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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Interferometric Characterization of the Earth's Atmosphere from Lagrange Point 2

Part of the NASA plans for future Earth Science missions calls for observations using novel vantage points that can produce science products otherwise unobtainable. Observations of the Earth from the Lagrange-2 point, L-2, (1.5 million km behind the Earth on the Earth-Sun line) affords a unique vantage point for atmospheric science. Spectral observation of the Earth's atmosphere using solar occultation techniques in the near infrared (1 to 4 microns) provides one of the most accurate methods of passively sensing attitude profiles of the major species (CO2, O3, O2, CH4, H2O N2O). While traditional polar orbiting occultation measurements can obtain about 14 measurements per day (2 per orbit), solar occultation observations from the Lagrange-2 point will yield hourly profile measurements at all latitudes. The expected spatial resolution is 2 km in altitude, 0.5 degrees in latitude, and 2 degrees in longitude. The result from 24 hours of observations will be a three-dimensional map of atmospheric composition. To accomplish this task from L-2 requires the development of a large moderate spectral resolution instrument whose entrance aperture is about 10 meters. Use of a standard telescope design with a 10-meter circular mirror or a 10-meter strip mirror would be prohibitively expensive and excessively massive. Instead, we are proposing the development of a 10-meter linear interferometer coupled to a Fourier transform imaging spectrometer. The result will be a highly efficient design with sufficient sensitivity, while having both spatial and spectral resolution to produce the desired results. Preliminary calculations show that seven species (CO2, O3, O2, CH4, H2O N2O) have clearly separated spectral features in the I to 4 microns range with sufficient absorption to produce profile information from near the Earth's surface to the middle stratosphere. For CO2 the estimated sensitivity to change is 0.33% or 1 part in 330. This should be sufficient to detect changes that are significant for the carbon cycle studies. Initial instrument design studies are underway to determine the optimum optical design for the interferometer-spectrometer as well as the necessary highly stable mechanical designs. Separate design studies are being conducted for the spacecraft. shuttle launch facility, low-light solar power design, thermal control, and unique navigation requirements to reach and maintain the tight halo orbit about L-2.

Herman, Jay R.↗
NASA NTRS2011

Retrieving Aerosol in a Cloudy Environment: Aerosol Availability as a Function of Spatial and Temporal Resolution

The challenge of using satellite observations to retrieve aerosol properties in a cloudy environment is to prevent contamination of the aerosol signal from clouds, while maintaining sufficient aerosol product yield to satisfy specific applications. We investigate aerosol retrieval availability at different instrument pixel resolutions, using the standard MODIS aerosol cloud mask applied to MODIS data and a new GOES-R cloud mask applied to GOES data for a domain covering North America and surrounding oceans. Aerosol availability is not the same as the cloud free fraction and takes into account the technqiues used in the MODIS algorithm to avoid clouds, reduce noise and maintain sufficient numbers of aerosol retrievals. The inherent spatial resolution of each instrument, 0.5x0.5 km for MODIS and 1x1 km for GOES, is systematically degraded to 1x1 km, 2x2 km, 4x4 km and 8x8 km resolutions and then analyzed as to how that degradation would affect the availability of an aerosol retrieval, assuming an aerosol product resolution at 8x8 km. The results show that as pixel size increases, availability decreases until at 8x8 km 70% to 85% of the retrievals available at 0.5 km have been lost. The diurnal pattern of aerosol retrieval availability examined for one day in the summer suggests that coarse resolution sensors (i.e., 4x4 km or 8x8 km) may be able to retrieve aerosol early in the morning that would otherwise be missed at the time of current polar orbiting satellites, but not the diurnal aerosol properties due to cloud cover developed during the day. In contrast finer resolution sensors (i.e., 1x1 km or 2x2 km) have much better opportunity to retrieve aerosols in the partly cloudy scenes and better chance of returning the diurnal aerosol properties. Large differences in the results of the two cloud masks designed for MODIS aerosol and GOES cloud products strongly reinforce that cloud masks must be developed with specific purposes in mind and that a generic cloud mask applied to an independent aerosol retrieval will likely fail.

Remer, Lorraine A.↗
NASA NTRS1998

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗
NASA NTRS1977

The effects of the atmospheric point-spread 'seeing' function on spatially resolved spectra of Jupiter

We present the results of an analysis of the effects of atmospheric seeing and of instrumental spectral and spatial resolution on the observed variation of absorption-line profiles across the disk of Jupiter. The technique described may be applied equally well to the analysis of observations of any extended astronomical source. These results show the necessity of obtaining accurate point-spread-function information during the course of observations of this nature. We also point out that in order to avoid the uncertainties and ambiguities inherent in attempts at deconvolution of observational data, one must properly convolve the appropriate spatial and spectral resolution functions with the models being tested and then compare the results with the observational data.

