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NASA NTRS1995

The gaseous extent of galaxies and the origin of Lyman-alpha absorption systems: A survey of galaxies in the fields of Hubble Space Telescope spectroscopic target QSOs

We present initial results of an imaging and spectroscopic survey of faint galaxies in fields of Hubble Space Telescope (HST) spectroscopic target QSOs. The primary objectives of the survey are (1) to determine the incidence, extent, and covering factor of extended gaseous envelopes of luminous galaxies and (2) to determine the fraction of Ly(alpha) absorption systems that arise in luminous galaxies. The goal of the survey is to identify in each field under construction all objects with apparent r-band magnitudes satisfying r less than 21.5 within angular distances to the QSOs satisfying 0 less thyan 1.3'. The current observations cover six fields and are 37% complete to the goal ofthe survey. These observations identify 46 galaxies at redshifts spanning z = 0.0700-0.5526 and at impact parameters to the QSOs spanning rho = 16.6-346.9/h kpc. Of these galaxies, 11 are coincident in redshift with absorption systems and 21 do not give rise to absorption to within sensitive upper limits. Nine galaxies are coincident in redshift with 'Ly(alpha)-forest' absorption systems that show Ly(alpha) absorption but no corresponding metal-line absorption, and two galaxies are coincident in redshift with C IV absorption systems that show both Ly(alpha) and C IV absorption. Various lines of evidence demonstrate that the coincident galaxies are responsible for the corresponding absorption systems and are not present as the result of chance coincidence or merely spatial correlated with the absorption systems. The most important evidence is that there exists a statistical anti-correlation between Ly(aplha) rest-frame equivalent width and the impact parameter. Each of five galaxies with rho = 70-160/h kpc give rise to Ly(alpha) absorption, and just one of nine galaxies with rho greater than 70-160/h kpc gives rise to Ly(alpha) absorption. At least eight of 23 Ly(alpha) absorption systyems arise in galaxies. On the basis of these results we reach the following conclusions: (1) At z less than or approximately = 1 most luminosu galaxies are surrounded by extended gaseous envelopes of approximately = 160/h kpc radius and of roughly unit covering factor. This conclusion confirms previous speculation that normal luminosu galaxies possess extended gaseous halos or extended gaseous disks. (2) At z less than or approximately = 1 the fraction of Ly(aplha) absorption systems-including Ly(alpha)-forest absorption systems-that arise in luminous galaxies is at least 0.32 +/- 0.10 and may be as high as 0.60 +/- 0.19. This conclusion runs contrary to the longstanding belief that Ly(alpha)-forest absorption systems arise in intergalactic clouds.

Lanzetta, Kenneth M.↗

NASA NTRS1999

Data Processing for the Near Earth Asteroid Rendezvous (NEAR), X-ray and Gamma-ray Spectrometer (XGRS) Ground System

An X-ray and Gamma-ray spectrometer (XGRS) is onboard the Near Earth Asteroid Rendezvous (NEAR) spacecraft to determine the elemental composition of the surface of the asteroid 433Eros. The Eros asteroid is highly non-spherical in physical shape and the development of data management and analysis methodologies are in several areas a divergence from traditional remotely sensed geographical information systems techniques. Field of view and asteroid surface geometry must be derived virtually and then combined with real measurements of solar, spectral and instrument calibration information to derive meaningful scientific results. Spatial resolution of planned geochemical maps will be improved from the initial conditions of low statistical significance per integration by repeated surface flyovers and regional spectral accumulation. This paper describes the results of a collaborative effort of design and development of the NEAR XGRS instrument ground system undertaken by participants at the Goddard Space Flight Center, University of Arizona, Cornell University, Applied Physics Laboratory, and Max Plank institute.

McClanahan, Timothy P.↗

NASA NTRS1999

Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

Germany, G. A.↗

NASA NTRS1999

Data Processing for the Near Earth Asteroid Rendezvous (NEAR), X-Ray and Gamma-Ray Spectrometer (XRS) Ground System

McClanahan, Timothy P.↗

NASA NTRS2000

Early Results from the MODIS Atmosphere Cloud Algorithms

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System platform launched in December 1999. With 36 spectral bands from the visible through the infrared, and spatial resolution from 250m to 1km, the instrument provides an unprecedented opportunity for global cloud studies. A comprehensive set of remote sensing algorithms for cloud masking and retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud top physical parameters (temperature, pressure, emissivity), cloud phase, cloud optical parameters (optical depth, effective particle radius, water path), visible cirrus reflectance, a contrail flag, and other derived parameters. All products are archived into two categories: pixel-level retrievals at a 1 km or 5 km spatial resolution at nadir (referred to as Level-2 products) and 1 degree global gridded statistics (Level-3 products). An overview of the MODIS atmosphere algorithms and products, their status, validation activities, and early level-2 and -3 results will be presented.

Platnick, S.↗

NASA NTRS2003

Evaluation of Algorithms for Compressing Hyperspectral Data

With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.

