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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Space Environment (Natural and Induced)

Considerable effort and improvement have been made in the study of ionizing radiation exposure occurring in various regions of space. Satellites and spacecrafts equipped with innovative instruments are continually refining particle data and providing more accurate information on the ionizing radiation environment. The major problem in accurate spectral definition of ionizing radiation appears to be the detailed energy spectra, especially at high energies, which is important parameter for accurate radiation risk assessment. Magnitude of risks posed by exposure to radiation in future space missions is subject to the accuracies of predictive forecast of event size of SPE, GCR environment, geomagnetic fields, and atmospheric radiation environment. Although heavy ion fragmentations and interactions are adequately resolved through laboratory study and model development, improvements in fragmentation cross sections for the light nuclei produced from HZE nuclei and their laboratory validation are still required to achieve the principal goal of planetary GCR simulation at a critical exposure site. More accurate prediction procedure for ionizing radiation environment can be made with a better understanding of the solar and space physics, fulfillment of required measurements for nuclear/atomic processes, and their validation and verification with spaceflights and heavy ion accelerators experiments. It is certainly true that the continued advancements in solar and space physics combining with physical measurements will strengthen the confidence of future manned exploration of solar system. Advancements in radiobiology will surely give the meaningful radiation hazard assessments for short and long term effects, by which appropriate and effective mitigation measures can be placed to ensure that humans safely live and work in the space, anywhere, anytime.

Kim, Myung-Hee Y.↗
NASA NTRS2011

NASA Soil Moisture Active Passive (SMAP) Mission Formulation

The Soil Moisture Active Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Earth Science Decadal Survey [1]. SMAP s measurement objectives are high-resolution global measurements of near-surface soil moisture and its freeze-thaw state. These measurements would allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. The soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP s planned observations can help mitigate these natural hazards, resulting in potentially great economic and societal benefits. SMAP measurements would also yield high resolution spatial and temporal mapping of the frozen or thawed condition of the surface soil and vegetation. Observations of soil moisture and freeze/thaw timing over the boreal latitudes will contribute to reducing a major uncertainty in quantifying the global carbon balance and help resolve an apparent missing carbon sink over land. The SMAP mission would utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna (see Figure 1) [2]. The radar and radiometer instruments would be carried onboard a 3-axis stabilized spacecraft in a 680 km polar orbit with an 8-day repeating ground track. The instruments are planned to provide high-resolution and high-accuracy global maps of soil moisture at 10 km resolution and freeze/thaw at 3 km resolution, every two to three days (see Table 1 for a list of science data products). The mission is adopting a number of approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). These approaches are being incorporated into the radiometer and radar flight hardware and ground processing designs.

Entekhabi, Dara↗
NASA NTRS1985

Dynamic and static initialization of a mesoscale model using VAS satellite data

Various mesoscale weather forecast model initialization procedures were tested in seven simulation forecasts for a 12 hr period in July 1981. Attention was given to the impacts of using as input radiosonde data, VISSR Atmospheric Sounder (VAS) data and a combination of VAS and data from a smoothed global analysis. The data were assimilated with successive correction objective analysis procedures. The model had a 60 km horizontal grid-length resolution, 14 layers in the vertical, and accounted for short- and long-wave energy in the surface energy budget but not in the atmosphere. Conventional data were used for the mass and moisture fields. The trials showed that VAS data enhanced the predictions of the temperature and mass variables, while winds were least accurately predicted when VAS data were entered in the initializations. Finally, statically initialized precipitation forecasts from radiosonde and/or VAS data exhibited equal skill.

Beauchamp, J. G.↗
NASA NTRS1982

Aviation weather services

The primary responsibilities of the National Weather Service (NWS) are to: provide warnings of severe weather and flooding for the protection of life and property; provide public forecasts for land and adjacent ocean areas for planning and operation; and provide weather support for: production of food and fiber; management of water resources; production, distribution and use of energy; and efficient and safe air operations.

Charles H. Sprinkle↗
NASA NTRS1991

Precipitation rates in the tropics - June 1984-May 1987

A study aimed at gaining better understanding of the heating potential of the tropics by examining the 'apparent' heat source (Q1), i.e. dry static energy budget, is presented. The Q1 budget and precipitation rates over a three year period are analyzed using a routine data set: the European Center for Medium-range Weather Forecasts analyses. A noticeable increase in the values of Q1 during years 2 and 3 compared to year 1 was observed, which is considered to be due to the changes in the ECMWF model physics that produced larger values of upper level divergence after May 1985. There is a slow eastward progression of maximum values across the Western Pacific during the calendar year 1986 and into early 1987.

