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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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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

A New Look at Data Usage by Using Metadata Attributes as Indicators of Data Quality

This study reviews the key metrics (users, distributed volume, and files) in multiple ways to gain an understanding of the significance of the metadata. Characterizing the usability of data by key metadata elements, such as discipline and study area, will assist in understanding how the user needs have evolved over time. The data usage pattern based on product level provides insight into the level of data quality. In addition, the data metrics by various services, such as the Open-source Project for a Network Data Access Protocol (OPeNDAP) and subsets, address how these services have extended the usage of data. Over-all, this study presents the usage of data and metadata by metrics analyses, which may assist data centers in better supporting the needs of the users.

metadata↗
NASA NTRS2016

Tropospheric Ozone Source Attribution in Southern California during Summer 2014 Based on Lidar Measurements and Model Simulations

In the past decades, significant efforts have been made to increase tropospheric ozone long-term monitoring. A large number of ground-based, airborne and space-borne instruments are currently providing valuable data to contribute to better understand tropospheric ozone budget and variability. Nonetheless, most of these instruments provide in-situ surface and column-integrated data, whereas vertically resolved measurements are still scarce. Besides ozonesondes and aircraft, lidar measurements have proven to be valuable tropospheric ozone profilers. Using the measurements from the tropospheric ozone differential absorption lidar (DIAL) located at the JPL Table Mountain Facility, California, and the GEOS-Chem and GEOS-5 model outputs, the impact of the North American monsoon on tropospheric ozone during summer 2014 is investigated. The influence of the Monsoon lightning-induced NOx will be evaluated against other sources (e.g. local anthropogenic emissions and the stratosphere) using also complementary data such as backward-trajectories analysis, coincident water vapor lidar measurements, and surface ozone in-situ measurements.

Lidar↗
NASA NTRS2017

Comparison of Two Bioinformatics Tools Used to Characterize the Microbial Diversity and Predictive Functional Attributes of Microbial Mats from Lake Obersee, Antarctica

In this study, using NextGen sequencing of the collective 16S rRNA genes obtained from two sets of samples collected from Lake Obersee, Antarctica, we compared and contrasted two bioinformatics tools, PICRUSt and Tax4Fun. We then developed an R script to assess the taxonomic and predictive functional profiles of the microbial communities within the samples. Taxa such as Pseudoxanthomonas, Planctomycetaceae, Cyanobacteria Subsection III, Nitrosomonadaceae, Leptothrix, and Rhodobacter were exclusively identified by Tax4Fun that uses SILVA database; whereas PICRUSt that uses Greengenes database uniquely identified Pirellulaceae, Gemmatimonadetes A1-B1, Pseudanabaena, Salinibacterium and Sinibacteraceae. Predictive functional profiling of the microbial communities using Tax4Fun and PICRUSt separately revealed common metabolic capabilities, while also showing specific functional IDs not shared between the two approaches. Combining these functional predictions using a customized R script revealed a more inclusive metabolic profile, such as hydrolases, oxidoreductases, transferases; enzymes involved in carbohydrate and amino acid metabolisms; and membrane transport proteins known for nutrient uptake from the surrounding environment. Our results present the first molecular-phylogenetic characterization and predictive functional profiles of the microbial mat communities in Lake Obersee, while demonstrating the efficacy of combining both the taxonomic assignment information and functional IDs using the R script created in this study for a more streamlined evaluation of predictive functional profiles of microbial communities.

Hyunmin Koo↗
NASA NTRS2018

Attribution of Flux Partitioning Variations Between Land Surface Models over the Continental U.S.

