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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Offshore Resource Assessment and Design Conditions: A Data Requirements and Gaps Analysis for Offshore Renewable Energy Systems

The offshore renewable energy industry requires accurate meteorological and oceanographic (“metocean”) data for evaluating the energy potential, economic viability, and engineering requirements of offshore renewable energy projects. It is generally recognized that currently available metocean data, instrumentation, and models are not adequate to meet all of the stakeholder needs on a national scale. Conducting wind and wave resource assessments and establishing load design conditions requires both interagency collaboration as well as valuable input from experts in industry and academia. Under the Department of Energy and Department of Interior Memorandum of Understanding, the Resource Assessment and Design Condition initiative supports collaborative national efforts by adding to core atmospheric and marine science knowledge relevant to offshore energy development. Such efforts include a more thorough understanding and data collection of key metocean phenomena such as wind velocity and shear; low-level jets; ocean, tidal, and current velocities; wave characteristics; geotechnical data relating to surface and subsurface characteristics; seasonal and diurnal variations; and the interaction among these conditions. Figure 1 presents a graphical representation of some metocean phenomena that can impact offshore energy systems. This document outlines the metocean observations currently available; those that are not available; and those that require additional temporal-spatial coverage, resolution, or processing for offshore energy in an effort to gather agreed-upon, needed observations.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Mesoscale evaluation of AMPS using AWARE radar observations of a wind and precipitation event over the Ross Island region of Antarctica

Surface, upper-air, and radar observations are used to assess the performance of the Antarctic Mesoscale Prediction System (AMPS) in simulating the mesoscale aspects of a wind and precipitation event over the Ross Island region of Antarctica that spanned January 16–20, 2016. The observations, collected during the Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE), provide a unique dataset for evaluating AMPS, especially the radar observations that facilitate a three-dimensional depiction of winds and precipitation. Comparisons of AMPS forecast data with surface meteorology, balloon-sounding, and profiling radar observations at and above sites near McMurdo Station reveal a mixture of similarities and differences. A generally southerly flow is evident at low levels in both the AMPS simulations and observed Doppler radial velocities. AMPS winds are comparable to those observed at the surface and aloft in terms of magnitude, direction, and timing but the strongest simulated southerly flow is displaced eastward relative to the observations. AMPS-simulated reflectivity over the broader Ross Island region is more limited in areal extent and smaller in magnitude than observed by a scanning Doppler radar. Three episodes of surface precipitation are observed near McMurdo Station over the five-day event with peak rates of ~3 mm h -1 and a total accumulation of ~22 mm. However, AMPS produces no surface precipitation at that location over the five-day event due to a low-level dry bias in the forecasts. Herein, the results show the first observationally based three-dimensional understanding of meteorology in the Ross Island region.

AMPS↗
DOE OSTI2010

Optimization of a solar powered absorption cycle under Abu Dhabi's weather conditions

In order for the solar absorption air conditioners to become a real alternative to the conventional vapour compression systems, their performance has to be improved and their total cost has to be reduced. A solar powered absorption cycle is modeled using the Transient System Simulation (TRNSYS) program and Typical Meteorological Year 2 data of Abu Dhabi. It uses evacuated tube collectors to drive a 10 kW ammonia-water absorption chiller. Firstly, the system performance and its total cost are optimized separately using single objective optimization algorithms. The design variables considered are: the collector slope, the collector mass flow rate, the collector area and the storage tank volume. The single objective optimization results show that MATLAB global optimization methods agree with the TRNSYS optimizer. Secondly, MATLAB is used to solve a multi-objective optimization problem to improve the system's performance and cost, simultaneously. The optimum designs are presented using Pareto curve and show the potential improvements of the baseline system. (author)

14 SOLAR ENERGY↗
DOE OSTI2019

Strong Influence of Irrigation on Water Budget and Land Surface Temperature in Indian Subcontinental River Basins

