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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Soybean Roots Grown under Heat Stress Show Global Changes in Their Transcriptional and Proteomic Profiles

Heat stress is likely to be a key factor in the negative impact of climate change on crop production. Heat stress significantly influences the functions of roots, which provide support, water, and nutrients to other plant organs. Likewise, roots play an important role in the establishment of symbiotic associations with different microorganisms. Despite the physiological relevance of roots, few studies have examined their response to heat stress. Here in this study, we performed genome-wide transcriptomic and proteomic analyses on isolated root hairs, which are a single, epidermal cell type, and compared their response to stripped roots. On average, we identified 1849 and 3091 genes differentially regulated in root hairs and stripped roots, respectively, in response to heat stress. Our gene regulatory module analysis identified 10 key modules that might control the majority of the transcriptional response to heat stress. We also conducted proteomic analysis on membrane fractions isolated from root hairs and compared these responses to stripped roots. These experiments identified a variety of proteins whose expression changed within 3 h of application of heat stress. Most of these proteins were predicted to play a significant role in thermo-tolerance, as well as in chromatin remodeling and post-transcriptional regulation. In conclusion, the data presented represent an in-depth analysis of the heat stress response of a single cell type in soybean.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Evaluation of single-footprint AIRS CH4 Profile Retrieval Uncertainties Using Aircraft Profile Measurements

We evaluate the uncertainties of methane optimal estimation retrievals from single footprint thermal infrared observations from the Atmospheric Infrared Sounder (AIRS). These retrievals are primarily sensitive to atmospheric methane in the mid-troposphere through the lower stratosphere (~2 to ~17 km). We compare to in situ observations made from aircraft during the Hiaper Pole to Pole Observations (HIPPO), the NASA Atmospheric Tomography Mission (ATom) campaigns, and from the NOAA ESRL aircraft network, between the surface and 5-13 km, across a range of years, latitudes between 60 S to 80 N, and over land and ocean. After a global, pressure dependent bias correction, we find that the land and ocean have similar biases and that the reported observation error (combined measurement and interference errors) of ~27 ppb is consistent with the standard deviation between aircraft and individual AIRS observations. A single measurement has measurement (noise related) uncertainty of ~17 ppb, a ~20 ppb uncertainty from radiative interferences (e.g. from water, temperature, etc.), and ~ 30 ppb due to “smoothing error”, which is partially removed when making comparisons to in situ measurements or models in a way that account for this regularization. We estimate a 16 ppb validation error because the aircraft typically did not measure methane at altitudes where the AIRS measurements have some sensitivity, e.g. the stratosphere. Daily averaged AIRS measurements of at least 9 observations over spatio-temporal domains of < 1 degree and 1 hour have a standard deviation of ~17 ppb versus aircraft, likely because the observation errors from temperature and water vapor (for example) are only partly reduced through averaging. Seasonal averages can reduce this ~17 ppb uncertainty further to ~10 ppb, as determined through comparison with NOAA aircraft, likely because uncertainties related to radiative effects of temperature and water vapor can be reduced when averaged over a season.

Susan Kulawik↗
DOE OSTI2011

THE LUMINOSITY PROFILES OF BRIGHTEST CLUSTER GALAXIES

We have derived detailed R-band luminosity profiles and structural parameters for a total of 430 brightest cluster galaxies (BCGs), down to a limiting surface brightness of 24.5 mag arcsec{sup -2}. Light profiles were initially fitted with a Sersic's R {sup 1/n} model, but we found that 205 ({approx}48%) BCGs require a double component model to accurately match their light profiles. The best fit for these 205 galaxies is an inner Sersic model, with indices n {approx} 1-7, plus an outer exponential component. Thus, we establish the existence of two categories of the BCG luminosity profiles: single and double component profiles. We found that double profile BCGs are brighter ({approx}0.2 mag) than single profile BCGs. In fact, the Kolmogorov-Smirnov test applied to these subsamples indicates that they have different total magnitude distributions, with mean values M{sub R} = -23.8 {+-} 0.6 mag for single profile BCGs and M{sub R} = -24.0 {+-} 0.5 mag for double profile BCGs. We find that partial luminosities for both subsamples are indistinguishable up to r = 15 kpc, while for r > 20 kpc the luminosities we obtain are on average 0.2 mag brighter for double profile BCGs. This result indicates that extra-light for double profile BCGs does not come from the inner region but from the outer regions of these galaxies. The best-fit slope of the Kormendy relation for the whole sample is a = 3.13 {+-} 0.04. However, when fitted separately, single and double profile BCGs show different slopes: a{sub single} = 3.29 {+-} 0.06 and a{sub double} = 2.79 {+-} 0.08. Also, the logarithmic slope of the metric luminosity {alpha} is higher in double profile BCGs ({alpha}{sub double} = 0.65 {+-} 0.12) than in single profile BCGs ({alpha}{sub single} = 0.59 {+-} 0.14). The mean isophote outer ellipticity (calculated at {mu} {approx} 24 mag arcsec{sup -2}) is higher in double profile BCGs (e{sub double} = 0.30 {+-} 0.10) than in single profile BCGs (e{sub single} = 0.26 {+-} 0.11). Similarly, the mean absolute value of inner minus outer ellipticity is also higher in double profile BCGs. From a subsample of 24 BCGs, we found strong evidence that extra-light at intermediate radii in double profile BCGs is related to the presence of a faint stellar envelope. Similarly, from another subsample of 12 BCGs we also found that extra-light is related to star formation. On the other hand, we did not find differences between these two BCG categories when we compared global cluster properties such as the BCG-projected position relative to the cluster X-ray center emission, X-ray luminosity, or BCG orientation with respect to the cluster position angle.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

