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Planetary Boundary Layer Height from AIRS, MERRA-2, and GPS Radio Occultation Data Products at NASA GES DISC, and Insights from Their Profiles Intercomparison

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides archive and distribution services for several data products in the Planetary Boundary Layer (PBL) category. As a new variable added to the Atmospheric Infrared Sounder (AIRS) Version 6 support product, the PBL height from AIRS is derived based on the gradients of the retrieved relative humidity profile, and provides the atmospheric pressure at the top of the PBL over the ocean. The GES DISC also hosts the Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) product generated by the Goddard Earth Observing System Model Version 5 (GEOS-5) data assimilation system. The PBL height from MERRA-2 is based on the total eddy diffusion coefficient of heat. The monthly PBL height has been made available in the Giovanni system (Giovanni is a Web-based application developed by the GES DISC providing a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data). Recently, the GES DISC began serving the global PBL height climatology product derived from the COSMIC/FORMOSAT-3 and TerraSAR-X Global Positioning System (GPS) radio occultation (RO) measurements from June 2006 to December 2015. In a previous study, we presented the monthly PBL height data from AIRS and MERRA-2 and demonstrated the GES DISC services which support data intercomparison, such as access, plotting, sub-setting, regridding, and generation of a multi-year monthly mean. We also provided intercomparison results, and found that different PBL height definitions contributed to significant differences of PBL height values between AIRS and MERRA-2. In this work, we present the 10-year seasonal climatologies from the AIRS, MERRA-2 and GPS-RO. We also used the cross section and vertical profile services in Giovanni to display and analyze the vertical atmosphere structure over regions where the PBL height derived from the AIRS and MERRA-2 are quite different. The examination of the AIRS and MERRA-2 three-dimensional data found that the relative humidity profiles had larger differences than the temperature profiles. The MERRA-2 gives more details than the AIRS for the vertical distribution of the humidity.

Ding, Feng↗

Satellite Sounder Products in NASA GES DISC & Services Supporting Their Applications

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at the Jet Propulsion Laboratory (JPL), provides processing, archiving, and distribution services for remotely-sensed data acquired by satellite sounders. Supported data sets begin chronologically with the legacy TIROS Operational Vertical Sounder (TOVS) Pathfinder, continue to the Atmospheric Infrared Sounder (AIRS), a modern hyperspectral sounder onboard the Aqua satellite, and are followed by data from the subsequent Suomi-National Polar-orbiting Partnership Cross-track Infrared Sounder (CrIS) mission and the Joint Polar Satellite System (JPSS) series CrIS missions. These satellite sounders provide long-term global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. Applications of sounder data products cover a broad range of fields, including meteorology climatology, hydrology, and air quality. The GES DISC has developed many services to assist users, including simplified and efficient methods for searching, accessing, downloading, and analytically exploring these satellite sounder data products. We have also developed the Giovanni system, a broadly used Web-based application, which provides a simple and intuitive way to visualize, analyze, and access Earth science remote sensing data. In this presentation, we will introduce the standard and near-real time sounder data products, and demonstrate our services through some use cases. Highlights of our service capabilities include data subset, vertical profile plot, inter-comparison, multi-year monthly/seasonal mean, interannual monthly/seasonal time series, and anomaly analysis.

Ding, Feng↗

Satellite-Based Drought Reporting on the Navajo Nation

The Navajo Nation (NN) is the largest reservation in the US, and faces challenges related to water management during long-term and widespread drought episodes. The Navajo Nation is a federally recognized tribe, which has boundaries within Arizona, New Mexico, and Utah. The Navajo Nation has a land area of over 70,000 square kilometers. The Navajo Nation Department of Water Resources (NNDWR) reports on drought and climatic conditions through the use of regional Standardized Precipitation Index (SPI) values and a network of in-situ rainfall, streamflow, and climate data. However, these data sources lack the spatial detail and consistent measurements needed to provide a coherent understanding of the drought regime within the Nation's regional boundaries. This project, as part of NASA's Western Water Applications Office (WWAO), improves upon the recently developed Drought Severity Assessment Tool (DSAT) to ingest satellite-based precipitation data to generate SPI values for specific administrative boundaries within the reservation. The tool aims to: (1) generate SPI values and summary statistics for regions of interest on various timescales, (2) to visualize SPI values within a web-map application, and (3) produce maps and comparative statistical outputs in the format required for annual drought reporting. The co-development of the DSAT with NN partners is integral to increasing the sustained use of Earth Observations for water management applications. This tool will provide data to support the NN in allocation of drought contingency dollars to the regions most adversely impacted by declines in water availability.

