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NASA NTRS2010

Space Weather Services at Goddard Space Flight Center

The Space Weather Laboratory (SWL) forms a focal point at GSFC for the generation of space weather tools and information. This information is based on data from space mission and ground observatories, as well as on forefront model calculations conducted at the Community Coordinated Modeling Center (CCMC). CCMC works with the research community to bring to bear the power of communitydeveloped space science models on space weather problems. Data from primarily from NASA missions but also from NOAA and other partner agencies are combined with model results into a fully configurable space weather information display by means of the iSWA system. This information and iSWA form the basis for and SWL-provided service to NASA's robotic mission fleet, which includes forecasts, regular updates, and warnings. This service benefits from a strong partnership with NASA's Space Radiation Analysis Group, and with the US Air Force Weather Agency. In this presentation, we provide a summary of space weather capabilities and services and we present an outlook into the future.

Hesse, M.↗
NASA NTRS2012

Policy for Robust Space-based Earth Science, Technology and Applications

Over the past six decades, satellite remote sensing technology has contributed to the transformation of using earth science not only to advance science, but to improve quality of life. With satellite missions launched almost every year, new types of earth science data are being incorporated into science, models and decision-making systems in a broad array of organizations. A challenge for space agencies has been ensuring that satellite missions serve both the scientific community and the applied community of decision makers without the missions becoming unfocused and overly expensive. By understanding and considering the needs of the environmental data and applied research user community early on in the mission-design process, agencies can ensure that satellites meet the needs of multiple constituencies. This paper describes the mission development process in the European Space Agency and the National Aeronautics and Space Administration and compares and contrasts the successes of and challenges faced by these agencies in balancing science and applications within their missions.

Brown, Molly E.↗
NASA NTRS2001

Ocean-Science Mission Needs: Real-Time AUV Data for Command, Control, and Model Inputs

Predictive models for tides, hydrodynamics, and bio-optical properties affecting the visibility and buoyancy of coastal waters are needed to evaluate the safety of personnel and equipment engaged in maritime operations under potentially hazardous conditions. Predicted currents can be markedly different for two-layer systems affected by terrestrial runoff than for well-mixed conditions because the layering decouples the surface and bottom Ekman layers and rectifies the current response to oscillatory upwelling-and downwelling-favorable winds. Standard ocean models (e.g. Princeton Ocean Model) require initial-and boundary data on the physical and optical properties of the multilayered water column to provide accurate simulations of heat budgets and circulation. Two observational systems are designed to measure vertically structured conditions on the West Florida Shelf (WFS): a tethered buoy network and an autonomous underwater vehicle (AUV) observational system. The AUV system is described with a focus on the observational systems that challenge or limit the communications command and control network for various types of measurement programs. These include vertical oscillatory missions on shelf transects to observe the optical and hydrographic properties of the water column, and bottom-following missions for measuring the bottom albedo. Models of light propagation, absorption, and conversion to heat as well as determination of the buoyancy terms for physical models require these measurements. High data rates associated with video bottom imagery are the most challenging for the real-time, command and control communications system, but they are met through a combination of loss-less and lossy data-compression methods, depending upon the data-rate of the radio links.

