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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2004

The Montage architecture for grid-enabled science processing of large, distributed datasets

Montage is an Earth Science Technology Office (ESTO) Computational Technologies (CT) Round III Grand Challenge investigation to deploy a portable, compute-intensive, custom astronomical image mosaicking service for the National Virtual Observatory (NVO). Although Montage is developing a compute- and data-intensive service for the astronomy community, we are also helping to address a problem that spans both Earth and Space science, namely how to efficiently access and process multi-terabyte, distributed datasets. In both communities, the datasets are massive, and are stored in distributed archives that are, in most cases, remote from the available Computational resources. Therefore, state of the art computational grid technologies are a key element of the Montage portal architecture. This paper describes the aspects of the Montage design that are applicable to both the Earth and Space science communities.

virtual observatory↗
NASA NTRS2008

The South American Land Data Assimilation System (SALDAS) 5-Year Retrospective Atmospheric Forcing Datasets

The definition and derivation of a 5-year, 0.125deg, 3-hourly atmospheric forcing dataset for the South America continent is described which is appropriate for use in a Land Data Assimilation System and which, because of the limited surface observational networks available in this region, uses remotely sensed data merged with surface observations as the basis for the precipitation and downward shortwave radiation fields. The quality of this data set is evaluated against available surface observations. There are regional difference in the biases for all variables in the dataset, with biases in precipitation of the order 0-1 mm/day and RMSE of 5-15 mm/day, biases in surface solar radiation of the order 10 W/sq m and RMSE of 20 W/sq m, positive biases in temperature typically between 0 and 4 K, depending on region, and positive biases in specific humidity around 2-3 g/Kg in tropical regions and negative biases around 1-2 g/Kg further south.

deGoncalves, Luis Gustavo G.↗
NASA NTRS2008

How Does Mediterranean Basin's Atmosphere Become Weak Moisture Source During Negative Phase of NAO: Use of AIRS, AMSR, TOVS, & TRMM Satellite Datasets Over Last Two NAO Cycles to Examine Governing Controls on E-P

The Mediterranean Sea is a noted 'concentration" basin in that it almost continuously exhibits positive evaporation minus precipitation (E - P ) properties -- throughout the four seasons and from one year to the next. Nonetheless, according to the ECMWF Era-40 48-year (1958-2005) climate reanalysis dataset, for various phases of the North Atlantic Oscillation (NAO) when the pressure gradient between Portugal and Iceland becomes either very relaxed (large negative NAO-Index) or in transition (small positive or negative NAO-Index), the atmospheric moisture source properties of the basin become weak, at times even reversed for several months (i.e., negative E - P). This behavior poses numerous questions concerning how and why these events occur. Moreover, it begs the question of what it would take for the basin to reach its tipping point in which P would exceed E throughout the rainy season (some six months) on an annually persistent basis -- and the sea would possibly transform to a recurring "dilution" basin. This talk investigates these questions by: (1) establishing over a period from 1979 to present, based on detailed analyses of satellite retrieval products from a combination of NASA-AQUA, NOAA-LEO, NASA/JAXA Scatterometer, and NASA-TRMM platforms, plus additional specialized satellite data products and ancillary meteorological datasets, the actual observation-based behavior of E - P, (2) diagnosing the salient physical and meteorological mechanisms that lead to the weaker E - P events during the analysis period, partly based on analyzing surface and upper air data at discrete stations in the western and eastern Mediterranean -- while at the same time evaluating the quality of the ERA-40 data over this same time period, (3) conducting GCM and high-resolution regional modeling experiments to determine if perturbed but realistic meteorological background conditions could maintain Mediterranean as a "dilution" basin through the October to March rainy season on annually recurring basis, and (4) investigating how such conditions might modify important internal and external climatic processes known to be closely related to the dynamical, thermal, and hydrological properties of the basin (e.g., drought frequency over Iberian peninsula, rainfall accumulation within Sahel, alteration of Levantine branch of east-west aligned open thermohaline cell, and modification of warm-salty intermediate flow through Gibraltar straight into North Atlantic).

