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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

IUE studies of X-ray K-M dwarfs

X-ray and ultraviolet data are presented with various optical data. Certain flare star and BY Draconis type variable star data are included. The results are discussed in terms of parameters of interest such as rotation and binary incidence. Deviations from correlations of properties that are found in the literature are noted. The fairly sizable number of red dwarfs that were observed inhance the value of the set of data. The coronae and the chromospheres of transition regions of the nearby stars are also considered.

Johnson, H. M.↗
NASA NTRS1990

Geosat altimeter observations of the surface circulation of the Southern Ocean

Using Geosat altimeter data for 26 months from November 1986 to December 1988 and a newly developed technique for the analysis of height data, the variability of the sea level and the surface geostrophic currents in the Southern Ocean is investigated. The processed Geosat data are used to examine the relationship between the mesoscale variability and the values of mean circulation, determined from historical hydrographic data. It is shown that the geographical patterns of both the mean flow and the mesoscale variability are correlated. An efficient objective-analysis algorithm for generating smoothed fields from observations randomly distributed in time and two space dimensions is developed and applied to 26 months of Geosat data. The smoothed fields are then used to investigate the large-scale low-frequency variability of the sea level and the surface geostrophic velocity in the Southern Ocean, in order to identify the mode of the observed variations.

Chelton, Dudley B.↗
NASA NTRS1985

Ozone and temperature trends

The measurement of temporal changes in ozone and temperature are discussed. The data are examined within the context of natural atmospheric variability and data problems. The results are compared to numerical model calculations. The major issues are defined in terms of goal achievement. Each parameter is considered in terms of instrument type, long term effects, and altitude.

Labitzke, K.↗
NASA NTRS2013

Detection and Attribution of Anthropogenic Climate Change Impacts

Human-influenced climate change is an observed phenomenon affecting physical and biological systems across the globe. The majority of observed impacts are related to temperature changes and are located in the northern high- and midlatitudes. However, new evidence is emerging that demonstrates that impacts are related to precipitation changes as well as temperature, and that climate change is impacting systems and sectors beyond the Northern Hemisphere. In this paper, we highlight some of this new evidence-focusing on regions and sectors that the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) noted as under-represented-in the context of observed climate change impacts, direct and indirect drivers of change (including carbon dioxide itself), and methods of detection. We also present methods and studies attributing observed impacts to anthropogenic forcing. We argue that the expansion of methods of detection (in terms of a broader array of climate variables and data sources, inclusion of the major modes of climate variability, and incorporation of other drivers of change) is key to discerning the climate sensitivities of sectors and systems in regions where the impacts of climate change currently remain elusive. Attributing such changes to human forcing of the climate system, where possible, is important for development of effective mitigation and adaptation. Current challenges in documenting adaptation and the role of indigenous knowledge in detection and attribution are described.

detection↗
NASA NTRS1986

Statistical relation between monthly mean precipitable water and surface-level humidity over global oceans

Monthly summaries of atmospheric soundings taken over 17 years from 49 midocean stations at small islands and weather ships distributed over major oceans are examined. Over tropical oceans, precipitable water is found to be a better predictor of surface-level humidity than surface-level air temperature. A statistical relation in the form of a polynomial is derived; from this relation, the monthly-mean, surface-level mixing ratio can be computed from monthly-mean precipitable water. The root-mean-square differences between the measured and derived values were found to be less than 8 x 10 to the -4th over most ocean areas. Such a relation is useful in deriving large-scale evaporation and latent heat flux data from the ocean, using spaceborne observations. The temporal and spatial variabilities of data deviations from this relation are examined. This relation is found to be applicable to all major ocean basins and can be used to monitor interannual variability. Boundary-layer thermodynamics of different air masses are suggested as an explanation of some characteristics of this relation.

Liu, W. T.↗
NASA NTRS1992

Empirical relationships among atmospheric variables from rawinsonde and field data as surrogates for AVIRIS measurements: Estimation of regional land surface evapotranspiration

Empirical relationships between variables are ways of securing estimates of quantities difficult to measure by remote sensing methods. The use of empirical functions was explored between: (1) atmospheric column moisture abundance W (gm H2O/cm(sup 2) and surface absolute water vapor density rho(q-bar) (gm H2O/cm(sup 3), with rho density of moist air (gm/cm(sup 3), q-bar specific humidity (gm H2O/gm moist air), and (2) column abundance and surface moisture flux E (gm H2O/(cm(sup 2)sec)) to infer regional evapotranspiration from Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) water vapor mapping data. AVIRIS provides, via analysis of atmospheric water absorption features, estimates of column moisture abundance at very high mapping rate (at approximately 100 km(sup 2)/40 sec) over large areas at 20 m ground resolution.

Conel, James E.↗
NASA NTRS1979

Modeling of terrain gradient for stochastically spaced rows of a measurement matrix

Terrain gradients are employed to evaluate passable regions for unmanned martian roving vehicle. Range data matrix is displaced randomly row wise at the shallow elevation angles near the skyline. The magnitude of the measurement noise in the elevation angles can approach that of the spacing of the same angle. By using a variable incremental data spacing scanning scheme, one can estimate this signal noise ratio. It is found that the error in slope estimate at far distance becomes large for a given elevation angle error. Evaluation of the in-path slopes can be expressed in terms of the inverse of the range slopes. This is because of the fact that the elevation angle is considered as a random variable while the range data are relatively less noisy. An error analysis is performed and it is found that the change of slope is a nonlinear function of the error in elevation angle.