Satellite-based↗

Constructing an AIRS Climatology for Data Visualization and Analysis to Serve the Climate Science and Application Communities

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding SNPP CrIS mission. The AIRS mission is entering its 15th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. The GES DISC, in collaboration with the AIRS Project, released product from the version 6 algorithm in early 2013. Giovanni, a Web-based application developed by the GES DISC, provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Most important variables from version 6 AIRS product are available in Giovanni. We are developing a climatology product using 14-year AIRS retrievals. The study can be a good start for the long term climatology from NASA sounders: the AIRS and the succeeding CrIS. This presentation will show the impacts to the climatology product from different aggregation methods. The climatology can serve climate science and application communities in data visualization and analysis, which will be demonstrated using a variety of functions in version 4 Giovanni. The highlights of these functions include user-defined monthly and seasonal climatology, inter annual seasonal time series, anomaly analysis.

AIRS↗

Machine Aided Indexing and the NASA Thesaurus

Machine Aided Indexing (MAI) is a Web-based application program for aiding the indexing of literature in the NASA Scientific and Technical Information (STI) Database. MAI was designed to be a convenient, fully interactive tool for determining the subject matter of documents and identifying keywords. The heart of MAI is a natural-language processor that accepts, as input, any user-supplied text, including abstracts, full documents, and Web pages. Within seconds, the text is analyzed and a ranked list of terms is generated. The 17,800 terms of the NASA Thesaurus serve as the foundation of the knowledge base used by MAI. The NASA Thesaurus defines a standard vocabulary, the use of which enables MAI to assist in ensuring that STI documents are uniformly and consistently accessible. Of particular interest to traditional users of the NASA Thesaurus, MAI incorporates a fully searchable thesaurus display module that affords word-search and hierarchy- navigation capabilities that make it much easier and less time-consuming to look up terms and browse, relative to lookup and browsing in older print and Portable Document Format (PDF) digital versions of the Thesaurus. In addition, because MAI is centrally hosted, the Thesaurus data are always current.

vonOfenheim, Bill↗

Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data

Web-based geospatial client applications such as Google Earth and NASA World Wind must listen to data requests, access appropriate stored data, and compile a data response to the requesting client application. This process occurs repeatedly to support multiple client requests and application instances. Newer Web-based geospatial clients also provide user-interactive functionality that is dependent on fast and efficient server responses. With massively large datasets, server-client interaction can become severely impeded because the server must determine the best way to assemble data to meet the client applications request. In client applications such as Google Earth, the user interactively wanders through the data using visually guided panning and zooming actions. With these actions, the client application is continually issuing data requests to the server without knowledge of the server s data structure or extraction/assembly paradigm. A method for efficiently controlling the networked access of a Web-based geospatial browser to server-based datasets in particular, massively sized datasets has been developed. The method specifically uses the Keyhole Markup Language (KML), an Open Geospatial Consortium (OGS) standard used by Google Earth and other KML-compliant geospatial client applications. The innovation is based on establishing a dynamic cascading KML strategy that is initiated by a KML launch file provided by a data server host to a Google Earth or similar KMLcompliant geospatial client application user. Upon execution, the launch KML code issues a request for image data covering an initial geographic region. The server responds with the requested data along with subsequent dynamically generated KML code that directs the client application to make follow-on requests for higher level of detail (LOD) imagery to replace the initial imagery as the user navigates into the dataset. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics. The method yields significant improvements in userinteractive geospatial client and data server interaction and associated network bandwidth requirements. The innovation uses a C- or PHP-code-like grammar that provides a high degree of processing flexibility. A set of language lexer and parser elements is provided that offers a complete language grammar for writing and executing language directives. A script is wrapped and passed to the geospatial data server by a client application as a component of a standard KML-compliant statement. The approach provides an efficient means for a geospatial client application to request server preprocessing of data prior to client delivery. Data is structured in a quadtree format. As the user zooms into the dataset, geographic regions are subdivided into four child regions. Conversely, as the user zooms out, four child regions collapse into a single, lower-LOD region. The approach provides an efficient data traversal path and mechanism that can be flexibly established for any dataset regardless of size or other characteristics.