A Module for Assimilating Hyperspectral Infrared Retrieved Profiles into the Gridpoint Statistical Interpolation System for Unique Forecasting Applications

Hyperspectral infrared sounder radiance data are assimilated into operational modeling systems however the process is computationally expensive and only approximately 1% of available data are assimilated due to data thinning as well as the fact that radiances are restricted to cloud-free fields of view. In contrast, the number of hyperspectral infrared profiles assimilated is much higher since the retrieved profiles can be assimilated in some partly cloudy scenes due to profile coupling other data, such as microwave or neural networks, as first guesses to the retrieval process. As the operational data assimilation community attempts to assimilate cloud-affected radiances, it is possible that the use of retrieved profiles might offer an alternative methodology that is less complex and more computationally efficient to solve this problem. The NASA Short-term Prediction Research and Transition (SPoRT) Center has assimilated hyperspectral infrared retrieved profiles into Weather Research and Forecasting Model (WRF) simulations using the Gridpoint Statistical Interpolation (GSI) System. Early research at SPoRT demonstrated improved initial conditions when assimilating Atmospheric Infrared Sounder (AIRS) thermodynamic profiles into WRF (using WRF-Var and assigning more appropriate error weighting to the profiles) to improve regional analysis and heavy precipitation forecasts. Successful early work has led to more recent research utilizing WRF and GSI for applications including the assimilation of AIRS profiles to improve WRF forecasts of atmospheric rivers and assimilation of AIRS, Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI) profiles to improve model representation of tropopause folds and associated non-convective wind events. Although more hyperspectral infrared retrieved profiles can be assimilated into model forecasts, one disadvantage is the retrieved profiles have traditionally been assigned the same error values as the rawinsonde observations when assimilated with GSI. Typically, satellitederived profile errors are larger and more difficult to quantify than traditional rawinsonde observations (especially in the boundary layer), so it is important to appropriately assign observation errors within GSI to eliminate potential spurious innovations and analysis increments that can sometimes arise when using retrieved profiles. The goal of this study is to describe modifications to the GSI source code to more appropriately assimilate hyperspectral infrared retrieved profiles and outline preliminary results that show the differences between a model simulation that assimilated the profiles as rawinsonde observations and one that assimilated the profiles in a module with the appropriate error values.

Berndt, Emily↗
NASA NTRS2003

Analysis of Near Simultaneous Jimsphere and AMPS High Resolution Wind Profiles

The high-resolution wind profile of the Automated Meteorological Profiling System (HRAMPS) is the proposed replacement for the Jimsphere measurement system used to support NASA Shuttle launches from the Eastern Test Range (ETR). Samples of twenty-six ETR near simultaneous Jimsphere and HRAMPS wind profiles were obtained for Shuttle program HRAMPS certification studies. Shuttle systems engineering certification is to ensure that spacecraft and launch vehicle systems performance and safety evaluations for each launch (derived from flight simulations with Jimsphere wind profile data bases) retain their validity when HRAMPS profiles are used on day-of-launch (DOL) in trajectory and loads simulations to support the commit-to-launch decision. This paper describes a statistical analysis of the near simultaneous profiles. In principle the differences between a Jimsphere profile and an HRAMPS profile should be attributed to tracking technology (radar versus GPS tracking of a Jimsphere flight element) and the method for derivation of wind vectors from the raw tracking data. In reality, it is not technically feasible to track the same Jimsphere balloon with the two systems. The aluminized Mylar surface of the standard Jimsphere flight element facilitates radar tracking, but it interferes with HRAMPS during simultaneous tracking. Suspending a radar reflector from an HRAMPS flight element (Jimsphere without aluminized coating) does not produce satisfactory Jimsphere profiles because of intermittent radar returns. Thus, differences between the Jimsphere and HRAMPS profiles are also attributed to differences in the trajectories of separate flight elements. Because of small sample size and a test period limited to one winter season, test measurements during extreme high winds aloft could not have been expected and did not occur. It is during the highest winds that the largest differences between Jimsphere and HRAMPS would occur because the distance between flight elements would be larger. Jimsphere radar tracking noise increases as a function of balloon displacement downrange. The Jimsphere data processing compensates for tracking signal/noise degradation by increasing the smoothing interval. The Jimsphere wind profile effective resolution is a function of downrange distance and altitude, whereas the effective resolution of the HRAMPS should be independent of those variables. The procedure used for editing Jimsphere spikes in Shuttle DOL profiles was not implemented for the Jimsphere profile measurements during the AMPS field tests. For this analysis a code was developed that essentially mimics DOL Jimsphere spike editing. Jimsphere profiles have somewhat more noise in the wavelength range less than 200m defined as the noise floor. No differences between Jimsphere and HRAMPS wind profile pairs have been found that would support denial of HRAMPS certification for application in Shuttle DOL applications. The reliability of the HRAMPS system, which is an important certification issue, is not addressed in this study.

Adelfang, S. I.↗