conserved in E ww (k) and is determined by the turbulent kinetic energy dissipation rate (ε), the CSB model also predicts that ϕ RSL scales with L BL /L d , where L BL is the length scale of attached eddies to z = d, and L d = u$_{*}^{3}$/ε is a macro-scale dissipation length.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Fungal mat growth and leaf colonization at the TRACE warming experiment, Mar - Aug 2024, Luquillo, Puerto Rico

This data package contains processed measurements on the growth of litter mat-forming fungi and the time to leaf colonization at the Tropical Responses to Altered Climate Experiment (TRACE). Located near the Sabana Field Research Station in Luquillo, Puerto Rico, the TRACE site is located in a mature, closed-canopy tropical rainforest within the Luquillo Experimental Forest (LEF). These data quantify fungal mat growth and the time to leaf colonization of fungi species Gymnopus johnstonii and Marasmius crinis-equi. The experiment was conducted in ambient (control) and experimentally warmed plots (4°C above ambient) during spring and summer periods to assess how litter mat-forming fungi respond to a range of environmental conditions of tropical wet forests. The data files include tables of relative fungal mat growth rates, time to leaf colonization, averages of soil temperature (°C), and number of dry days before leaf attachment. The data are stored in comma-separated values (CSV) format and viewable with any text editor, spreadsheet, or statistical software (e.g., R, Python, Excel). Associated metadata describe plot identifiers, measurement descriptions, and processing steps.

Agaric fungi↗
DOE OSTI2022

Advancing coupled fire-atmosphere research with HIGRAD/FIRETEC (w20_firetec) (CY 2021 Institutional Computing Annual Progress Report) [Slides]

LANL’s HIGRAD and FIRETEC models were used in a multi-scale simulation framework to investigate impacts of small-scale fuel heterogeneities on large-scale Pyro-Cb formation. Forest structural diversity is found to increase canopy fire spread, and thus risk of tree mortality in FIRETEC simulations. Structural diversity is associated with an increase in ladder fuels, which facilitate fire spread into the canopy. Low-intensity fire burning in marginal conditions is highly sensitive to small perturbation in atmospheric turbulence. These results highlight predictive limitations of individual fire simulations, and emphasize the need for ensemble simulations, especially for low-intensity, prescribed fire.

36 MATERIALS SCIENCE↗
DOE OSTI2025

WREF 3D Sonic Anemometer - Tower A / Raw Data

Tower A is one of four subcanopy towers that were installed in the WREF canopy across a transect distance of 200m. Tower A had two CSAT3-3D sonics mounted at a height of 2.7m a.g.l. One (A1) is facing 290 degrees; the second (A2) is facing 90 degrees. The towers were installed to observe flow just above the forest floor and to identify any advection flows in the canopy. These data were also part of a larger ICOS project looking at forest flow coupling/decoupling with tower sites in Italy and Czech Republic.

17 WIND ENERGY↗
DOE OSTI2025

TTP - WREF 3D Sonic Anemometer Tower B / Raw Data

Tower B is one of four subcanopy towers that were installed in the WREF canopy across a transect distance of 200m. Tower B had two CSAT3-3D sonics mounted at a height of 2.7 m a.g.l. One (B1) is facing 270 degrees; the second (B2) is facing 90 degrees. The towers were installed to observe flow just above the forest floor and to identify any advection flows in the canopy. These data were also part of a larger ICOS project looking at forest flow coupling/decoupling with tower sites in Italy and Czech Republic.

17 WIND ENERGY↗
DOE OSTI2025

Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'

This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine watershed' (Worsham et al., 2025). All data were collected in the East River, Washington Gulch, Slate River, and Coal Creek watersheds of Colorado. In the paper, we quantified the relative influence of climate, topographic, edaphic, and geologic factors on conifer stand structure and composition, and their functional relationships, at the watershed scale. We used waveform LiDAR data to derive spatially continuous stand structure metrics. We fused these with a species-level classification map to estimate tree species abundance. We applied generalized additive and generalized boosted models to evaluate the covariability of structural and compositional metrics with abiotic variables. The package contains the essential products required for reproducing our analysis and the tables and figures reported in the publication. The products comprise four classes: (1) geospatial data, (2) tabular data used for inferential analysis, (3) tabular data describing analytical results and performance statistics, and (4) a data user guide. (1) includes discretized waveform LiDAR data, locations and attributes of individual tree crowns, sampling locations and domain boundaries, a canopy height model, and raster files of estimated forest structural and compositional metrics at 100 m grid scale. (2) includes all response and explanatory variable values applied in inferential models. Response variables include conifer forest stand density, basal area, 95th percentile height, quadratic mean diameter, and others. Explanatory variables include climatic water deficit, actual evapotranspiration, elevation, heat load, soil available water content, and others. (3) includes results of training and testing several individual tree detection (ITD) algorithms, as well as inferential modeling results. (4) is a PDF user guide for this data package, including detailed descriptions and data dictionaries for all files. The data package root contains 17 assets: 8 compressed tape archive (.tar.gz) files, 5 comma-separated values (.csv) files, 3 Geographic Tagged Image File Format (GeoTIFF) (.tif) files, and 1 Portable Document Format (.pdf) file. The compressed .tar.gz archives contain ESRI shapefiles (.shp) .tif, compressed LASer (.laz), and .csv files. The archives must first be decompressed using the widely distributed command-line software utility TAR. All other files, including constituent files within the .tar.gz archives, can be opened in the open-source R statistical computing environment. Alternatively, .csv files may also be read in any simple text editor software or Microsoft Excel. Geospatial files including .shp and .tif files can also be opened in GIS software, such as QGIS (open-source) or ESRI ArcGIS (proprietary). The .pdf Data User Guide can be read with Adobe Acrobat Reader or other compatible readers.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2026

