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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Analysis of Ultra High Resolution Sea Surface Temperature Level 4 Datasets

Sea surface temperature (SST) studies are often focused on improving accuracy, or understanding and quantifying uncertainties in the measurement, as SST is a leading indicator of climate change and represents the longest time series of any ocean variable observed from space. Over the past several decades SST has been studied with the use of satellite data. This allows a larger area to be studied with much more frequent measurements being taken than direct measurements collected aboard ship or buoys. The Group for High Resolution Sea Surface Temperature (GHRSST) is an international project that distributes satellite derived sea surface temperatures (SST) data from multiple platforms and sensors. The goal of the project is to distribute these SSTs for operational uses such as ocean model assimilation and decision support applications, as well as support fundamental SST research and climate studies. Examples of near real time applications include hurricane and fisheries studies and numerical weather forecasting. The JPL group has produced a new 1 km daily global Level 4 SST product, the Multiscale Ultrahigh Resolution (MUR), that blends SST data from 3 distinct NASA radiometers: the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Very High Resolution Radiometer (AVHRR), and the Advanced Microwave Scanning Radiometer ? Earth Observing System(AMSRE). This new product requires further validation and accuracy assessment, especially in coastal regions.We examined the accuracy of the new MUR SST product by comparing the high resolution version and a lower resolution version that has been smoothed to 19 km (but still gridded to 1 km). Both versions were compared to the same data set of in situ buoy temperature measurements with a focus on study regions of the oceans surrounding North and Central America as well as two smaller regions around the Gulf Stream and California coast. Ocean fronts exhibit high temperature gradients (Roden, 1976), and thus satellite data of SST can be used in the detection of these fronts. In this case, accuracy is less of a concern because the primary focus is on the spatial derivative of SST. We calculated the gradients for both versions of the MUR data set and did statistical comparisons focusing on the same regions.

sea surface temperature SST)↗
NASA NTRS2011

Producing Science-Ready Radar Datasets for the Retrieval of Forest Structure Parameters from Backscatter: Correcting for Terrain Topography and Changes in Vegetation Reflectivity

Radar backscatter data contain both geometric and radiometric distortions due to underlying topography and the radar viewing geometry. Our objective is to develop a radiometric correction algorithm specific to the UAVSAR system configuration that would improve retrieval of forest structure parameters. UAVSAR is an airborne Lband radar capable of repeat?pass interferometry producing images with a spatial resolution of 5m. It is characterized by an electronically steerable antenna to compensate for aircraft attitude. Thus, the computation of viewing angles (i.e. look, incidence and projection) must include aircraft attitude angles (i.e. yaw, pitch and roll) in addition to the antenna steering angle. In this presentation, we address two components of radiometric correction: area projection and vegetation reflectivity. The first correction is applied by normalization of the radar backscatter by the local ground area illuminated by the radar beam. The second is a correction due to changes in vegetation reflectivity with viewing geometry.

polarimetry↗
NASA NTRS2016

Compiling a Comprehensive EVA Training Dataset for NASA Astronauts

Training for a spacewalk or extravehicular activity (EVA) is considered hazardous duty for NASA astronauts. This activity places astronauts at risk for decompression sickness as well as various musculoskeletal disorders from working in the spacesuit. As a result, the operational and research communities over the years have requested access to EVA training data to supplement their studies.