North, Keith H.↗
NASA NTRS2010

Biomass Burning Emissions from Fire Remote Sensing

Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

Ichoku, Charles↗
NASA NTRS2023

The Effect of the Ambient Solar Wind Medium on a CME-driven Shock and the Associated Gradual Solar Energetic Particle Event

We present simulation results of a gradual solar energetic particle (SEP) event detected on 2021 October 9 by multiple spacecraft, including BepiColombo (Bepi) and near-Earth spacecraft such as the Advanced Composition Explorer (ACE). A peculiarity of this event is that the presence of a high-speed stream (HSS) affected the low-energy ion component (≲5 MeV) of the gradual SEP event at both Bepi and ACE, despite the HSS having only a modest solar wind speed increase. Using the EUHFORIA (European Heliospheric FORecasting Information Asset) magnetohydrodynamic model, we replicate the solar wind during the event and the coronal mass ejection (CME) that generated it. We then combine these results with the energetic particle transport model PARADISE (PArticle Radiation Asset Directed at Interplanetary Space Exploration). We find that the structure of the CME-driven shock was affected by the nonuniform solar wind, especially near the HSS, resulting in a shock wave front with strong variations in its properties such as its compression ratio and obliquity. By scaling the emission of energetic particles from the shock to the solar wind compression at the shock, an excellent match between the PARADISE simulation and in situ measurements of ≲5 MeV ions is obtained. Our modeling shows that the intricate intensity variations observed at both ACE and Bepi were influenced by the nonuniform emission of energetic particles from the deformed shock wave and demonstrates the influence of even modest background solar wind structures on the development of SEP events.

Solar energetic particles↗
NASA NTRS2008

GEWEX Water and Energy Budget Study

Closing the global water and energy budgets has been an elusive Global Energy and Water-cycle Experiment (GEWEX) goal. It has been difficult to gather many of the needed global water and energy variables and processes, although, because of GEWEX, we now have globally gridded observational estimates for precipitation and radiation and many other relevant variables such as clouds and aerosols. Still, constrained models are required to fill in many of the process and variable gaps. At least there are now several atmospheric reanalyses ranging from the early National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) and NCEP/Department of Energy (DOE) reanalyses to the more recent ERA40 and JRA-25 reanalyses. Atmospheric constraints include requirements that the models state variables remain close to in situ observations or observed satellite radiances. This is usually done by making short-term forecasts from an analyzed initial state; these short-term forecasts provide the next guess, which is corrected by comparison to available observations. While this analysis procedure is likely to result in useful global descriptions of atmospheric temperature, wind and humidity, there is no guarantee that relevant hydroclimate processes like precipitation, which we can observe and evaluate, and evaporation over land, which we cannot, have similar verisimilitude. Alternatively, the Global Land Data Assimilation System (GLDAS), drives uncoupled land surface models with precipitation, surface solar radiation, and surface meteorology (from bias-corrected reanalyses during the study period) to simulate terrestrial states and surface fluxes. Further constraints are made when a tuned water balance model is used to characterize the global runoff observational estimates. We use this disparate mix of observational estimates, reanalyses, GLDAS and calibrated water balance simulations to try to characterize and close global and terrestrial atmospheric and surface water and energy budgets to within 10-20% for long term (1986-1995), large-scale global to regional annual means.

Roads, J.↗
NASA NTRS1984

Potential to kinetic energy conversion in wave number domain for the Southern Hemisphere

Preliminary results of a wave number study conducted for the South Pacific Convergence Zone (SPCZ) using FGGE data for the period January 10-27, 1979 are reported. In particular, three variables (geomagnetic height, z, vertical p-velocity, omega, and temperature, T) and one energy conversion quantity, omega-alpha (where alpha is the specific volume), are shown. It is demonstrated that wave number 4 plays an important role in the conversion from available potential energy to kinetic energy in the Southern Hemisphere tropics, particularly in the vicinity of the SPCZ. It is therefore suggested that the development and movement of wave number 4 waves be carefully monitored in making forecasts for the South Pacific region.

Huang, H.-J.↗
NASA NTRS1995

Radiation safety aspects of commercial high-speed flight transportation

High-speed commercial flight transportation is being studied for intercontinental operations in the 21st century, the projected operational characteristics for these aircraft are examined, the radiation environment as it is now known is presented, and the relevant health issues are discussed. Based on a critical examination of the data, a number of specific issues need to be addressed to ensure an adequate knowledge of the ionizing radiation health risks of these aircraft operations. Large uncertainties in our knowledge of the physical fields for high-energy neutrons and multiply-charged ion components need to be reduced. Improved methods for estimating risks in prenatal exposure need to be developed. A firm basis for solar flare monitoring and forecasting needs to be developed with means of exposure abatement.