Smith, Eric A.↗
NASA NTRS2010

Digital Astronaut Photography: A Discovery Dataset for Archaeology

Astronaut photography acquired from the International Space Station (ISS) using commercial off-the-shelf cameras offers a freely-accessible source for high to very high resolution (4-20 m/pixel) visible-wavelength digital data of Earth. Since ISS Expedition 1 in 2000, over 373,000 images of the Earth-Moon system (including land surface, ocean, atmospheric, and lunar images) have been added to the Gateway to Astronaut Photography of Earth online database (http://eol.jsc.nasa.gov ). Handheld astronaut photographs vary in look angle, time of acquisition, solar illumination, and spatial resolution. These attributes of digital astronaut photography result from a unique combination of ISS orbital dynamics, mission operations, camera systems, and the individual skills of the astronaut. The variable nature of astronaut photography makes the dataset uniquely useful for archaeological applications in comparison with more traditional nadir-viewing multispectral datasets acquired from unmanned orbital platforms. For example, surface features such as trenches, walls, ruins, urban patterns, and vegetation clearing and regrowth patterns may be accentuated by low sun angles and oblique viewing conditions (Fig. 1). High spatial resolution digital astronaut photographs can also be used with sophisticated land cover classification and spatial analysis approaches like Object Based Image Analysis, increasing the potential for use in archaeological characterization of landscapes and specific sites.

Stefanov, William L.↗
NASA NTRS2010

A Modeling and Verification Study of Summer Precipitation Systems Using NASA Surface Initialization Datasets

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse-type convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within parameterization schemes, model resolution limitations, and uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture, soil temperature, and sea surface temperature (SST) are necessary to better simulate the interactions between the surface and atmosphere, and ultimately improve predictions of summertime pulse convection. This paper describes a sensitivity experiment using the Weather Research and Forecasting (WRF) model. Interpolated land and ocean surface fields from a large-scale model are replaced with high-resolution datasets provided by unique NASA assets in an experimental simulation: the Land Information System (LIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) SSTs. The LIS is run in an offline mode for several years at the same grid resolution as the WRF model to provide compatible land surface initial conditions in an equilibrium state. The MODIS SSTs provide detailed analyses of SSTs over the oceans and large lakes compared to current operational products. The WRF model runs initialized with the LIS+MODIS datasets result in a reduction in the overprediction of rainfall areas; however, the skill is almost equally as low in both experiments using traditional verification methodologies. Output from object-based verification within NCAR s Meteorological Evaluation Tools reveals that the WRF runs initialized with LIS+MODIS data consistently generated precipitation objects that better matched observed precipitation objects, especially at higher precipitation intensities. The LIS+MODIS runs produced on average a 4% increase in matched precipitation areas and a simultaneous 4% decrease in unmatched areas during three months of daily simulations.

Jonathan L. Case↗
NASA NTRS2011

NASA SPoRT Initialization Datasets for Local Model Runs in the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can be used to initialize local model runs within the Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). These real-time datasets consist of surface-based information updated at least once per day, and produced in a composite or gridded product that is easily incorporated into the WRF EMS. The primary goal for making these NASA datasets available to the WRF EMS community is to provide timely and high-quality information at a spatial resolution comparable to that used in the local model configurations (i.e., convection-allowing scales). The current suite of SPoRT products supported in the WRF EMS include a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Greenness Vegetation Fraction (GVF) composite, and Land Information System (LIS) gridded output. The SPoRT SST composite is a blend of primarily the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared and Advanced Microwave Scanning Radiometer for Earth Observing System data for non-precipitation coverage over the oceans at 2-km resolution. The composite includes a special lake surface temperature analysis over the Great Lakes using contributions from the Remote Sensing Systems temperature data. The Great Lakes Environmental Research Laboratory Ice Percentage product is used to create a sea-ice mask in the SPoRT SST composite. The sea-ice mask is produced daily (in-season) at 1.8-km resolution and identifies ice percentage from 0 100% in 10% increments, with values above 90% flagged as ice.

