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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Water4Energy Tier-1 Raw Observations for TVA Seasonal Prediction, Version 1

Tier-1 (Step-1) raw observation staging collection for the Water4Energy Genesis Task-1 project on weeks-to-years prediction of Tennessee Valley temperature and precipitation. This data-only deposit includes CPC/PSL teleconnection indices, NOAA OISST monthly and ERSST sea-surface temperature, ERA5-derived daily 1° fields (t2m, tp, msl for 1980–2024), CFSv2 NMME ensemble-mean seasonal baselines, and a TVA boundary mask. The product supports seasonal teleconnection diagnostics and construction of AI ready-to-train packs published separately. Multi-terabyte hourly archives are excluded from this version.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

GSOD Based Daily Global Mean Surface Temperature and Mean Sea Level Air Pressure (1982-2011)

This data product contains all the gridded data set at 1/4 degree resolution in ASCII format. Both mean temperature and mean sea level air pressure data are available. It also contains the GSOD data (1982-2011) from NOAA site, contains station number, location, temperature and pressures (sea level and station level). The data package also contains information related to the data processing methods

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of WSR-88D Level III and MRMS Rainfall Estimates Against Rain Gauge Observations at the Savannah River Site

Rainfall data for the Savannah River Site (SRS) has been historically measured by rain gauges. These instruments serve as ground truth for most climatological and weather applications; however, gauge measurements are prone to errors or biases under certain weather conditions. Rainfall estimates from radar reflectivity values have been developed and improved over the years and serve as an alternative or supplement for gauge measurements. This study compares measurements from tipping bucket rain gauges with rainfall estimates from the NOAA NWS WSR-88D Level III hourly rainfall product and the Multi-Radar Multi-Sensor (MRMS) gauge-corrected precipitation estimate. Results show good agreement between radar derived amounts and ground measurements, with MRMS values showing correlation coefficients of 0.60-0.95 and RMSE values of less than 1.0 cm (0.4 in). The WSR-88D Level III estimates result in correlation coefficients of 0.46-0.86 and RMSE values of less than 1.3 cm (0.5 in). Few outliers are observed for each data pair and are evaluated against precipitation classification products (WSR-88D Hybrid Hydrometeor Classification product and MRMS Precipitation Flag product). The rain gauges used in this study are not part of the Hydrometeorological Automated Data System (HADS) network used to correct the MRMS estimates and therefore, results of this work provide an independent validation of the MRMS gauge correction scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Wave Classification Statistical Data for US Waters

Wave statistics computed using output from the NOAA WWIII hindcast simulations, spanning thirty years from 1980 to 2009. The statistics are computed based on frequency-directional variance density spectra every three hours for 1951 locations in US waters.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Extreme Significant Wave Heights for US Coastal Waters

Includes extreme significant wave heights, in meters, computed using peaks over threshold method on NOAA 30-year WWIII hindcast data. Extreme values for 5, 10, 25, 50, and 100 year return periods were computed. Sites cover US coastlines. Column 1: Site identifier/name Column 2: Site latitude Column 3: Site longitude Column 4: 5-year extreme Hs, in meters Column 5: 10-year extreme Hs, in meters Column 6: 25-year extreme Hs, in meters Column 7: 50-year extreme Hs, in meters Column 8: 100-year extreme Hs, in meters

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Tidal Currents in San Juan Archipelago, Washington

Re-analyzed acoustic Doppler current profiler (ADCP) data originally collected by NOAA CO-OPS (Center for Operational Oceanographic Products and Services) and equivalent point data from Pacific Northwest National Laboratory's FVCOM (Finite Volume Community Ocean Model) model of the region. Data are processed to products describing characteristics of tidal currents relevant to tidal turbines, as well as power output estimates for a notional turbine deployed from a surface platform or from the seabed at each location. These data underpin the results presented in their associated paper - see below.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Wave and Offshore Wind Resource in the U.S. Pacific Ocean Minor Outlying Islands