The U.S. DOE ARM User Facility Establishes a New Site for Studies of Land–Aerosol–Cloud Interactions in the Southeastern United States

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility has established a new site in the Bankhead National Forest (BNF) in northern Alabama that will gather data on how clouds, the land surface, and aerosols interact at a hierarchy of scales important to understanding and simulating the Earth system. Starting its operations in October 2024, the BNF site provides a multi-year opportunity for scientists to unravel complex land-atmosphere interactions. A suite of ground-based sensors, elevated tower-based instrumentation, and aerial facilities will enable scientists to investigate those interactions from within the canopy to the clouds. The Southeastern United States was recommended by the DOE ARM and its collaborators in the broader community as an important region to address their common scientific questions given the region’s abundant surface-forced convective clouds and mesoscale convective systems that pose ongoing challenges in Earth system models. The region is also home to significant terrain complexity and land-use heterogeneity that will unleash new understanding of anthropogenic and biogenic aerosol processes, boundary-layer aerosol-cloud interactions, and the interactions between the terrestrial ecosystem and coupled aerosol-cloud-radiation processes.

Aerosols↗
DOE OSTI2024

Scaling Individual Tree Transpiration With Thermal Cameras Reveals Interspecies Differences to Drought Vulnerability

Abstract Understanding tree transpiration variability is vital for assessing ecosystem water‐use efficiency and forest health amid climate change, yet most landscape‐level measurements do not differentiate individual trees. Using canopy temperature data from thermal cameras, we estimated the transpiration rates of individual trees at Harvard Forest and Niwot Ridge. PT‐JPL model was used to derive latent heat flux from thermal images at the canopy‐level, showing strong agreement with tower measurements ( R 2 = 0.70–0.96 at Niwot, 0.59–0.78 at Harvard at half‐hourly to monthly scales) and daily RMSE of 33.5 W/m 2 (Niwot) and 52.8 W/m 2 (Harvard). Tree‐level analysis revealed species‐specific responses to drought, with lodgepole pine exhibiting greater tolerance than Engelmann spruce at Niwot and red oak showing heightened resistance than red maple at Harvard. These findings show how ecophysiological differences between species result in varying responses to drought and demonstrate that these responses can be characterized by deriving transpiration from crown temperature measurements.

Javadian, Mostafa↗
DOE OSTI2023

Seeing the Disturbed Forest for the Trees: Remote Sensing Is Underutilized to Quantify Critical Zone Response to Unprecedented Disturbance

Understanding the severity and extent of near surface critical zone (CZ) disturbances and their ecosystem response is a pressing concern in the face of increasing human and natural disturbances. Predicting disturbance severity and recovery in a changing climate requires comprehensive understanding of ecosystem feedbacks among vegetation and the surrounding environment, including climate, hydrology, geomorphology, and biogeochemistry. Field surveys and satellite remote sensing have limited ability to effectively capture the spatial and temporal variability of disturbance and CZ properties. Technological advances in remote sensing using new sensors and new platforms have improved observations of changes in vegetation canopy structure and productivity; however, integrating measures of forest disturbance from various sensing platforms is complex. By connecting the potential for remote sensing technologies to observe different CZ disturbance vectors, we show that lower severity disturbance and slower vegetation recovery are more difficult to quantify. Case studies in montane forests from the western United States highlight new opportunities, including evaluating post-disturbance forest recovery at multiple scales, shedding light on understory vegetation regrowth, detecting specific physiological responses, and refining ecohydrological modeling. Learning from regional CZ disturbance case studies, we propose future directions to synthesize fragmented findings with (a) new data analysis using new or existing sensors, (b) data fusion across multiple sensors and platforms, (c) increasing the value of ground-based observations, (d) disturbance modeling, and (e) synthesis to improve understanding of disturbance.

54 ENVIRONMENTAL SCIENCES↗