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At least 865 records · Page 48
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NASA NTRS2018

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite Sea Surface Salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (National Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF ( Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive) V4 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by the satellite at approximately 1 centimeter) and in situ measurements (typically measured by Argo floats at 3 meters). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from the GMAO S2S reanalyses that assimilates/withholds along-track (L2) SSS. In particular, we contrast forecasts of the overestimated 2014 El Nino, the big 2015 El Nino, and the minor 2016 La Nina. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrades the mixed layer depth leading to more accurate coupled air/sea interaction.

Hackert, E.↗
NASA NTRS2019

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO Seasonal Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite sea surface salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (North American Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF (Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive satellite) V4.1 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by satellite at approximately 1-centimeter depth) and in situ measurements (typically measured by Argo floats at 3-meters depth). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from GMAO S2S spring reanalyses that assimilate/withhold along-track (L2) SSS. In particular, we contrast forecasts of the big 2015 El Nino, the 2017 La Nina and the 2018 weak El Nino. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrade the mixed layer depth leading to more accurate coupled air/sea interaction. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast forecasts initialized with the benefit of these two satellite SSS observation types. We assess the impact of gridded satellite sea surface salinity observations on dynamical ENSO forecasts for the big 2015 El Nino.

Hackert, E.↗
NASA NTRS2019

Overview and Evaluation of a Computational Bone Physiology Modeling Toolchain and Its Application to Testing of Exercise Countermeasures

Prolonged microgravity exposure disrupts natural bone remodeling processes and can lead to a significant loss of bone strength, increasing injury risk during missions and placing astronauts at a greater risk of bone fracture later in life. Resistance-based exercise during missions is used to combat bone loss, but current exercise countermeasures do not completely mitigate the effects of microgravity. To address this concern, we present work to develop a personalizable, site-specific computational modeling toolchain of bone remodeling dynamics to understand and estimate changes in volumetric bone mineral density (BMD) in response to microgravity-induced bone unloading and in-flight exercise. The toolchain is evaluated against data collected from subjects in a 70-day bedrest study and is found to provide insight into the amount of exercise stimulus needed to minimize bone loss, quantitatively predicting post-study volumetric BMD of control subjects who did not perform exercise, and qualitatively predicting the effects of exercise. Results suggest that, with additional data, the toolchain could be improved to aid in developing customized in-flight exercise regimens and predict exercise effectiveness.

Schepelmann, Alexander↗
NASA NTRS2019

A Remarkably Narrow RHESSI X-Ray Flare on 2011 September 25

The unusually narrow X-ray source imaged with the Ramaty High Energy Solar Spectroscopic Imager (RHESSI) during an impulsive spike lasting for ~10 s during the Geostationary Operational Environmental Satellite C7.9 flare on 2011 September 25 (SOL2011-09-25T03:32) was only ~2'' wide and ~10'' long. Comparison with Helioseismsic and Magnetic Imager magnetograms and Atmospheric Imaging Assembly images at 1700 Å shows that the X-ray emission was primarily from a long ribbon in the region of positive polarity with little if any emission from the negative polarity ribbon. However, a thermal plasma source density of ~10(exp 12)/cu.cm estimated from the RHESSI-derived emission measure and source area showed that this could best be interpreted as a coronal hard X-ray source in which the accelerated electrons with energies less than ~50 keV were stopped by Coulomb collisions in the corona, thus explaining the lack of the more usual bright X-ray footpoints. Analysis of RHESSI spectra shows greater consistency with a multi-temperature distribution and a low-energy cutoff to the accelerated electron spectrum of 22 keV compared to 12 keV if a single-temperature distribution is assumed. This leads to a change in the lower limit on the total energy in electrons by an order of magnitude, given the steepness of the best-fit electron spectrum with a power-law index of ~6.

