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NASA NTRS2002

Grids for Dummies: Featuring Earth Science Data Mining Application

This viewgraph presentation discusses the concept and advantages of linking computers together into data grids, an emerging technology for managing information across institutions, and potential users of data grids. The logistics of access to a grid, including the use of the World Wide Web to access grids, and security concerns are also discussed. The potential usefulness of data grids to the earth science community is also discussed, as well as the Global Grid Forum, and other efforts to establish standards for data grids.

Hinke, Thomas H.↗
NASA NTRS2020

Clouds Around the World: How a Simple Citizen Science Data Challenge Became a Worldwide Success

Citizen science is often recognized for its potential to directly engage the public in science, and is uniquely positioned to support and extend participants’ learning in science. In March 2018, the Global Learning and Observations to Benefit the Environment (GLOBE) Program, NASA’s largest and longest-lasting citizen science program about Earth, organized a month-long event that asked people around the world to contribute daily cloud observations and photographs of the sky (15 March–15 April 2018). What was considered a simple engagement activity turned into an unprecedented worldwide event that garnered major public interest and media recognition, collecting over 55,000 observations from 99 different countries, in more than 15,000 locations, on every continent including Antarctica. The event was called the “Spring Cloud Challenge” and was created to 1) engage the general public in the scientific process and promote the use of the GLOBE Observer app, 2) collect ground-based visual observations of varying cloud types during boreal spring, and 3) increase the number and locations of ground-based visual cloud observations collocated with cloud-observing satellites. The event resulted in roughly 3 times more observations than during the historic and highly publicized 2017 North American total solar eclipse. The dataset also includes observations over the Drake Passage in Antarctica and reports from intense Saharan dust events. This article describes how the challenge was crafted, outreach to volunteer scientists around the world, details of the data collected, and impact of the data.

GLOBE↗
NASA NTRS2014

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following:Level-1 GPM Microwave Imager (GMI) and partner radiometer productsLevel-2 Goddard Profiling Algorithm (GPROF) GMI and partner productsLevel-3 daily and monthly productsIntegrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.

precipitation↗
NASA NTRS1975

Acquisition and description of Mariner 10 television science data at Mercury

The Mariner 10 television science subsystem was an improved version of the Mariner 9 system, using 1500-mm-focal-length optics. An elaborate picture-taking sequence resulted in transmission of over 4000 frames back to earth during two flyby encounters with Mercury. These sequences utilized a real-time data rate of 117.6 kbit/s, resulting in coverage of about 75% of the lighted portion of Mercury's surface at a resolution of better than 2 km. The complete set of useful images, which amounted to about 3000 frames, was processed with three different types of digital image-processing enhancements.

Danielson, G. E., Jr.↗
NASA NTRS1998

Nimbus/TOMS Science Data Operations Support

1. Participate in and provide analysis of laboratory and in-flight calibration of UV sensors used for space observations of backscattered UV radiation. 2. Provide support to the TOMS Science Operations Center, including generating instrument command lists and analysis of TOMS health and safety data. 3. Develop and maintain software and algorithms designed to capture and process raw spacecraft and instrument data, convert the instrument output into measured radiance and irradiances, and produce scientifically valid products. 4. Process the TOMS data into Level 1, Level 2, and Level 3 data products. 5. Provide analysis of the science data products in support of NASA GSFC Code 916's research.

Childs, Jeff↗
NASA NTRS2018

Strategies to Maximize Science Data Availability for the GOES-R Series of Satellites

The Geostationary Operational Environmental Satellite-R Series (GOES-R) is the next generation of Untied States geostationary weather satellites. The GOES-R series significantly improves the detection and observation of environmental phenomena that directly affect public safety, protection of property and the economic health and prosperity of the United States and all countries within the western hemisphere. Given the real-time or ''now-casting'' nature of the GOES science gathering mission, any data outage or interruption can reduce warning times or scientific fidelity for critical weather data. GOES-R mission level requirements limit key performance product outages to a total of six hours per year to maximize science data availability. Lower level requirement only allow for 120 minutes of disruption between the spacecraft bus interface to the instruments. This requirement is met using both design features of the satellite and ground system, in addition to operational strategies.

Dudley, Renee↗
NASA NTRS1998

Nimbus/TOMS Science Data Operations Support

Projected goals include the following: (1) Participate in and provide analysis of laboratory and in-flight calibration of LTV sensors used for space observations of backscattered LTV radiation; (2) Provide support to the TOMS Science Operations Center, including generating instrument command lists and analysis of TOMS health and safety data; (3) Develop and maintain software and algorithms designed to capture and process raw spacecraft and instrument data, convert the instrument output into measured radiance and irradiances, and produce scientifically valid products; (4) Process the TOMS data into Level 1, Level 2, and Level 3 data products; (5) Provide analysis of the science data products in support of NASA GSFC Code 916's research.