Baxes, Gregory↗

Creating Satellite Data Products in the Cloud: SatCORPS Global Cloud Composites

Real time satellite observations and real time derived cloud products are becoming an important tool for both science as well as business ventures. The SatCORPS group leverages public and private cloud-based sources of satellite observations to create its Global Cloud Composite product in near real-time. This dataset allows others access to cloud information that can be accessed directly from the cloud. In this work, we describe the software algorithms and software infrastructure that we have created to create and distribute this product through our hybrid cloud and on-premises system that leverages the strengths and weaknesses of each platform. We will also describe the GCC product itself in terms of the scientific parameters available, resolution and temporal availability. Finally, we will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global cloud products with very low latency which we see that as filling a rapidly growing need in the research, modelling and business community. We present a detailed description of the SatCORPS GCC product in terms of the capabilities and research benefits as well as the delivery architecture in AWS. We take the discussion further and describe the web tools that the SatCORPS group has developed that allow users to access and use the GIS data that it creates.

Global Cloud Composite SatCORPS SMCE AWS↗

Software Tools Streamline Project Management

Three innovative software inventions from Ames Research Center (NETMARK, Program Management Tool, and Query-Based Document Management) are finding their way into NASA missions as well as industry applications. The first, NETMARK, is a program that enables integrated searching of data stored in a variety of databases and documents, meaning that users no longer have to look in several places for related information. NETMARK allows users to search and query information across all of these sources in one step. This cross-cutting capability in information analysis has exponentially reduced the amount of time needed to mine data from days or weeks to mere seconds. NETMARK has been used widely throughout NASA, enabling this automatic integration of information across many documents and databases. NASA projects that use NETMARK include the internal reporting system and project performance dashboard, Erasmus, NASA s enterprise management tool, which enhances organizational collaboration and information sharing through document routing and review; the Integrated Financial Management Program; International Space Station Knowledge Management; Mishap and Anomaly Information Reporting System; and management of the Mars Exploration Rovers. Approximately $1 billion worth of NASA s projects are currently managed using Program Management Tool (PMT), which is based on NETMARK. PMT is a comprehensive, Web-enabled application tool used to assist program and project managers within NASA enterprises in monitoring, disseminating, and tracking the progress of program and project milestones and other relevant resources. The PMT consists of an integrated knowledge repository built upon advanced enterprise-wide database integration techniques and the latest Web-enabled technologies. The current system is in a pilot operational mode allowing users to automatically manage, track, define, update, and view customizable milestone objectives and goals. The third software invention, Query-Based Document Management (QBDM) is a tool that enables content or context searches, either simple or hierarchical, across a variety of databases. The system enables users to specify notification subscriptions where they associate "contexts of interest" and "events of interest" to one or more documents or collection(s) of documents. Based on these subscriptions, users receive notification when the events of interest occur within the contexts of interest for associated document or collection(s) of documents. Users can also associate at least one notification time as part of the notification subscription, with at least one option for the time period of notifications.

Source record↗

DAAC Collaboration Overview for AGU

The Atmospheric Science Data Center (ASDC), Goddard Earth Sciences Data and Information Systems Center (GES DISC), Socioeconomic Data and Applications Center (SEDAC), Oak Ridge National Laboratory (ORNL), Land Processes DAAC, Alaska Satellite Facility (ASF), as well as NASA Global Imagery Browse Service (GIBS), Earth Science Data Systems (ESDS) Geographic Information Systems Team (EGIST), Earthdata Content Delivery Team, ArcGIS Online Governance Team, and the Systematic Data Transformation ACCESS team have come together to establish the ArcGIS DAAC Collaboration. This coalition of participants will demonstrate their use of the ArcGIS Enterprise to support Earth science research, applied science, and outreach using Earth Observing System Data and Information System (EOSDIS) data. This includes the use of web services to fuse data products across space and time through services (e.g. ArcGIS Image Services, Open Geospatial Consortium (OGC) Web Coverage Service (WCS), and OGC Web Mapping Services (WMS)) for analysis in Jupyter notebooks, desktop tools, and web based applications.