Case, Jonathan L.↗
NASA NTRS2012

Time-Series Analyses of Supergranule Characteristics Compared Between SDO/HMI, SOHO/MDI and Simulated Datasets

Supergranulation is a well-observed solar phenomenon despite its underlying mechanisms remaining a mystery. Originally considered to arise due to convective motions, alternative mechanisms have been suggested such as the cumulative downdrafts of granules as well as displaying wave-like properties. Supergranule characteristics are well documented, however. Supergranule cells are approximately 35 Mm across, have lifetimes on the order of a day and have divergent horizontal velocities of around 300 mis, a factor of 10 higher than their central radial components. While they have been observed using Doppler methods for more than half a century, their existence is also observed in other datasets such as magneto grams and Ca II K images. These datasets clearly show the influence of supergranulation on solar magnetism and how the local field is organized by the flows of supergranule cells. The Heliospheric and Magnetic Imager (HMI) aboard the Solar Dynamics Observatory (SDO) continues to produce Doppler images enabling the continuation of supergranulation studies made with SOHO/MDI, but with superior temporal and spatial resolution. The size-distribution of divergent cellular flows observed on the photosphere now reaches down to granular scales, allowing contemporaneous comparisons between the two flow components. SOHO/MDI Doppler observations made during the minima of cycles 22/23 and 23/24 exhibit fluctuations of supergranule characteristics (global averages of the supergranule size, size-range and horizontal velocity) with periods of 3-5 days. Similar fluctuations have been observed in SDO/HMI Dopplergrams and the high correlation between co-temporal HMI & MOl suggest a solar origin. Their nature has been probed by invoking data simulations that produce realistic Dopplergrams based on MOl data.

Williams, Peter E.↗
NASA NTRS2012

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provided the first coordinated intercomparison of publically available, standard global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multiangle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. A monthly, gridded database, in common format, facilitates further assessments, climate studies and the evaluation of climate models.

Stubenrauch, C. J.↗
NASA NTRS2011

Global Precipitation Measurement: Methods, Datasets and Applications

This paper reviews the many aspects of precipitation measurement that are relevant to providing an accurate global assessment of this important environmental parameter. Methods discussed include ground data, satellite estimates and numerical models. First, the methods for measuring, estimating, and modeling precipitation are discussed. Then, the most relevant datasets gathering precipitation information from those three sources are presented. The third part of the paper illustrates a number of the many applications of those measurements and databases. The aim of the paper is to organize the many links and feedbacks between precipitation measurement, estimation and modeling, indicating the uncertainties and limitations of each technique in order to identify areas requiring further attention, and to show the limits within which datasets can be used.

Global Climate Models (GCM)↗
NASA NTRS2015

Complementary Aerodynamic Performance Datasets for Variable Speed Power Turbine Blade Section from Two Independent Transonic Turbine Cascades

Two independent experimental studies were conducted in linear cascades on a scaled, two-dimensional mid-span section of a representative Variable Speed Power Turbine (VSPT) blade. The purpose of these studies was to assess the aerodynamic performance of the VSPT blade over large Reynolds number and incidence angle ranges. The influence of inlet turbulence intensity was also investigated. The tests were carried out in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility and at the University of North Dakota (UND) High Speed Compressible Flow Wind Tunnel Facility. A large database was developed by acquiring total pressure and exit angle surveys and blade loading data for ten incidence angles ranging from +15.8deg to −51.0deg. Data were acquired over six flow conditions with exit isentropic Reynolds number ranging from 0.05×106 to 2.12×106 and at exit Mach numbers of 0.72 (design) and 0.35. Flow conditions were examined within the respective facility constraints. The survey data were integrated to determine average exit total-pressure and flow angle. UND also acquired blade surface heat transfer data at two flow conditions across the entire incidence angle range aimed at quantifying transitional flow behavior on the blade. Comparisons of the aerodynamic datasets were made for three "match point" conditions. The blade loading data at the match point conditions show good agreement between the facilities. This report shows comparisons of other data and highlights the unique contributions of the two facilities. The datasets are being used to advance understanding of the aerodynamic challenges associated with maintaining efficient power turbine operation over a wide shaft-speed range.

