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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Shadow of the Future: Developing Trust and Software within the Exascale Computing Project

Collaboration and team science are emerging areas of interest in software production. Historically, multi-institutional research collaborations are difficult to initiate and maintain, negatively impacting communication, negotiation, and dialogue between industry, government, and academic researchers. The Exascale Computing Project (ECP), a massive, multi-team, high-stakes initiative, facilitated broader research collaboration under a shared funding structure and extended timeline to support scientific discovery. Here, we conducted interviews with ECP teams, representing a variety of domain specialties, research institutions, and programming backgrounds. Using thematic analysis, we assessed how ECP’s structure created an environment of increased trust among projects and how software shared between teams facilitated sustained collaboration. We found that the expectation of future collaboration, i.e., the shadow of the future, greatly enhanced trust among teams and the quality of scientific software produced. Based on our findings within ECP projects, we connect to the existing literature on trust in software engineering and share recommendations for sustainable multi-institutional collaboration and shared best software practices.

Exascale computing project↗
NASA NTRS2006

From Prime to Extended Mission: Evolution of the MER Tactical Uplink Process

To support a 90-day surface mission for two robotic rovers, the Mars Exploration Rover mission designed and implemented an intensive tactical operations process, enabling daily commanding of each rover. Using a combination of new processes, custom software tools, a Mars-time staffing schedule, and seven-day-a-week operations, the MER team was able to compress the traditional weeks-long command-turnaround for a deep space robotic mission to about 18 hours. However, the pace of this process was never intended to be continued indefinitely. Even before the end of the three-month prime mission, MER operations began evolving towards greater sustainability. A combination of continued software tool development, increasing team experience, and availability of reusable sequences first reduced the mean process duration to approximately 11 hours. The number of workshifts required to perform the process dropped, and the team returned to a modified 'Earth-time' schedule. Additional process and tool adaptation eventually provided the option of planning multiple Martian days of activity within a single workshift, making 5-day-a-week operations possible. The vast majority of the science team returned to their home institutions, continuing to participate fully in the tactical operations process remotely. MER has continued to operate for over two Earth-years as many of its key personnel have moved on to other projects, the operations team and budget have shrunk, and the rovers have begun to exhibit symptoms of aging.

mission operations↗
NASA NTRS2006

From Prime to Extended Mission: Evolution of the MER Tactical Uplink Process

To support a 90-day surface mission for two robotic rovers, the Mars Exploration Rover mission designed and implemented an intensive tactical operations process, enabling daily commanding of each rover. Using a combination of new processes, custom software tools, a Mars-time staffing schedule, and seven-day-a-week operations, the MER team was able to compress the traditional weeks-long command-turnaround for a deep space robotic mission to about 18 hours. However, there was never an intention of maintaining the pace of this process indefinitely. Even before the end of the three-month prime mission, MER operations began evolving towards greater sustainability. A combination of continued software tool development, increasing team experience, and availability of reusable sequences first reduced the mean process duration to approximately 11 hours. The number of workshifts required to perform the process dropped, and the team returned to a modified 'Earth-time' schedule. Additional process and tool adaptation eventually provided the option of planning multiple Martian days of activity within a single workshift, making 5- day-a-week operations possible. The vast majority of the science team returned to their home institutions, continuing to participate fully in the tactical operations process remotely. MER has continued to operate for over two Earth-years as many of its key personnel have moved on to other projects, the operations team and budget have shrunk, and the rovers have begun to exhibit symptoms of aging.

Mars exploration↗
NASA NTRSDate not supplied

Digital Lunar Exploration Sites (DLES)

After an almost 50-year absence, NASA along with a group of international and commercial partners will return humans to the surface of the Moon as part of the Artemis program. As with the preceding Apollo program, modeling and simulation (M&S) will be an enabling technology for achieving the Artemis mission objectives. Fortunately, M&S has advanced considerably in the past half century, permitting much more detailed and encompassing integrated representations of the Artemis systems. One modeling area of critical importance to simulating the Artemis elements and mission activities is the accurate and efficient modeling of the operational lunar environment. This is particularly challenging since the Artemis program is considering exploration sites in the area of the Lunar South Pole (LSP), far away from any previous surface exploration sites. Fortunately, we now have considerably more and better data from recent lunar sensing missions. A planetary science team and a human exploration simulation team at NASA’s Johnson Space Center are developing a suite of products called the Digital Lunar Exploration Sites (DLES). DLES is intended to provide some of the necessary lunar environmental data products. This paper describes the fundamental need for DLES, the science data sets that are going into DLES, some of the processes used to integrate this data into DLES products, the basic products that constitute DLES, and some examples of DLES in use.

