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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Digital processing of mesoscale analysis and space sensor data

The mesoscale analysis and space sensor (MASS) data management and analysis system on the research computer system is presented. The MASS data base management and analysis system was implemented on the research computer system which provides a wide range of capabilities for processing and displaying large volumes of conventional and satellite derived meteorological data. The research computer system consists of three primary computers (HP-1000F, Harris/6, and Perkin-Elmer 3250), each of which performs a specific function according to its unique capabilities. The overall tasks performed concerning the software, data base management and display capabilities of the research computer system in terms of providing a very effective interactive research tool for the digital processing of mesoscale analysis and space sensor data is described.

Hickey, J. S.↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
NASA NTRS1965

Transport and mixing in atmosphere

Standard meteorological data to compute transports of momentum, sensible heat and moisture in atmosphere - transport and mixing in atmosphere

METEOROLOGY↗
NASA NTRS1994

Atmospheric correction of LANDSAT TM thermal band using surface energy balance

Thermal infrared data of LANDSAT Thematic Mapper (TM) are hardly used, probably due to the difficulties met when trying to correct them for atmospheric effects. A method for correcting these data was designed, based on surface energy balance estimation of known wet and dry targets included in the TM image to be corrected. This method, only using the image itself and local meteorological data was tested and validated on various surfaces: agricultural, forest and rangeland. The root mean square error on corrected temperatures is on the order of 1C.

Vidal, Alain↗
NASA NTRS1995

Stratospheric and mesospheric pressure-temperature profiles from rotational analysis of CO2 lines in atmospheric trace molecule spectroscopy/ATLAS 1 infrared solar occultation spectra

A simple, classical, and expedient method for the retrieval of atmospheric pressure-temperature profiles has been applied to the high-resolution infrared solar absorption spectra obtained with the atmospheric trace molecule spectroscopy (ATMOS) instrument. The basis for this method is a rotational analysis of retrieved apparent abundances from CO2 rovibrational absorption lines, employing existing constituent concentration retrieval software used in the analysis of data returned by ATMOS. Pressure-temperature profiles derived from spectra acquired during the ATLAS 1 space shuttle mission of March-April 1992 are quantitatively evaluated and compared with climatological and meteorological data as a means of assessing the validity of this approach.

Stiller, G. P.↗
NASA NTRS2001

Microphysics, Meteorology, Microwave and Modeling of Mediterranean Storms: The M(sup 5) Problem

Comprehensive understanding of the microphysical nature of Mediterranean storms requires a combination of in situ meteorological data analysis and radar-passive microwave data analysis, effectively integrated with numerical modeling studies at various scales, particularly from synoptic scale down to mesoscale. The microphysical properties of and their controls on severe storms are intrinsically related to meteorological processes under which storms have evolved, processes which eventually select and control the dominant microphysical properties themselves. Insofar as hazardous Mediterranean storms, highlighted by the September 25-28/1992 Genova flood event, the October 5-7/1998 Friuli flood event, and the October 13-15/2000 Piemonte flood event (all taking place in northern Italy), developing a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution and the heterogeneous nature of precipitation fields within the storm domains. This involves convective development, stratiform transition and decay, orographic lifting, and sloped frontal lifting proc esses. This also involves vertical motions and thermodynamical instabilities governing physical processes that determine details of the liquid/ice water contents, size distributions, and fall rates of the various modes of hydrometeors found within the storm environments. This paper presents detailed 4-dimensional analyses of the microphysical elements of the three severe Mediterranean storms identified above, investigated with the aid of SSM/I and TRMM satellite measurements (and other remote sensing measurements). The analyses are guided by nonhydrostatic mesoscale model simulations at high resolution of the intense rain producing portions of the storm environments. The results emphasize how meteorological controls taking place at the large scale, coupled with localized terrain controls, ultimately determine the most salient features of the bulk microphysical properties of the storms. These results have bearing on precipitation remote sensing from space, and the role of modeling in designing precipitation retrieval algorithms.

