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At least 343 records · Page 19

A study of the feasibility of using sea and wind information from the ERS-1 satellite. Part 1: Wind scatterometer data

The use of scatterometer and altimeter data in wind and wave assimilation, and the benefits this offers for quality assurance and validation of ERS-1 data were examined. Real time use of ERS-1 data was simulated through assimilation of Seasat scatterometer data. The potential for quality assurance and validation is demonstrated by documenting a series of substantial problems with the scatterometer data, which are known but took years to establish, or are new. A data impact study, and an analysis of the performance of ambiguity removal algorithms on real and simulated data were conducted. The impact of the data on analyses and forecasts is large in the Southern Hemisphere, generally small in the Northern Hemisphere, and occasionally large in the Tropics. Tests with simulated data give more optimistic results than tests with real data. Errors in ambiguity removal results occur in clusters. The probabilities which can be calculated for the ambiguous wind directions on ERS-1 contain more information than is given by a simple ranking of the directions.

Anderson, D.↗

A Review of Magnetic Anomaly Field Data for the Arctic Region: Geological Implications

Due to its inaccessibility and hostile physical environment remote sensing data, both airborne and satellite measurements, has been the main source of geopotential data over the entire Arctic region. Ubiquitous and significant external fields, however, hinder crustal magnetic field studies. These potential field data have been used to derive tectonic models for the two major tectonic sectors of this region, the Amerasian and Eurasian Basins. The latter is dominated by the Nansen-Gakkel or Mid-Arctic Ocean Ridge and is relatively well known. The origin and nature of the Alpha and Mendeleev Ridges, Chukchi Borderland and Canada Basin of the former are less well known and a subject of controversy. The Lomonosov Ridge divides these large provinces. In this report we will present a summary of the Arctic geopotential anomaly data derived from various sources by various groups in North America and Europe and show how these data help us unravel the last remaining major puzzle of the global plate tectonic framework. While Magnetic anomaly data represent the main focus of this study recently derived satellite gravity data (Laxon and McAdoo, 1998) are playing a major role in Arctic studies.

Taylor, Patrick T.↗

A Review of Magnetic Anomaly Field Data for the Arctic Region: Geological Implications

Due to its inaccessibility and hostile physical environment remote sensing data, both airborne and satellite measurements, has been the main source of geopotential data over the entire Arctic region. Ubiquitous and significant external fields, however, hinder crustal magnetic field studies These potential field data have been used to derive tectonic models for the two major tectonic sectors of this region, the Amerasian and Eurasian Basins. The latter is dominated by the Nansen-Gakkel or Mid-Arctic Ocean Ridge and is relatively well known. The origin and nature of the Alpha and Mendeleev Ridges, Chukchi Borderland and Canada Basin of the former are less well known and a subject of controversy. The Lomonosov Ridge divides these large provinces. In this report we will present a summary of the Arctic geopotential anomaly data derived from various sources by various groups in North America and Europe and show how these data help us unravel the last remaining major puzzle of the global plate tectonic framework. While magnetic anomaly data represent the main focus of this study recently derived satellite gravity data are playing a major role in Arctic studies.

Taylor, Patrick T.↗

Estimating the National Carbon Abatement Potential of City Policies: A Data- Driven Approach

Cities are increasingly taking actions such as building code enforcement, urban planning, and public transit expansion to reduce emissions of carbon dioxide in their communities and municipal operations. However, many cities lack the quantitative information needed to estimate policy impacts and prioritize city actions in terms of carbon abatement potential and cost effectiveness. This report fills this research gap by providing methodologies to assess the carbon abatement potential of a variety of city actions. The methodologies are applied to an energy use data set of 23,458 cities compiled for the U.S. Department of Energy’s City Energy Profile tool. The analysis estimates the national carbon abatement potential of the most commonly implemented actions in six specific policy areas. The results of this analysis suggest that, in aggregate, cities could reduce nationwide carbon emissions by about 210 million metric tons of carbon dioxide (MMT CO 2 ) per year in a "moderate abatement scenario" by 2035 and 480 MMT CO 2 /year in a "high abatement scenario" by 2035 through these common actions typically within a city’s control in the six policy areas. The aggregate carbon abatement potential of these specific areas equates to a reduction of 3%-7% relative to 2013 U.S. emissions. At the city level, the results suggest the average city could reduce carbon emissions by 7% (moderate) to 19% (high) relative to current city-level emissions. City carbon abatement potential is sensitive to national and state policies that affect the carbon intensity of electricity and transportation. Specifically, the U.S. Clean Power Plan and further renewable energy cost reductions could reduce city carbon emissions overall, helping cities achieve their carbon reduction goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A multi-criteria CCUS screening evaluation of the Gulf of Mexico, USA