DLES↗
NASA NTRSDate not supplied

Digital Lunar Exploration Sites (DLES)

After an almost 50-year absence, NASA along with a group of international and commercial partners will return humans to the surface of the Moon as part of the Artemis program. As with the preceding Apollo program, modeling and simulation (M&S) will be an enabling technology for achieving the Artemis mission objectives. Fortunately, M&S has advanced considerably in the past half century, permitting much more detailed and encompassing integrated representations of the Artemis systems. One modeling area of critical importance to simulating the Artemis elements and mission activities is the accurate and efficient modeling of the operational lunar environment. This is particularly challenging since the Artemis program is considering exploration sites in the area of the Lunar South Pole (LSP), far away from any previous surface exploration sites. Fortunately, we now have considerably more and better data from recent lunar sensing missions. A planetary science team and a human exploration simulation team at NASA’s Johnson Space Center are developing a suite of products called the Digital Lunar Exploration Sites (DLES). DLES is intended to provide some of the necessary lunar environmental data products. This paper describes the fundamental need for DLES, the science data sets that are going into DLES, some of the processes used to integrate this data into DLES products, the basic products that constitute DLES, and some examples of DLES in use.

DLES↗
NASA NTRSDate not supplied

Artificial Intelligence (AI) Methods for Augmenting the IMPACT Tool Evidence Library

Development of the Evidence Library for use with the IMPACT probability risk assessment tool took several years and involved a staggering amount of effort from a multi-disciplinary team. A very significant amount of the labor effort to collect, assess and finalize the Clinical Finding Form (CliFF) for each of the 119 medical conditions was provided by physician subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team. Many AI tools such as ChatGPT are excellent at summarizing large amounts of information and the current project was initiated to determine how such tools might streamline laborious processes, e.g., review and summarization of many scientific research publications, to execute key steps more efficiently in the process of developing CliFFs. The process for collecting the evidence which is found in the CliFFs is well documented in the Evidence Library Methods document (ELM; HRP-48036*). Using ELM and the CliFF development instructions as a guideline, a team of developers is leveraging Microsoft Azure AI tools and services along with open-source frameworks, to construct an AI-assisted automated pipeline. This pipeline is designed to search, retrieve, and process the necessary data sources, and ultimately help generate the final version of a CliFF. Currently, the large language model evaluates the relevance of each source material to spaceflights, either as direct evidence or as an analog. Additionally, the model assists in extracting keywords and generating brief summaries to enhance augmented retrieval and search processes in later stages of CliFF development. Once the data is ready, the model can perform semantic search and retrieval, generating and extracting valuable information for the CliFF. For instance, it can handle epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. The steps that required reading and summarizing articles were viewed as providing the greatest return on investment since large language models are very efficient and accurate in summarizing large amounts of text. Since labor effort to complete the original CliFF was not recorded with sufficient granularity, comparisons with an AI tool-generated CliFF will provide merely an approximation of time saved. Upon completion of the process, the CliFF for the medical condition “appendicitis” generated with the support of AI-based methods will serve as a proof-of-concept and will be compared to the original appendicitis CliFF to determine if use of the tools resulted in content and conclusory similarity. Based upon the results from face validation of the two CliFFs, modifications to the process will be made if necessary and additional condition CliFFs will be evaluated. Ultimately, CliFFs for the entire set of medical conditions will be created with the assistance of AI tools. Depending on the cost savings realized, CliFFs for additional medical conditions can be created to expand the Evidence Library. Future direction includes specifying the characteristics of the reviewer (prompting the AI tools to generate output assuming the reviewer is a sub-specialist physician, or nurse or EMT/medic) to determine if the effects on AI-generated output are different based on knowledge, skills and abilities. *Exploration Medical Capability Evidence Library Methods, HRP-48036 Rev A, July 2022.

