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NASA NTRS2002

Investigation of Dynamic and Physical Processes in the Upper Troposphere and Lower Stratosphere

Research under this Cooperative Agreement has been funded by several NASA Earth Science programs: the Atmospheric Effects of Radiation Program (AEAP), the Upper Atmospheric Research Program (UARP), and most recently the Atmospheric Chemistry and Modeling Assessment Program (ACMAP). The purpose of the AEAP was to understand the impact of the present and future fleets of conventional jet traffic on the upper troposphere and lower stratosphere, while complementary airborne observations under UARP seek to understand the complex interactions of dynamical and chemical processes that affect the ozone layer. The ACMAP is a more general program of modeling and data analysis in the general area of atmospheric chemistry and dynamics, and the Radiation Sciences program.

Selkirk, Henry B.↗

NASA NTRS2015

Towards a Generic and Adaptive System-On-Chip Controller for Space Exploration Instrumentation

This paper introduces one of the first efforts conducted at NASA’s Jet Propulsion Laboratory (JPL) to develop a generic System-on-Chip (SoC) platform to control science instruments that are proposed for future NASA missions. The SoC platform is named APEX-SoC, where APEX stands for Advanced Processor for space Exploration, and is based on a hybrid Xilinx Zynq that combines an FPGA and an ARM Cortex-A9 dual-core processor on a single chip. The Zynq implements a generic and customizable on-chip infrastructure that can be reused with a variety of instruments, and it has been coupled with a set of off-chip components that are necessary to deal with the different instruments. We have taken JPL’s Compositional InfraRed Imaging Spectrometer (CIRIS), which is proposed for NASA icy moons missions, as a use-case scenario to demonstrate that the entire data processing, control and interface of an instrument can be implemented on a single device using the on-chip infrastructure described in this paper. We show that the performance results achieved in this preliminary version of the instrumentation controller are sufficient to fulfill the science requirements demanded to the CIRIS instrument in future NASA missions, such as Europa.

embedded system↗

NASA NTRS2007

Mars Reconnaissance Orbiter Mission: Systems Engineering Challenges on the Mars Reconnaissance Orbiter Mission

MRO project is a system of systems requiring system engineering team to architect, design, integrate, test, and operate these systems at each level of the project. The challenge of system engineering mission objectives into a single mission architecture that can be integrated tested, launched, and operated. Systems engineering must translate high-level requirements into integrated mission design. Systems engineering challenges were overcome utilizing a combination by creative designs built into MRO's flight and ground systems: a) Design of sophisticated spacecraft targeting and data management capabilities b) Establishment of a strong operations team organization; c) Implementation of robust operational processes; and d) Development of strategic ground tools. The MRO system has met the challenge of its driving requirements: a) MRO began its two-year primary science phase on November 7, 2006, and by July 2007, met it minimum requirement to collect 15 Tbits of data after only eight months of operations. Currently we have collected 22 Tbits. b) Based on current performance, mission data return could return 70 Tbits of data by the end of the primary science phase in 2008.

systems engineering↗

NASA NTRS2001

Quantitative Studies in Planetary Volcanism

Scientific research was conducted on volcanic processes on Mars, Venus, Io, the moon, and the Earth. The achievements led to scientific advances in the understanding of volcanic plumes, lava flow emplacements, coronae, and regoliths on the solid surfaces. This research led to multiple publications on each of the main topics of the proposal. Research was also presented at the annual Lunar and Planetary Science Conference at Houston. Typically, this grant contributed to 3-4 presentations each year. This grant demonstrated, numerous times, the usefulness of NASA mission data for advancing the understanding of volcanic processes on other planetary surfaces and the Earth.

Baloga, Stephen M.↗

NASA NTRS2018

NASA's Black Marble Product Suite: Validation Strategy

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500m resolution since January 2012 with data fro the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-terrain, vegetation, snow, lunar and stray light corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Current and planned validation activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at difference geographic locations and time periods representing the full range of retrieval conditions.