Laughlin, M. S.↗
NASA NTRS2015

Managing Large Datasets for Atmospheric Research

Since the mid-1980s, airborne and ground measurements have been widely used to provide comprehensive characterization of atmospheric composition and processes. Field campaigns have generated a wealth of insitu data and have grown considerably over the years in terms of both the number of measured parameters and the data volume. This can largely be attributed to the rapid advances in instrument development and computing power. The users of field data may face a number of challenges spanning data access, understanding, and proper use in scientific analysis. This tutorial is designed to provide an introduction to using data sets, with a focus on airborne measurements, for atmospheric research. The first part of the tutorial provides an overview of airborne measurements and data discovery. This will be followed by a discussion on the understanding of airborne data files. An actual data file will be used to illustrate how data are reported, including the use of data flags to indicate missing data and limits of detection. Retrieving information from the file header will be discussed, which is essential to properly interpreting the data. Field measurements are typically reported as a function of sampling time, but different instruments often have different sampling intervals. To create a combined data set, the data merge process (interpolation of all data to a common time base) will be discussed in terms of the algorithm, data merge products available from airborne studies, and their application in research. Statistical treatment of missing data and data flagged for limit of detection will also be covered in this section. These basic data processing techniques are applicable to both airborne and ground-based observational data sets. Finally, the recently developed Toolsets for Airborne Data (TAD) will be introduced. TAD (tad.larc.nasa.gov) is an airborne data portal offering tools to create user defined merged data products with the capability to provide descriptive statistics and the option to treat measurement uncertainty.

Chen, Gao↗
NASA NTRS2016

Earth Science Data Analytics: Bridging Tools and Techniques with the Co-Analysis of Large, Heterogeneous Datasets

The continuum of ever-evolving data management systems affords great opportunities to the enhancement of knowledge and facilitation of science research. To take advantage of these opportunities, it is essential to understand and develop methods that enable data relationships to be examined and the information to be manipulated. This presentation describes the efforts of the Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster to understand, define, and facilitate the implementation of ESDA to advance science research. As a result of the void of Earth science data analytics publication material, the cluster has defined ESDA along with 10 goals to set the framework for a common understanding of tools and techniques that are available and still needed to support ESDA.

science data analysis↗
NASA NTRS2017

Lunar Meteorites: A Global Geochemical Dataset

To date, the world's meteorite collections contain over 260 lunar meteorite stones representing at least 120 different lunar meteorites. Additionally, there are 20-30 as yet unnamed stones currently in the process of being classified. Collectively these lunar meteorites likely represent 40-50 distinct sampling locations from random locations on the Moon. Although the exact provenance of each individual lunar meteorite is unknown, collectively the lunar meteorites represent the best global average of the lunar crust. The Apollo sites are all within or near the Procellarum KREEP Terrane (PKT), thus lithologies from the PKT are overrepresented in the Apollo sample suite. Nearly all of the lithologies present in the Apollo sample suite are found within the lunar meteorites (high-Ti basalts are a notable exception), and the lunar meteorites contain several lithologies not present in the Apollo sample suite (e.g., magnesian anorthosite). This chapter will not be a sample-by-sample summary of each individual lunar meteorite. Rather, the chapter will summarize the different types of lunar meteorites and their relative abundances, comparing and contrasting the lunar meteorite sample suite with the Apollo sample suite. This chapter will act as one of the introductory chapters to the volume, introducing lunar samples in general and setting the stage for more detailed discussions in later more specialized chapters. The chapter will begin with a description of how lunar meteorites are ejected from the Moon, how deep samples are being excavated from, what the likely pairing relationships are among the lunar meteorite samples, and how the lunar meteorites can help to constrain the impactor flux in the inner solar system. There will be a discussion of the biases inherent to the lunar meteorite sample suite in terms of underrepresented lithologies or regions of the Moon, and an examination of the contamination and limitations of lunar meteorites due to terrestrial weathering. The bulk of the chapter will use examples from the lunar meteorite suite to examine important recent advances in lunar science, including (but not limited to the following: (1) Understanding the global compositional diversity of the lunar surface; (2) Understanding the formation of the ancient lunar primary crust; (3) Understanding the diversity and timing of mantle melting, and secondary crust formation; (4) Comparing KREEPy lunar meteorites to KREEPy Apollo samples as evidence of variability within the PKT; and (5) A better understanding of the South Pole Aitken Basin through lunar meteorites whose provenance are within that Terrane.