Gelfand, J.↗
NASA NTRS1983

High resolution telescope and spectrograph observations of solar fine structure in the 1600 A region

High spatial resolution spectroheliograms of the 1600 A region obtained during the HRTS rocket flight of 1978 February 13 are presented. The morphology, fine structure, and temporal behavior of emission bright points (BPs) in active and quiet regions are illustrated. In quiet regions, network elements persist as morphological units, although individual BPs may vary in intensity while usually lasting the flight duration. In cell centers, the BPs are highly variable on a 1 minute time scale. BPs in plages remain more constant in brightness over the observing sequence. BPs cover less than 4 percent of the quiet surface. The lifetime and degree of packing of BPs vary with the local strength of the magnetic field.

Cook, J. W.↗
NASA NTRS1989

Atmospheric correction of high resolution land surface images

Algorithms to correct for atmospheric-scattering effects in high-spatial resolution land-surface images require the ability to perform rapid and accurate computations of the top-of-atmosphere diffuse radiance field for arbitrarily general surface reflectance distributions (which may be both heterogeneous and non-Lambertian) and atmospheric models. Using three-dimensional radiative transfer (3DRT) theory algorithms are being developed. The methodology used to perform the 3DRT calculations is described. It is shown how these calculations are used to perform atmospheric corrections, and the sensitivity of the retrieved surface reflectances to atmospheric structural parameters is illustrated.

Diner, D. J.↗
NASA NTRS2008

Application of the CloudSat and NEXRAD Radars Toward Improvements in High Resolution Operational Forecasts

As computational power increases, operational forecast models are performing simulations with higher spatial resolution allowing for the transition from sub-grid scale cloud parameterizations to an explicit forecast of cloud characteristics and precipitation through the use of single- or multi-moment bulk water microphysics schemes. investments in space-borne and terrestrial remote sensing have developed the NASA CloudSat Cloud Profiling Radar and the NOAA National Weather Service NEXRAD system, each providing observations related to the bulk properties of clouds and precipitation through measurements of reflectivity. CloudSat and NEXRAD system radars observed light to moderate snowfall in association with a cold-season, midlatitude cyclone traversing the Central United States in February 2007. These systems are responsible for widespread cloud cover and various types of precipitation, are of economic consequence, and pose a challenge to operational forecasters. This event is simulated with the Weather Research and Forecast (WRF) Model, utilizing the NASA Goddard Cumulus Ensemble microphysics scheme. Comparisons are made between WRF-simulated and observed reflectivity available from the CloudSat and NEXRAD systems. The application of CloudSat reflectivity is made possible through the QuickBeam radiative transfer model, with cautious application applied in light of single scattering characteristics and spherical target assumptions. Significant differences are noted within modeled and observed cloud profiles, based upon simulated reflectivity, and modifications to the single-moment scheme are tested through a supplemental WRF forecast that incorporates a temperature dependent snow crystal size distribution.

Molthan, A. L.↗
NASA NTRS2023

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy Data Fusion to Map Global Surface Ozone Concentration and Associated Uncertainty

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R 2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m −3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Ozone↗
NASA NTRS2001

Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

Multispectral data requirements for Earth science applications are not always studied rigorously studied before a new remote sensing system is designed. A study of the spatial resolution, spectral bandpasses, and radiometric sensitivity requirements of real-world applications would focus the design onto providing maximum benefits to the end-user community. To support systematic studies of multispectral data requirements, the Applications Research Toolbox (ART) has been developed at NASA's Stennis Space Center. The ART software allows users to create and assess simulated datasets while varying a wide range of system parameters. The simulations are based on data acquired by existing multispectral and hyperspectral instruments. The produced datasets can be further evaluated for specific end-user applications. Spectral synthesis of multispectral images from hyperspectral data is a key part of the ART software. In this process, hyperspectral image cubes are transformed into multispectral imagery without changes in spatial sampling and resolution. The transformation algorithm takes into account spectral responses of both the synthesized, broad, multispectral bands and the utilized, narrow, hyperspectral bands. To validate the spectral synthesis algorithm, simulated multispectral images are compared with images collected near-coincidentally by the Landsat 7 ETM+ and the EO-1 ALI instruments. Hyperspectral images acquired with the airborne AVIRIS instrument and with the Hyperion instrument onboard the EO-1 satellite were used as input data to the presented simulations.