GEO Human Planet↗

NASA NTRS1977

Beneficial uses of space

The study elicited over 100 ideas for Space Processing. Of the elicited ideas, more than 20% involved processing of biologicals, or related medical and life sciences applications. Among these were High Purity Separation of Isoenzymes, and Development of Biorhythms applications data. Program planning for four products is outlined. Experimentation and testing resulted in definition of nearly 70 series of tests in ground-based laboratories, sounding rockets, etc., and space shuttle. Development schedules established timing and interrelationships of decisions involved in carrying these products to the point of production. The potential profitability of the four products is determined. Resources needed to achieve full scale production included use of shuttle for transportation, for which cost apportionment model was developed. R and D resources for the four products totalled $46,000,000 with Isoenzymes requiring the smallest expenditure, $4,000,000. A computerized profitability model (INVEST) was used to determine the measures of profitability of each product. Results build confidence that there will be a payoff.

Bloom, H. L.↗

NASA NTRS1983

The NASA MLA program

The NASA Multispectral Linear Array (MLA) program is structured to provide for the evolutionary development of advanced sensor concepts, technologies, and scientific basis for future remote sensing missions. Program elements include the development of multispectral visible and shortwave infrared (SWIR) detector arrays, optics and on-board signal processing technologies, sensor design studies, and supporting research. The research consists of advanced airborne sensor development with data acquisitions, field measurements, and supporting science studies. At the present time, two instrument concepts, including an imaging spectrometer, are in development as payloads for a series of Shuttle remote sensing research flights beginning as early as 1987. Progressively more advanced capability instruments suitable for extended duration Shuttle, free flyer, and space platform missions in the 1990's are also being studied.

Ando, K. J.↗

NASA NTRS1986

Catching the whispers from Uranus

Sophisticated telecommunications techniques are described that were used to acquire images of Uranus, its 14 moons and ten narrow rings darker than coal. The images, equal in quality to those transmitted from Saturn several years earlier despite the signal being weaker by 6 dB due to the increased distance, were received from Voyager 2 during its January 24, 1986 flyby of Uranus. Solutions to the problem of the weakening signal were found in modifications to Voyager's image processing system and NASA's ground tracking network. In April 1985, Voyager's prime flight data computer was reconfigured to accept only nonimaging science data, and its backup, only imaging data; the latter was reprogrammed to determine only arithmetic differences between adjacent pixel intensities rather than absolute intensities. By image compression, equivalent imaging information could be sent at lower bit rates. Instead of Golay coding, Reed-Solomon onboard encoding was used. These techniques gained the equivalent of 4-dB in imaging yield. Additional improvements were gained by using earth station antennas in pairs (the Parkes radio telescope and the Canberra ground station antenna). Moves under way to prepare for the Voyager encounter with Neptune in 1989 are described (using additional antennas and arrays, scaling up the Deep Space Network antennas from 64 m to 70 m, etc.) to assure almost Saturn-equivalent pictures despite a further 3.5-dB drop in signal strength.

Bartok, C. D.↗

NASA NTRS1990

High resolution, high frame rate video technology development plan and the near-term system conceptual design

The objective of the High Resolution, High Frame Rate Video Technology (HHVT) development effort is to provide technology advancements to remove constraints on the amount of high speed, detailed optical data recorded and transmitted for microgravity science and application experiments. These advancements will enable the development of video systems capable of high resolution, high frame rate video data recording, processing, and transmission. Techniques such as multichannel image scan, video parameter tradeoff, and the use of dual recording media were identified as methods of making the most efficient use of the near-term technology.

Ziemke, Robert A.↗

NASA NTRS1992

SPDB (science processing database): Quick reference guide

This contents of this draft copy include: how to log into the SPDB (Science Processing DataBase); how to navigate through menus; how to use ESC keys; how to get help; and how to quit the program. The Science Processing Database is an interactive, on-line system that provides updated information about Earth Observing System Project, including instruments, investigators, output data products, input requirements, retrieval algorithms, and VO datasets archived at DAAC's.