Mediavilla, R.↗
NASA NTRS1990

Total solar irradiance variability - 5 years of ERBE data

Data obtained by the ERBS solar monitors measuring total solar irradiance variability are discussed. The ERBS and NOAA-99 monitors derived 1365 W/sq m as the magnitude of the solar irradiance, normalized to 1 astronomical unit. The NOAA-10 monitor yielded 1363 W/m as the magnitude of the irradiance. The long-term precision of the monitors was demonstrated by the detection of the decreasing and increasing trends in the irradiance at levels of the order of 0.03 to 0.05 percent per year. The ERBS and NOAA-9 measurements demonstrated that solar variability exists in a systematic mode which is directly correlated with the solar magnetic activity, indicated by sunspot activity. It is argued that during the decline of sunspot cycle 22, the solar irradiance variability may be entirely different from that which was observed during the decline of cycle 21.

Lee, Robert B., III↗
NASA NTRS1984

The Possibility of Detection and Measurement of Cloud Structure in the Atmosphere of Uranus

Historical data concerning variability of surface brightness of the visible cloud deck are reviewed. The data do not rule out low contrast small cloud structures of the type measured in the Saturnian Voyager wind measurements. Convective models in which methane can condense suggest similar structure may be present at the level of the visible cloud deck in Uranus' atmosphere. Horizontal space and time scales derived from dynamical considerations lie within the accessible range of the wide and narrow angle Voyager cameras. Therefore, Voyager 2 may obtain significant dynamical information about the Uranian atmosphere.

Beebe, R.↗
NASA NTRS1994

Variability in pigment concentration in warm-core rings as determined by coastal zone color scanner satellite imagery from the Mid-Atlantic Bight

A time series of coastal zone color scanner (CZCS) derived chlorophyll (CZCS-chl) and sea surface temperature (SST) satellite imagery was developed for the Mid-Atlantic Bight (MAB). Warm-core rings (WCR) were identified by both the warmer SST signal as well as the low pigment concentrations of their cores. The variation in pigment concentrations and SST observed in satellite imagery over the geographic range and life span of four WCRs is investigated. The hypotheses are that pigment concentration increase during the lifetime of the WCR is a response to processes such as convective overturn, upwelling, edge enhancement due to increased vertical mixing, active convergence, or lateral exchange. Empirical orthogonal function analysis (EOF) is used to investigate the relationship between SST and pigment patterns observed in the presence of a WCR. The first two EOF modes explain more than 80% of the variability observed in all four WCRs and in both (SST and pigment) data sets. The results of this study show that, at the synoptic scales of staellite data, the variability observed in the WCRs is greater at the periphery of the rings. These results show that advective entrainment, rather than processes at ring center (e.g., shoaling of the pycnocline/nutricline in response to frictional decay) or at the periphery due to other processes such as vertical mixing, is the mechanism responsible for the observed variability.

Garcia-Moliner, Graciela↗
NASA NTRS2012

Detection of Bi-Directionality in Strain-Gage Balance Calibration Data

An indicator variable was developed for both visualization and detection of bi-directionality in wind tunnel strain-gage balance calibration data. First, the calculation of the indicator variable is explained in detail. Then, a criterion is discussed that may be used to decide which gage outputs of a balance have bi- directional behavior. The result of this analysis could be used, for example, to justify the selection of certain absolute value or other even function terms in the regression model of gage outputs whenever the Iterative Method is chosen for the balance calibration data analysis. Calibration data of NASA s MK40 Task balance is analyzed to illustrate both the calculation of the indicator variable and the application of the proposed criterion. Finally, bi directionality characteristics of typical multi piece, hybrid, single piece, and semispan balances are determined and discussed.

Ulbrich, Norbert↗
NASA NTRS2014

Missing Data and Multiple Imputation: An Unbiased Approach

The default method of dealing with missing data in statistical analyses is to only use the complete observations (complete case analysis), which can lead to unexpected bias when data do not meet the assumption of missing completely at random (MCAR). For the assumption of MCAR to be met, missingness cannot be related to either the observed or unobserved variables. A less stringent assumption, missing at random (MAR), requires that missingness not be associated with the value of the missing variable itself, but can be associated with the other observed variables. When data are truly MAR as opposed to MCAR, the default complete case analysis method can lead to biased results. There are statistical options available to adjust for data that are MAR, including multiple imputation (MI) which is consistent and efficient at estimating effects. Multiple imputation uses informing variables to determine statistical distributions for each piece of missing data. Then multiple datasets are created by randomly drawing on the distributions for each piece of missing data. Since MI is efficient, only a limited number, usually less than 20, of imputed datasets are required to get stable estimates. Each imputed dataset is analyzed using standard statistical techniques, and then results are combined to get overall estimates of effect. A simulation study will be demonstrated to show the results of using the default complete case analysis, and MI in a linear regression of MCAR and MAR simulated data. Further, MI was successfully applied to the association study of CO2 levels and headaches when initial analysis showed there may be an underlying association between missing CO2 levels and reported headaches. Through MI, we were able to show that there is a strong association between average CO2 levels and the risk of headaches. Each unit increase in CO2 (mmHg) resulted in a doubling in the odds of reported headaches.

Foy, M.↗