Ali Al↗
NASA NTRS2006

Cassini distributed instrument operations – what we’ve learned since Saturn orbit insertion

The Cassini mission to Saturn is complex with 12 science teams conducting distributed operations across the United States and Europe. Each Team includes scientists from around the world who actively participate in operations, including observation design, instrument commanding, downlink processing, and archiving. This represents a change in how JPL complex deep-space missions have been operated. Since Saturn Orbit Insertion (SOI), the Cassini Project has spent 17 months conducting science operations and has gained realworld experience that has tested the assumptions and rationale for this approach. We have learned that many of the expected benefits have been realized, but there were numerous unexpected challenges as well. This paper will discuss the lessons learned from the Cassini Tour experience to date. It will revisit the assumptions and rationale behind the distributed instrument operations design and will describe the results, good and bad, of implementing this method of operations. We will describe how Instrument Teams are structured, their roles and responsibilities, what challenges they faced going into orbital operations (the “tour”) and what creative solutions were proposed when funding limitations and schedule milestones prevented optimum solutions. We will also discuss the problems that have been encountered both on the ground and with the instruments, how these problems and anomalies were overcome, and what was learned along the way about the characteristics of distributed instrument operations.

Woncik, Pam↗
NASA NTRS2006

Cassini Distributed Instrument Operations: What We've Learned Since Saturn Orbit Insertion

The Cassini mission to Saturn is complex with 12 science teams conducting distributed operations across the United States and Europe. Each Team includes scientists from around the world who actively participate in operations, including observation design, instrument commanding, downlink processing, and archiving. This represents a change in how JPL complex deep-space missions have been operated. Since Saturn Orbit Insertion (SOI), the Cassini Project has spent 17 months conducting science operations and has gained real-world experience that has tested the assumptions and rationale for this approach. We have learned that many of the expected benefits have been realized, but there were numerous unexpected challenges as well. This paper will discuss the lessons learned from the Cassini Tour experience to date. It will revisit the assumptions and rationale behind the distributed instrument operations design and will describe the results, good and bad, of implementing this method of operations. We will describe how Instrument Teams are structured, their roles and responsibilities, what challenges they faced going into orbital operations (the 'tour') and what creative solutions were proposed when funding limitations and schedule milestones prevented optimum solutions. We will also discuss the problems that have been encountered both on the ground and with the instruments, how these problems and anomalies were overcome, and what was learned along the way about the characteristics of distributed instrument operations.

Cassini↗
NASA NTRS2017

Improvements in the On-Orbit Response Versus Scan Angle Characterization of the Aqua MODIS Reflective Solar Bands

The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) has been chosen by the Global Space-based Inter-Calibration System operational community as the reference sensor in cross-sensor calibration. A number of geostationary orbit and low-earth orbit sensors use the 0.64-μm band from Aqua MODIS as a calibration reference. After over 15 years on-orbit, the performance characteristics of the MODIS instrument have changed, with effects evident at short wavelengths. MODIS employs a reflectance-based calibration using the solar diffuser measurements with the monthly lunar observations facilitating a response versus scan angle characterization on-orbit. As the instrument continues to operate beyond its design lifetime of 6 years, the on-board calibrators alone are insufficient to accurately characterize the instrument's response at all scan angles. This results in a long-term reflectance drift, particularly observed in the 0.64- and 0.85-μm bands, while observing the temporally invariant desert sites. Long-term reflectance drifts of up to 2% and 3% are observed at the beginning of scan for the 0.64- and 0.85-μm bands, respectively. An approach using earth-view response to supplement the on-board calibrator measurements has been shown to overcome these inadequacies and is now implemented for the 0.64-, 0.85-, 0.46-, and 0.55-μm land bands of Aqua MODIS. This paper presents the details related to the algorithm implementation and an independent evaluation using the Dome Concordia site and deep-convective clouds. This approach has been reviewed, tested, and approved by the MODIS science team and has been implemented in the forward production of the MODIS L1B Collection 6 starting July 9, 2016. This enhanced approach has also been adopted in the MODIS L1B Collection 6.1 reprocess for the entire mission to facilitate an improved quality of downstream science products. The results with the enhanced approach reduce the reflectance drifts to within 0.5% for most cases.