Smith, Eric A.↗
DOE OSTI2021

Surface Meteorology at Teller Mile 47 Watershed, Seward Peninsula, Alaska, Ongoing from 2018

Meteorological data are currently being collected at one location at the Teller Mile 47 (TL_MM47) Research Basin Site, Seward Peninsula (N64 58' 36.918", W166 12' 32.67", 67 meters above sea level). The site was installed and initial measurements started in September 2018 and it has operated continuously since then. The meteorological station is co-located with a continuous snow depth sensor and two soil pits for subsurface temperature and moisture measurements. These data are being collected to better understand the energy dynamics above the active layer and permafrost. They complement in-situ snow and soil measurements also at this location. The data could also be used as supporting measurements for other research and modeling activities. There are 35 comma separated value format (*.csv) files provided, where each file contains the full data for an individual parameter (e.g. air temperature at 1.5 meters above the ground surface (teller_m47_air_temperature_150cm_ags_Avg.csv) or soil temperature 20 centimeters below ground surface (teller_m47_dry_soil_pit_temperature_20cmbgs_Avg.csv)) plus the time in Universal Coordinated Time (UTC) and Alaska Standard Time (UTC time minus nine hours). The site was installed and initial measurements started in September 2018. It has been operated continuously since. Primary data gaps are due to battery failure or sensor failure. These data are being collected to better understand the surface energy dynamics above the active layer and permafrost. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy?s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy?s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

OpenSolar: Promoting the Openness and Accessibility of Diverse Public Solar Datasets

Observational solar data is the foundation of data-driven research in solar power grid integration and power system operations. Compared to other fields in data science, the openness and accessibility of solar data is lacking, which prevents solar data science from catching up with the emerging trends of data science (e.g., deep learning). In this paper, OpenSolar, a package with both R and Python versions, is developed to enhance the openness and accessibility of publicly available solar datasets. The OpenSolar package provides access to multiple types of solar data, primarily from four datasets: (1) the National Renewable Energy Laboratory (NREL) Solar Power Data for Integration Studies dataset, (2) the NREL Solar Radiation Research Laboratory dataset, (3) the Sheffield Solar-Microgen database, and (4) the Dataport database. Unlike other open solar datasets that only contain meteorological data, the four datasets in the OpenSolar package also contain behind-the-meter power data, sky images, and solar power data with satisfactory temporal and spatial resolution and coverage. The overview, quality-control methods, and potential usage of the datasets, in conjunction with sample code implementing the OpenSolar functions, are described in this paper. The package is expected to assist in bridging the gaps between the research fields of solar energy, power systems, and data science.

14 SOLAR ENERGY↗
NASA NTRS1982

A comparison of HCMM surface temperatures with in situ temperature data

Algorithms were updated for a quicker analysis of computer compatible tapes in an effort to establish the absolute and relative accuracy of HCMM infrared data. Data for four case studies were identified and extracted from the tapes. These studies include three dates for the Nantucket Shoals region and one date for the Gulf of Mexico region. Upper air meteorological data, which are needed to make atmospheric correction of the HCMM data, are being reduced and prepared for calculation of the atmospheric effect.

Source record↗
NASA NTRS1990

Comparison of FFP predictions with measurements of a low-frequency signal propagated in the atmosphere

An experimental study of low-frequency propagation over a distance of 770 m was previously reported (J. Acoust. Soc. Am. Suppl. 1 86, S120 (1989)). For that study, sound speed profiles were reconstructed entirely from surface-layer micrometeorological data. When the acoustic data were compared with theoretical predictions from a fast field program (FFP), it was found that the FFP underpredicted sound levels measured in a shadow zone. Here, the effect on the predictions of including meteorological data for heights greater than the surface layer, i.e., wind profiles measured by a Doppler sodar, is discussed. Vertical structure of turbulence is simulated by stochastically perturbing the mean profiles, and the agreement between the acoustic data and FFP predictions is improved.

Wilson, K. Keith↗
NASA NTRS1977

NASA Global Atmospheric Sampling Program (GASP) data report for tape VL0006

The NASA Global Atmospheric Sampling Program (GASP) is obtaining measurements of atmospheric trace constituents in the upper troposphere and lower stratosphere using fully automated air sampling systems on board several commercial B-747 aircraft in routine airline service. Atmospheric ozone, and related flight and meteorological data were obtained during 245 flights of a Qantas Airways of Australia B-747 and two Pan American World Airways B-747s from July 1976 through September 1976. In addition, whole air samples, obtained during three flights, were analyzed for trichlorofluoromethane, and filter samples, obtained during four flights, were analyzed for sulfates, nitrates, fluorides, and chlorides. Flight routes and dates, instrumentation, data processing procedures, data tape specifications, and selected analyses are discussed.