Wilson, John W.↗
NASA NTRS2004

Interpretive Tools for Analysis of Coronal Images

Contents include list of publications resulting from grant: Magneto-Hydrodynamic Model of the Solar Corona and Interplanetary Medium. Coronal magnetic field topology and source of fast solar wind. Geophysical Importance of Global Magnetic Field Geometry and Density Distribution in Solar Wind Modeling. Empirical Model of the Corona-Solar Wind with Multiple Current Sheets. Model of the Solar Wind and its Comparison with ULYSSES. Physical properties of a coronal hole from a coronal diagnostic spectrometer, Mauna Loa Coronagraph, and LASCO observations during the Whole Sun Month. Semi-Empirical 2-D MHD Model of the Solar corona and Solar Wind: Energy Flow in the Corona. Source Region of High and Low Speed Wind during the Spartan. Three-dimensional coronal density structure. Cone Model for Halo CME's: Application to Space Weather Forecasting.

Ofman, Leon↗
NASA NTRS1998

Orbit selection and its impact on radiation warning architecture for a human mission to Mars

With the recent announcement of the discovery of the possibility of life on Mars, there is renewed interest in Mars missions, perhaps eventually in human missions. Astronauts on such missions are at risk to occasional periods of enhanced high energy particle flux from the sun known as Solar Particle Events. These events can pose a substantial risk to the health of the astronauts and to the on-board electronics. Effective forecast and warning of these events could provide time to take steps to minimize the risk (retreating to a safe haven, shutting down sensitive equipment, etc.) Providing that forecast capability, will require additional monitoring capability. The extent of this architecture is sensitive to the orbit selected for the transfer to and from Mars. This paper looks at the major classes of Mars missions (Conjunction and Opposition) and sub-categories of these classes and draws conclusions on the number of monitoring satellites needed for each, with a goal to reducing total system cost through optimum orbit selection.

Non-NASA Center↗
NASA NTRS1976

Monitoring solar radiation: The ERDA program

An overview of the Energy Research and Development Administration planned insolation data network is described. The design of the network is predicated on an analysis and definition of user requirements. Research and analysis projects covering data collection, forecasting and extrapolation are presented.

Koomanoff, F. A.↗
NASA NTRS2019

Uncertainty of Observation Impact Estimation in an Adjoint Model Investigated with an Observing System Simulation Experiment

Adjoint models are often used to estimate the impact of different observations on short-term forecast skill. A common difficulty with the evaluation of short term forecast quality is the choice of verification fields. The use of self-analysis fields for verification is typical but incestuous, and introduces uncertainty due to biases and errors in the analysis field. In this study, an observing system simulation experiment (OSSE) is used to explore the uncertainty in adjoint model estimations of observation impact. The availability of the true state for verification in the OSSE framework in the form of the Nature Run allows calculation of the observation impact without the uncertainties present in self-analysis verification. These impact estimates are compared to estimates calculated using self-analysis verification. The Global Earth Observing System version 5 (GEOS-5) forecast model with Gridpoint Statistical Interpolation (GSI) is used with the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) OSSE capability. The adjoint model includes moist processes, with total wet energy selected as the norm for evaluation of observation impacts. The results show that there are measurable but small discrepancies in the adjoint model estimation of observation impact. In general, observations of temperature and winds tend to have overestimated impacts with self-analysis verification, while observations of humidity and moisture-affected observations tend to have underestimated impacts. The small magnitude of the differences in impact estimates supports the robustness of the adjoint method of estimating observation impacts.

N C Prive↗
NASA NTRS1998

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗
NASA NTRS1979

Energy: An annotated selected bibliography

This updated bibliography contains approximately 7,000 selected references on energy and energy related topics from bibliographic and other data sources from June 1977. Under each subject heading the entries are arranged by the data, with the latest works first. Subject headings include: resources supply/demand, and forecasting; policy, legislation, and regulation; environment; consumption, conservation, and economics; analysis, systems, and modeling, and information sources and documentation. Fossil fuels, hydrogen and other fuels, liquid/solid wastes and biomass, waste heat utilization, and nuclear power sources are also included.

Blow, S. J.↗
NASA NTRS1982

ACEE program rationale and implementation

The impact of the Aircraft Energy Efficiency program (ACEE) on commercial aviation is examined. In addition to the emphasis on air transport fuel efficiency, topics such as airline operating costs, air transport effects on U.S. trade, and fuel price forecasts are addressed. An overview of the program and its contribution to aviation technology is included.

Aiken, W. S., Jr.↗
NASA NTRS2011

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and show sample output from summer 2010, compare the MODIS GVF data to the AVHRR monthly climatology, and illustrate the sensitivity of the Noah LSM within LIS and/or the coupled LIS/WRF system to the new MODIS GVF dataset.

Case, Jonathan L.↗