Angal, Amit↗
NASA NTRS2011

Crew Field Notes: A New Tool for Planetary Surface Exploration

The Desert Research and Technology Studies (DRATS) field tests of 2010 focused on the simultaneous operation of two rovers, a historical first. The complexity and data volume of two rovers operating simultaneously presented significant operational challenges for the on-site Mission Control Center, including the real time science support function. The latter was split into two "tactical" back rooms, one for each rover, that supported the real time traverse activities; in addition, a "strategic" science team convened overnight to synthesize the day's findings, and to conduct the strategic forward planning of the next day or days as detailed in [1, 2]. Current DRATS simulations and operations differ dramatically from those of Apollo, including the most evolved Apollo 15-17 missions, due to the advent of digital technologies. Modern digital still and video cameras, combined with the capability for real time transmission of large volumes of data, including multiple video streams, offer the prospect for the ground based science support room(s) in Mission Control to witness all crew activities in unprecedented detail and in real time. It was not uncommon during DRATS 2010 that each tactical science back room simultaneously received some 4-6 video streams from cameras mounted on the rover or the crews' backpacks. Some of the rover cameras are controllable PZT (pan, zoom, tilt) devices that can be operated by the crews (during extensive drives) or remotely by the back room (during EVAs). Typically, a dedicated "expert" and professional geologist in the tactical back room(s) controls, monitors and analyses a single video stream and provides the findings to the team, commonly supported by screen-saved images. It seems obvious, that the real time comprehension and synthesis of the verbal descriptions, extensive imagery, and other information (e.g. navigation data; time lines etc) flowing into the science support room(s) constitute a fundamental challenge to future mission operations: how can one analyze, comprehend and synthesize -in real time- the enormous data volume coming to the ground? Real time understanding of all data is needed for constructive interaction with the surface crews, and it becomes critical for the strategic forward planning process.

Horz, Friedrich↗
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 NTRS1988

The Shuttle Imaging Radar B (SIR-B) experiment report

The primary objective of the SIR-B experiment was to acquire multiple-incidence-angle radar imagery of a variety of Earth's surfaces to better understand the effects of imaging geometry on radar backscatter. A complementary objective was to map extensive regions of particular interest. Under these broad objectives, many specific scientific experiments were defined by the 43 SIR-B Science Team members, including studies in the area of geology, vegetation, radar penetration, oceanography, image analysis, and calibration technique development. Approximately 20 percent of the planned digital data were collected, meeting 40 percent of the scientific objectives. This report is an overview of the SIR-B experiment and includes the science investigations, hardware design, mission scenario, mission operations, events of the actual missions, astronaut participation, data products (including auxiliary data), calibrations, and a summary of the actual coverage. Also included are several image samples.

Cimino, Jo Bea↗
NASA NTRS2007

Key and Driving Requirements for the Juno Payload of Instruments

The Juno Mission was selected in the summer of 2005 via NASA's New Frontiers competitive AO process (refer to http://www.nasa.gov/home/hqnews/2005/jun/HQ_05138_New_Frontiers_2.html). The Juno project is led by a Principle Investigator based at Southwest Research Institute [SwRI] in San Antonio, Texas, with project management based at the Jet Propulsion Laboratory [JPL] in Pasadena, California, while the Spacecraft design and Flight System Integration are under contract to Lockheed Martin Space Systems Company [LM-SSC] in Denver, Colorado. the payload suite consists of a large number of instruments covering a wide spectrum of experimentation. The science team includes a lead Co-investigator for each one of the following experiments: A Magnetometer experiment (consisting of both a FluxGate Magnetometer (FGM) built at Goddard Space Flight Center GSFC] and a Scalar Helium Magnetometer (SHM) built at JPL, a MicroWave Radiometer (MWR) also built at JPL, a Gravity Science experiment (GS) implemented via the telecom subsystem, two complementary particle instruments (Jovian Auroral Distribution Experiment, JADE developed by SwRI and Juno Energetic-particle Detector Instrument, JEDI from the Applied Physics Lab (APL)--JEDI and JADE both measure electrons and ions), an Ultraviolet Spectrometer (UVS) also developed at SwRI, and a radio and plasma (WAVES) experiment (from the University of Iowa). In addition, a visible camera (JunoCam) is included in the payload to facilitate education and public outreach (designed & fabricated by Malin Space Science Systems [MSSS]).

