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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Solar system exploration from the Moon: Synoptic and comparative study of bodies in our Planetary system

An observational approach to Planetary Sciences and exploration from Earth applies to a quite limited number of targets, but most of these are spatially complex, and exhibit variability and evolution on a number of temporal scales which lie within the scope of possible observations. Advancing our understanding of the underlying physics requires the study of interactions between the various elements of such systems, and also requires study of the comparative response of both a given object to various conditions and of comparable objects to similar conditions. These studies are best conducted in 'campaigns', i.e. comprehensive programs combining simultaneous coherent observations of every interacting piece of the puzzle. The requirements include both imaging and spectroscopy over a wide spectral range, from UV to IR. While temporal simultaneity of operation in various modes is a key feature, these observations are also conducted over extended periods of time. The moon is a prime site offering long unbroken observation times and high positional stability, observations at small angular separation from the sun, comparative studies of planet Earth, and valuable technical advantages. A lunar observatory should become a central piece of any coherent set of planetary missions, supplying in-situ explorations with the synoptic and comparative data necessary for proper advance planning, correlative observations during the active exploratory phase, and follow-up studies of the target body or of related objects.

Bruston, P.↗
NASA NTRS1995

Observations of the Global Characteristics and Regional Radiative Effects of Marine Cloud Liquid Water

The large-scale spatial distribution and temporal variability of cloud liquid water path (LWP) over the world's oceans and the relationship of cloud LWP to temperature and the radiation budget are investigated using recent satellite measurements from the Special Sensor Microwave/Imager (SSM/I), the Earth Radiation Budget Experiment (ERBE), and the International Satellite Cloud Climatology Project (ISCCP). Observations of cloud liquid water on a 2.5 deg x 2.5 deg and are used over a 53-month period beginning July 1987 and ending in December 1991. The highest values of cloud liquid water (greater than 0.13 kg/sq m) occur largely along principal routes of northern midlatitude storms and in areas dominated by tropical convection. The zonally averaged structure is distinctly trimodal, where maxima appear in the midlatitudes and near the equator. The average marine cloud LWP over the globe is estimated to be about 0.113 kg/sq m. Its highest seasonal variability is typically between 15% and 25% of the annual mean but in certain locations can exceed 30%. Comparisons of cloud LWP to temperature for low clouds during JJA and DJF of 1990 show significant positive correlations at colder temperatures and negative correlations at warmer temperatures. The correlations also exhibit strong seasonal and regional variation. Coincident and collocated observations of cloud LWP from the SSM/I and albedo measurements from the Earth Radiation Budget Satellite (ERBS) and the NOAA-10 satellite are compared for low clouds in the North Pacific and North Atlantic. The observed albedo-LWP relationships correspond reasonably well with theory, where the average cloud effective radius (r(sub e)) is 11.1 microns and the standard deviation is 5.2 microns. The large variability in the inferred values of r(sub e) suggests that other factors may be important in the albedo-LWP relationships. In terms of the effect of the LWP on the net cloud forcing, the authors find that a 0.05 kg/sq m increase in LWP (for LWP less than 0.2 kg/sq m) results in a -25 W/sq m change in the net cloud forcing at a solar zenith angle of 75 deg.

Greenwald, Thomas J.↗
NASA NTRS1998

Feature Detection in Linked Derived Spaces

This paper describes by example a strategy for plotting and interacting with data in multiple metric spaces. The example system was designed for use with time-varying computational fluid dynamics (CFD) datasets, but the methodology is directly applicable to other types of field data. The central objects embodied by the tool are {\em portraits}, which show the data in various coordinate systems, while preserving their spatial connectivity and temporal variability. The coordinates are derived in various ways from the field data, and an important feature is that new and derived portraits can be created interactively. The primary operations supported by the tool are brushing and linking: the user can select a subset of a given portrait, and this subset is highlighted in all portraits. The user can combine highlighted subsets from an arbitrary number of portraits with the usual logical operators, thereby indicating where an arbitrarily complex set of conditions holds. The system is useful for exploratory visualization and feature detection in multivariate data.