Continued research into reservoir characterization along with offshore carbon dioxide (CO 2 ) transportation and infrastructure assets is needed to facilitate development of safe and successful carbon capture, utilization, and storage (CCUS) projects. This paper outlines a multi-criteria evaluation methodology that incorporates disparate sets of quantitative, spatially variable data into a decision-making framework for screening the Gulf of Mexico (GOM) outer continental shelf (OCS) for potentially viable CO 2 storage and enhanced oil recovery (EOR) sites. Criteria categories include favorable geologic characteristics, logistics, and potential risks. Data compiled for 14 criteria from several publicly available geographic information system (GIS) layers was aggregated over 2559 spatially balanced points across the study area using the National Energy Technology Laboratory (NETL)-developed Cumulative Spatial Impact Layers™ (CSIL) GIS tool. Criteria are weighted by qualitative expert opinion relative to their perceived importance to given scenarios— the output of combined criteria values and weights enables regional CO 2 storage suitability differentiation. The methodology considers both technical and non-technical factors impacting CCUS decision-making. The flexible methodology enables a systematic approach to regional ranking at high spatial resolution over a large study domain. Additionally, the framework enables high-grading of priority sites that warrant further characterization and follow-on analysis. Areas along the Louisiana coast and Mississippi River Delta consistently rank high for all scenarios largely a result of the favorable geology with the potential for stacked storage, as well as the density of existing pipelines and platforms, and proximity to several onshore CO 2 sources. High-graded regions for the CO 2 EOR-related scenarios are typically located further offshore towards the middle and edge of the OCS compared to higher priority regions for the geologic storage scenarios which fall closer to the Louisiana coastline.

54 ENVIRONMENTAL SCIENCES↗

Spherical earth gravity and magnetic anomaly analysis by equivalent point source inversion

To facilitate geologic interpretation of satellite elevation potential field data, analysis techniques are developed and verified in the spherical domain that are commensurate with conventional flat earth methods of potential field interpretation. A powerful approach to the spherical earth problem relates potential field anomalies to a distribution of equivalent point sources by least squares matrix inversion. Linear transformations of the equivalent source field lead to corresponding geoidal anomalies, pseudo-anomalies, vector anomaly components, spatial derivatives, continuations, and differential magnetic pole reductions. A number of examples using 1 deg-averaged surface free-air gravity anomalies of POGO satellite magnetometer data for the United States, Mexico, and Central America illustrate the capabilities of the method.

Von Frese, R. R. B.↗

Atmospheric Characterization of the US Offshore Sites and Impact on Turbine Performance

Reliable, long term offshore atmospheric data is critical to development of the US offshore wind industry. There exists significant lack of meteorological, oceanographic, and geological data at potential US offshore sites1. Assessment of wind resources at heights in the range of 25-200m is needed to understand and characterize offshore wind turbine performance. Data from the US Department of Energy owned WindSentinel buoy from two US offshore sites and one European site is analyzed. Low Level Jet (LLJ) phenomena and its potential impact on the performance of an offshore wind turbine is investigated.

offshore atmospheric data, meteorological, oceanog↗

Atmospheric Characterization of the US Offshore Sites and Impact on Turbine Performance (Poster)

Reliable, long term offshore atmospheric data is critical to development of the US offshore wind industry. There exists significant lack of meteorological, oceanographic, and geological data at potential US offshore sites. Assessment of wind resources at heights in the range of 25-200m is needed to understand and characterize offshore wind turbine performance. Data from the US Department of Energy owned WindSentinel buoy from two US offshore sites and one European site is analyzed. Low Level Jet (LLJ) phenomena and its potential impact on the performance of an offshore wind turbine is investigated.