Irrigation modulates the terrestrial water budget, especially in intensively irrigated regions such as Indian sub-continent river basins, where 35% of agricultural land has been irrigated during 2010. Here, we investigate the impact of irrigation on water budget components and land surface temperature (LST), as well as seasonal and annual trends of irrigation water demand in response to climate variability over the Indian sub-continental region. We use the Variable Infiltration Capacity (VIC) model coupled with an irrigation scheme (VIC-IRR) to represent the irrigation activities. The VIC-IRR model was calibrated and evaluated against in-situ and remote sensing observations including streamflow from India-Water Resource Information System (WRIS), Terrestrial Water Storage Change (TWSC) from Gravity Recovery and Climate Experiment (GRACE), LST from Advanced Along-Track Scanning Radiometer (AATSR), and observed gravimetric soil moisture data from India Meteorology Department (IMD). We conducted two simulations (i.e., with and without irrigation) over 18 Indian sub-continental basins at 0.25° spatial resolution from 1951 to 2012. The comparison between the two simulations indicates that as a result of irrigation, evapotranspiration (ET) increases in all the basins. We find that mean annual ET of Indus and Ganges basins increases by 47% and 12%, respectively due to irrigation. After irrigation, basin averaged total runoff (TR) was increased in the most irrigated basins (i.e., Sabarmati, Ganges, and Indus) by 4.62%, 11.87% and 7.06% in the monsoon, pre-monsoon, and post-monsoon seasons, respectively. The land surface temperature was cooled down in range of 0.2-0.65 °C in the Indian sub-continental basins especially in Ganges and Indus basins. Compare to other basins; irrigation water demand was high in Indus and Ganges basins during the post-monsoon season. Using the nonparametric Mann–Kendall trend test we find that in the pre-monsoon and monsoon seasons over the study period, irrigation demand decreased by 8.25 mm/year in 13 basins. Whereas for the post-monsoon season, irrigation water demand increased in 12 out of the 18 basins. Changes in irrigation demands are largely driven by changes in soil moisture due to decline in the summer monsoon precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Novel Deep Learning Transformer Model for Short to Sub‐Seasonal Streamflow Forecast

Accurate short-to-subseasonal streamflow forecasts are becoming crucial for effective water management in an increasingly variable climate. However, streamflow forecast remains challenging over extended lead times, uncertainty in meteorological inputs, and increased frequency and variability in extreme weather and climate events. We implemented a Future Time Series Transformer (FutureTST) model for streamflow forecasting that separately integrates past meteorological and streamflow data while incorporating future weather conditions. FutureTST achieves a mean Nash-Sutcliffe Efficiency (NSE) of 0.82 to 0.67 for 1- to 30-day streamflow forecasts. Incorporating upstream streamflow information improved forecast accuracy by up to 10%. During real-time forecast, FutureTST maintains higher forecast skills of 9.03 for 1-day and 5.74 for 14-day forecasts. In contrast, calibrated process-based hydrological model forecasts become unreliable beyond a 4-day lead time. Our findings demonstrate the potential of FutureTST as a reliable streamflow forecasting tool that offers a valuable addition to operational flood monitoring systems and climate-resilient decision-making.

Ambika, Anukesh Krishnankutty [Oak Ridge National ↗
DOE OSTI2026

GPM IMERG V07B and V06B: Evaluation Using Ground-Based Radar Observations and Application in Global Mesoscale Convective System Tracking

This study evaluates the latest Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07B) against its predecessor V06B, for studying mesoscale convective systems (MCSs). Both versions are compared using ground-based radar and rain gauge data from five meteorologically diverse regions: the contiguous United States (including eastern coastlines), Amazon rainforest, central Argentina mountains, equatorial Indian Ocean, and northern Australia across multiple temporal (0.5–6 hours) and spatial scales (0.1°–0.25°). An updated global MCS tracking dataset is developed by integrating satellite-observed infrared brightness temperature with IMERG V07B. Comparation of IMERG against radar observations reveals that IMERG demonstrates better performance in capturing the probability distribution and quantitative contributions of rainfall (from no-rain to intense-rain conditions) over tropical oceans than over land, with marked improvements in IMERG V07B for heavy-to-intense rain (> 10 mm h-1). Over land, systematic biases persist: IMERG tends to overestimate light-to-moderate rain (1–10 mm h-1) while underestimating heavy-to-intense rain. Additionally, aggregating IMERG to coarser resolutions (3-hourly or 0.25°) improves consistency with radar observations, outperforming the 1-hourly/0.1° resolution. The new IMERG V07B-based global MCS dataset exhibits consistent statistical characteristics with the V06B-based dataset, despite lower mean rain rates and reduced heavy precipitation contributions. These findings offer valuable insights for utilizing IMERG V07B in global precipitation studies, MCS characterization, and model evaluation.