challenges↗
NASA NTRS2007

Overview of TRMM Data Products and Services

November 27, 2007 marks the l0th anniversary of the launch of the Tropical Rainfall Measuring Mission (TRMM) satellite. In anticipation of this anniversary, this paper will present an overview of the various TRMM data products currently available including the standard products, near real-time products, special products, and prototype products. It also will present an easy way to obtain these data. TRMM standard products have been publicly available since a few months after launch in November 1997. TRMM is currently on version 6 of the data product. Version 3 was the "at launch" version. The approval for each of these versions came through the Joint TRMM Science Team. Standard products are divided into 3 categories: single TRMM instrument, Visible Infrared Scanner (VIRS), TRMM Microwave Imager (TMI), and Precipitation Radar (PR); combined TRMM products (PR and TMI); finally TRMM and other satellites (combined, TMI, SSMI, AMSRE, AMSU). The single TRMM instrument products are processed through 4 levels: Level lA, science data packets processed into orbital files; Level 1B and lC, geolocated data at the instrument field of view; Level 2, geolocated, geophysical parameters at the instrument field of view; Level 3, time aggregated, gridded geophysical parameters. These products are available with 24 hours of production through an anonymous ftp account on trmmopen.gsfc.nasa.gov. The TRMM data system started to produce near real-time products at the end of 1999. They are currently available only through a controlled user account. However, approval to get access to this account can be obtained by sending a note to Erich.F.Stoclter@nasa.gov providing the reason for access and contact information including a valid email. TRMM is not restricting access but needs the information to determine the usefulness of near-real time data to the general science community including applications agencies. TRMM near real-time products are swath products up to Level 2 of processing. The oldest data in the swath is generally no older than 120 minutes when it becomes available to the community. The real-time products including a VIRS level lB, a TMI parameter reduced 1B, a TMI level 2 parameter reduced rain product, a PR level 2 surface rain product, and a PR level 2 rain product with 25 vertical levels. Currently, TRMM also produces a gridded 3 hour global merged product from several radiometers including AMSU and from radiometercalibrated IR data. The paper also describes several simple-format gridded text products available fiom the trmmopen.gsfc.nasa.gov anonymous fip server denoted as 3668 products. These products were produced to provide rain estimates from the three TRMM instruments in a universal format (ASCII) that requires very little data format knowledge. The paper goes on to describe prototype L1 radiometer products that apply an early intercalibration approach that provides a starting point to be used for Global Precipitation Measurement mission radiometer products. The paper also provides a brief overview of a precipitation features data product being produced using TRMM products including the Lighting Imaging Sensor (LIS) using an algorithm developed at the University of Utah and distributed by that organization. The paper concludes with some possible changes to products that are planned for the next reprocessing cycle and special services such as geographical subsetting available to the science community.

Stocker, Erich Franz↗
NASA NTRS2000

First Astronaut- Rover Interaction Field Test

The first Astronaut - Rover (ASRO) Interaction field test was conducted successfully on February 22-27, 1999, in Silver Lake, Mojave Desert, California in a representative planetary surface terrain. This test was a joint effort between the NASA Ames Research Center , Moffett Field, California and the NASA Johnson Space Center, Houston, Texas. As prototype advanced planetary surface space suit and rover technologies are being developed for human planetary surface exploration , it has been determined that it is important to better understand the potential interaction and benefits of an EVA astronaut interacting with a robotic rover . This interaction between an EVA astronaut and a robotic rover is seen as complementary and can greatly enhance the productivity and safety of surface excursions . This test also identified design requirements and options in an advanced space suit and robotic rover. The test objectives were: 1. To identify the operational domains where the EVA astronauts and rover are complementary and can interact and thus collaborate in a safe , productive and cost- effective way, 2. To identify preliminary requirements and recommendations for advanced space suits and rovers that facilitate their cooperative and complementary interaction, 3. To develop operational procedures for the astronaut-rover teams in the identified domains, 4. To test these procedures during representative mission scenarios during field tests by simulating the exploration of a planetary surface by an EVA crew interacting with a robotic rover, 5. To train a space suited test subject, simulated Earth-based and l or lander-based science teams, and robotic vehicle operators in mission configurations, and 6. To evaluate and understand socio-technical aspects of the astronaut - rover interaction experiment in order to guide future technologies and designs. Test results and areas for future research in the design of planetary space suits will be discussed .