Brian Dennis↗
NASA NTRS2023

ALMA Observations of Molecular Complexity in the Large Magellanic Cloud: Probing the Star-forming Region N 160

Hot molecular cores represent one of the earliest stages of high mass star formation, yet the number of known extragalactic hot cores is currently very small (six). A typical Galactic hot core found around a forming massive star is small, dense, hot, and it is rich in complex organic molecules (COMs; six or more atoms including carbon). In this presentation, we report the results of 1.2 mm continuum and molecular line single-pointing observations with the Atacama Large Millimeter/submillimeter Array (ALMA) of the field in the Large Magellanic Cloud (LMC) we dubbed N160A–mm. The goal of our study is to investigate the chemical complexity in this region and search for hot cores. The LMC is an ideal location for studying hot core chemistry in an environment distinctly different from the Milky Way due to its lower metallicity and strong UV radiation. N160A–mm is located in the star-forming region N160 south of 30 Doradus. It hosts two dominant young stellar objects and water (H2O), methanol (CH3OH), and hydroxyl (OH) masers, indicating ongoing star formation. We detect six 1.2 mm continuum sources, five of which are associated with the CH3OH emission peaks and/or extended emission. Methyl cyanide (CH3CN), another COM, is found towards the brightest continuum source in N160A–mm (N160A–mm A), and smaller molecules typically associated with Galactic hot cores (e.g., SO2, SO) are detected in four sources. Using spectral modeling, we estimate the rotational temperatures and column densities of the continuum sources. Based on the derived temperature of above 100 K, we identify N160–mm A as a hot core candidate. Most of the sources in N160A–mm exhibit a complex kinematic structure, providing evidence for large scale motions in the region (e.g., outflows, rotation). We compare the molecular abundances measured for N160-mm A to those found in Galactic hot cores and other LMC hot cores to investigate the impact of the environment on hot core chemistry.

Amanda Broadmeadow↗
NASA NTRS1978

Time delay occultation data of the Helios spacecraft for probing the electron density distribution in the solar corona

S-band time delay measurements were collected from the spacecraft Helios A and B during three solar occultations in 1975/76 within heliocentric distances of about 3 and 215 earth radius in terms of range, Doppler frequency shift, and electron content. Characteristic features of measurement and data processing are described. Typical data sets are discussed to probe the electron density distribution near the sun (west and east limb as well) including the outer and extended corona. Steady-state and dynamical aspects of the solar corona are presented and compared with earth-bound-K-coronagraph measurements. Using a weighted least squares estimation, parameters of an average coronal electron density profile are derived in a preliminary analysis to yield electron densities at r = 3, 65, 215 earth radius. Transient phenomena are discussed and a velocity of propagation v is nearly equal to 900 km/s is determined for plasma ejecta from a solar flare observed during an extraordinary set of Helios B electron content measurements.

Edenhofer, P.↗
NASA NTRS2020

An Analysis of the North Polar Spur using HaloSat

We present HaloSat X-ray observations of the entirety of the bright X-ray emitting feature known14as the North Polar Spur (NPS). The large field of view of HaloSat enabled coverage of the entire15bright NPS in only fourteen fields, which were each observed for≈30,000 s. We find that the NPS16fields are distinct in both brightness and spectral shape from the surrounding halo fields. We fit the17NPS as two thermal components in ionization equilibrium with temperatures kTcool≈0.087 keV18and kThot≈0.28 keV. We note a temperature gradient in the NPS hot component with an inner19arc temperature warmer than the outer arc. The emission measures we find for the cool component20of the NPS is a factor of 3-5 greater than that of the hot component, which suggests that the bulk of21the NPS material is in the≈0.1 keV component. We evaluate distance estimates of 0.4 kpc and 8.022kpc for the NPS. Our findings suggest a preference for a distant NPS with an energy of≈6×105423erg, an age of≈10 Myr, and pressures consistent with a 10μG magnetic field associated with the24Fermi bubbles. The electron density≈10×10−3cm−3is consistent with estimates for the shock25region surrounding a galactic scale event.

Daniel M LaRocca↗
NASA NTRS1989

Ginzburg-Landau theory for the solid-liquid interface of bcc elements. II - Application to the classical one-component plasma, the Wigner crystal, and He-4

The previously developed Ginzburg-Landau theory for calculating the crystal-melt interfacial tension of bcc elements to treat the classical one-component plasma (OCP), the charged fermion system, and the Bose crystal. For the OCP, a direct application of the theory of Shih et al. (1987) yields for the surface tension 0.0012(Z-squared e-squared/a-cubed), where Ze is the ionic charge and a is the radius of the ionic sphere. Bose crystal-melt interface is treated by a quantum extension of the classical density-functional theory, using the Feynman formalism to estimate the relevant correlation functions. The theory is applied to the metastable He-4 solid-superfluid interface at T = 0, with a resulting surface tension of 0.085 erg/sq cm, in reasonable agreement with the value extrapolated from the measured surface tension of the bcc solid in the range 1.46-1.76 K. These results suggest that the density-functional approach is a satisfactory mean-field theory for estimating the equilibrium properties of liquid-solid interfaces, given knowledge of the uniform phases.