Gauntner, D. J.↗
DOE OSTI2024

Resilient design in nuclear energy: Critical lessons from a cross-disciplinary analysis of the Fukushima Dai-ichi nuclear accident

This paper presents a multidisciplinary analysis of the Fukushima Dai-ichi Nuclear Power Plant accident. Along with the latest observations and simulation studies, we synthesize the time-series and event progressions during the accident across multiple disciplines, including in-plant physics and engineering systems, operators’ actions, emergency responses, meteorology, radionuclide release and transport, land contamination, and health impacts. We identify three key factors that exacerbated the consequences of the accident: (1) the failure of Unit 2 containment venting, (2) the insufficient integration of radiation measurements and meteorology data in the evacuation strategy, and (3) the limited risk assessment and emergency preparedness. We conclude with new research and development directions to improve the resilience of nuclear energy systems and communities, including (1) meteorology-informed proactive venting, (2) machine learning-enabled adaptive evacuation zones, and (3) comprehensive risk-informed emergency planning while leveraging the experience from responses to other disasters.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS1976

NASA Global Atmospheric Sampling Program (GASP) data report for tape VL0004

The NASA Global Atmospheric Sampling Program (GASP) is obtaining measurements of atmospheric trace constituents in the upper troposphere and lower stratosphere using fully automated air sampling systems on board several commercial B-747 aircraft in routine airline service. Atmospheric ozone, water vapor, and related flight and meteorological data were obtained during 139 flights of a United Airlines B-747 and a Pan American World Airways B-747 from December 1975 through March 1976. In addition, sample bottles were exposed during three flights and analyzed for trichlorofluoromethane, and filter samples were exposed during five flights and analyzed for sulfates, nitrates, and chlorides. Flight routes and dates, instrumentation, data processing procedures, data tape specifications, and selected analyses are discussed.

Holdeman, J. D.↗
NASA NTRS1979

A field study of air flow and turbulent features of advection fog

The setup and initial operation of a set of specialized meteorological data collection hardware are described. To study the life cycle of advection fogs at a lake test site, turbulence levels in the fog are identified, and correlated with the temperature gradients and mean wind profiles. A meteorological tower was instrumented to allow multiple-level measurements of wind and temperature on a continuous basis. Additional instrumentation was: (1)hydrothermograph, (2)microbarograph, (3)transmissometers, and (4)a boundary layer profiler. Two types of fogs were identified, and important differences in the turbulence scales were noted.

Connell, J. D.↗
NASA NTRSDate not supplied

Gigatraj: An Atmospheric Trajectory Model

Atmospheric trajectory models have a long history of success in tracking air motions in the lower stratosphere and upper troposphere over periods of up to a few days. Parcels have been traced backwards from observations to identify whatever phenomena (strong convection, volcanic eruptions, rocket launches, etc.) put their signature on them. Parcels have also been initialized at a known event and traced forward to examine their subsequent physical and chemical evolution. We describe a new trajectory model, "gigatraj," that aims to increase exibility by (a) making it straightforward to use new meteorological data sources, including those not based on regular latitude-longitude grids; (b) enabling a run-time choice of vertical coordinate system for kinematic and/or quasi-isentropic calculations; (c) allowing for the output of arbitrary meteorological products, selectable by the user and interpolated to the parcels' locations and times. The model can be run in a serial or parallel processing environment, so that large numbers of parcels can be traced in a reasonable time. Information is presented on model accuracy and performance. The former is demonstrated by runs using both test-pattern winds (comparing expected paths with actual output) and real-world winds (comparing forward and backward runs to characterize how well parcels retrace their paths). Sample cases are also shown, including a reverse domain lling (RDF) calculation illustrating a tropopause fold event. Model output can be displayed using the new Visualization And Lagrangian dynamics Immersive eXtended Reality (VALIXR) system, and an example will be shown. In addition, we describe work to incorporate a version of gigatraj into the Goddard Earth Observing System (GEOS) of NASA's Global Modeling and Assimilation O ce (GMAO) at Goddard Space Flight Center. This enables trajectory calculations to be performed within the running GEOS model at the latter's native time resolution, instead of using the winds from every few hours. It also provides access to all of GEOS's internal variables as they are calculated. This module may be useful, for example, for tracking rapid chemical changes in a Lagrangian framework.

dynamics↗
NASA NTRS2015

Enhancing the NASA Prediction of Worldwide Energy Resource Web Data Delivery System with Geographic Information System (GIS) Capabilities

Renewable energy technologies are changing the face of the world's energy market. Currently, these technologies are being incorporated within existing structures to increase energy efficiency. Crucial to the success of the emerging renewable market is the availability of accurate, global solar radiation, and meteorology data. This poster traces the history of the development of an effort to distribute data parameters from NASA's research for use in the energy sector applications spanning from renewable energy to energy efficiency. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings.

Chandler, William S.↗