Zhang, Sihan↗
DOE OSTI2011

Dose Calculation For Accidental Release Of Radioactive Cloud Passing Over Jeddah

For the evaluation of doses after the reactor accident, in particular for the inhalation dose, a thorough knowledge of the concentration of the various radionuclide in air during the passage of the plume is required. In this paper we present an application of the Gaussian Plume Model (GPM) to calculate the atmospheric dispersion and airborne radionuclide concentration resulting from radioactive cloud over the city of Jeddah (KSA). The radioactive cloud is assumed to be emitted from a reactor of 10 MW power in postulated accidental release. Committed effective doses (CEDs) to the public at different distance from the source to the receptor are calculated. The calculations were based on meteorological condition and data of the Jeddah site. These data are: pasquill atmospheric stability is the class B and the wind speed is 2.4m/s at 10m height in the N direction. The residence time of some radionuclides considered in this study were calculated. The results indicate that, the values of doses first increase with distance, reach a maximum value and then gradually decrease. The total dose received by human is estimated by using the estimated values of residence time of each radioactive pollutant at different distances.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications

A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011), the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems, one vertically profiling and another operated over a variety of scanning modes, were utilized to obtain forcing for the simulations, and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20 W m –2 and 100 W m –2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011, whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. In conclusion, validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.

17 WIND ENERGY↗
DOE OSTI2018

PV TOMCAT

PV TOMCAT predicts the outdoor operating temperature and output power of a PV module based on measured physical properties and outdoor conditions. It includes a ray tracing model of a PV module, which runs in the commercial SunSolve ray tracer. Output from this model is combined with meteorological time series data to produce a combined input file for a finite-element model of heat conduction and radiation. Finally, this finite-element model is run in the commercial COMSOL Multiphysics software, producing time series outputs of temperature and power.

Deceglie, Michael↗
DOE OSTI2018

Erroneous Attribution of Deep Convective Invigoration to Aerosol Concentration

Abstract Contiguous time–height cloud objects at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site are matched with surface condensation nuclei (CN) concentrations and retrieved thermodynamic and kinematic vertical profiles for warm-cloud-base, cold-cloud-top systems in convectively unstable environments. Statistical analyses show that previously published conclusions that increasing CN concentrations cause a decrease in minimum cloud-top temperature (CTT) at the SGP site through the aerosol convective invigoration effect are unfounded. The CN–CTT relationship is statistically insignificant, while correlations between convective available potential energy (CAPE), level of neutral buoyancy (LNB), and CN concentration account for most of the change in the CN–CTT positive correlation. Removal of clouds with minimum CTTs > −36°C from the analysis eliminates the CN–CTT correlation. Composited dirty conditions at the SGP have ~1°C-warmer low levels and ~1°C-cooler upper levels than clean conditions. This correlation between aerosol concentrations and thermodynamic profiles may be caused by an increase in regional rainfall preceding deep convective conditions as CN concentration decreases. Increased rainfall can be expected to increase wet deposition of aerosols, cool low-level temperatures, and warm upper-level temperatures. The masking of a potential aerosol effect by such small thermodynamic changes implies that the strategy of analyzing subsets of aerosol data by binned meteorological factor values is not a valid method for discerning an aerosol effect in some situations. These findings highlight the need for more careful, detailed, and strategic observations to confidently isolate and quantify an aerosol deep convective invigoration effect.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin

This data package is associated with the publication “Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River Basin” submitted to Biogeosciences (Shi et al., 2024; doi: 10.22541/au.171053013.30286044/v1). In this research, data products, leaf area index (LAI), gross primary production (GPP), and evapotranspiration (ET), from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to quantify the resistance and resilience of different ecosystem types in the Columbia River Basin (CRB). A machine learning algorithm, random forest (RF), was used to examine the impacts of precipitation, vapor pressure deficit (VPD), and burn severity from Monitoring Trends in Burn Severity (MTBS) on ecosystem resilience. The data package includes the processed MODIS data products, precipitation, VPD, and burn severity in 138 fire regions in CRB and the input files for RF model training. This data package includes six folders. The MODIS products are included in three MODIS_* folders with shell scripts for data clipping and *ncl files for data processing: (1) “/MODIS_LAI_CRB”; (2) “/MODIS_GPP_CRB”; and (3) “/MODIS_ET_CRB”. All the processed data for each fire event are NetCDF formatted. The MTBS burn severity data and the shell and *ncl scripts used for data processing are in the folder named (4) “MTBS_fire”. The ERA meteorological fields and the data processing scritps are in (5) “ERA_Var_CR”. All the scripts for figure development are in the format of *ncl and in the folder (6) “paper_scripts”. See the file ending in “flmd.csv” for a list of all files contained in this data package and descriptions for each. Tabular column headers and units are described in the data dictionary file ending in “dd.csv”.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Evaluating the Contribution of Climate Forcing and Forest Dynamics to Accelerating Carbon Sequestration by Forest Ecosystems in the Northeastern U.S.: Final Report