Henze, Chris↗
NASA NTRS2003

Evaluation of a Multi-Decadal Simulation of Stratospheric Ozone by Comparison with Total Ozone Mapping Spectrometer (TOMS) Observations

One key application of atmospheric chemistry and transport models is prediction of the response of ozone and other constituents to various natural and anthropogenic perturbations. These include changes in composition, such as the previous rise and recent decline in emission of man-made chlorofluorcarbons, changes in aerosol loading due to volcanic eruption, and changes in solar forcing. Comparisons of hindcast model results for the past few decades with observations are a key element of model evaluation and provide a sense of the reliability of model predictions. The 25 year data set from Total Ozone Mapping Spectrometers is a cornerstone of such model evaluation. Here we report evaluation of three-dimensional multi-decadal simulation of stratospheric composition. Meteorological fields for this off-line calculation are taken from a 50 year simulation of a general circulation model. Model fields are compared with observations from TOMS and also with observations from the Stratospheric Aerosol and Gas Experiment (SAGE), Microwave Limb Sounder (MLS), Cryogenic Limb Array Etalon Spectrometer (CLAES), and the Halogen Occultation Experiment (HALOE). This overall evaluation will emphasize the spatial, seasonal, and interannual variability of the simulation compared with observed atmospheric variability.

Douglass, Anne R.↗
NASA NTRS2004

The Ultra-Luminous X-ray Source Population from the Chandra Archive of Galaxies

One hundred fifty-four discrete non-nuclear Ultra-Luminous X-ray (ULX) sources, with spectroscopically-determined intrinsic X-ray luminosities greater than 1 e39 ergs/s, are identified in 82 galaxies observed with Chandra's Advanced CCD Imaging Spectrometer. Source positions, X-ray luminosities, and spectral and timing characteristics are tabulated. Statistical comparisons between these X-ray properties and those of the weaker discrete sources in the same fields (mainly neutron star and stellar-mass black hole binaries) are made. Sources above approximately le38 ergs per second display similar spatial, spectral, color, and variability distributions. In particular, there is no compelling evidence in the sample for a new and distinct class of X-ray object such as the intermediate-mass black holes. 83% of ULX candidates have spectra that can be described as absorbed power laws with index = 1.74 and column density = 2.24e21 l per square centimeter, or approximately 5 times the average Galactic column. About 20% of the ULX's have much steeper indices indicative of a soft, and likely thermal, spectrum. The locations of ULXs in their host galaxies are strongly peaked towards their galaxy centers. The deprojected radial distribution of the ULX candidates is somewhat steeper than an exponential disk, indistinguishable from that of the weaker sources. About 5--15% of ULX candidates are variable during the Chandra observations (which average 39.5 ks). Comparison of the cumulative X-ray luminosity functions of the ULXs to Chandra Deep Field results suggests approximately 25% of the sources may be background objects including 14% of the ULX candidates in the sample of spiral galaxies and 44% of those in elliptical galaxies implying the elliptical galaxy ULX population is severely compromised by background active galactic nuclei. Correlations with host galaxy properties confirm the number and total X-ray luminosity of the ULXs are associated with recent star formation and with galaxy merging and interactions. The preponderance of ULXs in star-forming galaxies as well as their similarities to less-luminous sources suggest they originate in a young but short-lived population such as the high-mass X-ray binaries with a smaller contribution (based on spectral slope) from recent supernovae. The number of ULXs in elliptical galaxies scales with host galaxy mass and can be explained most simply as the high-luminosity end of the low-mass X-ray binary population.

Swartz, Douglas A.↗
NASA NTRS2004

Tropospheric Wind Monitoring During Day-of-Launch Operations for NASA's Space Shuttle Program

The Environments Group at the National Aeronautics and Space Administration's Marshall Space Flight Center monitors the winds aloft above Kennedy Space Center (KSC) in support of the Space Shuttle Program day-of-launch operations. Assessment of tropospheric winds is used to support the ascent phase of launch. Three systems at KSC are used to generate independent tropospheric wind profiles prior to launch; 1) high resolution jimsphere balloon system, 2) 50-MHz Doppler Radar Wind Profiler (DRWP) and 3) low resolution radiosonde system. All independent sources are compared against each other for accuracy. To assess spatial and temporal wind variability during launch countdown each jimsphere profile is compared against a design wind database to ensure wind change does not violate wind change criteria.

Decker, Ryan↗
NASA NTRS2004

Tropospheric Wind Monitoring During Day-of-Launch Operations for National Aeronautics and Space Administration's Space Shuttle Program

The Environments Group at the National Aeronautics and Space Administration's Marshall Space Flight Center (NASA/MSFC) monitors the winds aloft at Kennedy Space Center (KSC) during the countdown for all Space Shuttle launches. Assessment of tropospheric winds is used to support the ascent phase of launch. Three systems at KSC are used to generate independent tropospheric wind profiles prior to launch; 1) high resolution Jimsphere balloon system, 2) 50-MHz Doppler Radar Wind Profiler (DRWP) and 3) low resolution radiosonde system. Data generated by the systems are used to assess spatial and temporal wind variability during launch countdown to ensure wind change observed does not violate wind change criteria constraints.

