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At least 829 records · Page 46

MODIS Science Algorithms and Data Systems Lessons Learned

For almost 10 years, standard global products from NASA's Earth Observing System s (EOS) two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors are being used world-wide for earth science research and applications. This paper discusses the lessons learned in developing the science algorithms and the data systems needed to produce these high quality data products for the earth sciences community. Strong science team leadership and communication, an evolvable and scalable data system, and central coordination of QA and validation activities enabled the data system to grow by two orders of magnitude from the initial at-launch system to the current system able to reprocess data from both the Terra and Aqua missions in less than a year. Many of the lessons learned from MODIS are already being applied to follow-on missions.

Wolfe, Robert E.↗

NASA ESDIS Employs the Latest Generation Web Analytics Tool

Under the auspices of NASA's Earth Observing System Data and Information System (EOSDIS), The Earth Science Data and Information System (ESDIS) Project distributes science data to a wide community of users through its Distributed Active Archive Centers (DAACs). Much of this data is made available via interactive websites - which involve links, downloads, on page interaction, and referrals to additional online pages. To meet the earth science data and information needs of many data users representing numerous different science domains, over 80 specialized websites are supported by multiple distributed organizations under the ESDIS umbrella.

Web Metrics↗

A Ceph S3 Object Data Store for HEP

We present a novel data format design that obviates the need for data tiers by storing individual event data products in column objects. The objects are stored and retrieved through Ceph S3 technology, with a layout designed to minimize metadata volume and maximize data processing parallelism. Performance benchmarks of data storage and retrieval are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

An approach to effective UHF (S/L band) data communications for satellite Personal Communication Service (PCS)

Reliable signaling information transfer is fundamental in supporting the needs of data communication PCS via LMS (Land Mobile Service) SSs (satellite systems). The needs of the system designer can be satisfied only through the collection of media information that can be brought to bear on the pertinent design issues. We at ISI hope to continue our dialogue with fading media experts to address the unique data communications needs of PCS via LMS SSs.

Hayase, Joshua Y.↗

Research needs in ocean color data analysis

The success of the effort to extract several subsurface oceanographic parameters from remotely sensed ocean color data will depend to a great extent upon the existence of adequate theoretical models relating the desired oceanographic parameters to the upwelling radiances to be observed. In order to guide the development of these models, and to check their accuracies, a considerable amount of experimental work must be performed. The theoretical and experimental work needed to develop techniques for the quantitative analysis of satellite ocean color data is described.

Mccluney, W. R.↗

Final Design for Thermal/Epithermal eXperiments using High 240 Pu Content Plutonium/Aluminum Zero Power Research Reactor Plates with Polyethylene Moderator (IER 520 Final Design CED-2 Report)

The US Department of Energy Nuclear Criticality Safety Program (NCSP) convened a multinational Thermal Epithermal eXperiments (TEX) meeting in July of 2011 to discuss the data and experimental needs of criticality safety practitioners. The number one and two priority integral experiment data needs were for 239 Pu and 240 Pu, with special emphasis on cross section performance in the intermediate energy range (from 0.625 eV to 100 keV). LLNL measured five critical configurations with LANL for the plutonium test bed (IER-184) and published the experiments as International Criticality Safety Benchmark Evaluation Project evaluation PUMET-MIXED-002. Modeling of the benchmark configurations using ENDF/B-VIII.0 nuclear data showed significant overprediction of reactivity for configurations that had a large percentage of fissions in the intermediate energy regime. This report documents a variation on the TEX plutonium test bed to provide a test of 240 Pu cross sections, with sensitivity of the configuration to 240 Pu radiative capture and fission cross sections a priority for the design.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Human Mars Landing Site and Impacts on Mars Surface Operations

This paper describes NASA's initial steps for identifying and evaluating candidate Exploration Zones (EZs) and Regions of Interests (ROIs) for the first human crews that will explore the surface of Mars. NASA's current effort to define the exploration of this planet by human crews, known as the Evolvable Mars Campaign (EMC), provides the context in which these EZs and ROIs are being considered. The EMC spans all aspects of a human Mars mission including launch from Earth, transit to and from Mars, and operations on the surface of Mars. Studies related to Mars surface operations and related system capabilities have led to the current definition of an EZ as well as ROIs. An EZ is a collection of ROIs that are located within approximately 100 kilometers of a centralized landing site. ROIs are areas that are relevant for scientific investigation and/or development/maturation of capabilities and resources necessary for a sustainable human presence. The EZ also contains one or more landing sites and a habitation site that will be used by multiple human crews during missions to explore and utilize the ROIs within the EZ. With the EMC as a conceptual basis, the EZ model has been refined to a point where specific site selection criteria for scientific exploration and in situ resource utilization can be defined. In 2015 these criteria were distributed to the planetary sciences community and the in situ resource utilization and civil engineering communities as part of a call for EZ proposals. The resulting "First Landing Site/Exploration Zone Workshop for Human Missions to the Surface of Mars" was held in October 2015 during which 47 proposals for EZs and ROIs were presented and discussed. Proposed locations spanned all longitudes and all allowable latitudes (+/- 50 degrees). Proposed justification for selecting one of these EZs also spanned a significant portion of the scientific and resource criteria provided to the community. Workshop results will be used to prepare for follow-on workshops to refine our understanding of proposed EZs and ultimately select a single location to be explored and utilized by human crews. Another significant workshop outcome was a recognition that new data will be needed to refine our understanding of the value of proposed EZs. These new data will come in part from existing spacecraft at Mars and may come from future robotic Mars missions as appropriate consideration is given to these new data needs during mission definition and development.