Zeigler, R. A.↗
NASA NTRS2016

Tracking and Establishing Provenance of Earth Science Datasets: A NASA-based Example

Information quality is of paramount importance to science. Accurate, scientifically vetted and statistically meaningful and, ideally, reproducible information engenders scientific trust and research opportunities. Therefore, so-called Highly Influential Scientific Assessments (HISA) such as the U.S. Third National Climate Assessment undergo a very rigorous process to ensure transparency and credibility. As an activity to support the transparency of such reports, the U.S. Global Change Research Program has developed the Global Change Information System (GCIS). Specifically related to the transparency of NCA3, a recent activity was carried out to trace the provenance as completely as possible for all figures in the NCA3 report that predominantly used NASA data. This paper discusses lessons learned from this activity that trace the provenance of NASA figures in a major HISA-class pdf report.

Ramapriyan, Hampapuram K.↗
NASA NTRS2016

Tracking and Establishing Provenance of Earth Science Datasets: A NASA-Based Example

Information quality is of paramount importance to science. Accurate, scientifically vetted and statistically meaningful and, ideally, reproducible information engenders scientific trust and research opportunities. Not surprisingly, federal bodies (e.g., NASA, NOAA, USGS) have very strictly affirmed the importance of information quality in their product requirements. So-called Highly Influential Scientific Assessments (HISA) such as The Third US National Climate Assessment (NCA3) published in 2014 undergo a very rigorous review process to ensure transparency and credibility. To support the transparency of such reports, the U.S. Global Change Research Program (USGCRP) has developed the Global Change Information System (GCIS). A recent activity was performed to trace the provenance as completely as possible for all NCA3 figures that were predominantly based on NASA data. This poster presents the mechanics of that project and the lessons learned from that activity.

Ramapriyan, Hampapuram K.↗
NASA NTRS2017

Systemic Response to Microgravity: Utilizing GeneLab Datasets to Identify Molecular Targets for Future Hypotheses-Driven Spaceflight Studies

Biological risks associated with microgravity are a major concern for long-term space travel. Although determination of risk has been a focus for NASA research, data examining systemic (i.e., multi- or pan-tissue) responses to space flight are sparse. To perform our analysis, we utilized the NASA GeneLab database which is a publicly available repository containing a wide array of omics results from experiments conducted with: i) with different flight conditions (space shuttle (STS) missions vs. International Space Station (ISS); ii) a variety of tissues; and 3) assays that measure epigenetic, transcriptional, and protein expression changes. Meta-analysis of the transcriptomic data from 7 different murine and rat data sets, examining tissues such as liver, kidney, adrenal gland, thymus, mammary gland, skin, and skeletal muscle (soleus, extensor digitorum longus, tibialis anterior, quadriceps, and gastrocnemius) revealed for the first time, the existence of potential master regulators coordinating systemic responses to microgravity in rodents. We identified p53, TGF(beta)1 and immune related pathways as the highly prevalent pan-tissue signaling pathways that are affected by microgravity. Some variability in the degree of change in their expression across species, strain and time of flight was also observed. Interestingly, while certain skeletal muscle (gastrocnemius and soleus) exhibited an overall down-regulation of these genes, some other muscle types such as the extensor digitorum longus, tibialis anterior and quadriceps, showed an up-regulated expression, indicative of potential compensatory mechanisms to prevent microgravity-induced atrophy. Key genes isolated by unbiased systems analyses displayed a major overlap between tissue types and flight conditions and established TGF(beta)1 to be the most connected gene across all data sets. Finally, a set of microgravity responsive miRNA signature was identified and based on their predicted functional state and subsequent impact on health, a theoretical health risk score was calculated. The genes and miRNAs identified from our analyses can be targeted for future research involving efficient countermeasure design. Our study thus exemplifies the utility of GeneLab data repository to aid in the process of performing novel hypothesis based spaceflight research aimed at elucidating the global impact of environmental stressors at multiple biological scales.

GeneLab↗