17 WIND ENERGY↗

favela3/Maize.N-cycle.Function

Supplemental sequence processing and R statistical analysis for publication which compares the microbiome of 27 Zea cultivars: 12 Inbred maize genotypes, 9 hybrids, and 6 wild teosinte. The project contains amplicon data for various genes: 16S rRNA, ITS, bacterial amoA, Archeal amoA, nirS, nirK, and nosZ. In addition to functional potential assay data, and N2O flux.

Favela, Alonso↗

Theoretical modelling and meteorological analysis for the AASE mission

Providing real time constituent data analysis and potential vorticity computations in support of the Airborne Arctic Stratospheric Experiment (AASE) is discussed. National Meteorological Center (NMC) meteorological data and potential vorticity computations derived from NMC data are projected onto aircraft coordinates and provided to the investigators in real time. Balloon and satellite constituent data are composited into modified Lagrangian mean coordinates. Various measurements are intercompared, trends deduced and reconstructions of constituent fields performed.

Schoeberl, Mark R.↗

Software Development to Assist in the Processing and Analysis of Data Obtained Using Fiber Bragg Grating Interrogation Systems

A fiber Bragg grating is a portion of a core of a fiber optic stand that has been treated to affect the way light travels through the strand. Light within a certain narrow range of wavelengths will be reflected along the fiber by the grating, while light outside that range will pass through the grating mostly undisturbed. Since the range of wavelengths that can penetrate the grating depends on the grating itself as well as temperature and mechanical strain, fiber Bragg gratings can be used as temperature and strain sensors. This capability, along with the light-weight nature of the fiber optic strands in which the gratings reside, make fiber optic sensors an ideal candidate for flight testing and monitoring in which temperature and wing strain are factors. A team of NASA Dryden engineers has been working to advance the fiber optic sensor technology since the mid 1990 s. The team has been able to improve the dependability and sample rate of fiber optic sensor systems, making them more suitable for real-time wing shape and strain monitoring and capable of rivaling traditional strain gauge sensors in accuracy. The sensor system was recently tested on the Ikhana unmanned aircraft and will be used on the Global Observer unmanned aircraft. Since a fiber Bragg grating sensor can be placed every halfinch on each optic fiber, and since fibers of approximately 40 feet in length each are to be used on the Global Observer, each of these fibers will have approximately 1,000 sensors. A total of 32 fibers are to be placed on the Global Observer aircraft, to be sampled at a rate of about 50 Hz, meaning about 1.6 million data points will be taken every second. The fiber optic sensors system is capable of producing massive amounts of potentially useful data; however, methods to capture, record, and analyze all of this data in a way that makes the information useful to flight test engineers are currently limited. The purpose of this project is to research the availability of software capable of processing massive amounts of data in both real-time and post-flight settings, and to produce software segments that can be integrated to assist in the task as well. The selected software must be able to: (1) process massive amounts of data (up to 4GB) at a speed useful in a real-time settings (small fractions of a second); (2) process data in post-flight settings to allow test reproduction or further data analysis, inclusive; (3) produce, or make easier to produce, three-dimensional plots/graphs to make the data accessible to flight test engineers; and (4) be customized to allow users to use their own processing formulas or functions and display the data in formats they prefer. Several software programs were evaluated to determine their utility in completing the research objectives. These programs include: OriginLab, Graphis, 3D Grapher, Visualization Sciences Group (VSG) Avizo Wind, Interactive Analysis and Display System (IADS), SigmaPlot, and MATLAB.