Cook, Sid↗

NASA NTRS2012

Cosmic Ray Studies with the Fermi Gamma-ray Space Telescope Large Area Telescope

The Large Area Telescope (LAT) on the Fermi Gamma-ray Space Telescope provides both direct and indirect measurements of galactic cosmic rays (CR). The LAT high-statistics observations of the 7 GeV - 1 TeV electron plus positron spectrum and limits on spatial anisotropy constrain models for this cosmic-ray component. On a galactic scale, the LAT observations indicate that cosmic-ray sources may be more plentiful in the outer Galaxy than expected or that the scale height of the cosmic-ray diffusive halo is larger than conventional models. Production of cosmic rays in supernova remnants (SNR) is supported by the LAT gamma-ray studies of several of these, both young SNR and those interacting with molecular clouds.

Thompson, David J.↗

NASA NTRS2011

Cosmic Ray Studies with the Fermi Gamma-ray Space Telescope Large Area Telescope

The Large Area Telescope (LAT) on the Fermi Gamma-ray Space Telescope provides both direct and indirect measurements of Galactic cosmic rays (CR). The LAT high-statistics observations of the 7 GeV - 1 TcV electron plus positron spectrum and limits on spatial anisotropy constrain models for this cosmic-ray component. On a Galactic scale, the LAT observations indicate that cosmic-ray sources may be more plentiful in the outer Galaxy than expected or that the scale height of the cosmic-ray diffusive halo is larger than conventional models. Production of cosmic rays in supernova remnants (SNR) is supported by the LAT gamma-ray studies of several of these, both young SNR and those interacting with molecular clouds.

Thompson, D. J.↗

NASA NTRS2015

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: 1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products. 2. Goddard Profiling Algorithm (GPROF) GMI and partner products. 3. Integrated Multi-satellitE Retrievals for GPM (IMERG) products. (early, late, and final)A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.In this presentation, we will present GPM data products and services with examples.

NASA GES DISC↗

NASA NTRS2014

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following:Level-1 GPM Microwave Imager (GMI) and partner radiometer productsLevel-2 Goddard Profiling Algorithm (GPROF) GMI and partner productsLevel-3 daily and monthly productsIntegrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.

precipitation↗

NASA NTRS2017

Large-Scale Circulation and Climate Variability

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Perlwitz, J.↗

NASA NTRS2022

Multisensor Machine Learning to Retrieve High Spatiotemporal Resolution Land Surface Temperature

Climate change is making heat waves more frequent, long-lasting, and severe. While multiple satellite types provide data to monitor surface temperature, geostationary (GEO) sensors provide near-continuous, continental-scale observations which can better capture the diurnal variability of land surface temperature (LST) than intermittent observations from low-earth orbit (LEO) sensors. However, standard products from GEO satellites are available at coarsened spatial and temporal resolutions compared to the native sensor resolution. Using datasets from the NASA Earth Exchange, we leveraged co-located, co-temporal observations from LEO and GEO satellites to learn a data-driven mapping using a convolutional neural network. The resulting NASA Earth eXchange Artificial Intelligence LST (NEXAI-LST) achieved a mean absolute error of 1.73 K relative to the target LEO product and improves on both spatial and temporal resolution [2 km, 10 minute] compared to the GEO full disk standard product [10 km, hourly]. In validation against measurements from a ground-based sensor network, NEXAI-LST achieves similar or better fit than both LEO and GEO standard products, while depending none of the prior knowledge of land surface and atmospheric states required by physical-statistical models. Further, application of the model to unseen LEO and GEO satellites demonstrates robust generalization of the model across spatial region, time of day, and sensor. In support of NASA’s open-source science initiative, we make our NEXAI-LST product, model, and codes available to facilitate data exploration and further studies.

Kate Marie Duffy↗

NASA NTRS1978

A parametric multiclass Bayes error estimator for the multispectral scanner spatial model performance evaluation

The author has identified the following significant results. The probability of correct classification of various populations in data was defined as the primary performance index. The multispectral data being of multiclass nature as well, required a Bayes error estimation procedure that was dependent on a set of class statistics alone. The classification error was expressed in terms of an N dimensional integral, where N was the dimensionality of the feature space. The multispectral scanner spatial model was represented by a linear shift, invariant multiple, port system where the N spectral bands comprised the input processes. The scanner characteristic function, the relationship governing the transformation of the input spatial, and hence, spectral correlation matrices through the systems, was developed.