Zeng, X. C.↗
NASA NTRS1992

Age-related decrements in bone mineral density in women over 65

Age-related changes in bone density contribute to the risk of fractures. To describe the relationship between age and bone mass in elderly women, we studied a large cohort of women over age 65 years who were recruited from population-based lists in four cities in the United States. Bone density in g/cm2 was measured by single-photon absorptiometry (SPA) and dual x-ray absorptiometry (DXA) at the distal and proximal radius, the calcaneus, the lumbar spine, and the proximal femur. Centralized data collection was used to control data quality and consistency. We found a strong inverse relationship between bone density and age for most sites. Decrements in bone density between women aged 65-69 years and women 85 years and older exceeded 16% in all regions except the spine, where the difference between the two age groups was 6%. Ward's triangle and the calcaneus exhibited the largest decrements, with 26 and 21%, respectively. The estimates of annual changes in bone mineral density by linear regression at sites other than the spine ranged from -0.82% at the femoral neck and trochanter to -1.30% at Ward's triangle. Correlations between the different regions ranged from r = 0.51 between the proximal radius and Ward's triangle to r = 0.66 between the distal radius and calcaneus. We conclude that the inverse relationship between age and bone mass measured by absorptiometry techniques in white women continues into the ninth decade of life. The relationship is strongest for bone density of Ward's triangle and the calcaneus and weakest for the spine.

NASA Discipline Musculoskeletal↗
NASA NTRS1977

Optimal estimation for discrete time jump processes

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are obtained. The approach is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. A general representation for optimum estimates and recursive equations for minimum mean squared error (MMSE) estimates are obtained. MMSE estimates are nonlinear functions of the observations. The problem of estimating the rate of a DTJP when the rate is a random variable with a probability density function of the form cx super K (l-x) super m and show that the MMSE estimates are linear in this case. This class of density functions explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Vaca, M. V.↗
NASA NTRS1990

Buoyancy-driven melt segregation in the earth's moon. I - Numerical results

The densities of lunar mare magmas have been estimated at liquidus temperatures for pressures from 0 to 47 kbar (0.4 GPa; center of the moon) using a third-order Birch-Murnaghan equation and compositionally dependent parameters from Large and Carmichael (1987). Results on primary magmatic compositions represented by pristine volcanic glasses suggest that the density contrast between very-high-Ti melts and their liquidus olivines may approach zero at pressures of about 25 kbar (2.5 GPa). Since this is the pressure regime of the mantle source regions for these magmas, a compositional limit of eruptability for mare liquids may exist that is similar to the highest Ti melt yet observed among the lunar samples. Although the moon may have generated magmas having greater than 16.4 wt pct TiO2, those melts would probably not have reached the lunar surface due to their high densities, and may have even sunk deeper into the moon's interior as negatively buoyant diapirs. This process may have been important for assimilative interactions in the lunar mantle. The phenomenon of melt/solid density crossover may therefore occur not only in large terrestrial-type objects but also in small objects where, despite low pressures, the range of melt compositions is extreme.

Delano, J. W.↗
NASA NTRS1973

An equation of state for oxygen and nitrogen

Recent measurements of the thermodynamic properties of oxygen and nitrogen have been used to develop a single equation of state for both fluids; with appropriate coefficients, the equation describes the pressure-density-temperature surface for each fluid within the estimated experimental uncertainty of the data. The formulation uses least squares curve fitting of the equation of state to the available experimental data (including pressure-density-temperature data, saturation data, and measured isochoric heat capacities). New vapor pressure equations and equations for the ideal gas heat capacities of oxygen and nitrogen are included for use in calculation of derived thermodynamic properties.

Jacobsen, R. T.↗
NASA NTRS1985

African land-cover classification using satellite data

Data from the advanced very high resolution radiometer sensor on the National Oceanic and Atmospheric Administration's operational series of meteorological satellites were used to classify land cover and monitor vegetation dynamics for Africa over a 19-month period. There was a correspondence between seasonal variations in the density and extent of green leaf vegetation and the patterns of rainfall associated with the movement of the Intertropical Convergence Zone. Regional variations, such as the 1983 drought in the Sahel of western Africa, were observed. Integration of the weekly satellite data with respect to time for a 12-month period produced a remotely sensed estimate of primary production based upon the density and duration of green leaf biomass. Eight of the 21-day composited data sets covering an 11-month period were used to produce a general land-cover classification that corresponded well with those of existing maps.