Hicks, Rebecca↗

Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study

Highlights: • Earth observation data has potential for use in epidemiology but is seldom validated. • The performance of two EO products varied depending on numerous factors. • Epidemiologists should use their own weather stations to record meteorological data. • Daily estimates of meteorological variables are associated with rotavirus infection. • Choice of climate data source should be determined by the research question. Longitudinal and time series analyses are needed to characterize the associations between hydrometeorological parameters and health outcomes. Earth Observation (EO) climate data products derived from satellites and global model-based reanalysis have the potential to be used as surrogates in situations and locations where weather-station based observations are inadequate or incomplete. However, these products often lack direct evaluation at specific sites of epidemiological interest.

54 ENVIRONMENTAL SCIENCES↗

Program Instrumentation and Trace Analysis

Several attempts have been made recently to apply techniques such as model checking and theorem proving to the analysis of programs. This shall be seen as a current trend to analyze real software systems instead of just their designs. This includes our own effort to develop a model checker for Java, the Java PathFinder 1, one of the very first of its kind in 1998. However, model checking cannot handle very large programs without some kind of abstraction of the program. This paper describes a complementary scalable technique to handle such large programs. Our interest is turned on the observation part of the equation: How much information can be extracted about a program from observing a single execution trace? It is our intention to develop a technology that can be applied automatically and to large full-size applications, with minimal modification to the code. We present a tool, Java PathExplorer (JPaX), for exploring execution traces of Java programs. The tool prioritizes scalability for completeness, and is directed towards detecting errors in programs, not to prove correctness. One core element in JPaX is an instrumentation package that allows to instrument Java byte code files to log various events when executed. The instrumentation is driven by a user provided script that specifies what information to log. Examples of instructions that such a script can contain are: 'report name and arguments of all called methods defined in class C, together with a timestamp'; 'report all updates to all variables'; and 'report all acquisitions and releases of locks'. In more complex instructions one can specify that certain expressions should be evaluated and even that certain code should be executed under various conditions. The instrumentation package can hence be seen as implementing Aspect Oriented Programming for Java in the sense that one can add functionality to a Java program without explicitly changing the code of the original program, but one rather writes an aspect and compiles it into the original program using the instrumentation. Another core element of JPaX is an observation package that supports the analysis of the generated event stream. Two kinds of analysis are currently supported. In temporal analysis the execution trace is evaluated against formulae written in temporal logic. We have implemented a temporal logic evaluator on finite traces using the Maude rewriting system from SRI International, USA. Temporal logic is defined in Maude by giving its syntax as a signature and its semantics as rewrite equations. The resulting semantics is extremely efficient and can handle event streams of hundreds of millions events in few minutes. Furthermore, the implementation is very succinct. The second form of even stream analysis supported is error pattern analysis where an execution trace is analyzed using various error detection algorithms that can identify error-prone programming practices that may potentially lead to errors in some different executions. Two such algorithms focusing on concurrency errors have been implemented in JPaX, one for deadlocks and the other for data races. It is important to note, that a deadlock or data race potential does not need to occur in order for its potential to be detected with these algorithms. This is what makes them very scalable in practice. The data race algorithm implemented is the Eraser algorithm from Compaq, however adopted to Java. The tool is currently being applied to a code base for controlling a spacecraft by the developers of that software in order to evaluate its applicability.

Havelund, Klaus↗

Primordial features and Planck polarization

With the Planck 2015 Cosmic Microwave Background (CMB) temperature and polarization data, we search for possible features in the primordial power spectrum (PPS). We revisit the Wiggly Whipped Inflation (WWI) framework and demonstrate how generation of some particular primordial features can improve the fit to Planck data. WWI potential allows the scalar field to transit from a steeper potential to a nearly flat potential through a discontinuity either in potential or in its derivatives. WWI offers the inflaton potential parametrizations that generate a wide variety of features in the primordial power spectra incorporating most of the localized and non-local inflationary features that are obtained upon reconstruction from temperature and polarization angular power spectrum. At the same time, in a single framework it allows us to have a background parameter estimation with a nearly free-form primordial spectrum. Using Planck 2015 data, we constrain the primordial features in the context of Wiggly Whipped Inflation and present the features that are supported both by temperature and polarization. WWI model provides more than 13 improvement in χ{sup 2} fit to the data with respect to the best fit power law model considering combined temperature and polarization data from Planck and B-mode polarization data from BICEP and Planck dust map. We use 2-4 extra parameters in the WWI model compared to the featureless strict slow roll inflaton potential. We find that the differences between the temperature and polarization data in constraining background cosmological parameters such as baryon density, cold dark matter density are reduced to a good extent if we use primordial power spectra from WWI. We also discuss the extent of bispectra obtained from the best potentials in arbitrary triangular configurations using the BI-spectra and Non-Gaussianity Operator (BINGO).

