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The Radio Science experiments at Voyager 1 Saturn encounter which included two atmospheric occultations, a planetary ring occultation, and ring scattering experiment were supported by Deep Space Stations in Australia (DSS 43) and Spain (DSS 63). The DSN Radio Science System data flow from receipt of the radio signals at the antenna to delivery of the recorded data to the project are described.
Trends in the areas of science, data systems, instruments and space technologies and their related infrastructures that will be experienced in earth remote sensing activities from LEO in the 1990s are discussed. Interdisciplinary studies will examine the flow of energy through the earth system, encompassing surveys of atmospheric and ocean circulations, the hydrologic cycle, and biogeochemical cycles. Mainframe computer assimilation of large data inputs will be associated with distributed microcomputer processing and analyses. Single satellite antennas will scan several microwave frequencies simultaneously, e.g., taking data on vegetation, water, and ice. Broadening the range of simultaneous observations will require multiinstrumented free-flying platforms, placed in orbit, repaired and/or retrieved by the Shuttle. Future instrumentation will include visible/IR imagers and the multifrequency microwave sounders with capabilities mainly limited by the availability of sufficient data-handling facilities.
Software assets from existing Earth science missions can be reused for the new decadal survey missions that are being planned by NASA in response to the 2007 Earth Science National Research Council (NRC) Study. The new missions will require the development of software to curate, process, and disseminate the data to science users of interest and to the broader NASA mission community. In this paper, we discuss new tools and a blossoming community that are being developed by the Earth Science Data System (ESDS) Software Reuse Working Group (SRWG) to improve capabilities for reusing NASA software assets.
NASA's Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has as its key measurement objective the frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements at 10 km and 3 km resolutions respectively, would enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections Soil moisture measurements are also of great importance in assessing floods and for monitoring drought. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. The SMAP measurement concept utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The SMAP radiometer and radar flight hardware and ground processing designs are incorporating approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). The radar and radiometer instruments are planned to operate in a 680 km polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments would yield global maps of soil moisture and freeze/thaw state to be provided at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. This product and the underlying brightness temperatures have characteristics similar to those provided by the Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are unique opportunities for common data product development and continuity between the two missions. SMAP also has commonalities with other satellite missions having L-band radiometer and/or radar sensors applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.
This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project.
NASA's Earth Science Data Systems process, archive and distribute petabytes of Earth Observation data to a variety of end users. These end users will face dramatically increased data size in the near future, bringing about new challenges and opportunities in analyzing those data. One area of particular ferment currently is Machine Learning. Many Machine Learning methods are black boxes, limiting direct insight into the data's properties. However, they can be used for a variety of data enhancement purposes, such as parameter retrieval, data fusion and image classification and segmentation. The Earth Observing System Data and Information System is also evolving to host large data volumes in the cloud, enabling data proximal analysis. As part of this effort, an Analytics framework is being developed to support and enhance user analysis of the data. By using standards based services in the framework, diverse user communities can be served, while also allowing inter-system collaboration in the analysis process.
Science data systems can enable more comprehensive Earth system research by evolving to take advantage of advances in commercial computer technology services. Since their inception twenty five years ago, NASA's Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs) have periodically evolved to utilize new technology and expand research using the exponential growth and diversity of Earth observations. Recently, with the advent of a maturing commercial compute services industry and upcoming high data volume missions such as the Surface Water and Ocean Topography (SWOT) mission and the NASA-Indian Space Research Organization Synthetic Aperture Radar (NISAR) mission, options were explored and a decision made to utilize commercial compute and storage services. This paper presents an overview of the concept of operations under development for the DAACs in the Cloud. We highlight the goals and expected advantages of utilizing Cloud services. We outline EOSDIS operations tenets and driving principles. A high-level view of EOSDIS system of systems target architecture serves as context for describing principle interactions. Concepts for key DAAC system and EOSDIS enterprise functions characterize automated end-to-end operations but mark nominal check and recovery points. Concepts are presented for managing Cloud resources, including organizational roles and responsibilities of the NASA project and DAAC personnel. Scenarios we use to further distinguish between what the system will do and what configuration and controls operators will have. Examples include interactions with data providers and data consumers with both in-cloud and on-premise facilities.
