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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

The effect of a turbulent wake on the stagnation point. I - Skin friction results

The response of a boundary layer in the stagnation region of a two-dimensional body to fluctuations in the freestream is examined. The analysis is restricted to laminar incompressible flow. The assumed form of the velocity distribution at the edge of the boundary layer represents both a pulsation of the incoming flow, and an oscillation of the stagnation point streamline. Both features are essential in accurately representing the effect which freestream spatial and temporal nonuniformities have upon the unsteady boundary layer. Finally, a simple model is proposed which relates the characteristic parameters in a turbulent wake to the unsteady boundary-layer edge velocity. Numerical results are presented for both an arbitrary two-dimensional geometry and a circular cylinder.

Wilson, Dennis E.↗
NASA NTRS1994

Optimizing tertiary storage organization and access for spatio-temporal datasets

We address in this paper data management techniques for efficiently retrieving requested subsets of large datasets stored on mass storage devices. This problem represents a major bottleneck that can negate the benefits of fast networks, because the time to access a subset from a large dataset stored on a mass storage system is much greater that the time to transmit that subset over a network. This paper focuses on very large spatial and temporal datasets generated by simulation programs in the area of climate modeling, but the techniques developed can be applied to other applications that deal with large multidimensional datasets. The main requirement we have addressed is the efficient access of subsets of information contained within much larger datasets, for the purpose of analysis and interactive visualization. We have developed data partitioning techniques that partition datasets into 'clusters' based on analysis of data access patterns and storage device characteristics. The goal is to minimize the number of clusters read from mass storage systems when subsets are requested. We emphasize in this paper proposed enhancements to current storage server protocols to permit control over physical placement of data on storage devices. We also discuss in some detail the aspects of the interface between the application programs and the mass storage system, as well as a workbench to help scientists to design the best reorganization of a dataset for anticipated access patterns.

Chen, Ling Tony↗
NASA NTRS1995

Leak detection utilizing analog binaural (VLSI) techniques

A detection method and system utilizing silicon models of the traveling wave structure of the human cochlea to spatially and temporally locate a specific sound source in the presence of high noise pandemonium. The detection system combines two-dimensional stereausis representations, which are output by at least three VLSI binaural hearing chips, to generate a three-dimensional stereausis representation including both binaural and spectral information which is then used to locate the sound source.

Hartley, Frank T.↗
NASA NTRS1995

Regional scale evaporation and the atmospheric boundary layer

In this review we briefly summarize some current models of evaporation and the atmospheric boundary layer (ABL) and discuss new experimental and computational oppurtunities that may aid our understanding of evaporation at these larger scales. In particular, consideration is given to remote sensing of the atmosphere, computational fluid dynamics and the role numerical models can play in understanding land-atmosphere interactions. These powerful modeling and measurement tools are allowing us to visualize and study spatial and temporal scales previously untouched, thereby increasing the oppurtunities to improve our understanding of land-atmosphere interaction.

Parlange, Marc B.↗
NASA NTRS2003

Earth Science Futuristic Trends and Implementing Strategies

For the last several years, there is a strong trend among the science community to increase the number of space-based observations to get a much higher temporal and spatial resolution. Such information will eventually be useful in higher resolution models that can provide predictability with higher precision. Such desirability puts a tremendous burden on any single implementing entity in terms of budget, technology readiness and compute power. The health of planet Earth is not governed by a single country, but in reality, is everyone's business living on this planet. Therefore, with this notion, it is becoming an impractical problem by any single organization/country to undertake. So far, each country per their means has proceeded along satisfactorily in implementing or benefiting directly or indirectly from the Earth observation data and scientific products. However, time has come that this is becoming a humongous problem to be undertaken by a single country. Therefore, this paper gives some serious thoughts in what options are there in undertaking this tremendous challenge. The problem is multi-dimensional in terms of budget, technology availability, environmental legislations, public awareness, and communication limitations. Some of these issues are introduced, discussed and possible implementation strategies are provided in this paper to move out of this predicament. A strong emphasis is placed on international cooperation and collaboration to see a collective benefit for this effort.