Coastal environments such as islands have unique opportunities for renewable energy resources. This work explores the wave and offshore wind energy potential for the U.S. Pacific Ocean Minor Outlying Islands, including Baker Island, Howland Island, Jarvis Island, Johnston Atoll, Kingman Reef, Palmyra Atoll, and Wake Island. A numerical wave model based on WAVEWATCH III and SWAN (both are NWS / NOAA models) was developed, validated, and executed to generate a 32-year hindcast dataset suitable for resource characterization for each island. A complementary offshore wind resource characterization is provided for the same time period based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5). Each island has five netcdf files: 1. wave_[island]_annual_J_map.nc: the data used to generate the map of annual averaged omnidirectional wave power (J [kW/m]) 2. wave_[island]_100m_IEC: six IEC parameters at 100m isobath from 1979/01/01 to 2020/12/31, output hourly 3. wave_[island]_5km_IEC: six IEC parameters at 5km from the shoreline 1979/01/01 to 2020/12/31, output hourly 4. wind_island_100mASL_windspeed_timeseries.nc: wind speed timeseries from ERA5 at 100 m above sea level within a 60 km radius of the island (m/s) 1979/01/01 to 2010/12/31, output hourly 5. wind_island_100mASL_winddirection_timeseries.nc: wind direction timeseries from ERA5 at 100 m above sea level within a 60 km radius of the island (degrees) 1979/01/01 to 2010/12/31, output hourly

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

The LAKE model input dataset for three Arctic lakes

This dataset contains meteorological data collected for three Arctic lakes and compiled to satisfy input requirements of the LAKE 2.0 model. The dataset was generated to act as a benchmarking dataset for future model-data inter-comparisons. The LAKE 2.0 model simulates temperatures within the water later and the sedimentary layer of a lake. The LAKE2.0. is an open-source code and available to download via this weblike http://tesla.parallel.ru/Viktor/LAKE/-/wikis/LAKE-model (last visit July 14, 2021). The meteorological data are required to simulate the surface energy balance at the surface of a lake. This dataset includes a compilation of the meteorological data pulled from multiple data streams, including National Oceanic and Atmospheric Administration (NOAA) climate data, Circumarctic Lakes Observation Network (CALON) data, and the United States Geological Survey (USGS) data. The data were compiled for three Arctic lakes: FoxDen (66.55877, -164.45670), Atqasuk (70.452497, -156.951984), and Toolik (68.63150, -149.60740). Each meteorological data is in comma-delimited format (file extension ‘.dat’) and includes eight columns: Temperature [K], Pressure [Pa], longwave downward radiation [W/m2], shortwave downward radiation [W/m2], “U” wind speed [m/s], ”V” wind speed [m/s], humidity [kg/kg], precipitation [m/s]. In addition to the meteorological data file, we included setup and driver files. The Toolik lake is the deepest out of three lakes and has inflowing and outflowing groundwater data. InflowOutflowREADME.txt has more information about inflow and outflow flies. The other two lakes are much shallower and modeled as a closed system (i.e. no water inflow or outflow).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Manuscript model outputs, model source code, and figure scripts: The role of geomorphology in mediating biomass allocation impacts on salt-marsh resilience and carbon accumulation

This data package provides model source code (C++), model outputs, and figure generation scripts (R) needed to reproduce the following manuscript: Bruns, Nicholas E., Genevieve L. Noyce, and Matthew L. Kirwan. "The Role of Geomorphology in Mediating Biomass Allocation Impacts on Salt-Marsh Resilience and Carbon Accumulation." Estuarine, Coastal and Shelf Science 327 (December 2025): 109549. https://doi.org/10.1016/j.ecss.2025.109549. This manuscript investigates how geomorphology mediates the impact of biomass allocation shifts on salt marsh persistence and carbon (C) sequestration under sea level rise. We use a 1-D soil-column model (Kirwan and Mudd 2012) to perform experiments across a range of static root:shoot ratios (RSR = 1-4) spanning observed values. The model explicitly simulates interactions between tidal inundation, productivity, inorganic sediment deposition, and organic matter accumulation. Experiments determine whether geomorphic feedbacks amplify, dampen, or leave unchanged the ecosystem response to biomass allocation shifts. A first experiment uses constant sea level rise (2.5 mm/yr) to examine equilibrium dynamics and their influence on carbon accumulation rates across different suspended sediment concentrations (SSC). A second set of experiments calculates threshold sea level rise rates for marsh drowning across RSR and SSC combinations. Final experiments apply accelerating sea level rise scenarios (2000-2200) derived from NOAA projections (Sweet et al. 2022) to generate an envelope of expected responses, quantifying the importance of biomass allocation shifts on marsh carbon accumulation and persistence. All experiments are repeated across SSC ranging from 5-50 mg/L to investigate how these interactions vary in micro-tidal marshes with different sediment supplies. Package contents: * README.txt with detailed description of package contents and instructions for reproducing manuscript figures and model outputs * R scripts for generating all manuscript figures * C++ baseline model code from Kirwan and Mudd (2012) * C++ source code for 4 experimental model variants used in the manuscript, extending above baseline code * Model input files (.csv, .txt) including sea level rise scenarios * Model output files (.txt) used in manuscript analyses Temporal coverage: Model simulations span years 1900-2200, with accelerating sea level rise scenarios for 2000-2200. Key variables: Root:shoot ratio, suspended sediment concentration, carbon accumulation rate, vertical accretion rate, marsh elevation, inundation depth, threshold sea level rise rate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