Carder, Kendall L.↗
NASA NTRS2019

Progress Towards Modeling the Mars Science Laboratory PICA-NuSil Heatshield

The data collected by the Mars Science Laboratory (MSL) Entry, Descent and Landing Instrumentation, MEDLI, have become an established reference to assess the performance of engineering models of the Phenolic Impregnated Carbon Ablator (PICA) and to validate hypersonic computational fluid dynamics (CFD) tools for entry systems. MEDLI measurements are also extensively used as validation reference for current developments of high-fidelity material response models for PICA. So large has been the scientific output and impact of MEDLI that a follow-up instrumentation suite MEDLI2 is underway for the upcoming Mars 2020 mission.A feature neglected thus far in the modeling of the MSL heatshield, is the presence of a silicone-based room temperature vulcanizing coating designated NuSil CV-1144-0. NuSil was used to coat the entire MSL heatshield, including the MEDLI plugs, to mitigate the spread of phenolic dust from PICA, and limit contamination during clean room operations. NuSil CV-1144-0 is a space grade siloxane copolymer, designed as an oxygen protection barrier for extreme low temperature environment.Assessments conducted during MSL development demonstrated that the presence of NuSil had no adverse effect on the performance of PICA. However, evidence from ground testing of PICA-NuSil (PICA-N) models in the HyMETS arc-jet test facility suggests that the silicone changes the high temperature response of PICA. It is therefore critical to assess the importance of modeling the coating in ongoing code validation efforts.

Bessire, Brody K.↗
NASA NTRS2002

Solar particle event organ doses and dose equivalents for interplanetary crews: variations due to body size

Proper assessments of spacecraft shielding requirements and concomitant estimates of risk to critical body organs of spacecraft crews from energetic space radiation require accurate, quantitative methods of characterizing the compositional changes in these radiation fields as they pass through the spacecraft and overlying tissue. When estimating astronaut radiation organ doses and dose equivalents it is customary to use the Computerized Anatomical Man (CAM) model of human geometry to account for body self-shielding. Usually, the distribution for the 50th percentile man (175 cm height; 70 kg mass) is used. Most male members of the U.S. astronaut corps are taller and nearly all have heights that deviate from the 175 cm mean. In this work, estimates of critical organ doses and dose equivalents for interplanetary crews exposed to an event similar to the October 1989 solar particle event are presented for male body sizes that vary from the 5th to the 95th percentiles. Overall the results suggest that calculations of organ dose and dose equivalent may vary by as much as approximately 15% as body size is varied from the 5th to the 95th percentile in the population used to derive the CAM model data. c2002 Published by Elsevier Science Ltd on behalf of COSPAR.

NASA Discipline Radiation Health↗
NASA NTRS2009

Demonstration of Effects on Tropical Cyclone Forecasts with a High Resolution Global Model from Variation in Cumulus Convection Parameterization

The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models that have been developed at Goddard Space Flight Center to support NASA's earth science research in data analysis, observing system modeling and design, climate and weather prediction, and basic research. The work presented used GEOS-5 with 0.25o horizontal resolution and 72 vertical levels (up to 0.01 hP) resolving both the troposphere and stratosphere, with closer packing of the levels close to the surface. The model includes explicit (grid-scale) moist physics, as well as convective parameterization schemes. Results will be presented that will demonstrate strong dependence in the results of modeling of a strong hurricane on the type of convective parameterization scheme used. The previous standard (default) option in the model was the Relaxed Arakawa-Schubert (RAS) scheme, which uses a quasi-equilibrium closure. In the cases shown, this scheme does not permit the efficient development of a strong storm in comparison with observations. When this scheme is replaced by a modified version of the Kain-Fritsch scheme, which was originally developed for use on grids with intervals of order 25 km such as the present one, the storm is able to develop to a much greater extent, closer to that of reality. Details of the two cases will be shown in order to elucidate the differences in the two modeled storms.

Miller, Timothy L.↗
NASA NTRS2017

The Diverse Data, User Driven Services and the Power of Giovanni at NASA GES DISC

This presentation provides an overview of remote sensing and model data at GES (Goddard Earth Sciences) DISC (Data and Information Services Center); Overview of data services at GES DISC (Registration with NASA data system; Searching and downloading data); Giovanni (Geospatial Interactive Online VisualizationANd aNalysis Infrastructure): online data exploration tool; and NASA Earth Data and Information System.

model↗
NASA NTRS2019

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

With the rise in big data and analytics, machine learning is transforming many industries. It is being increasingly employed to solve a wide range of complex problems, producing autonomous systems that support human decision-making. For the aircraft engine industry, machine learning of historical and existing engine data could provide insights that help drive for better engine design. This work explored the application of machine learning to engine preliminary design. Engine core-size prediction was chosen for the first study because of its relative simplicity in terms of number of input variables required (only three). Specifically, machine-learning predictive tools were developed for turbofan engine core-size prediction, using publicly available data of two hundred manufactured engines and engines that were studied previously in NASA aeronautics projects. The prediction results of these models show that, by bringing together big data, robust machine-learning algorithms and data science, a machine learning-based predictive model can be an effective tool for turbofan engine core-size prediction. The promising results of this first study paves the way for further exploration of the use of machine learning for aircraft engine preliminary design.