Habib, Shahid↗
NASA NTRS2004

Regional and Global CO and Aerosol Correlations: An Integrated Approach of Surface, Satellite, and Aircraft Measurements and Model Simulations

We investigate regional and global CO and fine mode aerosol correlations by combining GOCART model simulations with various measurements from surface (CMDL /CO and AERONET / aerosol), satellite (MOPl3T / CO and MODIS / aerosol), and aircraft. CO mixing ratios and aerosol concentrations are examined using surface and aircraft measurements on several representative regions. Satellite observations provide the comparisons of CO column and aerosol fine model AOD at global scale. Numerical model simulation allows us to compare CO and aerosol properties without temporal and spatial limitation and with the capability to trace emissions by isolating different somces. Our zonal mean comparisons confirm the previous researches that the variations of CO and aerosol properties are out of phase by several month. over northern hemisphere middle latitudes where anthropogenic emissions dominate. Over the biomass burning dominating regions, such as southern hemisphere (SH) extra-tropical zone, the concentration and column properties of CO and aerosol show more agreement. Long- term transport and local chemistry drive the biggest phase shift of CO and aerosol properties over remote SH ocean regions. There are much more complicated relationships CO and aerosol properties over stations and small regions due to emission, transport, and local chemistry.

Bian-Hui-Sheng↗
NASA NTRS2006

Night and Day: The Opacity of Clouds Measured by the Mars Orbiter Laser Altimeter (MOLA)

The Mars Orbiter Laser Altimeter (MOLA) [l] on the Mars Global Surveyor spacecraft ranged to clouds over the course of nearly two Mars years [2] using an active laser ranging system. While ranging to the surface, the instrument was also able to measure the product of the surface reflectivity with the two-way atmospheric transmission at 1064 nm. Furthermore, the reflectivity has now been mapped over seasonal cycles using the passive radiometric capability built into MOLA [3]. Combining these measurements, the column opacity may be inferred. MOLA uniquely provides these measurements both night and day. This study examines the pronounced nighttime opacity of the aphelion season tropical water ice clouds, and the indiscernibly low opacity of the southern polar winter clouds. The water ice clouds (Figure 1) do not themselves trigger the altimeter but have measured opacities tau > 1.5 and are temporally and spatially correlated with temperature anomalies predicted by a Mars Global Circulation Model (MGCM) that incorporates cloud radiative effects [4]. The south polar CO2 ice clouds trigger the altimeter with a very high backscatter cross-section over a thickness of 3-9 m and are vertically dispersed over several km, but their total column opacities lie well below the MOLA measurement limit of tau = 0.7. These clouds correspond to regions of supercooled atmosphere that may form either very large specularly reflecting particles [2] or very compact, dense concentrations (>5x10(exp 6)/cu m) of 100-p particles

Neumann, G. A.↗
NASA NTRS2011

4D Dynamic Required Navigation Performance Final Report

New advanced four dimensional trajectory (4DT) procedures under consideration for the Next Generation Air Transportation System (NextGen) require an aircraft to precisely navigate relative to a moving reference such as another aircraft. Examples are Self-Separation for enroute operations and Interval Management for in-trail and merging operations. The current construct of Required Navigation Performance (RNP), defined for fixed-reference-frame navigation, is not sufficiently specified to be applicable to defining performance levels of such air-to-air procedures. An extension of RNP to air-to-air navigation would enable these advanced procedures to be implemented with a specified level of performance. The objective of this research effort was to propose new 4D Dynamic RNP constructs that account for the dynamic spatial and temporal nature of Interval Management and Self-Separation, develop mathematical models of the Dynamic RNP constructs, "Required Self-Separation Performance" and "Required Interval Management Performance," and to analyze the performance characteristics of these air-to-air procedures using the newly developed models. This final report summarizes the activities led by Raytheon, in collaboration with GE Aviation and SAIC, and presents the results from this research effort to expand the RNP concept to a dynamic 4D frame of reference.

Finkelsztein, Daniel M.↗
NASA NTRS2016

Role of Updraft Velocity in Temporal Variability of Global Cloud Hydrometeor Number

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

cloud condensation nuclei↗
NASA NTRS2016

GC23G-1310: Investigation Into the Effects of Climate Variability and Land Cover Change on the Hydrologic System of the Lower Mekong Basin