LAI, EVI, NDVI, and kNDVI in 23 pantropical forests affected by 21 cyclones

Statement of purpose: Cyclones alter the function and composition of tropical forests, making effects of intensifying cyclones on carbon-rich forests a critical topic of study. Here, we quantified cyclone-induced damage and recovery of 21 cyclone disturbances affecting 23 pantropical forest sites between 1988-2017 utilizing leaf area index (LAI), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and transformed NDVI (kNDVI) values from Google Earth Engine. Field observations collected in a meta-analysis (Bomfim et al., 2022, in review) were used to ground-truth and test effects of soil resource availability and disturbance factors on damage and recovery. This meta-analysis also served as the basis to begin vegetation index extraction, utilizing unique site and date combinations, from tropical forests effect by cyclone disturbances. We began collecting NDVI (5km resolution) from the NOAA Climate Data Record (CDR) of AVHRR Normalized Difference Vegetation Index (NDVI), Version 5 data product (Vermote, 2019) for all case studies included, 42. Next, we began extracting Landsat data from Landsat 4, 5, and 8, courtesy of the U.S. Geological Survey, in search of higher resolution data. We selected a 3 by 3 Landsat pixel area, leading to a 90m resolution data extraction. The specific imagery used includes Landsat 4 USGS Landsat 4 TM Collection 1 Tier 1 TOA (top of atmosphere) Reflectance, Landsat 5 USGS Landsat 5 TM (thematic mapper) Collection 1 Tier 1 TOA Reflectance, and Landsat 8 USGS Landsat 8 Collection 1 Tier 1 TOA Reflectance. Within Google Earth Engine, we selected the date and location (latitude and longitude), calculated NDVI, kNDVI, and EVI utilizing Landsat bands (see metadata_NGEE-tropics_cyclones), and extracted post- and pre-cyclone values for each case study to calculate cyclone-induced change in the vegetative index. Due to limited spatial resolution of Landsat remote sensing data, MODIS products were investigated next. First, the MOD13Q1.006 Terra Vegetation Indices 16-Day Global 250m product was used to extract 250m EVI and NDVI (Didan, 2015) and then the MCD15A3H.006 MODIS Leaf Area Index/FPAR 4-Day Global 500m product product was used to extract LAI 500m (Myneni et al., 2015). Pre- and post-cyclone values, change in the vegetative index, and standard deviation for all values are included in the main csv (see case_study_data.csv) for all vegetative indices collected, including LAI 500m, EVI 250m, NDVI 250m, NDVI 90m, kNDVI 90m, EVI 90m, and NDVI 5km. Lastly, recovery values were calculated utilizing a standardization method (see metadata_NGEE-tropics_cyclones) and recovery values for MODIS (see MODIS_recovery.csv) and Landsat (Landsat_recovery.csv) data are included.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

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

This is the AmeriFlux version of the carbon flux data for the site US-xRN NEON Oak Ridge National Lab (ORNL). 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↗
DOE OSTI2022

AmeriFlux US-Bsg Burns Sagebrush

This is the AmeriFlux version of the carbon flux data for the site US-Bsg Burns Sagebrush. Site Description - The site was established in 2012 and is part of a NOAA observation network for high precision measurements of carbon dioxide concentrations. It is located about 60 km southwest of Burns, Oregon in the Oregon High Desert. The vegetation in this area is dominated by sagebrush. The sampling inlets are at the heights of 18.5, 28.5, and 38.5 m. Gas analysis is performed with a Picarro 2302 Cavity Ringdown Spectrometer and a Li-Cor 7200 enclosed path IRGA. The tower is also equipped with a set of meteorological instruments, including an HMP sensor, radiation sensors (incoming and diffuse PAR, Net radiometer), and a CSAT3 sonic anemometer. This site is also part of the PhenoCam network operated by Harvard University and the University of New Hampshire.

