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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

BOREAS RS-12 Automated Ground Sunphotometer Measurements in the SSA

The BOREAS RSS-12 team collected both ground and airborne sunphotometer measurements for use in characterizing the aerosol optical properties of the atmosphere during the BOREAS data collection activities. These measurements are to be used to: 1) measure the magnitude and variability of the aerosol optical depth in both time and space; 2) determine the optical properties of the boreal aerosols; and 3) atmospherically correct some remotely sensed data acquired during BOREAS. These data cover selected days and times from May to September 1994 and were taken from one of two ground sites near Candle Lake in the SSA. The data described in this document are from the field sunphotometer data. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2005

Seasonal And Regional Differentiation Of Bio-Optical Properties Within The North Polar Atlantic

Using data collected during spring and summer seasons in the north polar Atlantic we examined the variability of the spectral absorption, a(lambda), and backscattering, b(sub b)(lambda), coefficients of surface waters and its relation to phytoplankton pigment concentration and composition. For a given chlorophyll a concentration (TChla), the concentrations of photosynthetic carotenoids (PSC), photoprotective carotenoids (PPC), and total accessory pigments (AP) were consistently lower in spring than in summer. The chlorophyll-specific absorption coefficients of phytoplankton and total particulate matter were also lower in spring, which can be partly attributed to lower proportions of PPC, PSC, and AP in spring. The spring values of the green-to-blue band ratio of the absorption coefficient were higher than the summer ratios. The blue-to-green ratios of backscattering coefficient were also higher in spring. The higher b(sub b) values and lower blue-to-green b(sub b) ratios in summer were likely associated with higher concentrations of detrital particles in summer compared to spring. Because the product of the green-to-blue absorption ratio and the blue-to-green backscattering ratio is a proxy for the blue-to-green ratio of remote-sensing reflectance, we conclude that the performance of ocean color band-ratio algorithms for estimating pigments in the north polar Atlantic is significantly affected by seasonal shifts in the relationships between absorption and TChla as well as between backscattering and TChla. Intriguingly, however, fairly good estimate of the particulate beam attenuation coefficient at 660 nm (potential measure of total particulate matter or particulate organic carbon concentration) can be obtained by applying a single blue-to-green band-ratio algorithm for both spring and summer seasons.

Stramska, Malgorzata↗
NASA NTRS1993

Backscatter Characteristics of the Winter Sea Ice Cover in the Beaufort

The microwave backscatter statistics of the sea ice cover in the winter Beaufort Sea were characterized using C-band Synthetic Aperture Radar (SAR) data collected by ERS-1. Sea ice backscatter signatures were sampled from SAR image data collected during the winter of 1991/92 and winter of 1992/93. The spatial and temporal variabilities of the backscatter signatures of different ice types are discussed. The results show considerable seasonal stability of the backscatter signature of multi-year ice as well as first-year ice. Small amplitude regional variations of the multi-year ice backscatter can be observed. Consistent contrast between multiyear ice and first-year ice is maintained throughout the season.

Kwok, R.↗
NASA NTRS2004

Sensor Web Dynamic Measurement Techniques and Adaptive Observing Strategies

Sensor Web observing systems may have the potential to significantly improve our ability to monitor, understand, and predict the evolution of rapidly evolving, transient, or variable environmental features and events. This improvement will come about by integrating novel data collection techniques, new or improved instruments, emerging communications technologies and protocols, sensor mark-up languages, and interoperable planning and scheduling systems. In contrast to today's observing systems, "event-driven" sensor webs will synthesize real- or near-real time measurements and information from other platforms and then react by reconfiguring the platforms and instruments to invoke new measurement modes and adaptive observation strategies. Similarly, "model-driven" sensor webs will utilize environmental prediction models to initiate targeted sensor measurements or to use a new observing strategy. The sensor web concept contrasts with today's data collection techniques and observing system operations concepts where independent measurements are made by remote sensing and in situ platforms that do not share, and therefore cannot act upon, potentially useful complementary sensor measurement data and platform state information. This presentation describes NASA's view of event-driven and model-driven Sensor Webs and highlights several research and development activities at the Goddard Space Flight Center.