Blonksi, Slawomir↗
NASA NTRS2003

Adaptation of Mesoscale Weather Models to Local Forecasting

Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes objective and subjective verification methodologies. Objective (e.g., statistical) verification of point forecasts is a stringent measure of model performance, but when used alone, it is not usually sufficient for quantifying the value of the overall contribution of the model to the weather-forecasting process. This is especially true for mesoscale models with enhanced spatial and temporal resolution that may be capable of predicting meteorologically consistent, though not necessarily accurate, fine-scale weather phenomena. Therefore, subjective (phenomenological) evaluation, focusing on selected case studies and specific weather features, such as sea breezes and precipitation, has been performed to help quantify the added value that cannot be inferred solely from objective evaluation.

Manobianco, John T.↗
NASA NTRS1985

Present and future CCDs for UV and X-ray scientific measurements

Interacting quantum efficiencies in excess of 50 percent have been demonstrated with CCDs throughout the spectral range 600-9,00 A, and comparable sensitivity is expected to continue to wavelengths as short as a few Angstroms. Nondispersive X-ray spectra throughout the 250-8000 V range have been obtained with an FWHM spectral resolution of 200-250 eV. At present, however, both spectral and spatial resolution is limited at some energies by the diffusion of photogenerated charge into more than one picture element. Progress in reducing charge diffusion is reported, with particular attention given to a theoretical diffusion model and its implications for further improvement.

Janesick, J. R.↗
NASA NTRS1991

Advanced infrared astronomy

This task supports the application of infrared heterodyne spectroscopy and other high resolution techniques, as well as infrared arrays to ultra-high resolution studies of molecular constituents of planetary atmospheres. High spectral and spatial resolution measurement and analysis of individual spectral lines permits the retrieval of distributions of atmospheric molecular abundances and temperatures and thus, information on local photochemical processes. Determination of absolute line positions to better than 10(exp -8) permits direct measurement of gas velocities to a few m/sec and thus, the study of dynamics. Observations are made from ground based observatories.

Kostiuk, Theodor↗
NASA NTRS1993

Distribution and geologic history of materials excavated by the lunar crater Bullialdus

The crater Bullialdus is a 61 km, Eratosthenian-age impact crater located on the western edge of Mare Nubium. Previous analysis of the spatial distribution of materials in the area using nine telescopic near-infrared spectra suggested a possible three-layer structure prior to the impact event: two shallow gabbroic layers and one deeper noritic layer (from a potential depth of 5.5 km). The initial interpretation of this stratigraphy was that Bullialdus may have tapped a layered mafic pluton, such as have been invoked to explain the existence of Mg-suite rocks. High-spatial resolution CCD images of Bullialdus were analyzed to better map the spatial distribution of the observed lithologies, and to assess the plausibility of the pluton interpretation.

Tompkins, Stefanie↗
NASA NTRS1994

Gradients in giant branch morphology in the core of 47 Tucanae

I describe an algorithm which uses the high spatial resolution of the Hubble Space Telescope to complement the high spatial-to-noise, approximately symmetric point response function, relatively large spatial coverage, and standard filters available from ground based images of crowded fields. Applying this technique to the central regions of the globular cluster 47 Tucanae, I find that the morphology of the giant branch in the core is significantly different from that in more distant regions (r approximately equals 5 to 10 core radii) of the cluster. In particular, there appear to be fewer bright giants in the core, along with an enhanced `asymptotic giant branch' (AGB) sequence. Depletion of giants has been observed in the cores of other dense clusters, and may be due to `stripping' of large stars by stellar encounters and/or mass transfer in binary systems. Central concentrations of true asymptotic giant branch stars are not expected to result from dynamical processes; possibly some of these stars may be evolved blue stragglers.