Source record↗
NASA NTRS2005

Lessons Learned From Developing Three Generations of Remote Sensing Science Data Processing Systems

The Biospheric Information Systems Branch at NASA s Goddard Space Flight Center has developed three generations of Science Investigator-led Processing Systems for use with various remote sensing instruments. The first system is used for data from the MODIS instruments flown on NASA s Earth Observing Systems @OS) Terra and Aqua Spacecraft launched in 1999 and 2002 respectively. The second generation is for the Ozone Measuring Instrument flying on the EOS Aura spacecraft launched in 2004. We are now developing a third generation of the system for evaluation science data processing for the Ozone Mapping and Profiler Suite (OMPS) to be flown by the NPOESS Preparatory Project (NPP) in 2006. The initial system was based on large scale proprietary hardware, operating and database systems. The current OMI system and the OMPS system being developed are based on commodity hardware, the LINUX Operating System and on PostgreSQL, an Open Source RDBMS. The new system distributes its data archive across multiple server hosts and processes jobs on multiple processor boxes. We have created several instances of this system, including one for operational processing, one for testing and reprocessing and one for applications development and scientific analysis. Prior to receiving the first data from OMI we applied the system to reprocessing information from the Solar Backscatter Ultraviolet (SBUV) and Total Ozone Mapping Spectrometer (TOMS) instruments flown from 1978 until now. The system was able to process 25 years (108,000 orbits) of data and produce 800,000 files (400 GiB) of level 2 and level 3 products in less than a week. We will describe the lessons we have learned and tradeoffs between system design, hardware, operating systems, operational staffing, user support and operational procedures. During each generational phase, the system has become more generic and reusable. While the system is not currently shrink wrapped we believe it is to the point where it could be readily adopted, with substantial cost savings, for other similar tasks.

Tilmes, Curt↗
NASA NTRS1997

Encounter Geometry and Science Data Gathering Simulation

Each space mission follows the process cycle of design, development, intergration and test, launch and operation, science analysis and archive. The desire for more frequent and cost effective missions has motivated various new research and development efforts to reduce the design to launch period and the operarion/analysis costs.

Cost↗
NASA NTRS2011

Directional Limits on Persistent Gravitational Waves Using LIGO S5 Science Data

The gravitational-wave (GW) sky may include nearby pointlike sources as well as astrophysical and cosmological stochastic backgrounds. Since the relative strength and angular distribution of the many possible sources of GWs are not well constrained, searches for GW signals must be performed in a model-independent way. To that end we perform two directional searches for persistent GWs using data from the LIGO S5 science run: one optimized for pointlike sources and one for arbitrary extended sources. The latter result is the first of its kind. Finding no evidence to support the detection of GWs, we present 90% confidence level (CL) upper-limit maps of GW strain power with typical values between 2 - 20 X 10 (exp -50) strain2Hz(exp -1) and 5 - 35 X 10 (exp -49) strain2Hz(exp -1)/sr for pointlike and extended sources respectively. The limits on pointlike sources constitute a factor of 30 improvement over the previous best limits. We also set 90% CL limits on the narrow-band root-mean-square GW strain from interesting targets including Sco X-1, SN1987A and the Galactic Center as low as approximately equal 7 X 10(exp -25) in the most sensitive frequency range near 160Hz. These limits are the most constraining to date and constitute a factor of 5 improvement over the previous best limits.

Abadie, J.↗
NASA NTRS2017

Embracing Open Source for NASA's Earth Science Data Systems

The overarching purpose of NASAs Earth Science program is to develop a scientific understanding of Earth as a system. Scientific knowledge is most robust and actionable when resulting from transparent, traceable, and reproducible methods. Reproducibility includes open access to the data as well as the software used to arrive at results. Additionally, software that is custom-developed for NASA should be open to the greatest degree possible, to enable re-use across Federal agencies, reduce overall costs to the government, remove barriers to innovation, and promote consistency through the use of uniform standards. Finally, Open Source Software (OSS) practices facilitate collaboration between agencies and the private sector. To best meet these ends, NASAs Earth Science Division promotes the full and open sharing of not only all data, metadata, products, information, documentation, models, images, and research results but also the source code used to generate, manipulate and analyze them. This talk focuses on the challenges to open sourcing NASA developed software within ESD and the growing pains associated with establishing policies running the gamut of tracking issues, properly documenting build processes, engaging the open source community, maintaining internal compliance, and accepting contributions from external sources. This talk also covers the adoption of existing open source technologies and standards to enhance our custom solutions and our contributions back to the community. Finally, we will be introducing the most recent OSS contributions from NASA Earth Science program and promoting these projects for wider community review and adoption.