Talabac, Stephen J.↗
NASA NTRS2015

Epidemiologic and Environmental Risk Factors of Rift Valley Fever in Southern Africa from 2008 to 2011

Background: Rift Valley fever (RVF) outbreaks have been associated with periods of widespread and above normal rainfall over several months. Knowledge on the environmental factors influencing disease transmission dynamics has provided the basis for developing models to predict RVF outbreaks in Africa. From 2008 to 2011, South Africa experienced the worst wave of RVF outbreaks in almost 40 years. We investigated rainfall associated environmental factors in southern Africa preceding these outbreaks. Methods: RVF epizootic records obtained from the World Animal Health Information Database (WAHID), documenting livestock species affected, location, and time, were analyzed. Environmental variables including rainfall and satellite-derived normalized difference vegetation index (NDVI) data were collected and assessed in outbreak regions to understand the underlying drivers of the outbreaks. Results: The predominant domestic vertebrate species affected in 2008 and 2009 were cattle, when outbreaks were concentrated in the eastern provinces of South Africa. In 2010 and 2011, outbreaks occurred in the interior and southern provinces affecting over 16,000 sheep. The highest number of cases occurred between January and April but epidemics occurred in different regions every year, moving from the northeast of South Africa toward the southwest with each progressing year. The outbreaks showed a pattern of increased rainfall preceding epizootics ranging from 9 to 152 days; however, NDVI and rainfall were less correlated with the start of the outbreaks than has been observed in eastern Africa. Conclusions: Analyses of the multiyear RVF outbreaks of 2008 to 2011 in South Africa indicated that rainfall, NDVI, and other environmental and geographical factors, such as land use, drainage, and topography, play a role in disease emergence. Current and future investigations into these factors will be able to contribute to improving spatial accuracy of models to map risk areas, allowing adequate time for preparation and prevention before an outbreak occurs.

Rift Valley Fever (RVF)↗
NASA NTRSDate not supplied

Reliability-Based Damage Tolerance Framework for Achieving Highly Reusable Launch Systems

The United States Space Force and NASA are exploring approaches that enable rapid launch response via highly reusable launch systems. One hindrance to achieving high reusability is the inability to meet damage tolerance requirements. To this end, a framework for applying reliability-based damage tolerance to space structures is presented. The reliability-based approach employs probabilistic distributions of key input variables such as material properties, geometry, loads, inspection probability, and defect characteristics to predict hardware reliability for the planned mission life. The probabilistic variables needed to perform the reliability assessments are defined and recommendations on how to collect the required data are provided. Several example problems illustrate the implementation and execution of this approach.

Leland Shimizu↗
NASA NTRS1994

Measurements of striae in CR+ doped YAG laser crystals

Striations in Czochralski (CZ) grown crystals have been observed in materials such as GaAs, silicon, photorefractive crystals used for data storage, potassium titanyl phosphate crystals and LiNbO3. Several techniques have been used for investigating these defects including electron microscopy, laser scanning tomography, selective photoetching, X-ray diffuse scattering, interference orthoscopy, laser interferometry and micro-Fourier transform infrared spectroscopy mapping. A 2mm thick sample of the material to be investigated is illuminated with light that is absorbed and non-absorbed by the ion concentration to be observed. The back surface of the sample is focused onto a solid-state image detector and images of the input beam and absorbed (and diffracted) beams are captured at two wavelengths. The variation of the coefficient of absorption asa function of distance on the sample can be derived from these measurements. A Big Sky Software Beamcode system is used to capture and display images. Software has been written to convert the Beamcode data files to a format that can be imported into a spreadsheet program such as Quatro Pro. The spreadsheet is then used to manipulate and display data. A model of the intensity map of the striae collected by the imaging system has been proposed and a data analysis procedure derived. From this, the variability of the attenuation coefficient alpha can be generated. Preliminary results show that alpha may vary by a factor of four or five over distances of 100 mu m. Potential errors and problems have been discovered and additional experiments and improvements to the experimental setup are in progress and we must now show that the measurement techniques and data analysis procedures provide 'real' information. Striae are clearly visible at all wavelengths including white light. Their basic spatial frequency does not change radically, at least when changing from blue to green to white light. Further experimental and theoretical work can be done to improve the data collection techniques and to verify the data analysis procedures.