Kosmo, Joseph J.↗
NASA NTRS1998

NASA Lewis' Telescience Support Center Supports Orbiting Microgravity Experiments

The Telescience Support Center (TSC) at the NASA Lewis Research Center was developed to enable Lewis-based science teams and principal investigators to monitor and control experimental and operational payloads onboard the International Space Station. The TSC is a remote operations hub that can interface with other remote facilities, such as universities and industrial laboratories. As a pathfinder for International Space Station telescience operations, the TSC has incrementally developed an operational capability by supporting space shuttle missions. The TSC has evolved into an environment where experimenters and scientists can control and monitor the health and status of their experiments in near real time. Remote operations (or telescience) allow local scientists and their experiment teams to minimize their travel and maintain a local complement of expertise for hardware and software troubleshooting and data analysis. The TSC was designed, developed, and is operated by Lewis' Engineering and Technical Services Directorate and its support contractors, Analex Corporation and White's Information System, Inc. It is managed by Lewis' Microgravity Science Division. The TSC provides operational support in conjunction with the NASA Marshall Space Flight Center and NASA Johnson Space Center. It enables its customers to command, receive, and view telemetry; monitor the science video from their on-orbit experiments; and communicate over mission-support voice loops. Data can be received and routed to experimenter-supplied ground support equipment and/or to the TSC data system for display. Video teleconferencing capability and other video sources, such as NASA TV, are also available. The TSC has a full complement of standard services to aid experimenters in telemetry operations.

Hawersaat, Bob W.↗
NASA NTRS2000

Gravitational Physics Research

Gravitational physics research at ISPAE is connected with NASA's Relativity Mission (Gravity Probe B (GP-B)) which will perform a test of Einstein's General Relativity Theory. GP-B will measure the geodetic and motional effect predicted by General Relativity Theory with extremely stable and sensitive gyroscopes in an earth orbiting satellite. Both effects cause a very small precession of the gyroscope spin axis. The goal of the GP-B experiment is the measurement of the gyroscope precession with very high precision. GP-B is being developed by a team at Stanford University and is scheduled for launch in the year 2001. The related UAH research is a collaboration with Stanford University and MSFC. This research is focussed primarily on the error analysis and data reduction methods of the experiment but includes other topics concerned with experiment systems and their performance affecting the science measurements. The hydrogen maser is the most accurate and stable clock available. It will be used in future gravitational physics missions to measure relativistic effects such as the second order Doppler effect. The HMC experiment, currently under development at the Smithsonian Astrophysical Observatory (SAO), will test the performance and capability of the hydrogen maser clock for gravitational physics measurements. UAH in collaboration with the SAO science team will study methods to evaluate the behavior and performance of the HMC. The GP-B data analysis developed by the Stanford group involves complicated mathematical operations. This situation led to the idea to investigate alternate and possibly simpler mathematical procedures to extract the GP-B measurements form the data stream. Comparison of different methods would increase the confidence in the selected scheme.

Wu, S. T.↗
NASA NTRS2006

The NPOESS Preparatory Project Science Data Segment: Brief Overview

The NPOESS Preparatory Project (NPP) provides remotely-sensed land, ocean, atmospheric, ozone, and sounder data that will serve the meteorological and global climate change scientific communities while also providing risk reduction for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government s future low-Earth orbiting satellite system monitoring global weather and environmental conditions. NPOESS and NPP are a new era, not only because the sensors will provide unprecedented quality and volume of data but also because it is a joint mission of three federal agencies, NASA, NOAA, and DoD. NASA's primary science role in NPP is to independently assess the quality of the NPP science and environmental data records. Such assessment is critical for making NPOESS products the best that they can be for operational use and ultimately for climate studies. The Science Data Segment (SDS) supports science assessment by assuring the timely provision of NPP data to NASA s science teams organized by climate measurement themes. The SDS breaks down into nine major elements, an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. This paper will describe how the NPP SDS will leverage on NASA experience to provide a mission-reliable research capability for science assessment of NPP derived measurements.

Schweiss, Robert J.↗