Accurate quantification of the terrestrial evapotranspiration (ET) components of plant transpiration (T), soil evaporation (E) and evaporation of the intercepted water (I) is necessary for improving our understanding of the links between the carbon and water cycles. Recent studies have noted that, among the modeled estimates, large disagreements exist in the relative contributions of T, E and I to the total ET. As these models are often used in data assimilation environments for incorporating and extending ET relevant remote sensing measurements, understanding the sources of inter-model differences in ET components is also necessary for improving the utilization of such remote sensing measurements. This study quantifies the contributions of two key factors explaining inter-model disagreements to the uncertainty in total ET: (1) contribution of the local partitioning and (2) regional distribution of ET. The analysis is conducted by using outputs from a suite of land surface models in the North American Land Data Assimilation System (NLDAS) configuration. For most of these models, transpiration is the dominant component of the ET partition. The results indicate that the uncertainty in local partitioning dominates the inter-model spread in modeled soil evaporation E. The inter-model differences in T are dominated by the uncertainty in the distribution of ET over the Eastern U.S. and the local partitioning uncertainty in the Western U.S. The results also indicate that uncertainty in the T estimates is the primary driver of total ET errors. Over the majority of the U.S., the contribution of the two factors of uncertainty to the overall uncertainty is non-trivial.

uncertainty↗
NASA NTRS2018

Attribution of Flux Partitioning Variations Between Land Surface Models Over the Continental U.S.

Accurate quantification of the terrestrial evapotranspiration (ET) components of plant transpiration (T), soil evaporation (E) and evaporation of the intercepted water (I) is necessary for improving our understanding of the links between the carbon and water cycles. Recent studies have noted that, among the modeled estimates, large disagreements exist in the relative contributions of T, E and I to the total ET. As these models are often used in data assimilation environments for incorporating and extending ET relevant remote sensing measurements, understanding the sources of inter-model differences in ET components is also necessary for improving the utilization of such remote sensing measurements. This study quantifies the contributions of two key factors explaining inter-model disagreements to the uncertainty in total ET: (1) contribution of the local partitioning and (2) regional distribution of ET. The analysis is conducted by using outputs from a suite of land surface models in the North American Land Data Assimilation System (NLDAS) configuration. For most of these models, transpiration is the dominant component of the ET partition. The results indicate that the uncertainty in local partitioning dominates the inter-model spread in modeled soil evaporation E. The inter-model differences in T are dominated by the uncertainty in the distribution of ET over the Eastern U.S. and the local partitioning uncertainty in the Western U.S. The results also indicate that uncertainty in the T estimates is the primary driver of total ET errors. Over the majority of the U.S., the contribution of the two factors of uncertainty to the overall uncertainty is non-trivial.

evapotranspiration partitioning; transpiration; so↗
NASA NTRS2019

Synthetic Aperture Radar and Optical Remote Sensing of Crop Damage Attributed to Severe Weather in the Central United States

Damaging hail and wind from severe thunderstorms threatens agricultural areas annually, especially across the central United States where agriculture is prevalent. On average, these storms produce $160 to $580 million worth of damage in the US every year and contribute significantly to food prices, crop insurance, and agricultural related stocks. However, hail damage is not regularly ground-surveyed like tornadoes. Optical (visible, NIR (Near Infra-Red), and SWIR (Short-Wave Infra-Red) remote sensing techniques have been shown to successfully identify and monitor hail damage swaths. Techniques of identification and monitoring hail damage swaths from synthetic aperture radar (SAR) are currently unexplored. We hypothesize that hail-damaged cropland will exhibit lower power return than surrounding healthy vegetation due to changes in the geometry of the targets. Further analysis is needed to determine a threshold for future automated monitoring of hail damage swaths.

Bell, Jordan↗
NASA NTRS2019

Observation and Attribution of Temperature Trends near the Stratopause from HALOE