Cady, Fredrick M.↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We investigate two related approaches to prediction of GS cloud properties from SGS variability: the critical saturation ratio method, and the critical relative humidity method. We find significant correlation between GS cloud water and SGS supersaturation when the critical saturation ratio is set at 100%, as well as a notable relationship between GS cloud water and the width of the SGS total water distribution. Critical relative humidity also compares well with GS cloud water. However, we also find that the assumptions of a static critical saturation ratio of 100% to be unrealistic, as well as a fixed SGS distribution width. Empirical calculations from the ARISE data show a large sensitivity of these SGS variables to GS relative humidity, and so a SGS parameterization allowing them to vary according to GS thermodynamic properties may result in more realistic GS cloud water values.

J. Brant Dodson↗
NASA NTRSDate not supplied

A Path to Improving Simulated Properties of Low Clouds over the Beaufort Sea using Airborne In Situ Observations of Subgrid-Scale Variability

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. One of the main reasons for this problem are the possible unrealistic assumptions that models/reanalyses make about the subgrid-scale (SGS) variability of meteorological properties, as well as the relationship between SGS variability and grid-scale (GS) cloud properties. We utilize cloud and thermodynamic data of low level (primarily) liquid clouds collected from two aircraft campaigns conducted over the Beaufort Sea to better understand and characterize this problem. Examining data from the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign and the 1998 First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE) reveals that GS cloud water variability is closely related with SGS distribution of total water (i.e. water vapor + cloud water). We examine the influence of three assumed SGS parameters on the estimation of GS cloud water: the width of the SGS PDF of total water (ΔQT), the shape of the SGS PDF, and the critical saturation ratio (Scrit), which partitions the SGS PDF into water that is available or not for conversion to cloud water. Both Scrit and ΔQT influence predicted GS cloud water strongly. ARISE and FIRE-ACE disagree somewhat in the details, but both campaigns support the possibility that more realistic representations of these two parameters may lead to more realistic GS cloud water. In particular, both parameters are sensitive to GS relative humidity, and so we examine the effects of allowing these quantities to vary as an empirically-derived linear function of GS relative humidity. In contrast, the shape of the PDF has little effect on the predicted cloud water – a surprising result that merits additional investigation.

J Brant Dodson↗
NASA NTRS1988

Thermal analysis of wildfires and effects on global ecosystem cycling

Biomass combustion plays an important role in the earth's biogeochemical cycling. The monitoring of wildfires and their associated variables at global scales is feasible and can lead to predictions of the influence of combustion on biogeochemical cycling and tropospheric chemistry. Remote sensing data collected during the 1985 California wildfire season indicate that the information content of key thermal and infrared/thermal wave band channels centered at 11.5 microns, 3.8 microns, and 2.25 microns are invaluable for discriminating and calculating fire related variables. These variables include fire intensity, rate-of-spread, soil cooling recovery behind the fire front, and plume structure. Coinciding Advanced Very High Resolution Radiometer (AVHRR) data provided information regarding temperature estimations and the movement of the smoke plume from one wildfire into the Los Angeles basin.

Ambrosia, Vincent G.↗
NASA NTRS1982

Spectral estimates of solar radiation intercepted by corn canopies

Reflectance factor data were acquired with a Landsat band radiometer throughout two growing seasons for corn (Zea mays L.) canopies differing in planting dates, populations, and soil types. Agronomic data collected included leaf area index (LAI), biomass, development stage, and final grain yields. The spectral variable, greenness, was associated with 78 percent of the variation in LAI over all treatments. Single observations of LAI or greenness have limited value in predicting corn yields. The proportions of solar radiation intercepted (SRI) by these canopies were estimated using either measured LAI or greenness. Both SRI estimates, when accumulated over the growing season, accounted for approximately 65 percent of the variation in yields. Models which simulated the daily effects of weather and intercepted solar radiation on growth had the highest correlations to grain yields. This concept of estimating intercepted solar radiation using spectral data represents a viable approach for merging spectral and meteorological data for crop yield models.