This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project.
Given the reality of a Big Data future, we need to reevaluate our ability to quickly process immense amounts of data while maintaining our responsibility of stewarding our archives. At National Aeronautics and Space Administration (NASA), our Science Missions Directorate and Earth Science Data Systems have been exploring the commercial cloud as a potential mechanism for data ingest, archive, and distribution since 2015. This talk will discuss our timeline and strategies being employed and will discuss the process of introducing commercial cloud entities into a largely on-premise hardware-reliant approach to ingest, archive, and distribution. We will address topics such as vendor lock-in, varying compute and costing strategies, and end-user adoption. Please join us for an open and authentic conversation about the opportunities we are embracing and the risks we are undertaking as a part of this evolution.
Algorithm Theoretical Basis Documents (ATBDs) are documents which accompany Earth observation data products generated from algorithms. While ATBDs are essential to scientific reproducibility, these key documents are not standardized and are often difficult to find. In this paper, we present the prototype Algorithm Publication Tool (APT), a cloud-based ATBD authoring and editing tool for NASA’s Earth science data systems. A standardized ATBD information model is also described as well as lessons learned from developing the prototype tool.
The number of variables measured during airborne field campaigns has increased more than tenfold over the last thirty years. With this increase in measurements, the complexity for distributed active archive centers (DAACs) to distribute the data and for data users to search for and find measurements of interest has also increased. Part of this complexity arises from the unique variable names in suborbital atmospheric composition field studies. With limited guidelines related to variable naming, variable names and structures can vary significantly, even for the same type of variable. It is common for instrument scientists to use their intended measurable quantity as the data variable name. This can make it difficult for users to locate and interact with a particular variable across multiple data sets. One effective solution to this problem, identified by the Earth Science Data System (ESDS) ICARTT Refresh Working Group [1], was to introduce variable standard names that can be used as tags for each data variable. This allows similar measurements (e.g., dew point) to be categorized and located across field campaigns, regardless of what variable name the instrument scientist has used. From this the atmospheric composition variable standard names were developed with the goal to use Findable, Accessible, Interoperable, and Reusable (FAIR) principles [2] and provide context for all users, while remaining connected to those in the subject area. These standard names have been successfully implemented in FIREX-AQ, CAMP 2EX, ACTIVATE, and DCOTSS field campaigns.
The purpose of this paper is to discuss how the Climate and Forecast (CF) Metadata Conventions and netCDF standard have influenced the recommendations and guidance provided to producers of data products based on NASA’s Earth observations. It has been long-recognized that interoperable datasets and use of standards and conventions are beneficial to the users of these datasets, especially those who make use of multiple datasets for their research and applications. The Dataset Interoperability Working Group (DIWG), one of NASA’s Earth Science Data System Working Groups (ESDSWGs), was established in 2013, and has developed and published many recommendations. The Data Product Development Guide (DPDG) Working Group, established in 2018 as another of the ESDSWGs, has published a DPDG for Data Producers and a Quick Start Guide, incorporating guidance from many sources, including the recommendations from the DIWG. The DPDG includes recommendations regarding data formats (prominently netCDF-4) and metadata based primarily on the CF Metadata Conventions and the Attribute Convention for Data Discovery (ACDD). In early 2023, it was decided that the Resource Center for Data Producers (RCDP) Working Group be established as another ESDSWG, with the goals of providing all the information relevant and helpful for data producers via an easily accessible website, and of recommending how the DPDG and QSG could be maintained as living documents, given the rapidly changing technologies, and the need for incorporating the experience and feedback from the users of these documents.