Core Size↗
NASA NTRS2016

Advancing User Supports with a Structured How-To Knowledge Base for Earth Science Data

It is a challenge to access and process fast growing Earth science data from satellites and numerical models, which may be archived in very different data format and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and/or formats. A type of structured online document, data recipe, were created in beginning 2013 by Goddard Earth Science Data and Information Services Center (GES DISC). A data recipe is the How-To document created by using the fixed template, containing step-by-step instructions with screenshots and examples of accessing and working with real data. The recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant to some recipes. In 2014, the NASA Earth Science Data System Working Group (ESDSWG) for data recipes was established, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group started with inventory and analysis of existing EOSDIS-wide online help documents, and provided recommendations and guidelines and for writing and grouping data recipes. This presentation will overview activities of creating How-To documents at GES DISC and ESDSWG. We encourage feedback and contribution from users for improving the data How-To knowledge base.

how-to↗
NASA NTRSDate not supplied

Foundation AI Models for Science

Foundation Models (FM) are AI models that are designed to replace a task or an application specific model. These FM can be applied to many different downstream applications. These FM are trained using self supervised techniques and can be built on any type of sequence data. The use of self supervised learning removes the hurdle for developing a large labeled dataset for training. Most FM use transformer architecture utilizes the notion of self attention which allows the network to model the influence of distant data points to each other both in space and time. The FM models exhibit emergent properties that are induced from the data. FM can be an important tool for science. The scale of these models results in better performance for different downstream applications and these applications show better accuracy over models built from scratch. FM drastically reduces the cost of entry to build different downstream applications both in time and effort. FM for selected science datasets such as optical satellite data, can accelerate applications ranging from data quality monitoring, feature detection and prediction. FM can make it easier to infuse AI into scientific research by removing the training data bottleneck and increasing the use of science data.

Manil Maskey↗
NASA NTRS2006

Sensor to User - NASA/EOS Data for Coastal Zone Management Applications Developed from Integrated Analyses: Verification, Validation and Benchmark Report

The NASA Applied Sciences Program seeks to transfer NASA data, models, and knowledge into the hands of end-users by forming links with partner agencies and associated decision support tools (DSTs). Through the NASA REASoN (Research, Education and Applications Solutions Network) Cooperative Agreement, the Oceanography Division of the Naval Research Laboratory (NRLSSC) is developing new products through the integration of data from NASA Earth-Sun System assets with coastal ocean forecast models and other available data to enhance coastal management in the Gulf of Mexico. The recipient federal agency for this research effort is the National Oceanic and Atmospheric Administration (NOAA). The contents of this report detail the effort to further the goals of the NASA Applied Sciences Program by demonstrating the use of NASA satellite products combined with data-assimilating ocean models to provide near real-time information to maritime users and coastal managers of the Gulf of Mexico. This effort provides new and improved capabilities for monitoring, assessing, and predicting the coastal environment. Coastal managers can exploit these capabilities through enhanced DSTs at federal, state and local agencies. The project addresses three major issues facing coastal managers: 1) Harmful Algal Blooms (HABs); 2) hypoxia; and 3) freshwater fluxes to the coastal ocean. A suite of ocean products capable of describing Ocean Weather is assembled on a daily basis as the foundation for this semi-operational multiyear effort. This continuous realtime capability brings decision makers a new ability to monitor both normal and anomalous coastal ocean conditions with a steady flow of satellite and ocean model conditions. Furthermore, as the baseline data sets are used more extensively and the customer list increased, customer feedback is obtained and additional customized products are developed and provided to decision makers. Continual customer feedback and response with new improved products are required between the researcher and customer. This document details the methods by which these coastal ocean products are produced including the data flow, distribution, and verification. Product applications and the degree to which these products are used successfully within NOAA and coordinated with the Mississippi Department of Marine Resources (MDMR) is benchmarked.