Bauer, M. E.↗
NASA NTRS1990

Further study of terrain effects on the mesoscale spectrum of atmospheric motions

Wind and temperature data collected on commercial airliners are used to investigate the effects of underlying terrain on mesoscale variability. These results expand upon those of Nastrom et al., by including all available data from the Global Atmospheric Sampling Program (GASP) and by more closely focusing on the coupling of variance with the roughness of the underlying terrain over mountainous regions. The earlier results, showing that variances are larger over mountains than over oceans or plains, with greatest increases at wavelengths below about 80 km, are confirmed. Statistical tests are used to confirm that these differences are highly significant. Over mountainous regions the roughness of the underlying terrain was parameterized from topographic data and it was found that variances are highly correlated with roughness and, in the troposphere, with background windspeed. Average variances over the roughest terrain areas range up to about ten times larger than those over the oceans. These results are found to follow the scaling with stability predicted in the framework of linenar gravity wave theory. The implications of these results for vertical transports of momentum and energy, assuming they are due to gravity waves and considering the effects of intermittency and anisotroy, are also discussed.

Jasperson, W. H.↗
NASA NTRS1993

Scintillation fading on a low elevation angle satellite path: Assessing the Austin experiment at 11.2 GHz

The University of Texas at Austin is now in its fifth year of observing an 11.2 GHz INTELSAT satellite beacon with an elevation angle of only 5.8 degrees. Measurements of the rainfall rate, beacon level, the radiometric sky temperature, and of meteorological parameters are ongoing. The experiment is motivated by the fact that significant increases in coverage can be obtained from a given geostationary orbit location if acceptable performance can be achieved at elevation angles below the current standard at Ku-Band of 10 degrees. The topics covered include the following: data collection, data processing, scintillation fading vs. rain fading, diurnal and seasonal variations, power spectrum, and variability of the beacon standard deviation.

Vogel, W. J.↗
NASA NTRS2007

Reusable, Extensible High-Level Data-Distribution Concept

A framework for high-level specification of data distributions in data-parallel application programs has been conceived. [As used here, distributions signifies means to express locality (more specifically, locations of specified pieces of data) in a computing system composed of many processor and memory components connected by a network.] Inasmuch as distributions exert a great effect on the performances of application programs, it is important that a distribution strategy be flexible, so that distributions can be adapted to the requirements of those programs. At the same time, for the sake of productivity in programming and execution, it is desirable that users be shielded from such error-prone, tedious details as those of communication and synchronization. As desired, the present framework enables a user to refine a distribution type and adjust it to optimize the performance of an application program and conceals, from the user, the low-level details of communication and synchronization. The framework provides for a reusable, extensible, data-distribution design, denoted the design pattern, that is independent of a concrete implementation. The design pattern abstracts over coding patterns that have been found to be commonly encountered in both manually and automatically generated distributed parallel programs. The following description of the present framework is necessarily oversimplified to fit within the space available for this article. Distributions are among the elements of a conceptual data-distribution machinery, some of the other elements being denoted domains, index sets, and data collections (see figure). Associated with each domain is one index set and one distribution. A distribution class interface (where "class" is used in the object-oriented-programming sense) includes operations that enable specification of the mapping of an index to a unit of locality. Thus, "Map(Index)" specifies a unit, while "LocalLayout(Index)" specifies the local address within that unit. The distribution class can be extended to enable specification of commonly used distributions or novel user-defined distributions. A data collection can be defined over a domain. The term "data collection" in this context signifies, more specifically, an abstraction of mappings from index sets to variables. Since the index set is distributed, the addresses of the variables are also distributed.