With the impending arrival of new, high-data-volume Earth observation missions, NASA’s ability to effectively ingest, process, and archive large amounts of data requires the most cost-effective, flexible, and scalable data-management architectures and technologies. To meet these demands, NASA's Earth Science Data Systems (ESDS) Program is implementing a strategic vision to develop and operate multiple components of NASA's Earth Observing System Data and Information System (EOSDIS) in a commercial cloud environment. As more earth observing data is moved into the cloud, NASA EOSDIS wants to share our reasoning for moving data into the commercial cloud, as well as demonstrate how end-users can take advantage of both data in the cloud and cloud-deployed services. This presentation explains the enterprise reasons for moving data into the cloud, specifically the scalability of cloud systems, the flexibility to pivot to the most optimal language/system/architecture, and the reduced redundancy of a common architecture. Then we primarily focus on the user-driven reasons for moving to the cloud. Equal access to high performance computing helps all parties, especially users that don't have access to their own on-premise computing infrastructure. Rapid deployment allows users to spin up their own systems without needing the extensive platform previously required for large scale development. Cost effectiveness allows users a wide breadth of computing options, from super computer ability to small scale development, which can help underserved communities. Finally we link to internal resources that users can utilize to begin their cloud based development journey without having to be an expert in the field.
GRACE-D accelerometer data show significant bias jumps since one month after the launch of the GRACE Follow-On (GRACE-FO) satellites in May 2018, making them inapplicable for correcting GRACE-FO products for non-gravitational accelerations. The GRACE-FO Science Data System (SDS) compensated this issue by transplanting the GRACE-C accelerometer data toward that of GRACE-D. Recently, GRACE-FO SDS implemented an updated transplant method, used in the latest release of GRACE-FO data. Here, we examine the impact of updated accelerometer transplant data (ACH) on GRACE-FO measurements at all levels: (a) Level-1B inter-satellite laser ranging residuals measured along satellite orbit, (b) Level-2 time-variable gravity solutions from all SDS centers (JPL, CSR, and GFZ), and (c) Level-3 mascon solutions. We show that inter-satellite laser ranging residuals are modified at low frequencies below 1 mHz, affecting the along-orbit analysis of large-scale time-variable gravity signals. When mapped into monthly Level-2 spherical harmonic coefficients of geopotential, the low-frequency change in inter-satellite ranging residuals leads to substantial improvement of coefficients associated with resonant orders (i.e., 15, 30, 45, etc.) and C 30 . We also present an improved SLR-derived C 30 which significantly improves the agreement with updated GRACE-FO C 30 at seasonal and interannual timescales. Moreover, we demonstrate the noise reduction in mass change estimates from new GRACE-FO Level-2 data over oceans, Greenland, and Antarctica for all SDS solutions. GRACE-FO mascon solutions show a moderate change in the updated release. Our comprehensive analyses demonstrate high-quality estimates of non-gravitational accelerations by the updated transplant method, resulting in more accurate GRACE-FO time-variable gravity and mass change observations.
NASA's Earth Science Data and Information System (ESDIS) Project has implemented a fully automated system for assigning Digital Object Identifiers (DOIs) to Earth Science data products being managed by its network of 12 distributed active archive centers (DAACs). A key factor in the successful evolution of the DOI registration system over last 7 years has been the incorporation of community input from three focus groups under the NASA's Earth Science Data System Working Group (ESDSWG). These groups were largely composed of DOI submitters and data curators from the 12 data centers serving the user communities of various science disciplines. The suggestions from these groups were formulated into recommendations for ESDIS consideration and implementation. The ESDIS DOI registration system has evolved to be fully functional with over 5,000 publicly accessible DOIs and over 200 DOIs being held in reserve status until the information required for registration is obtained. The goal is to assign DOIs to the entire 8000+ data collections under ESDIS management via its network of discipline-oriented data centers. DOIs make it easier for researchers to discover and use earth science data and they enable users to provide valid citations for the data they use in research. Also for the researcher wishing to reproduce the results presented in science publications, the DOI can be used to locate the exact data or data products being cited.
Viewgraphs on Applied Information Systems Research Program Workshop are presented. Topics covered include: the Earth Observing System Data and Information System; the planetary data system; Astrophysics Data System project review; OAET Computer Science and Data Systems Programs; the Center of Excellence in Space Data and Information Sciences; and CASIS background.
The system requirements of three selected Life Science laboratory concepts are defined for the mission phases of prelaunch, launch, on orbit, descent, and post landing. For Vol. 1, see N76-15765.
The purpose of this document is to describe the Cassini/Huygens science data archive system which includes policy, roles and responsibilities, description of science and supplementary data products or data sets, metadata, documentation, software, and archive schedule and methods for archive transfer to the NASA Planetary Data System (PDS).