79 ASTRONOMY AND ASTROPHYSICS↗

A Web Service and Android Application for the Distribution of Rainfall Estimates and Earth Observation Data

The full potential of Satellite Rainfall Estimates (SRE) can only be realized if timely access to the datasets is possible. Existing data distribution web portals are often focused on global products and offer limited customization options, especially for the purpose of routine regional monitoring. Furthermore, most online systems are designed to meet the needs of desktop users, limiting the compatibility with mobile devices. In response to the growing demand for SRE and to address the current limitations of available web portals a project was devised to create a set of freely available applications and services, available at a common portal that can: (1) simplify cross-platform access to Tropical Rainfall Measuring Mission Online Visualization and Analysis System (TOVAS) data (including from Android mobile devices), (2) provide customized and continuous monitoring of SRE in response to user demands and (3) combine data from different online data distribution services, including rainfall estimates, river gauge measurements or imagery from Earth Observation missions at a single portal, known as the Tropical Rainfall Measuring Mission (TRMM) Explorer. The TRMM Explorer project suite includes a Python-based web service and Android applications capable of providing SRE and ancillary data in different intuitive formats with the focus on regional and continuous analysis. The outputs include dynamic plots, tables and data files that can also be used to feed downstream applications and services. A case study in Southern Angola is used to describe the potential of the TRMM Explorer for SRE distribution and analysis in the context of ungauged watersheds. The development of a collection of data distribution instances helped to validate the concept and identify the limitations of the program, in a real context and based on user feedback. The TRMM Explorer can successfully supplement existing web portals distributing SRE and provide a cost-efficient resource to small and medium-sized organizations with specific SRE monitoring needs, namely in developing and transition countries.

precipitation↗

Big Data Challenges for Large Radio Arrays

Future large radio astronomy arrays, particularly the Square Kilometre Array (SKA), will be able to generate data at rates far higher than can be analyzed or stored affordably with current practices. This is, by definition, a "big data" problem, and requires an end-to-end solution if future radio arrays are to reach their full scientific potential. Similar data processing, transport, storage, and management challenges face next-generation facilities in many other fields.