The Lower Mekong Basin (LMB) is an economically and ecologically important region that experiences hydrologic hazards such as floods and droughts, which can directly affect human well-being and limit economic growth and development. To effectively develop long-term plans for addressing hydrologic hazards, the regional hydrological response to climate variability and land cover change needs to be evaluated. This research aims to investigate how climate variability, specifically variations in the precipitation regime, and land cover change will affect hydrologic parameters both spatially and temporally within the LMB. The research goal is achieved by (1) modeling land cover change for a baseline land cover change scenario as well as changes in land cover with increases in forest or agriculture and (2) using projected climate variables and modeled land cover data as inputs into the Variable Infiltration Capacity (VIC) hydrologic model to simulate the changes to the hydrologic system. The VIC model outputs were analyzed against historic values to understand the relative contribution of climate variability and land cover to change, where these changes occur, and to what degree these changes affect the hydrology. This study found that the LMB hydrologic system is more sensitive to climate variability than land cover change. On average, climate variability was found to increase discharge and evapotranspiration (ET) while decreasing water storage. The change in land cover show that increasing forest area will slightly decrease discharge and increase ET while increasing agriculture area increases discharge and decreases ET. These findings will help the LMB by supporting individual country policy to plan for future hydrologic changes as well as policy for the basin as a whole.

Hydrology↗
NASA NTRS2017

The GEOS-5 Neural Network Retrieval (NNR) for AOD

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from MODIS observations on board the Terra and Aqua satellites. In this talk, I will present the implementation of and recent updates to the GEOS-5 NNR for MODIS collection 6 data.

Castellanos, Patricia↗
NASA NTRS2018

Spectral Response and Effective Area Functions of the Hitomi Imaging Instruments

We describe the tools and the underlying methods and principles for generating the spectral response functions for the four imaging instruments that were flown on the Hitomi x-ray astronomy satellite [Soft X-ray Spectrometer, or SXS; Soft X-ray Imager, or SXI, and two Hard X-ray Imagers, or HXI]. In essence, the spectral response function is a temporally and spatially averaged effective area and line-spread-function. For model-fittingx-ray spectra from an instrument, the spectral response function encapsulates the end-to-end physics of the entire system from telescope to detector, and also includes satellite attitude drift, exposure corrections, and in the case of the HXIs, drift in the telescope/detector alignment system. Accuracy in the construction of the spectral response functions is, therefore, critical to maximize the science return from the data.

Yaqoob, Tahir↗
NASA NTRS2019

Radar Altimetry as a Proxy for Determining Terrestrial Water Storage Variability in Tropical Basins

The Gravity Recovery and Climate Experiment (GRACE) mission has provided us with unforeseen information on terrestrial water-storage (TWS) variability, contributing to our understanding of global hydrological processes, including hydrological extreme events and anthropogenic impacts on water storage. Attempts to decompose GRACE-based TWS signals into its different water storage layers, i.e., surface water storage (SWS), soil moisture, groundwater and snow, have shown that SWS is a principal component, particularly in the tropics, where major rivers flow over arid regions at high latitudes. Here, we demonstrate that water levels, measured with radar altimeters at a limited number of locations, can be used to reconstruct gridded GRACE-based TWS signals in the Amazon basin, at spatial resolutions ranging from 0.5 to 3°, with mean absolute errors (MAE) as low as 2.5 cm and correlations as high as 0.98. We show that, at 3° spatial resolution, spatially-distributed TWS time series can be precisely reconstructed with as few as 41 water-level time series located within the basin. The proposed approach is competitive when compared to existing TWS estimates derived from physically based and computationally expensive methods. Also, a validation experiment indicates that TWS estimates can be extrapolated to periods beyond that of the model regression with low errors. The approach is robust, based on regression models and interpolation techniques, and offers a new possibility to reproduce spatially and temporally distributed TWS that could be used to fill inter-mission gaps and to extend GRACE-based TWS time series beyond its timespan.

Terrestrial water storage↗
NASA NTRS2022

Using Atmospheric Trace Gas Vertical Profiles to Evaluate Model Fluxes: A Case Study of Arctic-Cap Observations and Geos Simulations for the ABoVE Domain

Accurate estimates of carbon–climate feedbacks require an independent means for evaluating surface flux models at regional scales. The altitude-integrated enhancement (AIE) derived from the Arctic Carbon Atmospheric Profiles (Arctic-CAP) project demonstrates the utility of this bulk quantity for surface flux model evaluation. This bulk quantity leverages background mole fraction values from the middle free troposphere, is agnostic to uncertainties in boundary layer height, and can be derived from model estimates of mole fractions and vertical gradients. To demonstrate the utility of the bulk quantity, six airborne profiling surveys of atmospheric carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) throughout Alaska and northwestern Canada between April and November 2017 were completed as part of NASA’s Arctic–Boreal Vulnerability Experiment (ABoVE). The Arctic-CAP sampling strategy involved acquiring vertical profiles of CO2, CH4, and CO from the surface to 5 km altitude at 25 sites around the ABoVE domain on a 4- to 6-week time interval. All Arctic-CAP measurements were compared to a global simulation using the Goddard Earth Observing System (GEOS) modeling system. Comparisons of the AIE bulk quantity from aircraft observations and GEOS simulations of atmospheric CO2, CH4, and CO highlight the fidelity of the modeled surface fluxes. The model–data comparison over the ABoVE domain reveals that while current state-of-the-art models and flux estimates are able to capture broad-scale spatial and temporal patterns in near-surface CO2 and CH4 concentrations, more work is needed to resolve fine-scale flux features that are captured in CO observations