Tucker, C. J.↗
NASA NTRS2015

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar↗
NASA NTRS1983

Atmospheric attenuation for correlated satellite communication ground sites

Link margin estimates are calculated for 30/20 GHz satellite communication systems employing closely-spaced (4 to 100 km) 'dual diversity' switched ground sites. The link margin estimates are based on a new analysis in which the bivariate rain attenuation density function for two correlated ground sites is modelled by an exponential density function. The results of the exponential density function analysis enable derivation of a direct relation between rain margin estimates and probability of exceedance (link availability). Margins typically in the range 2 to 12 dB are calculated for various ground site separations and summarized for seven city locations and five satellite orbit positions over the U.S. The results can be easily extended to other EHF satellite frequencies and other locations.

Christopher, P.↗
NASA NTRS1996

Ambient mass density effects on the International Space Station (ISS) microgravity experiments

The Marshall engineering thermosphere model was specified by NASA to be used in the design, development and testing phases of the International Space Station (ISS). The mass density is the atmospheric parameter which most affects the ISS. Under simplifying assumptions, the critical ambient neutral density required to produce one micro-g on the ISS is estimated using an atmospheric drag acceleration equation. Examples are presented for the critical density versus altitude, and for the critical density that is exceeded at least once a month and once per orbit during periods of low and high solar activity. An analysis of the ISS orbital decay is presented.

Smith, O. E.↗
NASA NTRS2024

Storm-Time Variability of Terrestrial Hydrogen Exosphere: Kinetic Simulation Results

Recent studies of TWINS Lyman-α observations have reported an increase in geocoronal column brightness during geomagnetic storms, indicating enhanced exospheric hydrogen atom density (NH). This suggests a complex role of exospheric neutrals in determining storm-time magnetosphere dynamics and their energy release through charge-exchange processes. We developed a Model for Analyzing Terrestrial Exosphere (MATE) to investigate storm-time exospheric behaviors and their physical drivers. MATE traces test hydrogen atoms backward in time from locations in the exosphere to a nominal exobase altitude of 500 km, employing Newtonian mechanics with gravitational force. The model then calculates the phase-space densities (PSDs) of test hydrogen atoms at the exobase using the Maxwellian distribution with physics-based exobase conditions from the TIMEGCM upper atmosphere model. MATE maps PSDs at the exobase to the exosphere using Liouville’s Theorem under collisionless assumptions and derives NH by integrating the PSDs across velocity space. We conducted MATE simulation before, during, and after a minor geomagnetic storm from 12 to 18 June 2008, and compared the model results with NH estimates from the TWINS geocorona data. MATE reproduces storm-time density enhancements soon after the minimum Dst is reached, matching well with a general trend of TWINS NH estimates. The results suggest that upper atmospheric heating during a geomagnetic storm increases the number of ballistic and escaping hydrogen atoms entering the exosphere from the exobase, thereby boosting NH. However, the magnitude of modeled NH mismatches the TWINS NH estimates. The potential mechanisms of this density discrepancy include the physics excluded in the MATE model — such as neutralneutral collisions, neutral-plasma charge exchange, solar radiation pressure, and photoionization — as well as the higher exobase hydrogen density of TIMEGCM compared to typical empirical values, which will be addressed in future.

Hyunju K Connor↗
NASA NTRS1994

In-flight estimation of gyro noise on the Upper Atmosphere Research Satellite (UARS) and Extreme Ultraviolet Explorer (EUVE) missions

This paper characterizes the low-frequency noise response of the Teledyne dry rotor inertial reference unit (DRIRU) gyroscopes on the Upper Atmosphere Research Satellite (UARS) and the Extreme Ultraviolet Explorer (EUVE). The accuracy of spacecraft attitude estimation algorithms that use gyro data for propagating the spacecraft attitude is sensitive to gyro noise. EUVE gyro data were processed to validate a single-axis gyro noise model, which is used onboard various spacecraft. The paper addresses the potential impact of temperature effects on the gyro noise model and the overall impact on attitude determination accuracy. The power spectral density (PSD) of the gyro noise is estimated from UARS in-flight data by Fast Fourier Transform (FFT). The role of actuator dynamics on the PSD function is also discussed.

Lee, M.↗