Combining↗

Planetary Protection at Marshall Space Flight Center

Introduction: NASA Marshall Space Flight Center (MSFC) is historically known for its role in propulsion. While this is still the mainstay of MSFC’s expertise, many unique capabilities exist at MSFC which pertain to Planetary Protection (PP), including 1) identifying PP threats, and 2) developing novel methods to neutralize those threats. Furthermore, because these capabilities exist among diverse groups at MSFC, this work promotes collaboration both within and outside MSFC to expand and develop PP studies related to a full spectrum of NASA research, design, manufacture, and test interests. This abstract describes the PP research ongoing at MSFC and describes how it contributes to NASA’s overall PP objectives. Microbial Identification in Cleanrooms: One of the greatest threats to successful implementation of PP requirements is recontamination post bioburden reduction. One method to prevent recontamination is to keep the spacecraft in clean environments (i.e. cleanrooms) as much as possible during assembly and integration. However, cleanrooms are not without their own sources of contamination, which is why NASA is interested in monitoring the cleanliness of cleanrooms and characterizing the microbial species present. Such information allows a greater understanding of the resistance of these microbes to cleaning methods, as well as the risk of their contaminating the targeted planetary body of a given mission. MSFC has multiple cleanrooms of various ISO cleanliness levels onsite. We sampled the air and surfaces of three of these rooms, isolated microbes, and then sequenced the 16S rRNA gene or ITS region of the 18S rRNA gene for bacterial and fungal isolates, respectively. This has resulted in a microbial library which currently includes nearly 100 isolates. Microbial Enumeration of Spacecraft Materials: Currently, there are only a couple bioburden reduction methods approved by NASA, and often the harshness of these methods presents additional concerns or risks related to material properties. The goal of this research is to assess the microbial content of solid rocket motor (SRM) materials potentially used for lander missions. This work aims to more accurately define the risk of planetary contamination by providing empirical data associated with commonly used SRM raw materials. In this study, we pulverized nonmetallic SRM materials using a cryogenic grinder, then analyzed the resulting substrate for microbial colony forming units (CFU). We found that many SRM nonmetallic materials do not harbor detectable bioburden, though a range existed depending on the material. The results from this work provide quantitative data to potentially reduce concerns of contamination, while also providing a foundation for follow up studies into additional sterilization methods and molecular identification of contaminating microbes. Space Environmental Effects on Microbial Survival: One potential area of microbial reduction is the space environment. Understanding the survivability of hardy microbes in space-like conditions is a crucial first step in answering how space may reduce bioburden and if it can be relied upon for adherence to PP requirements. This work studied the effects of ultraviolet (UV) and ionizing radiation on survival of Bacillus atrophaeus spores. Microbes were dried on relevant polymeric materials then exposed to space environmental stressors. Coupons were submerged in water, diluted, and plated to determine survival compared with controls. We found that both UV and ionizing radiation were capable of reducing viability by nearly 99%, but there were still survivors, some with changed morphology indicating resistance mechanisms within certain cells. Manufacturing credit: Finally, given the above-mentioned limitations of the NASA-approved bioburden reduction methods, there is interest in understanding if manufacturing processes may provide enough bioburden reduction without additional PP-specific bakeouts. For instance, some material additives may be antimicrobial. Given this, we investigated the effects of several commonly used rubber additives on the growth of B. atrophaeus spores. We found that some of the materials inhibited growth of the spores, possibly supporting the use of these additives on missions with PP constraints. Future work into manufacturing credit for bioburden reduction includes inoculation of green insulation with B. atrophaeus spores, followed by a typical cure. Thermal profiles will be verified for appropriate temperature and durations to meet PP requirements, and cured samples will be analyzed using a cryogenic grinder to determine survivability of spores.

Chelsi D. Cassilly↗

Hypothesis-Agnostic Network-Based Analysis of Real-World Data Suggests Ondansetron is Associated with Lower COVID-19 Any Cause Mortality

Background: The COVID-19 pandemic generated a massive amount of clinical data, which potentially hold yet undiscovered answers related to COVID-19 morbidity, mortality, long-term effects, and therapeutic solutions.Objectives: The objectives of this study were (1) to identify novel predictors of COVID-19 any cause mortality by employing artificial intelligence analytics on real-world data through a hypothesis-agnostic approach and (2) to determine if these effects are maintained after adjusting for potential confounders and to what degree they are moderated by other variables.Methods: A Bayesian statistics-based artificial intelligence data analytics tool (bAIcis®) within the Interrogative Biology® platform was used for Bayesian network learning and hypothesis generation to analyze 16,277 PCR+ patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated Bayesian networks that enabled unbiased identification of significant predictors of any cause mortality for specific COVID-19 patient populations. These findings were further analyzed by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping.Results: We found that in the COVID-19 PCR+ patient cohort, early use of the antiemetic agent ondansetron was associated with decreased any cause mortality 30 days post-PCR+ testing in mechanically ventilated patients.Conclusions: The results demonstrate how a real-world COVID-19-focused data analysis using artificial intelligence can generate unexpected yet valid insights that could possibly support clinical decision making and minimize the future loss of lives and resources.

60 APPLIED LIFE SCIENCES↗