Bussey, Ben↗

Spectroscopic Determination of the Physical Conditions in Hot Optically Thin Sources

Astrophysical Plasma Emission Database - APED consists of atomic data, primarily theoretical, needed to calculate X-ray through optical emission spectra of hot thermal plasmas. These data are supplemented by experimental values, such as laboratory plasma wave- lengths, and are validated by experiment only rarely. Thus the comparison of predicted spectra to astrophysical spectra serves as invaluable feedback on the quality of the models. Following up on unfavorable comparisons, we have communicated atomic data needs to atomic theorists and experimental plasma physicists so that improvements can be made to the database. The database is now reasonably complete from approx. 1 to 30 A, and from - 90 to 180 A, with significant gaps remaining in the range 30 to 90 A. Astrophysical Plasma Emission Code - APEC uses the APED data as inputs and computes level populations and line emissivities using a rate matrix solver. Tabulated models for a fine grid of temperatures and densities can be applied to observational data. The current public version of APEC output uses an input ionization balance model, assuming CIE; however, we have a working version to calculate the ionization state of the gas. We will begin testing non-equilibrium ionization (NEI) models over the next year - we are now finalizing the atomic database needed to perform the ionization state calculations. At that time, the code will be made public. We have developed optimized error codes, additional testing protocols and substantial documentation, in preparation for this public release. Secondarily, we have begun to investigate the use of APED and APEC for X-ray photoionized plasma, beginning with opacity modeling (e.g. warm absorbers). Application to bright AGN Chandra grating spectra suggests that the accurate wavelengths in APED are of great importance to fitting the data. We are exploring additional subroutines to APEC to extend its usefulness for X-ray photoionized plasma, e.g. to include collisional or photo-excitation of metastable levels for absorption.

Oliversen, Ronald J.↗

Maintaining Trust in Reduction: Preserving the Accuracy of Quantities of Interest for Lossy Compression

As the growth of data sizes continues to outpace computational resources, there is a pressing need for data reduction techniques that can significantly reduce the amount of data and quantify the error incurred in compression. Compressing scientific data presents many challenges for reduction techniques since it is often on non-uniform or unstructured meshes, is from a high-dimensional space, and has many Quantities of Interests (QoIs) that need to be preserved. To illustrate these challenges, we focus on data from a large scale fusion code, XGC. XGC uses a Particle-In-Cell (PIC) technique which generates hundreds of PetaBytes (PBs) of data a day, from thousands of timesteps. XGC uses an unstructured mesh, and needs to compute many QoIs from the raw data, f.One critical aspect of the reduction is that we need to ensure that QoIs derived from the data (density, temperature, flux surface averaged momentums, etc.) maintain a relative high accuracy. We show that by compressing XGC data on the high-dimensional, nonuniform grid on which the data is defined, and adaptively quantizing the decomposed coefficients based on the characteristics of the QoIs, the compression ratios at various error tolerances obtained using a multilevel compressor (MGARD) increases more than ten times. We then present how to mathematically guarantee that the accuracy of the QoIs computed from the reduced f is preserved during the compression. We show that the error in the XGC density can be kept under a user-specified tolerance over 1000 timesteps of simulation using the mathematical QoI error control theory of MGARD, whereas traditional error control on the data to be reduced does not guarantee the accuracy of the QoIs.

Gong, Qian↗

Pollutant emissions from and within a model gas turbine combustor at elevated pressures and temperatures

Conventional and advanced gas turbine engines are coming under increased scrutiny regarding pollutant emissions. This, in turn, has created a need to obtain in-situ experimental data at practical conditions, as well as exhaust data, and to obtain the data in combustors that reflect modern designs. The in-situ data are needed to (1) assess the effects of design modifications on pollutant formation, and (2) develop a detailed data base on combustor performance for the development and verification of computer modeling. This paper reports on a novel high pressure, high temperature facility designed to acquire such data under controlled conditions and with access (optical and extractive) for in-situ measurements. To evaluate the utility of the facility, a model gas turbine combustor was selected which features practical hardware design, two rows of jets (primary and dilution) with four jets in each row, and advanced wall cooling techniques with laser drilled effusive holes. The dome is equipped with a flat-vaned swirler with vane angles of 60 degrees. Data are obtained at combustor pressures ranging from 2 to 10 atmospheres of pressure, levels of air preheat to 427 C, combustor reference velocities from 10.0 to 20.0 m/s, and an overall equivalence ratio of 0.3. Exit plane and in-situ measurements are presented for HC, O2, CO2, CO, and NO(x). The exit plane emissions of NO(x) correspond to levels reported from practical combustors and the in-situ data demonstrate the utility and potential for detailed flow field measurements.