Hall, Callie↗
NASA NTRS2017

Towards a Preservation Content Standard for Earth Observation Data

Information from Earth observing missions (remote sensing with airborne and spaceborne instruments, and in situ measurements such as those from field campaigns) is proliferating in the world. Many agencies across the globe are generating important datasets by collecting measurements from instruments on board aircraft and spacecraft, globally and constantly. The data resulting from such measurements are a valuable resource that needs to be preserved for the benefit of future generations. These observations are the primary record of the Earths environment and therefore are the key to understanding how conditions in the future will compare to conditions today. Earth science observational data, derived products and models are used to answer key questions of global significance. In the near-term, as long as the missions data are being used actively for scientific research, it continues to be important to provide easy access to the data and services commensurate with current information technology. For the longer term, when the focus of the research community shifts toward new missions and observations, it is essential to preserve the previous mission data and associated information. This will enable a new user in the future to understand how the data were used for deriving information, knowledge and policy recommendations and to repeat the experiment to ascertain the validity and possible limitations of conclusions reached in the past and to provide confidence in long term trends that depended on data from multiple missions. Organizations that collect, process, and utilize Earth observation data today have a responsibility to ensure that the data and associated content continue to be preserved by them or are gathered and handed off to other organizations for preservation for the benefit of future generations. In order to ensure preservation of complete content necessary for understanding and reusing the data and derived digital products from todays missions, it is necessary to develop a specification of such preservation content. While there are existing standards that address archival and preservation in general, there are no existing international standards or specifications today to address what content should be preserved. The purpose of this paper is to outline briefly the existing standards that apply to preservation, describe a recent effort in getting an international standard in place for specifying preservation content for Earth observation data and derived digital data products and the remaining work needed to arrive at a standard.

ISO Standards↗
NASA NTRS1985

Global scale diagnoses of FGGE data

Descriptive global scale diagnoses of the First Global Atmospheric Research Experiment SOP-1 analyses were made and compared against controlled, real data integrations of the Goddard Laboratory of Atmospheric Science (GLAS) general circulation model (GCM) as well as other data sets. The effects of critical latitudes were studied; the influence of tropical wind data and latent heating upon the GLAS GCM was diagnosed; planetary wave structure on various time scales from the diurnal to the monthly was studied; and the GLAS analyses were compared with other analyses. Short term controlled GLAS GCM integrations show that: (1) the inclusion of tropical wind data in real data integrations has an important influence in the mid-latitude prediction in both hemispheres; and (2) the tropical divergent wind reacts almost immediately to alteration of the tropical latent heating. The presence or absence of zonally averaged easterlies depends strongly upon the presence of tropical latent heating.

Paegle, J.↗
NASA NTRS1976

General purpose simulation system of the data management system for Space Shuttle mission 18

A simulation program for the flow of data through the Data Management System of Spacelab and Space Shuttle was presented. The science, engineering, command and guidance, navigation and control data were included. The programming language used was General Purpose Simulation System V (OS). The science and engineering data flow was modeled from its origin at the experiments and subsystems to transmission from Space Shuttle. Command data flow was modeled from the point of reception onboard and from the CDMS Control Panel to the experiments and subsystems. The GN&C data flow model handled data between the General Purpose Computer and the experiments and subsystems. Mission 18 was the particular flight chosen for simulation. The general structure of the program is presented, followed by a user's manual. Input data required to make runs are discussed followed by identification of the output statistics. The appendices contain a detailed model configuration, program listing and results.