This report summarizes work to improve quantitative understanding of the terrestrial ecosystem processes that control carbon sequestration in unmanaged forests It builds upon the comprehensive long-term observations of CO2 fluxes, climate and forest structure and function at the Harvard Forest in Petersham, MA. This record includes the longest CO2 flux time series in the world. The site is a keystone for the AmeriFlux network. Project Description The project synthesizes observations made at the Harvard Forest HFEMS and Hemlock towers, which represent the dominant mixed deciduous and coniferous forest types in the northeastern United States. The 20+ year record of carbon uptake at Harvard Forest and the associated comprehensive meteorological and biometric data, comprise one of the best data sets to challenge ecosystem models on time scales spanning hourly, daily, monthly, interannual and multi-decadal intervals, as needed to understand ecosystem change and climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

SWiFT site atmospheric characterization

Historical meteorological tall tower data are analyzed from the Texas Tech University 200 m tower to characterize the atmospheric trends of the Scaled Wind Farm Technologies (SWiFT) site. In this report the data are analyzed to reveal bulk atmospheric trends, temporal trends and correlations of atmospheric variables. Through this analysis for the SWiFT turbines the site International Electrotechnical Commission (IEC) classification is determined to be class III-C. Averages and distributions of atmospheric variables are shown, revealing large fluctuations and the importance of understanding the actual site trends as opposed to simply using averages. The site is significantly directional with the average wind speed from the south, and particularly so in summer and fall. Site temporal trends are analyzed from both seasonal (time of the year) to daily (hour of the day) perspectives. Atmospheric stability is seen to vary most with time of day and less with time of year. Turbulence intensity is highly correlated with stability, and typical daytime unstable conditions see double the level of turbulence intensity versus that experienced during the average stable night. Shear, veer and atmospheric stability correlations are shown, where shear and veer are both highest for stable atmospheric conditions. An analysis of the Texas Tech University tower anemometer measurements is performed which reveals the extent of the tower shadow effects and sonic tilt misalignment.

17 WIND ENERGY↗
DOE OSTI2016

Marine Ice Nuclei Collections – MAGIC (MAGIC-IN) Final Campaign Summary

This campaign augmented measurements obtained via deployment of the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s ARM Mobile Facility (AMF) in the Marine ARM GPCI1 Investigation of Clouds (MAGIC) field campaign. The measurements, comprised of shipboard aerosol collections obtained during the five legs of the summer 2013 cruises, were sent for offline processing to measure ice nucleating particle (INP) number concentrations. The forty-three sample periods each represented, nominally, 24-hour segments during outbound and inbound transits of the Horizon Spirit. The samples were collected at locations between Los Angeles and Hawaii. Eight samples have been analyzed for immersion freezing temperature spectra thus far, using funding from other grants. Remaining samples are being frozen until support for further processing is obtained. Future analyses will investigate the inorganic/organic proportions of ice nuclei, in addition to determining the genetic composition of the overall biological community associated with INPs. Resulting correlations will be compared with other archived aerosol quantities, meteorological and ocean data (e.g., temperature, wind speed, sea surface temperature, etc…) and satellite ocean color products. These findings will ultimately aid in parameterizing oceanic (e.g., sea spray) INP emissions in regional and global scale models, when illustrating aerosol connections to cloud phases and properties. Independent future analyses of frozen filter samples, as proposed by collaborating investigators at the time of this report, will include single particle analyses of marine boundary layer aerosol compositions and morphology. The MAGIC-IN data are considered representative of the oligotrophic, low Chlorophyll-a (with the exception of near-shore) ocean regions, which exist along the MAGIC transect. Current analyses suggest that INP numbers in the marine boundary layer over this region are typically low, compared to existing measurements over marine areas and those collected in the laboratory as the result of realistic sea spray particle generation. These findings, along with separate studies, confirm the existence of highly variable emission sources for INP from oceans, (though weaker than land-based emissions at modestly cooled temperatures).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Department of Energy WindSentinel Loan Program Description