CO2↗
NASA NTRSDate not supplied

The GEOS Neural Network Retrieval (NNR) for Multi-spectral AOD

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from multiple sensors. In this presentation, I will present recent updates to the GEOS-5 NNR for estimation of spectral AOD from MODIS and VIIRS, and the potential for multi-channel AOD assimilation to provide constraints on aerosol composition.

GEOS↗
NASA NTRSDate not supplied

The GEOS Neural Network Retrieval (NNR) for Multi-spectral AOD

One of the difficulties in data assimilation is the need for multi-sensor data merging that can account for temporal and spatial biases between satellite sensors. In the Goddard Earth Observing System Model Version 5 (GEOS-5) aerosol data assimilation system, a neural network retrieval (NNR) is used as a mapping between satellite observed top of the atmosphere (TOA) reflectance and AOD, which is the target variable that is assimilated in the model. By training observations of TOA reflectance from multiple sensors to map to a common AOD dataset (in this case AOD observed by the ground based Aerosol Robotic Network, AERONET), we are able to create a global, homogenous, satellite data record of AOD from multiple sensors. In this presentation, I will present recent updates to the GEOS-5 NNR for estimation of spectral AOD from MODIS and VIIRS, and the potential for multi-channel AOD assimilation to provide constraints on aerosol composition.

Patricia Castellanos↗
NASA NTRS1998

Seasonally Frozen Soil Monitoring Using Passive Microwave Satellite Data and Simulation Modeling

Satellite data and simulation modeling were used to assess seasonally frozen soils in the central US - Canada borders area (46-53 degrees N and 96-108 degrees). We used Scanning Multichannel Microwave Radiometer (SMMR) satellite data to delineate the top layer of frozen soils. SMMR is a passive microwave sensor having five channels (6.6, 10, 18, 21 and 37 GHz) with a horizontal and vertical polarization. SMRR data are available between 1978-1987 with noon and midnight overpass and footprint sizes between 25 km and 150 km. SMMR data were processed from resampled 1/4 degree grid cells during fall freeze-up and spring thaw (fall 1985 - spring 1987). The dielectric properties of a target may directly affect the satellite signal. The dielectric value is an order of magnitude smaller for frozen soil water. There are other significant changes to the emitted microwave signal from changes to the surface physical temperature, attenuation of the soil signal from plant water and soil moisture. We further characterized the temporal and spatial dynamic of frozen soils using the FroST (Frozen Soil Temperature) simulation model. The FroST model was used to further predict soil water and ice content, and soil temperature. SMMR results were compared versus 5-cm soil temperature data from available weather stations (14 in Canada and 11 for available months in the US). SMMR data were analyzed as a function of frequency, polarization, polarization difference, and "frequency gradient". In addition, vegetation density, physical temperature and snow depth were also considered. Preliminary analysis of SMMR derived frozen soil/thaw classification using a simple threshold classification indicates a mean overall classification accuracy by season of 85 percent. A sensitivity analysis for different soils with varying amounts of snow was conducted with FroST, which showed that the amount of snow, and the time of snow fall and melt affected the ice and water content, and depth of thaw. These results indicate a potential source of flooding and erosion under conditions when melting snow and spring rains provide a source of infiltrating water.

Toll, D. L.↗
NASA NTRS1985

Calculation of geopotential and temperature fields from an array of nearly continuous wind observations

The accuracy is studied of temperature estimates derived from the divergence equation when wind observations of various spatial and temporal resolutions and accuracies are available. The basic data set used is the high resolution model data set used by Kuo and Anthes (1984a) in observing systems simulation experiments (OSSE) designed to estimate the errors in heat and moisture budgets (Kuo and Anthes, 1984b) calculated from the AVE-SESAME-1979 spatial observational network. This model data set is modified in ways to simulate wind observations that appear feasible from an operational regional network of wind profilers.

Kuo, Ying-Hwa↗