Decker, Ryan K.↗
NASA NTRS2004

Autonomous In-Situ Resources Prospector

This presentation will describe the concept of an autonomous, intelligent, rover-based rapid surveying system to identify and map several key lunar resources to optimize their ISRU (In Situ Resource Utilization) extraction potential. Prior to an extraction phase for any target resource, ground-based surveys are needed to provide confirmation of remote observation, to quantify and map their 3-D distribution, and to locate optimal extraction sites (e.g. ore bodies) with precision to maximize their economic benefit. The system will search for and quantify optimal minerals for oxygen production feedstock, water ice, and high glass-content regolith that can be used for building materials. These are targeted because of their utility and because they are, or are likely to be, variable in quantity over spatial scales accessible to a rover (i.e., few km). Oxygen has benefits for life support systems and as an oxidizer for propellants. Water is a key resource for sustainable exploration, with utility for life support, propellants, and other industrial processes. High glass-content regolith has utility as a feedstock for building materials as it readily sinters upon heating into a cohesive matrix more readily than other regolith materials or crystalline basalts. Lunar glasses are also a potential feedstock for oxygen production, as many are rich in iron and titanium oxides that are optimal for oxygen extraction. To accomplish this task, a system of sensors and decision-making algorithms for an autonomous prospecting rover is described. One set of sensors will be located in the wheel tread of the robotic search vehicle providing contact sensor data on regolith composition. Another set of instruments will be housed on the platform of the rover, including VIS-NIR imagers and spectrometers, both for far-field context and near-field characterization of the regolith in the immediate vicinity of the rover. Also included in the sensor suite are a neutron spectrometer, ground-penetrating radar, and an instrumented cone penetrometer for subsurface assessment. Output from these sensors will be evaluated autonomously in real-time by decision-making software to evaluate if any of the targeted resources has been detected, and if so, to quantify their abundance. Algorithms for optimizing the mapping strategy based on target resource abundance and distribution are also included in the autonomous software. This approach emphasizes on-the-fly survey measurements to enable efficient and rapid prospecting of large areas, which will improve the economics of ISRU system approaches. The mature technology will enable autonomous rovers to create in-situ resource maps of lunar or other planetary surfaces, which will facilitate human and robotic exploration.

Dissly, R. W.↗
NASA NTRS2010

The Impact of the Evolving Satellite Data Record on Reanalysis Water and Energy Fluxes During the Past 30 Years

Retrospective analyses (reanalyses) use a fixed assimilation model to take diverse observations and synthesize consistent, time-dependent fields of state variables and fluxes (e.g. temperature, moisture, momentum, turbulent and radiative fluxes). Because they offer data sets of these quantities at regular space / time intervals, atmospheric reanalyses have become a mainstay of the climate community for diagnostic purposes and for driving offline ocean and land models. Of course, one weakness of these data sets is the susceptibility of the flux products to uncertainties because of shortcomings in parameterized model physics. Another issue, perhaps less appreciated, is the fact that the discreet changes in the evolving observational system, particularly from satellite sensors, may also introduce artifacts in the time series of quantities. In this paper we examine the ability of the NASA MERRA (Modern Era Retrospective Analysis for Research and Applications) and other recent reanalyses to determine variability in the climate system over the satellite record (~ the last 30 years). In particular we highlight the effect on reanalyses of discontinuities at the junctures of the onset of passive microwave imaging (Special Sensor Microwave Imager) in late 1987 as well as improved sounding and imaging with the Advanced Microwave Sounding Unit, AMSU-A, in 1998. We examine these data sets from two perspectives. The first is the ability to capture modes of variability that have coherent spatial structure (e.g. ENSO events and near-decadal coupling to SST changes) and how these modes are contained within trends in near global averages of key quantities. Secondly, we consider diagnostics that measure the consistency in energetic scaling in the hydrologic cycle, particularly the fractional changes in column-integrated water vapor versus precipitation as they are coupled to radiative flux constraints. These results will be discussed in the context of implications for science objectives and priorities of the NASA Energy and Water Cycle Study, NEWS.