The U.S. Department of Energy (DOE) currently owns two AXYS WindSentinel buoys that collect a comprehensive set of meteorological and oceanographic data to support resource characterization for wind energy offshore. The two buoys were delivered to DOE’s Pacific Northwest National Laboratory (PNNL) in September, 2014. After acceptance testing and initial performance testing and evaluation at PNNL’s Marine Sciences Laboratory in Sequim, Washington, the buoys have been deployed off the U.S. East Coast. One buoy was deployed approximately 42 km east of Virginia Beach, Virginia from December, 2014 through June, 2016. The second buoy was deployed approximately 5 km off Atlantic City, New Jersey in November, 2015. Data from the buoys are available to the public. Interested parties can create an account and log in to http://offshoreweb.pnnl.gov. In response to a number of inquiries and unsolicited proposals, DOE’s Wind Energy Technologies Office is implementing a program, to be managed by PNNL, to lend the buoys to qualified parties for the purpose of acquiring wind resource characterization data in areas of interest for offshore wind energy development. This document describes the buoys, the scope of the loans, the process of how borrowers will be selected, and the schedule for implementation of this program, including completing current deployments.

17 WIND ENERGY↗
DOE OSTI2019

Low-Cost Multiparameter Device for Solar Resource Applications

The National Renewable Research Laboratory (NREL) Solar Radiation Research Laboratory (SRRL), in collaboration with Arable Labs Inc., deployed, calibrated, and characterized Arable Lab's Mark low-cost, multiparameter sensor system. Arable Labs was selected by the U.S. Department of Energy for a small business voucher to work with NREL to tap into the knowledge and expertise Arable needs to tailor and evaluate the Mark device for broader solar energy applications. The device is a complete and independent unit. It is a self-powered, off-the-shelf solution for remote solar irradiance and meteorological sensing and data collection. Calibration of devices against the SRRL instruments provides an understanding of the quality of a new instrument compared to peers. The characterization process provides an understanding of the variability compared to high-quality instruments and essentially provides methods to correct the sources of the variabilities.

14 SOLAR ENERGY↗
DOE OSTI2021

Powering the Blue Economy Foundational Research & Development Topics Reliability for Marine Energy Power Systems

Ocean observing platforms are deployed across the world’s oceans to collect meteorological and oceanographic data. Current technology makes use of solar panels and battery banks to provide power to these platforms, which can be challenging at high latitudes due to lack of solar insolation and cold temperatures. Marine renewable energy (MRE) generation offers a potential improvement in consistent power generation throughout the year for this use on ocean observation buoys. This report analyzes existing reliability of high latitude coastal weather buoys and tsunami detection buoys to determine performance standards that MRE generation sources must meet to become viable power sources for these remote systems. Using measurements recorded from the U.S. National Data Buoy Center’s coastal weather buoys and tsunami detection buoys, the analysis calculated the historic data availability – or the percentage of time a measurement is recorded – to evaluate the reliability of ocean observation buoys. The results show that coastal weather buoys operate at 74% data availability and the tsunami detection systems operate at an average 72% data availability. The results describe the total reliability of the system, including many different types of failures not associated with the power system such as mooring failures or equipment failures caused by extreme weather. Power system outages may only account for a small portion of the system failures. Reliability is an important design criterion for the power system of ocean observation platforms. Future power systems that would be designed for these buoys, such as an MRE generator, need to have a minimum reliability of 72% and 74% to meet the overall performance of the weather buoys and tsunami buoys, respectively. However, power system reliability likely needs to be much higher than overall system reliability, so that power system outages do not negatively impact the overall performance of the buoy.

42 ENGINEERING↗
DOE OSTI2023

NDBC Buoy 46011

The purpose of this dataset is to provide filtered, averaged buoy surface meteorological and oceanographic data and standardize the data format into NetCDF. The buoy was deployed by NDBC. These data are a part of the observational database created for supporting the floating offshore wind project within the DOE-funded ORACLE project.

17 WIND ENERGY↗