Earth Science↗
NASA NTRS2022

NASA's Next Generation of Atmospheric Data Science

The Multi-Angle Imager for Aerosols (MAIA) and the Tropospheric Emission: Monitoring of Pollution(TEMPO) are NASA’s next-generation satellite missions for air quality monitoring. These missions will produce high-quality, high-resolution air quality data to support cross-displinary research. The MAIA mission is collaborating with health science researchers and epidemiologists to study the impacts of air quality on health outcomes. TEMPO aims to improve our understanding of tropospheric air pollution chemistry and our ability to make predictions about air quality and climate forcing. TEMPO will offer hourly measurements of tropospheric ozone, aerosols, and clouds focused on North America at high-spatial resolution, while MAIA will produce high-resolution measurements of speciated particulate matter targeting densely populated cities around the globe. Data from these missions will help improve our understanding of the sources, types, and interactions among the aerosols and trace gases that are polluting Earth’s atmosphere, as well as our understanding of the impact of air pollution on pollution on a wide range of important areas including human health, agriculture, weather, and climate change. The challenges of cross-disciplinary research, computationally expensive multi-variate analyses, and high-resolution data at both local and global scales are driving substantial changes across all of NASA’s Distributed Active Archive Centers (DAACs). High resolution data at scales such these requires a new approach to data ingest, archive, and publication. Like other NASA DAACs, the Atmospheric Science Data Center (ASDC), the DAAC that will be responsible for publishing MAIA and TEMPO data products has historically archived and distributed data on premise. DAACs of the future will archive and distribute data in the cloud, enabling them to remake themselves as research-focused data centers that will support on-demand, data-intensive computations for highly accurate retrospective analyses and predictions. Under the new paradigm, data formats and metadata must support on-demand spatial and temporal sub-setting, as well as other data transformation services such as re-gridding and re-sampling. This presentation will discuss work being done to address data formatting and metadata requirements in this dynamic new environment. In addition to the changes in data stewardship practices at the ASDC, the increased focus on supporting scientific research is driving changes in the relationship between DAACs and researchers. While the ASDC will continue to provide first rate data management and stewardship, it is increasingly focused on serving as a partner not only to the science teams that gather and produce the data it publishes, but to the researchers that use that data.

Beth Huffer↗
NASA NTRS2011

NASA Life Sciences Data Repositories: Tools for Retrospective Analysis and Future Planning

As NASA transitions from the Space Shuttle era into the next phase of space exploration, the need to ensure the capture, analysis, and application of its research and medical data is of greater urgency than at any other previous time. In this era of limited resources and challenging schedules, the Human Research Program (HRP) based at NASA s Johnson Space Center (JSC) recognizes the need to extract the greatest possible amount of information from the data already captured, as well as focus current and future research funding on addressing the HRP goal to provide human health and performance countermeasures, knowledge, technologies, and tools to enable safe, reliable, and productive human space exploration. To this end, the Science Management Office and the Medical Informatics and Health Care Systems Branch within the HRP and the Space Medicine Division have been working to make both research data and clinical data more accessible to the user community. The Life Sciences Data Archive (LSDA), the research repository housing data and information regarding the physiologic effects of microgravity, and the Lifetime Surveillance of Astronaut Health (LSAH-R), the clinical repository housing astronaut data, have joined forces to achieve this goal. The task of both repositories is to acquire, preserve, and distribute data and information both within the NASA community and to the science community at large. This is accomplished via the LSDA s public website (http://lsda.jsc.nasa.gov), which allows access to experiment descriptions including hardware, datasets, key personnel, mission descriptions and a mechanism for researchers to request additional data, research and clinical, that is not accessible from the public website. This will result in making the work of NASA and its partners available to the wider sciences community, both domestic and international. The desired outcome is the use of these data for knowledge discovery, retrospective analysis, and planning of future research studies.

Thomas, D.↗
NASA NTRS2005

Giovanni: A System for Rapid Access, Visualization and Analysis of Earth Science Data Online

Collecting data and understanding data structures traditionally are the first steps that a user must take, before the core investigation can begin. This is a time-consuming and challenging task, especially when science objectives require users to deal with large multi-sensor data that are usually in different formats and internal structures. The Goddard Earth Sciences Data and Information Services Center (GES DISC) has created the GES DISC Interactive Online Visualization and ANalysis Infrastructure, Giovanni, to enable Web-based visualization and analysis of satellite remotely sensed meteorological, oceanographic, and hydrologic data sets, without users having to download data. The current operational Giovanni interfaces provide the capability to process a number of important satellite measurements, such as (1) ozone and other trace gases from TOMS, OMI, HALOE, and MLS; (2) air temperature, water vapor, and geopotential height from AIRS; (3) aerosols from MODIS TerrdAqua, and GOCART model; (4) precipitation from TRMM and ground measurements; (5) chlorophyll and other ocean color products from SeaWiFS and MODIS Aqua; and (6) sea surface temperature from MODIS Aqua. Depending on the input data structure, the system provides simple statistical analysis and creates time-averaged area plot, area-averaged time series, animations, Hovmoller latitude vs. time and longitude vs. time plots, as well as vertical profiles. The inter-comparison interfaces allow a user to compare observations from different instruments, to conduct anomaly analysis, and to study basic relationships between physical parameters. Giovanni handles data with different temporal and spatial resolutions and, thus, enables both regional and global long-term climate research and short-term special events investigation, as well as data validations and assessments. Because of its simplicity of usage, Giovanni is powerful and versatile, able to assist a wide range of users, from the discipline scientists conducting preliminary research in various fields, to students in the classroom learning about weather, climate, and other natural phenomena. Giovanni can be accessed from: http://disc. esfc.nasa.gov/techlab/giovanni/index.shtml

Shen, S.↗