Robertson, Franklin R.↗
NASA NTRS2011

Neutral Mass Spectrometer (NMS) for the Lunar Atmosphere and Dust Environment Explorer (LADEE) Mission

The Lunar Atmosphere and Dust Environment Explorer (LADEE) mission currently scheduled for launch in early 2013 aboard a Minotaur V will orbit the moon at a nominal periselene of 50 km to characterized the lunar atmosphere and dust environment. The science instrument payload includes a neutral mass spectrometer as well as an ultraviolet spectrometer and a dust detector. Although to date only He, Ar-40, K, Na and Rn-222 have been firmly identified in the lunar exosphere and arise from the solar wind (He), the lunar regolith (K and Na) and the lunar interior (Ar-40, Rn-222), upper limits have been set for a large number of other species, LADEE Neutral Mass Spectrometer (NMS) observations will determine the abundance of several species and substantially lower the present upper limits for many others. Additionally, LADEE NMS will observe the spatial distribution and temporal variability of species which condense at nighttime and show peak concentrations at the dawn terminator (e,g, Ar-40), possible episodic release from the lunar interior, and the results of sputtering or desorption processes from the regolith. In this presentation, we describe the LADEE NMS hardware and the anticipated science results.

Collier, Michael R.↗
NASA NTRS2013

Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation

Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.

Data Assimilation↗
NASA NTRS2017

VISAGE Visualization for Integrated Satellite, Airborne and Ground-Based Data Exploration

The primary goal of the VISAGE project is to facilitate more efficient Earth Science investigations via a tool that can provide visualization and analytic capabilities for diverse coincident datasets. This proof-of-concept project will be centered around the GPM Ground Validation program, which provides a valuable source of intensive, coincident observations of atmospheric phenomena. The data are from a wide variety of ground-based, airborne and satellite instruments, with a wide diversity in spatial and temporal scales, variables, and formats, which makes these data difficult to use together. VISAGE will focus on "golden cases" where most ground instruments were in operation and multiple research aircraft sampled a significant weather event, ideally while the GPM Core Observatory passed overhead. The resulting tools will support physical process studies as well as satellite and model validation.

Data fusion↗
NASA NTRS2018

Observation Error Specification for Near-Surface Soil Moisture Assimilation: Does It Matter?

The observation error variances assumed in the data assimilation (DA) of remotely sensed near-surface soil moisture observations are known to have unrealistic spatial patterns. The temporal variability in the errors is also typically neglected. Soil moisture errors cannot be directly calculated at large scales, and the globally distributed errors are unknown. We apply several approaches to estimating the observation errors (R matrix) for near-surface soil moisture DA experiments, to establish whether the assumed errors are important to the DA performance, and hence whether uncertainty in the observation error specification is a likely source of uncertainty in soil moisture DA output.

Draper, Clara↗
NASA NTRS2019

Remote Sensing of Sea Surface Salinity: Comparison of Satellite and In Situ Observations and Impact of Retrieval Parameters

Since 2009, three low frequency microwave sensors have been launched into space with the capability of global monitoring of sea surface salinity (SSS). The European Space Agency's (ESA's) Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), onboard the Soil Moisture and Ocean Salinity mission (SMOS), and National Aeronautics and Space Administration's (NASA's) Aquarius and Soil Moisture Active Passive mission (SMAP) use L-band radiometry to measure SSS. There are notable differences in the instrumental approaches, as well as in the retrieval algorithms. We compare the salinity retrieved from these three spaceborne sensors to in situ observations from theArgo network of drifting floats, and we analyze some possible causes for the differences. We present comparisons of the long-term global spatial distribution, the temporal variability for a set of regions of interest and statistical distributions. We analyze some of the possible causes for the differences between the various satellite SSS products by reprocessing the retrievals from Aquarius brightness temperatures changing the model for the sea water dielectric constant and the ancillary product for the sea surface temperature. We quantify the impact of these changes on the differences in SSS between Aquarius and SMOS.We also identify the impact of the corrections for atmospheric effectsrecently modified in the Aquarius SSS retrievals. All three satellites exhibit SSS errors with a strong dependence on sea surface temperature, but this dependence varies significantly with the sensor. We show that these differences are first and foremost due to the dielectric constant model, then to atmospheric corrections and to a lesser extent to the ancillary product of the sea surface temperature.

SSS↗
NASA NTRS2023

A GeoNEX-Based High-Spatiotemporal-Resolution Product of Land Surface Downward Shortwave Radiation and Photosynthetically Active Radiation

Surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) play critical roles in the Earth’s surface processes. As the main inputs of various ecological, hydrological, carbon, and solar photovoltaic models, increasing requirements for high-spatiotemporal-resolution DSR and PAR es- timation with high accuracy have been observed in recent years. However, few existing products satisfy all of these requirements. This study employed a well-established physical-based lookup table (LUT) approach to the GeoNEX gridded top-of-atmosphere bidirectional reflectance factor data acquired by the Advanced Hi- mawari Imager (AHI) and Advanced Baseline Imager (ABI) sensors. It produced a data product of DSR and PAR over both AHI and ABI coverage at an hourly temporal step with a 1 km spatial resolution. GeoNEX DSR data were validated over 63 stations, and GeoNEX PAR data were validated over 27 stations. The vali- dation showed that the new GeoNEX DSR and PAR products have accuracy higher than other existing prod- ucts, with root mean square error (RMSE) of hourly GeoNEX DSR achieving 74.3Wm−2 (18.0%), daily DSR estimation achieving 18.0 W m−2 (9.2 %), hourly GeoNEX PAR achieving 34.9 W m−2 (19.6 %), and daily PAR achieving 9.5 W m−2 (10.5 %). The study also demonstrated the application of the high-spatiotemporal- resolution GeoNEX DSR product in investigating the spatial heterogeneity and temporal variability of surface solar radiation. The data product can be freely accessed through the NASA Advanced Supercomputing Division GeoNEX data portal: https://data.nas.nasa.gov/geonex/geonexdata/GOES16/GEONEX-L2/DSR-PAR/ (last ac- cess: 12 March 2023) and https://data.nas.nasa.gov/geonex/geonexdata/HIMAWARI8/GEONEX-L2/DSR-PAR/ (last access: 12 March 2023) (https://doi.org/10.5281/zenodo.7023863; Wang and Li, 2022).

Surface downward shortwave radiation (DSR)↗
NASA NTRSDate not supplied

PM 2.5 Concentrations over Major Metropolitan Regions Inferred from Airborne High Spectral Resolution Lidar Measurements Using Machine Learning Regression

We use measurements of near-surface aerosol backscatter, extinction, and depolarization acquired by four NASA Langley Research Center airborne High Spectral Resolution Lidars (HSRLs) to develop a machine learning regression methodology to infer PM2.5 concentrations at the surface and aloft. These airborne HSRL measurements were acquired over major metropolitan regions in the United States and Asia during more than 170 flights since 2010. Hourly surface PM2.5 measurements from the EPA air quality system and similar networks in other countries acquired within 10 km and 15 minutes of these near-surface HSRL measurements are used to train models that compute PM2.5 concentrations from the HSRL measurements. We examine several regression methods and find that exponential Gaussian Process algorithms consistently give the best performance in terms of the lowest root-mean-square (RMS) errors and the highest correlations. Model performance varies significantly depending on various combinations of HSRL aerosol measurements (e.g., aerosol backscatter, extinction, depolarization, backscatter color ratios, lidar ratios, aerosol optical thickness) and retrievals (e.g., mixed layer height, aerosol type) used in the regressions. Models that use near-surface measurements of aerosol backscatter and aerosol intensive properties such as depolarization, backscatter color ratio, and lidar ratio typically give the best performance with RMS errors around 4 mg/m3 and correlation coefficients above 0.9. HSRL measurements were often acquired when the aircraft flew systematic “raster-scan” patterns for several hours over these cities. These flight patterns enabled measurements of the spatial, temporal, and vertical variabilities in the distributions of aerosol backscatter and aerosol intensive properties and allowed us to derive the corresponding variabilities in PM2.5 concentrations. We present examples of such variabilities over urban areas in the United States as well as Asia. We describe also how the distribution of surface PM2.5 varies with aerosol type and use these retrievals to examine model simulations of surface PM2.5 in these metropolitan regions. We also discuss how this methodology may be applied to measurements from satellite lidars such as CALIOP on CALIPSO and ATLID on EarthCARE.

lidar↗
NASA NTRS1991

Computation of three-dimensional flows using two stream functions

An approach to compute 3-D flows using two stream functions is presented. The method generates a boundary fitted grid as part of its solution. Commonly used two steps for computing the flow fields are combined into a single step in the present approach: (1) boundary fitted grid generation; and (2) solution of Navier-Stokes equations on the generated grid. The presented method can be used to directly compute 3-D viscous flows, or the potential flow approximation of this method can be used to generate grids for other algorithms to compute 3-D viscous flows. The independent variables used are chi, a spatial coordinate, and xi and eta, values of stream functions along two sets of suitably chosen intersecting stream surfaces. The dependent variables used are the streamwise velocity, and two functions that describe the stream surfaces. Since for a 3-D flow there is no unique way to define two sets of intersecting stream surfaces to cover the given flow, different types of two sets of intersecting stream surfaces are considered. First, the metric of the (chi, xi, eta) curvilinear coordinate system associated with each type is presented. Next, equations for the steady state transport of mass, momentum, and energy are presented in terms of the metric of the (chi, xi, eta) coordinate system. Also included are the inviscid and the parabolized approximations to the general transport equations.

Greywall, Mahesh S.↗