Cascade↗
NASA NTRS2015

Complementary Aerodynamic Performance Datasets for Variable Speed Power Turbine Blade Section from Two Independent Transonic Turbine Cascades

Two independent experimental studies were conducted in linear cascades on a scaled, two-dimensional mid-span section of a representative Variable Speed Power Turbine (VSPT) blade. The purpose of these studies was to assess the aerodynamic performance of the VSPT blade over large Reynolds number and incidence angle ranges. The influence of inlet turbulence intensity was also investigated. The tests were carried out in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility and at the University of North Dakota (UND) High Speed Compressible Flow Wind Tunnel Facility. A large database was developed by acquiring total pressure and exit angle surveys and blade loading data for ten incidence angles ranging from +15.8deg to −51.0deg. Data were acquired over six flow conditions with exit isentropic Reynolds number ranging from 0.05×106 to 2.12×106 and at exit Mach numbers of 0.72 (design) and 0.35. Flow conditions were examined within the respective facility constraints. The survey data were integrated to determine average exit total-pressure and flow angle. UND also acquired blade surface heat transfer data at two flow conditions across the entire incidence angle range aimed at quantifying transitional flow behavior on the blade. Comparisons of the aerodynamic datasets were made for three "match point" conditions. The blade loading data at the match point conditions show good agreement between the facilities. This report shows comparisons of other data and highlights the unique contributions of the two facilities. The datasets are being used to advance understanding of the aerodynamic challenges associated with maintaining efficient power turbine operation over a wide shaft-speed range.

Turbine↗
NASA NTRS2014

Fixing Dataset Search

Three current search engines are queried for ozone data at the GES DISC. The results range from sub-optimal to counter-intuitive. We propose a method to fix dataset search by implementing a robust relevancy ranking scheme. The relevancy ranking scheme is based on several heuristics culled from more than 20 years of helping users select datasets.

science data↗
NASA NTRS2017

New-Generation NASA Aura Ozone Monitoring Instrument (OMI) Volcanic SO2 Dataset: Algorithm Description, Initial Results, and Continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)

Since the fall of 2004, the Ozone Monitoring Instrument (OMI) has been providing global monitoring of volcanic SO2 emissions, helping to understand their climate impacts and to mitigate aviation hazards. Here we introduce a new-generation OMI volcanic SO2 dataset based on a principal component analysis (PCA) retrieval technique. To reduce retrieval noise and artifacts as seen in the current operational linear fit (LF) algorithm, the new algorithm, OMSO2VOLCANO, uses characteristic features extracted directly from OMI radiances in the spectral fitting, thereby helping to minimize interferences from various geophysical processes (e.g., O3 absorption) and measurement details (e.g., wavelength shift). To solve the problem of low bias for large SO2 total columns in the LF product, the OMSO2VOLCANO algorithm employs a table lookup approach to estimate SO2 Jacobians (i.e., the instrument sensitivity to a perturbation in the SO2 column amount) and iteratively adjusts the spectral fitting window to exclude shorter wavelengths where the SO2 absorption signals are saturated. To first order, the effects of clouds and aerosols are accounted for using a simple Lambertian equivalent reflectivity approach. As with the LF algorithm, OMSO2VOLCANO provides total column retrievals based on a set of predefined SO2 profiles from the lower troposphere to the lower stratosphere, including a new profile peaked at 13 km for plumes in the upper troposphere. Examples given in this study indicate that the new dataset shows significant improvement over the LF product, with at least 50% reduction in retrieval noise over the remote Pacific. For large eruptions such as Kasatochi in 2008 (approximately 1700 kt total SO2/ and Sierra Negra in 2005 (greater than 1100DU maximum SO2), OMSO2VOLCANO generally agrees well with other algorithms that also utilize the full spectral content of satellite measurements, while the LF algorithm tends to underestimate SO2. We also demonstrate that, despite the coarser spatial and spectral resolution of the Suomi National Polar-orbiting Partnership (Suomi-NPP) Ozone Mapping and Profiler Suite (OMPS) instrument, application of the new PCA algorithm to OMPS data produces highly consistent retrievals between OMI and OMPS. The new PCA algorithm is therefore capable of continuing the volcanic SO2 data record well into the future using current and future hyperspectral UV satellite instruments.