Still, Chris↗
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 OSTI2011

ESG-CET Final Progress Title

Drawing to a close after five years of funding from DOE's ASCR and BER program offices, the SciDAC-2 project called the Earth System Grid (ESG) Center for Enabling Technologies has successfully established a new capability for serving data from distributed centers. The system enables users to access, analyze, and visualize data using a globally federated collection of networks, computers and software. The ESG software - now known as the Earth System Grid Federation (ESGF) - has attracted a broad developer base and has been widely adopted so that it is now being utilized in serving the most comprehensive multi-model climate data sets in the world. The system is used to support international climate model intercomparison activities as well as high profile U.S. DOE, NOAA, NASA, and NSF projects. It currently provides more than 25,000 users access to more than half a petabyte of climate data (from models and from observations) and has enabled over a 1,000 scientific publications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

PMEL contributions to the collaboration: SCALING THE EARTH SYSTEM GRID TO PETASCALE DATA for the DOE SciDACs Earth System Grid Center for Enabling Technologies

Drawing to a close after five years of funding from DOE's ASCR and BER program offices, the SciDAC-2 project called the Earth System Grid (ESG) Center for Enabling Technologies has successfully established a new capability for serving data from distributed centers. The system enables users to access, analyze, and visualize data using a globally federated collection of networks, computers and software. The ESG software now known as the Earth System Grid Federation (ESGF) has attracted a broad developer base and has been widely adopted so that it is now being utilized in serving the most comprehensive multi-model climate data sets in the world. The system is used to support international climate model intercomparison activities as well as high profile U.S. DOE, NOAA, NASA, and NSF projects. It currently provides more than 25,000 users access to more than half a petabyte of climate data (from models and from observations) and has enabled over a 1,000 scientific publications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

TweetAurora.com – Citizen Scientists Experiencing the Extremes of Space Weather

On the evening of October 24, 2011 a geomagnetic storm raged across Europe and the United States. Aurora was visible as far south as Alabama in the US, and social media networks helped transmit the visibility of the lights. The purpose of this proposal is a proof of concept demonstration for collecting, analyzing, and interpreting data on the dynamics and evolution of auroral events via real-time social media, which acts as a sensor array distributed in both time and space. We will validate the efficacy of this observational framework by comparison to measurements and predictions of geomagnetic activity as provided by the NOAA Space Weather Prediction Center. We hypothesize that time-domain volunteered information (VI) from the Twitter social network can be derived with sufficient integrity to track events as they unfold and possibly predict events and their impending severity. By comparing the derived information with other space-based and ground-based measurements of an event, we further hypothesize that the derived information can be used as a complementary data source for scientific research of the event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

A National Strategy for Advancing Climate Modeling

Climate models are the foundation for understanding and projecting climate and climate-related changes and are thus critical tools for supporting climate-related decision making. This study developed a holistic strategy for improving the nation's capability to accurately simulate climate and related Earth system changes on decadal to centennial timescales. The committee's report is a high level analysis, providing a strategic framework to guide progress in the nation's climate modeling enterprise over the next 10-20 years. This study was supported by DOE, NSF, NASA, NOAA, and the intelligence community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Mapping and Assessment of the United States Ocean Wave Energy Resource

This project estimates the naturally available and technically recoverable U.S. wave energy resources, using a 51-month Wavewatch III hindcast database developed especially for this study by National Oceanographic and Atmospheric Administration's (NOAA's) National Centers for Environmental Prediction. For total resource estimation, wave power density in terms of kilowatts per meter is aggregated across a unit diameter circle. This approach is fully consistent with accepted global practice and includes the resource made available by the lateral transfer of wave energy along wave crests, which enables wave diffraction to substantially reestablish wave power densities within a few kilometers of a linear array, even for fixed terminator devices. The total available wave energy resource along the U.S. continental shelf edge, based on accumulating unit circle wave power densities, is estimated to be 2,640 TWh/yr, broken down as follows: 590 TWh/yr for the West Coast, 240 TWh/yr for the East Coast, 80 TWh/yr for the Gulf of Mexico, 1570 TWh/yr for Alaska, 130 TWh/yr for Hawaii, and 30 TWh/yr for Puerto Rico. The total recoverable wave energy resource, as constrained by an array capacity packing density of 15 megawatts per kilometer of coastline, with a 100-fold operating range between threshold and maximum operating conditions in terms of input wave power density available to such arrays, yields a total recoverable resource along the U.S. continental shelf edge of 1,170 TWh/yr, broken down as follows: 250 TWh/yr for the West Coast, 160 TWh/yr for the East Coast, 60 TWh/yr for the Gulf of Mexico, 620 TWh/yr for Alaska, 80 TWh/yr for Hawaii, and 20 TWh/yr for Puerto Rico.

16 TIDAL AND WAVE POWER↗