Bailyn, Charles D.↗
NASA NTRS1961

Infrared and Reflected Solar Radiation Measurements from the TIROS 2 Meteorological Satellite

TIROS II contains instrumentation for measuring infrared and reflected solar radiation from the earth and its atmosphere. A medium resolution scanning radiometer and a low resolution non-scanning radiometer are employed. The satellite's spin provides the scan line of the medium resolution radiometer which is then advanced by the orbital motion. The spatial resolution is about 40 miles square when the earth directly beneath the satellite is viewed. The five channels employ bolometer detectors and filters to limit the spectral responses to five bands: 6 to 6.5 microns, 8 to 12 microns, 0.2 to 6 microns, 8 to 30 microns, and 0.55 to 0.75 microns. These five bands study, respectively: radiation in the water vapor absorption band; day and nighttime cloud cover; albedo; thermal radiation; and visual maps for comparison with satellite vidicon pictures. The low resolution non-scanning radiometer measures the earth's black-body temperature and albedo. Its field when viewing directly below is a circle of 450 miles diameter, covering part of each frame from the wide-field television camera. This radiometer consists of two thermistors, each in the apex of a reflective cone which provides optical gain. One thermistor is black and responds to both thermal and reflected solar radiation. The second responds to thermal but reflects solar radiation. The design, calibration, performance, and data reduction for both systems are discussed herein.

Bandeen, W. R.↗
NASA NTRS2010

Ambiguity of Quality in Remote Sensing Data

This slide presentation reviews some of the issues in quality of remote sensing data. Data "quality" is used in several different contexts in remote sensing data, with quite different meanings. At the pixel level, quality typically refers to a quality control process exercised by the processing algorithm, not an explicit declaration of accuracy or precision. File level quality is usually a statistical summary of the pixel-level quality but is of doubtful use for scenes covering large areal extents. Quality at the dataset or product level, on the other hand, usually refers to how accurately the dataset is believed to represent the physical quantities it purports to measure. This assessment often bears but an indirect relationship at best to pixel level quality. In addition to ambiguity at different levels of granularity, ambiguity is endemic within levels. Pixel-level quality terms vary widely, as do recommendations for use of these flags. At the dataset/product level, quality for low-resolution gridded products is often extrapolated from validation campaigns using high spatial resolution swath data, a suspect practice at best. Making use of quality at all levels is complicated by the dependence on application needs. We will present examples of the various meanings of quality in remote sensing data and possible ways forward toward a more unified and usable quality framework.

Lynnes, Christopher↗
NASA NTRSDate not supplied

On the Advantages of Using Harmonized Landsat Sentinel-2 Data for Monitoring Environmental Change

NASA coordinates the Satellite Needs Working Group, dedicated to identifying, communicating, and addressing Earth observation needs of federal agencies. In 2016, the Harmonized Landsat Sentinel-2 (HLS) dataset was formulated and implemented to fulfill multiple needs. The combination of acquisitions from the Landsat and Sentinel-2 platforms results in a global dataset of surface reflectance with a temporal resolution of two days, while retaining the geometry and 30-meter spatial resolution of Landsat data. This harmonization allows for seamless integration with the 40-year archive of Landsat data. The HLS dataset is now available on the Google Earth Engine, enabling HLS utilization in various algorithms and frameworks essential for monitoring environmental change worldwide. During this presentation, we will demonstrate and discuss the advantages of using HLS data in comparison to using separate streams of Landsat and Sentinel-2 data in existing time series-based frameworks for change monitoring. Specifically, we will explore the application of HLS for continuous monitoring of deforestation using time series-based algorithms traditionally run with Landsat data. Additionally, we will showcase the benefits of HLS data for near real-time monitoring of forest disturbance in tropical regions. These examples underscore the value and utility of the HLS dataset for environmental monitoring and analysis.

Pontus Olofsson↗
NASA NTRS1984

Thematic Mapper Data Quality and Performance Assessment in Renewable Resources/agriculture Remote Sensing

It is believed that the increased spatial resolution will provide solutions to proportion estimation error due to mixed pixels, and the increased spectral resolution will provide for the identification of important agricultural features such as crop stage, and condition. The results of analyses conducted relative to these hypothesis from sample segments extracted from the 4-band Detroit scene and the 7-band Mississippi County, Arkansas engineering test scene are described. Several studies were conducted to evaluate the geometric and radiometric performance of the TM to determine data viability for the more pertinent investigations of TM utility. In most cases this requirement was more than sufficiently satisfied. This allowed the opportunity to take advantage of detailed ground observations for several of the sample segments to assess class separability and detection of other important features with TM. The results presented regarding these TM characteristics show that not only is the increased definition of the within scene variance captured by the increased spatial and spectral resolution, but that the mid-IR bands (5 and 7) are necessary for optimum crop type classification. Both qualitative and quantitative results are presented that describe the improvements gained with the TM both relative to the MSS and on its own merit.

Bizzell, R. M.↗