Source record↗

NASA NTRS2005

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes data management of NASA remote sensing data for Northern Eurasia Earth Science Partnership Initiative (NEESPI). Many types of ground and integrative (e.g., satellite, GIs) data will be needed and many models must be applied, adapted or developed for properly understanding the functioning of Northern Eurasia cold and diverse regional system. Mechanisms for obtaining the requisite data sets and models and sharing them among the participating scientists are essential. The proposed project targets integration of remote sensing data from AVHRR, MODIS, and other NASA instruments on board US- satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEPNCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗

NASA NTRS2006

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes the recently awarded ACCESS project to provide data management of NASA remote sensing data for the Northern Eurasia Earth Science Partnership Initiative (NEESPI). The project targets integration of remote sensing data from MODIS, and other NASA instruments on board US-satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEP/NCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗

NASA NTRS2009

TRMM .25 deg x .25 deg Gridded Precipitation Text Product

Since the launch of the Tropical Rainfall Measuring Mission (TRMM), the Precipitation Measurement Missions science team has endeavored to provide TRMM precipitation retrievals in a variety of formats that are more easily usable by the broad science community than the standard Hierarchical Data Format (HDF) in which TRMM data is produced and archived. At the request of users, the Precipitation Processing System (PPS) has developed a .25 x .25 gridded product in an easily used ASCII text format. The entire TRMM mission data has been made available in this format. The paper provides the details of this new precipitation product that is designated with the TRMM designator 3G68.25. The format is packaged into daily files. It provides hourly precipitation information from the TRMM microwave imager (TMI), precipitation radar (PR), and TMI/PR combined rain retrievals. A major advantage of this approach is the inclusion only of rain data, compression when a particular grid has no rain from the PR or combined, and its direct ASCII text format. For those interested only in rain retrievals and whether rain is convection or stratiform, these products provide a huge reduction in the data volume inherent in the standard TRMM products. This paper provides examples of the 3G68 data products and their uses. It also provides information about C tools that can be used to aggregate daily files into larger time samples. In addition, it describes the possibilities inherent in the spatial sampling which allows resampling into coarser spatial sampling. The paper concludes with information about downloading the gridded text data products.

Stocker, Erich↗

NASA NTRS2010

Kepler Mission's Focal Plane Characterization Models Implementation

The Kepler Mission photometer is an unusually complex array of CCDs. A large number of time-varying instrumental and systemic effects must be modeled and removed from the Kepler pixel data to produce light curves of sufficiently high quality for the mission to be successful in its planet-finding objective. After the launch of the spacecraft, many of these effects are difficult to remeasure frequently, and various interpolations over a small number of sample measurements must be used to determine the correct value of a given effect at different points in time. A library of software modules, called Focal Plane Characterization (FC) Models, is the element of the Kepler Science Data Pipeline (hereafter "pipeline") that handles this. FC, or products generated by FC, are used by nearly every element of the SOC processing chain. FC includes Java components: database persistence classes, operations classes, model classes, and data importers; and MATLAB code: model classes, interpolation methods, and wrapper functions. These classes, their interactions, and the database tables they represent, are discussed. This paper describes how these data and the FC software work together to provide the pipeline with the correct values to remove non-photometric effects caused by the photometer and its electronics from the Kepler light curves. The interpolation mathematics is reviewed, as well as the special case of the sky-to-pixel,pixel-to-sky coordinate transformation code, which incorporates a compound model that is unique in the SOC software.

mission↗

NASA NTRS2021

NASA Framework for the Ethical Use of Artificial Intelligence (AI)

The NASA Framework for the Ethical Use of Artificial Intelligence (AI) provides six key principles to guide NASA's use of AI. The principles are NASA's AI must be 1. Fair, 2., Explainable and transparent, 3. Accountable, 4. Secure and safe, 5. Human-centric and societally beneficial, and 6. Scientifically and technically robust. The framework describes each ethical AI principle, and then applies that principle to NASA work. The framework also includes a list of questions practitioners should use to guide their AI work. Finally, the framework focuses on concrete, practical considerations for the next five - ten years, while also beginning to lay the foundation for longer-term disruptive change as human-level (or beyond) AI is created.