This study considers time series of temperature versus pressure, T(p), from the Halogen Occultation Experiment (HALOE) across the stratopause region, where the effects of radiative forcings from the greenhouse gases (CO2 and H2O) and from ozone are most pronounced. Trend analyses are from 1993-2005 for HALOE T(p) values at seven levels from 3.0 to 0.3 hPa with a vertical resolution of about 4 km and for eight latitude zones from 65°S to 65°N. The HALOE trends at 2.0 hPa are of the order of -1.0 K/decade across the tropics and subtropics, but then become smaller (-0.5 K/decade) at the middle latitudes. The near-global HALOE trend profile has a minimum cooling rate of -0.2 K/decade at 1.0 hPa, although it is more negative in the southern hemisphere and slightly positive in the northern hemisphere. The combined radiative forcings from CO2, H2O, and ozone are from -0.4 to -0.6 K/decade for 1993-2005 and are hemispherically symmetric. HALOE temperature trend and total radiative cooling profiles differ from those reported from observations and calculations for 1980-2000, mainly because the ozone trends changed from clearly negative in the 1980s through mid-1990s to slightly positive during the time of HALOE. Trends for the tracer, HALOE methane (CH4), increase from 2 to 4 %/decade from 50 hPa to 10 hPa, indicating an acceleration of the Brewer/Dobson circulation. Analyses of time series of CH4 across the stratopause reveal more variability in the northern hemisphere, where wave dissipation likely contributes to the heating.

Remsberg, Ellis↗
NASA NTRSDate not supplied

Mapping the Capabilities and Attributes of Solid Oxide Electrochemical Systems to Human Spaceflight Needs

NASA is sponsoring the development of a solid oxide electrochemical oxygen separation and compression system. This system is capable of extracting oxygen from a process stream of spacecraft cabin air, and compressing it to >27,000 kPa without mechanical compressors. Process temperatures are >650C, but the materials in contact with the oxygen do not burn. The system is called eCOG-C, Electrochemical Oxygen Generator and Compressor. A system capable of producing high pressure, high purity oxygen may have application as a method of recharging space suit oxygen tanks during human exploration missions. This paper describes the key performance parameters of a space suit oxygen tank recharge system, and places the key performance parameters of eCOG-c in the context of other methods of space suit oxygen tank recharge. This paper compares the eCOG-c configuration to an earlier electrochemical oxygen generator that has been prototyped and tested. Areas of emphasis for eCOG-C development are listed and described.

John Graf↗
NASA NTRSDate not supplied

NO2 Anomalies - Economy Attribution and Rapid Climate Response

Using principal component (PC) analysis of 16 years of monthly series of NO2 from OMI/Aura, we show that it is the third PC (PC3) from the full hierarchy of principal modes that is best coupled with the economic indicators. This coupling is positive, i.e. PC3 and economic indicators manifest positive covariance. However, the economic variability can explain only 40% of the information in PC3. Furthermore, this mode by itself explains only 3% of the total deseasonalized NO2 variability. We thus conclude that, while having an unambiguous impact, the economy can be awarded at best third order of importance in driving the deseasonalized NO2 series, i.e. after seasonal variability is removed from the series. Once we identified PC3 as the NO2 mode that is coupled with economic variability, we use this mode as an indicator and look for rapid climate adjustments to that part of NO2 variability that we are confident is coupled with the economic variability. We focus on observational data from the Atmospheric Infrared Sounder (AIRS) on board of NASA Aqua satellite, decompose series of surface skin temperature and clear-sky outgoing longwave radiances (OLR) into principal components, and identify potential impacts of NO2 PC3 on these climate variables.

NO2↗
NASA NTRSDate not supplied

NO2 Anomalies - Economy Attribution and Rapid Climate Response

Using principal component (PC) analysis of 16 years of monthly series of NO2 from OMI/Aura, we show that it is the third PC (PC3) from the full hierarchy of principal modes that is best coupled with the economic indicators. This coupling is positive, i.e. PC3 and economic indicators manifest positive covariance. However, the economic variability can explain only 40%of the information in PC3. Furthermore, this mode by itself explains only 3% of the total deseasonalized NO2 variability. We thus conclude that, while having an unambiguous impact, the economy can be awarded at best third order of importance in driving the deseasonalized NO2 series, i.e. after seasonal variability is removed from the series. Once we identified PC3 as the NO2 mode that is coupled with economic variability, we use this mode as an indicator and look for rapid climate adjustments to that part of NO2 variability that we are confident is coupled with the economic variability. We focus on observational data from the Atmospheric Infrared Sounder (AIRS) on board of NASA Aqua satellite, decompose series of surface skin temperature and clear-sky outgoing longwave radiances (OLR) into principal components, and identify potential impacts of NO2 PC3 on these climate variables.

NO2↗