Bengtson, N. M.↗
NASA NTRS2006

Space and Ground Trades for Human Exploration and Wearable Computing

Human exploration of the Moon and Mars will present unique trade study challenges as ground system elements shift to planetary bodies and perhaps eventually to the bodies of human explorers in the form of wearable computing technologies. This presentation will highlight some of the key space and ground trade issues that will face the Exploration Initiative as NASA begins designing systems for the sustained human exploration of the Moon and Mars, with an emphasis on wearable computing. We will present some preliminary test results and scenarios that demonstrate how wearable computing might affect the trade space noted below. We will first present some background on wearable computing and its utility to NASA's Exploration Initiative. Next, we will discuss three broad architectural themes, some key ground and space trade issues within those themes and how they relate to wearable computing. Lastly, we will present some preliminary test results and suggest guidance for proceeding in the assessment and creation of a value-added role for wearable computing in the Exploration Initiative. The three broad ground-space architectural trade themes we will discuss are: 1. Functional Shift and Distribution: To what extent, if any, should traditional ground system functionality be shifted to, and distributed among, the Earth, Moon/Mars, and the human. explorer? 2. Situational Awareness and Autonomy: How much situational awareness (e.g. environmental conditions, biometrics, etc.) and autonomy is required and desired, and where should these capabilities reside? 3. Functional Redundancy: What functions (e.g. command, control, analysis) should exist simultaneously on Earth, the Moon/Mars, and the human explorer? These three themes can serve as the axes of a three-dimensional trade space, within which architectural solutions reside. We will show how wearable computers can fit into this trade space and what the possible implications could be for the rest of the ground and space architecture(s). We intend this to be an example of explorer-centric thinking in a fully integrated explorer paradigm, where integrated explorer refers to a human explorer having instant access to all relevant data, knowledge of the environment, science models, health and safety-related events, and other tools and information via wearable computing technologies. The trade study approach will include involvement from the relevant stakeholders (Constellation Systems, CCCI, EVA Project Office, Astronaut office, Mission Operations, Space Life Sciences, etc.) to develop operations concepts (and/or operations scenarios) from which a basic high-level set of requirements could be extracted. This set of requirements could serve as a foundation (along with stakeholder buy-in) that would help define the trade space and assist in identifying candidate technologies for further study and evolution to higher-level technology readiness levels.

Lupisella, Mark↗
NASA NTRS2008

Effective Interpolation of Incomplete Satellite-Derived Leaf-Area Index Time Series for the Continental United States

Many earth science modeling applications employ continuous input data fields derived from satellite data. Environmental factors, sensor limitations and algorithmic constraints lead to data products of inherently variable quality. This necessitates interpolation of one form or another in order to produce high quality input fields free of missing data. The present research tests several interpolation techniques as applied to satellite-derived leaf area index, an important quantity in many global climate and ecological models. The study evaluates and applies a variety of interpolation techniques for the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf-Area Index Product over the time period 2001-2006 for a region containing the conterminous United States. Results indicate that the accuracy of an individual interpolation technique depends upon the underlying land cover. Spatial interpolation provides better results in forested areas, while temporal interpolation performs more effectively over non-forest cover types. Combination of spatial and temporal approaches offers superior interpolative capabilities to any single method, and in fact, generation of continuous data fields requires a hybrid approach such as this.

Jasinski, Michael F.↗
NASA NTRS2012

Earth-Science Data Co-Locating Tool

This software is used to locate Earth-science satellite data and climate-model analysis outputs in space and time. This enables the direct comparison of any set of data with different spatial and temporal resolutions. It is written in three separate modules that are clearly separated for their functionality and interface with other modules. This enables a fast development of supporting any new data set. In this updated version of the tool, several new front ends are developed for new products. This software finds co-locatable data pairs for given sets of data products and creates new data products that share the same spatial and temporal coordinates. This facilitates the direct comparison between the two heterogeneous datasets and the comprehensive and synergistic use of the datasets.

Lee, Seungwon↗