OMI↗
NASA NTRS2019

NASA Dataset Interoperability Recommendations for Earth Science

NASA ESDS (Earth Science Data and Information System) Dataset Interoperability Working Group has been developing recommendations since 2012 aimed at improving interoperability of EOS (Earth Observing System) datasets. The first set of recommendations were published in 2016 as ESDS RFC-028. The latest set of recommendations is currently undergoing review and will be available as ESDS RFC-036 soon.This talk will inform the ESIP (Earth Science Information Partners) community about the recommendations because their application is relevant to other data producers as well.

Jelenak, Aleksandar↗
NASA NTRS2019

Alternative Datasets for Identification of Earth Science Events and Data

Alternative, or non-traditional, data sources can be used to generate datasets which can in turn be analyzed for temporal, spatial and climatological patterns. Events and case studies inferred from the analysis of these patterns can be used by the remote sensing community to more effectively search for Earth observation data. In this paper, we present a new alternative Earth science dataset created from the National Weather Service’s Area Forecast Discussion (AFD) documents. We then present an exploratory methodology for identifying interesting climatological patterns within the AFD data and a corresponding motivating example as to how these data and patterns can be used to search for relevant events or case studies.

Alternative data↗
NASA NTRS2019

Alternative Datasets for Identification of Earth Science Events and Data

Alternative, or non-traditional, data sources can be used to generate datasets which can in turn be analyzed for temporal, spatial and climatological patterns. Events and case studies inferred from the analysis of these patterns can be used by the remote sensing community to more effectively search for Earth observation data. In this paper, we present a new alternative Earth science dataset created from the National Weather Service’s Area Forecast Discussion (AFD) documents. We then present an exploratory methodology for identifying interesting climatological patterns within the AFD data and a corresponding motivating example as to how these data and patterns can be used to search for relevant events or case studies.

Bugbee, Kaylin↗
NASA NTRS2019

Dataset Documentation FROST: Features Relevant to Ocean Worlds Surface Terrain

We present an analog dataset that provides examples of possible terrain features, geometry, and appearance at the 1-10cm scale on ocean worlds/icy moons such as Europa, Enceladus, and Pluto. The motivation for collecting this dataset was a lack of available high-resolution digital models suitable for development of surface missions to these bodies, including use for simulation of mechanics, sampling, and imaging. NASA field opportunities to Death Valley, California and the Atacama Desert, Chile were leveraged in order to observe and record analog sites.

Wong, Uland↗
NASA NTRS2020

Precision Assessment of the HPLC Phytoplankton Pigment Dataset Analyzed by NASA to Quantify Global Variability in Support of Ocean Color Remote Sensing

The ability to generate chlorophyll a (Chl a) assessments from ocean color orbital sensors, such as VIIRS and MODIS, that satisfy the requirements to be climate-quality data record (CDR) quality is contingent in part on the quality of the in situ ground or sea truth observations that serve as datasets for vicarious calibration and algorithm validation activities. NASA has a mandate to collect, analyze, and distribute in situ data of the highest possible quality with documented uncertainties and in keeping with established performance metrics. Using a dataset of over 18,000 HPLC phytoplankton pigment samples representing water collected in all major ocean basins analyzed a central laboratory (Field Support Group (FSG) of the Ocean Ecology Laboratory (OEL) at NASA Goddard Space Flight Center (GSFC)), we performed an assessment of the global precision among sample replicates of Chl a as well as major accessory pigments. We investigated the impacts of filtration volume, water basin, collection technique, pigment concentration, and different filtration volumes for replicate filters on replicate filter precision, as well as investigating any pigment-specific differences. Our results quantify sample variability with the goal of understanding any systemic biases or biogeographic influences.

Thomas, Crystal S.↗