Drennan, S. A.↗

Statistical methods and neural network approaches for classification of data from multiple sources

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

Benediktsson, Jon Atli↗

Task 51 - Cloud-Optimized Format Study

The cloud infrastructure provides a number of capabilities that can dramatically improve access and use of Earth Observation data. However, in many cases, data may need to be reorganized and/or reformatted in order to make them tractable to support cloud-native analysis/access patterns. The purpose of this study is to examine the pros and cons of different formats for storing data on the cloud. The evaluation will focus on both enabling high-performance data access and usage as well as to meet the existing scientific data stewardship needs of EOSDIS.

Durbin, Chris↗

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗

Data simulation for the Lightning Imaging Sensor (LIS)

This project aims to build a data analysis system that will utilize existing video tape scenes of lightning as viewed from space. The resultant data will be used for the design and development of the Lightning Imaging Sensor (LIS) software and algorithm analysis. The desire for statistically significant metrics implies that a large data set needs to be analyzed. Before 1990 the quality and quantity of video was insufficient to build a usable data set. At this point in time, there is usable data from missions STS-34, STS-32, STS-31, STS-41, STS-37, and STS-39. During the summer of 1990, a manual analysis system was developed to demonstrate that the video analysis is feasible and to identify techniques to deduce information that was not directly available. Because the closed circuit television system used on the space shuttle was intended for documentary TV, the current value of the camera focal length and pointing orientation, which are needed for photoanalysis, are not included in the system data. A large effort was needed to discover ancillary data sources as well as develop indirect methods to estimate the necessary parameters. Any data system coping with full motion video faces an enormous bottleneck produced by the large data production rate and the need to move and store the digitized images. The manual system bypassed the video digitizing bottleneck by using a genlock to superimpose pixel coordinates on full motion video. Because the data set had to be obtained point by point by a human operating a computer mouse, the data output rate was small. The loan and subsequent acquisition of a Abekas digital frame store with a real time digitizer moved the bottleneck from data acquisition to a problem of data transfer and storage. The semi-automated analysis procedure was developed using existing equipment and is described. A fully automated system is described in the hope that the components may come on the market at reasonable prices in the next few years.

Boeck, William L.↗

The use of remotely sensed data for operational fisheries oceanography

Satellite remote sensing data are used under two contexts in fisheries: as a tool for fisheries research and as a means to provide operational support to fishing activities. Fishing operations need synoptic data provided timely; fisheries research needs that type of data and, also, good short-term climatologies. A description is given of several experiences conducted around the world which have employed or are using satellite data for operational fisheries problems. An overview is included of the Portuguese program for fisheries support using remotely sensed data provided by satellites and in situ observations conducted by fishermen. Environmental products useful for fisheries necessarily combine satellite and in situ data. The role of fishermen as a source of good, near-real-time in situ environmental data is stressed; so far, this role seems to have been largely overlooked.

Fiuza, Armando F. G.↗

Key ingredients needed when building large data processing systems for scientists

Why is building a large science software system so painful? Weren't teams of software engineers supposed to make life easier for scientists? Does it sometimes feel as if it would be easier to write the million lines of code in Fortran 77 yourself? The cause of this dissatisfaction is that many of the needs of the science customer remain hidden in discussions with software engineers until after a system has already been built. In fact, many of the hidden needs of the science customer conflict with stated needs and are therefore very difficult to meet unless they are addressed from the outset in a system's architectural requirements. What's missing is the consideration of a small set of key software properties in initial agreements about the requirements, the design and the cost of the system.

Earth Observing System EOS↗

MSR Salt Spill Accident Testing Using Eutectic NaCl-UCl 3

Assessing the potential consequences of identified accident scenarios is an essential part of the licensing process for a new nuclear reactor and is achieved by using accident progression models. A likely accident scenario that will be evaluated by developers of molten salt reactors (MSRs) is a spill of radionuclide-bearing fuel salt onto the reactor containment floor (i.e., a salt spill accident). Models to determine the consequences of a molten salt spill accident need to be parameterized and validated using experimental data, but little experimental effort has been dedicated to fill these data gaps to date. Specifically, data is needed to enable model development for individual processes (e.g., spreading, heat transfer, corrosion, radionuclide vaporization, and aerosol generation) that quantifies the sensitivities towards the initial conditions of the spill, the ambient environment, and the features of the containment. In addition, integrated experiments that simulate salt spill accidents will need to be conducted to provide insight into coupled processes and data for model validation, but these experiments will require the use of proven methods to quantify the processes under evaluation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