Mobasseri, B. G.↗

NASA NTRS2016

Statistical Correlation of Low-Altitude ENA Emissions with Geomagnetic Activity from IMAGE MENA Observations

Plasma sheet particles transported Earthward during times of active magnetospheric convection can interact with exospheric/thermospheric neutrals through charge exchange. The resulting Energetic Neutral Atoms (ENAs) are free to leave the influence of the magnetosphere and can be remotely detected. ENAs associated with low-altitude (300-800 km) ion precipitation in the high-latitude atmosphere/ionosphere are termed low-altitude emissions (LAEs). Remotely observed LAEs are highly nonisotropic in velocity space such that the pitch angle distribution at the time of charge exchange is near 90deg. The Geomagnetic Emission Cone of LAEs can be mapped spatially, showing where proton energy is deposited during times of varying geomagnetic activity. In this study we present a statistical look at the correlation between LAE flux (intensity and location) and geomagnetic activity. The LAE data are from the MENA imager on the IMAGE satellite over the declining phase of solar cycle 23 (2000-2005). The SYM-H, AE, and Kp indices are used to describe geomagnetic activity. The goal of the study is to evaluate properties of LAEs in ENA images and determine if those images can be used to infer properties of ion precipitation. Results indicate a general positive correlation to LAE flux for all three indices, with the SYM-H showing the greatest sensitivity. The magnetic local time distribution of LAEs is centered about midnight and spreads with increasing activity. The invariant latitude for all indices has a slightly negative correlation. The combined results indicate LAE behavior similar to that of ion precipitation.

Mackler, D. A.↗

NASA NTRSDate not supplied

Three Years of Airborne Observations During NASA Activate: A Statistical Summary of Chemical, Optical, and Microphysical Aerosol Properties Over the Western North Atlantic Ocean

Airborne observations are critical to understanding Earth’s climate system and surface-level air quality by providing both spatial and vertical information that is not possible through ground measurement networks or satellite observations. Airborne platforms allow assessments of long-range transport, vertical redistribution, boundary-layer dynamics, and cloud-aerosol-interactions that are critical to model evaluation and satellite validation. Still, the high cost and effort of aircraft operations can limit measurement campaigns to short, focused time periods. Multiple deployments are often necessary for seasonal comparisons, and results can be limited if target phenomenon are infrequent. Subsequent analyses typically focus on case studies, especially if deployment conditions are climatologically anomalous. The NASA ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) mission was designed to overcome these limitations by operating semi-continuously over multiple months during multiple seasons. Flight plans were intentionally simple, repetitive, and systematic to provide a statistically robust dataset that could be utilized similarly to a ground-network. Here, we present an overview of three years (2020-2022) of aerosol measurements from the NASA HU-25 Falcon aircraft supporting the ACTIVATE mission. Data from 179 flights were considered, the majority of which were based at NASA Langley Research Center and flown locally over the Wester North Atlantic Ocean just east of Hampton, VA, USA. Airmass characteristics tended to transition from continental outflow near the coast to mostly marine over the open ocean. Seasonal, diurnal, spatial, and vertical trends in aerosol microphysical, optical, and chemical properties are discussed in the context of synoptic scale meteorology. Statistical benefits of the ACTIVATE sampling strategy are discussed with regard to future model evaluation.

Luke D Ziemba↗

NASA NTRS1981

Unbiased estimation of oceanic mean rainfall from satellite borne radiometer measurements

The statistical properties of the radar derived rainfall obtained during the GARP Atlantic Tropical Experiment (GATE) are used to derive quantitative estimates of the spatial and temporal sampling errors associated with estimating rainfall from brightness temperature measurements such as would be obtained from a satelliteborne microwave radiometer employing a practical size antenna aperture. A basis for a method of correcting the so called beam filling problem, i.e., for the effect of nonuniformity of rainfall over the radiometer beamwidth is provided. The method presented employs the statistical properties of the observations themselves without need for physical assumptions beyond those associated with the radiative transfer model. The simulation results presented offer a validation of the estimated accuracy that can be achieved and the graphs included permit evaluation of the effect of the antenna resolution on both the temporal and spatial sampling errors.

Mittal, M. C.↗

NASA NTRS1976

Toward the modeling of land use change: A spatial analysis using remote sensing and historical data

It was hypothesized that the chronological observation of land use change could be shown to follow a predictable pattern and these patterns could be correlated with other statistical data to develop transition probabilities suitable for modeling purposes. A literature review and preliminary research, however, indicated a totally stochastic approach was not practical for simulating land use change and thus a more deterministic approach was adopted. The approach used assumes the determinants of the land use conversion process are found in the market place, where land transactions among buyers and sellers occur. Only one side of the market transaction process is studied, however, namely, the purchaser's desires in securing an ideal or suitable site. The problem was to identify the ideal qualities, quantities or attributes desired in an industrial site (or housing development), and to formulate a general algorithmic statement capable of identifying potential development sites. Research procedures involved developing a list of variables previously noted in the literature to be related to site selection and streamlining the list to a set suitable for statistical testing. A sample of 157 industries which have located (or relocated) in the 16-county Knoxville metropolitan region since 1950 was selected for industrial location analysis. Using NASA color infrared photography and Tennessee Valley Authority historical aerial photography, data were collected on the spatial characteristics of each industrial location event. These data were then subjected to factor analysis to determine the interrelations of variables.

Honea, R. B.↗

NASA NTRS2016

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

climate projection↗