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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Atmospheric dispersion modeling: Challenges of the Fukushima Daiichi response

In this research, the U.S. Department of Energy’s (DOE) National Atmospheric Release Advisory Center (NARAC) provided a wide range of predictions and analyses as part of the response to the Fukushima Daiichi Nuclear Power Plant accident including: daily Japanese weather forecasts and atmospheric transport predictions to inform planning for field monitoring operations and to provide U.S. government agencies with ongoing situational awareness of meteorological conditions; estimates of possible dose in Japan based on hypothetical U.S. Nuclear Regulatory Commission scenarios of potential radionuclide releases to support protective action planning for U.S. citizens; predictions of possible plume arrival times and dose levels at U.S. locations; and source estimation and plume model refinement based on atmospheric dispersion modeling and available monitoring data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Lidar Buoy Data Dictionary: For the 2020 – 2021 California Deployments

Pacific Northwest National Laboratory (PNNL) manages two AXYS WindSentinel™ buoys (Buoys #120 and #130) on behalf of the U.S. Department of Energy (DOE) that collect a comprehensive set of meteorological and oceanographic (metocean) data to support resource characterization for wind energy offshore. The buoys have been deployed off the California coast in partnership with the Bureau of Ocean Energy Management (BOEM) from September 2020 through October 2021. One buoy was deployed within the Morro Bay Call Area offshore central California; the other buoy was deployed within the Humboldt Call Area off the coast of northern California. The measurements from the buoys are used to characterize the metocean conditions near potential locations for offshore wind lease areas and are uploaded to DOE’s Data Archive and Portal (DAP). Plots are updated on the DAP webpage to visualize the recent metocean measurements. This document serves as a data dictionary – or reference guide – for understanding and interpreting the data available from the buoys. This document includes: (1) specifications for the buoy instrumentation (Section 2.0) (2) description of each plot and definition of measured parameters (Section 3.0) (3) description of data files and naming convention (Appendix A) (4) reference guide of measurements and variables (Appendix B).

17 WIND ENERGY↗
DOE OSTI2023

Integrating LEO and GEO Observations: Toward Optimal Summertime Satellite Precipitation Retrieval

Abstract Reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for understanding the Earth’s hydrological cycle. Precipitation estimation over land and coastal regions is necessary for addressing the high degree of spatial heterogeneity of water availability and demand, and for resolving the extremes that modulate and amplify hazards such as flooding and landslides. Advancements in computation power along with unique high spatiotemporal and spectral resolution data streams from passive meteorological sensors aboard geosynchronous Earth-orbiting (GEO) and low Earth-orbiting (LEO) satellites offer exciting opportunities to retrieve information about surface precipitation phenomena using data-driven machine learning techniques. In this study, the capabilities of U-Net–like architecture are investigated to map instantaneous, summertime surface precipitation intensity at the spatial resolution of 2 km. The calibrated brightness temperature products from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) radiometer are combined with multispectral images (visible, near-infrared, and infrared bands) from the Advanced Baseline Imager (ABI) aboard the GOES-R satellites as main inputs to the U-Net–like precipitation algorithm. Total precipitable water and 2-m temperature from the Global Forecast System (GFS) model are also used as auxiliary inputs to the model. The results show that the U-Net–like algorithm can capture fine-scale patterns and intensity of surface precipitation at high spatial resolution over stratiform and convective precipitation regimes. The evaluations reveal the potential of extracting relevant, high spatial features over complex surface types such as mountainous regions and coastlines. The algorithm allows users to interpret the inputs’ importance and can serve as a starting point for further exploration of precipitation systems within the field of hydrometeorology.

Meteorology & Atmospheric Sciences↗
DOE OSTI2012

ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, Surface Meteorology (williams-surfmet)

This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Meteorological and hydrological parameters for 17 locations of meteorological stations of the East River Watershed

The Data Package includes a set of csv files of input meteorological parameters for locations of 17 meteorological stations within the East River watershed. These meteorological datasets were downloaded from the (1) PRISM database--monthly precipitation, air temperature (minimum, mean, and maximum), vapor pressure deficit (minimum and maximum), and dewpoint temperature, and (2) NCEP/NCAR Reanalysis database – wind database. The datasets were used for calculations of the Potential Evapotranspiration (ETo), Actual Evapotranspiration (ET), Standard Precipitation Index (SPI) , Standard Evapotranspiration-Precipitation Index (SPEI) for the period from 1966 to 2021. The main research questions addressed are: the evaluation of the long-term temporal trends of climatic parameters, hierarchical clustering, and areal mapping/zonation of the East River watershed. Calculations were conducted in the Rstudio environment. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.The input datasets were downloaded from (a) PRISM database (the Northwest Alliance for Computational Science and Engineering at the Oregon State University), and (b) NCEP/NCAR Reanalysis database.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A meteorology and snow dataset from adjacent forested and meadow sites at Crested Butte, CO, USA

This dataset contains meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains during water years 2019-2021. Data collection had an emphasis on paired open-forest sites and included three forested elevations. In total, we present 270 snow pit observations, 4,019 snow depth measurements, and three years of meteorological forcing from two weather stations (one in a meadow, the other in an adjacent forest). The dataset is described in a forthcoming publication of the same name: A meteorology and snow dataset from adjacent forested and meadow sites at Crested Butte, CO, USA (Bonner et al., 2022).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Implementing Best Practices for Data Quality Assessment of the National Renewable Energy Laboratory's Solar Resource and Meteorological Assessment Project: Preprint

Effective solar radiation measurements for research and economic analyses require a strict protocol for maintenance, calibration, and documentation to minimize station downtime and data corruption. The National Renewable Energy Laboratory's Concentrating Solar Power: Best Practices Handbook for the Collection and Use of Solar Resource Data includes guidelines for operating a solar measurementstation. This paper describes a suite of automated and semi-automated routines based on the best practices handbook as developed for the National Renewable Energy Laboratory Solar Resource and Meteorological Assessment Project. These routines allow efficient inspection and data flagging to alert operators of conditions that require immediate attention. Although the handbook is targeted forconcentrating solar power applications, the quality-assessment procedures described are generic and should benefit many solar measurement applications. The routines use data in one-minute measurement resolution, as suggested by the handbook, but they could be modified for other time scales.

14 SOLAR ENERGY↗