Artificial Intelligence↗

NASA NTRSDate not supplied

Exploring the Moon: Training Astronauts for Artemis Missions

For the first time in over 50 years, NASA scientists are training astronauts assigned to lunar missions. The successful Artemis 1 test flight in 2022 set the stage for future human missions to the Moon. The Artemis II mission will send astronauts to fly by the Moon, providing the first opportunity since Apollo for humans to directly observe and document the lunar surface from a few thousand kilometers, including the lunar far side. Artemis III will be the first human mission to land and explore the Moon’s surface near the lunar South Pole. To prepare for Artemis exploration, geology training for the Artemis II crew and detailed training plans for Artemis III and beyond are in full swing. NASA scientists have been working for several years with the Flight Operations Directorate (FOD) at the Johnson Space Center on a progressive geology training program that starts with incoming astronaut classes, offers opportunities to maintain the geology proficiency between flight assignments, and trains the broader engineering-operations-management community in geology and field operations. In the spring of 2023, our team developed an introductory week-long class called Lunar Fundamentals and delivered this content to the Artemis II crew, as well as key NASA Flight Control Team members. The Lunar Fundamentals curriculum combines basic geographic and geologic information about the Moon; includes detailed content on major geologic processes, the lunar environment, lunar volatiles, and sample science; provides historical context of our growing knowledge about the Moon; and introduces new lunar data sets and tools for exploring the lunar surface. With the Lunar Fundamentals foundation, we continue development of the advanced planetary science classroom content for the Artemis III crew, together with field training science objectives and plans. Partnering with our FOD colleagues, we are building an integrated training plan for lunar science, exploration field methods, and operational skills to ensure that the Artemis astronauts exploring the Moon will have the necessary foundation in geology and lunar science to achieve mission success.

Astronauts training↗

NASA NTRSDate not supplied

Harmonizing Multi-Disciplinary Data for Applied Research: A Comprehensive Analysis of GES DISC Datasets through NLP and TF-IDF Techniques

Data centers distribute data encompassing multiple disciplines, making it necessary to evaluate dataset applicability to applied research. Typically, these datasets are generated by specialized science teams and consist of single-discipline data, such as atmospheric temperature, pressure, and precipitation, leading to unique dataset formats and access services. However, in applied research, the utilization of datasets from multiple disciplines is commonly necessary. The increasing availability of research literature citing Earth Science datasets presents an opportunity to analyze the usage of datasets in multi-disciplinary research. This study proposes a novel approach wherein research publications citing datasets archived at the GES DISC (Goddard Earth Sciences Data and Information Services Center) are collected, and each publication is associated with specific research topics through the application of Natural Language Processing (NLP), using the Term Frequency Inverse Document Frequency (TF-IDF) technique on the publication titles and abstracts. Through this analysis, we gain insights into the distribution of dataset disciplines as they are being used in various applied research areas. This knowledge is essential for the development of dataset tools and services tailored to effectively support applied research studies, as it enhances a data center's comprehension of how datasets from multiple disciplines are integrated into research endeavors.

Infometrics↗

NASA NTRS2016

The Teaching of Anthropogenic Climate Change and Earth Science via Technology-Enabled Inquiry Education

A gap has existed between the tools and processes of scientists working on anthropogenic global climate change (AGCC) and the technologies and curricula available to educators teaching the subject through student inquiry. Designing realistic scientific inquiry into AGCC poses a challenge because research on it relies on complex computer models, globally distributed data sets, and complex laboratory and data collection procedures. Here we examine efforts by the scientific community and educational researchers to design new curricula and technology that close this gap and impart robust AGCC and Earth Science understanding. We find technology-based teaching shows promise in promoting robust AGCC understandings if associated curricula address mitigating factors such as time constraints in incorporating technology and the need to support teachers implementing AGCC and Earth Science inquiry. We recommend the scientific community continue to collaborate with educational researchers to focus on developing those inquiry technologies and curricula that use realistic scientific processes from AGCC research and/or the methods for determining how human society should respond to global change.

technology↗