James, Mark↗
NASA NTRS2010

Changes in the Mass Balance of the Greenland Ice Sheet in a Warming Climate During 2003-2009

Mass changes of the Greenland ice sheet (GIS) derived from ICESat and GRACE data both show that the net mass loss from GIS during 2003-2009 is about 175 Gt/year, which contributes 0.5mm/yr global sea-level rise. The rate of mass loss has increased significantly since the 1990's when the GIS was close to mass balance. Even though the GIS was close to mass balance during the 1990's, it was already showing characteristics of responding to8 warmer climate, specifically thinning at the margins and thickening inland at higher elevations. During 2003-2009, increased ice thinning due to increases in melting and acceleration of outlet glaciers began to strongly exceed the inland thickening from increases in accumulation. Over the entire GIS, the mass loss between the two periods, from increased melting and ice dynamics, increased by about 190 Gt/year while the mass gain, from increased precipitation and accumulation, increased by only about 15Gt/year. These ice changes occurred during a time when the temperature on GIS changed at rate of about 2K/decade. The distribution of elevation and mass changes derived from ICESat have high spatial resolution showing details over outlet glaciers, by drainage systems, and by elevation. However, information on the seasonal cycle of changes from ICESat data is limited, because the ICESat lasers were only operated during two to three campaigns per year of about 35 days duration each. In contrast, the temporal resolution of GRACE data, provided by the continuous data collection, is much better showing details of the seasonal cycle and the inter-annual variability. The differing sensitivity of the ICESat altimetry and the GRACE gravity methods to motion of the underlying bedrock from glacial isostatic adjustment (GIA) is used to evaluate the GIA corrections provided by models. The two data types are also combined to make estimates of the partitioning of the mass gains and losses among accumulation, melting, and ice discharge from outlet glaciers.

Zwally, H. Jay↗
NASA NTRS2010

Seagrass Health Modeling and Prediction with NASA Science Data

Previous research has demonstrated that MODIS data products can be used as inputs into the seagrass productivity model developed by Fong and Harwell (1994). To further explore this use to predict seagrass productivity, Moderate Resolution Imaging Spectroradiometer (MODIS) custom data products, including Sea Surface Temperature, Light Attenuation, and Chlorophyll-a have been created for use as model parameter inputs. Coastal researchers can use these MODIS data products and model results in conjunction with historical and daily assessment of seagrass conditions to assess variables that affect the productivity of the seagrass beds. Current monitoring practices involve manual data collection (typically on a quarterly basis) and the data is often insufficient for evaluating the dynamic events that influence seagrass beds. As part of a NASA-funded research grant, the University of Mississippi, is working with researchers at NASA and Radiance Technologies to develop methods to deliver MODIS derived model output for the northern Gulf of Mexico (GOM) to coastal and environmental managers. The result of the project will be a data portal that provides access to MODIS data products and model results from the past 5 years, that includes an automated process to incorporate new data as it becomes available. All model parameters and final output will be available through the use National Oceanic and Atmospheric Administration?s (NOAA) Environmental Research Divisions Data Access Program (ERDDAP) tools as well as viewable using Thematic Realtime Environmental Distributed Data Services (THREDDS) and the Integrated Data Viewer (IDV). These tools provide the ability to create raster-based time sequences of model output and parameters as well as create graphs of model parameters versus time. This tool will provide researchers and coastal managers the ability to analyze the model inputs so that the factors influencing a change in seagrass productivity can be determined over time.

Robinson, Harold D.↗
NASA NTRS2011

Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

Frost, Susan A.↗
NASA NTRS2012

Mixed Layer Heights Derived from the NASA Langley Research Center Airborne High Spectral Resolution Lidar

The NASA airborne High Spectral Resolution Lidar (HSRL) has been deployed on board the NASA Langley Research Center's B200 aircraft to several locations in North America from 2006 to 2012 to aid in characterizing aerosol properties for over fourteen field missions. Measurements of aerosol extinction (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) during 349 science flights, many in coordination with other participating research aircraft, satellites, and ground sites, constitute a diverse data set for use in characterizing the spatial and temporal distribution of aerosols, as well as properties and variability of the Mixing Layer (ML) height. We describe the use of the HSRL data collected during these missions for computing ML heights and show how the HSRL data can be used to determine the fraction of aerosol optical thickness within and above the ML, which is important for air quality assessments. We describe the spatial and temporal variations in ML heights found in the diverse locations associated with these experiments. We also describe how the ML heights derived from HSRL have been used to help assess simulations of Planetary Boundary Layer (PBL) derived using various models, including the Weather Research and Forecasting Chemistry (WRF-Chem), NASA GEOS-5 model, and the ECMWF/MACC models.

Scarino, Amy J.↗