Matthew Steven Tisdale↗

Temperature Anomalies from the AIRS Product in Giovanni for the Climate Community

The Atmospheric Infrared Sounder (AIRS) mission began with the launch of Aqua in 2002. Over 15 years of AIRS products have been used by the climate research and application communities. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding Suomi National Polar-Orbiting Partnership (SNPP) Cross-track Infrared Sounder (CrIS) mission. We generated a Multi-year Monthly Mean and Anomaly product using 14 years of AIRS standard monthly product. The product includes Air Temperature at the Surface and Surface Skin Temperature, both in Ascending/Daytime and Descending/Nighttime mode. The temperature variables and their anomalies are deployed to Giovanni, a Web-based application developed by the GES DISC. Giovanni provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. It is also a powerful tool that stakeholders can use for decision support in planning and preparing for increased climate variability. In this presentation, we demonstrate the functions in Giovanni with use cases employing AIRS Multi-year Monthly Mean and Anomaly variables.

Giovann↗

Accessing Data Stored in Amazon S3 Using the Hyrax OPeNDAP Server

For three years we have been investigating data storage and retrieval in the Amazon Cloud, striving to optimize both storage structures and (cache-enhanced retrieval processes. These optimizations are hidden from data users, who simply employ the Data Access Protocol (DAP), a popular, Web-based Application Programmer Interface (API) developed by OPeNDAP. We present our collected findings and their realization in the Hyrax data server. Specific techniques include caching data on spinning disk; accessing sharded data in place; optimizing the organizational structures for data within the flat key-value space of Simple Storage Service (S3); and employing an API extension that permits simultaneous operations on many datasets in a single request.

Data access↗

Is Structured Agile an Oxymoron? Tales from Implementing and Executing Agile in a US Government Environment

To paraphrase a famous quote, "No plan survives contact with the reality." Software (SW) development is often a classic example of this: whatever the plan was for a particular development, it often does not survive contact with technical realities, budget realities, program realities and schedule realities. Traditionally, SW development has followed a waterfall methodology with requirements being rigorously specified before the design, which was completed before the coding and unit testing started, which were in turn finished before validation and verification started. This model of SW engineering derives much from the HW engineering of large systems, and has been the standard methodology used in US government software acquisitions and systems for decades, with highly variable results. US Government SW requirements are built around Waterfall concepts, which assume that the plan will survive contact with reality, or at least that modifications to the plan are relatively small, and relatively few.Because of the inefficiencies and difficulties inherent in Waterfall, the commercial SW world started using a different SW development methodology called Agile more than 20 years ago. Agile believes that a plan should evolve and learn rapidly in response to the realities encountered. At its core, there are a few key elements of Agile:- A small team of people which is highly flexible and adaptive. The team collaborates and interoperates through sophisticated development architectures and release environments- An iterative, incremental development and release approach which is based upon the concept that knowledge comes from experience within the team, and that the team makes decisions based upon what it knows- A team culture which prizes transparency, inspection and adaptation. These values are necessary so that the team experience and decision making is transparent and responsive to the realities encountered during development and testingSo, how to use Agile in a US Government environment? GMSEC (Goddard Mission Services Evolution Center) develops satellite ground system software for NASA and other US Government agencies. The SW developed by the team contains a large code base of many applications used within satellite mission operations centers. It spans the full gamut of SW development types: from SW which is in a classic maintenance and sustainment mode, to new developments with a fairly well understood scope and approach, to new developments whose scope and approach are quite unclear and which require significant research and prototyping. Team members move between all of these different types of SW development. Waterfall was inadequate to the programmatic and technical needs of the team, as well as the various types of SW development being done. The software plan was not surviving contact with the technical and programmatic realities experienced by the team. To address this, the team started a small pilot project in 2016 to test the use of Agile within a small subset of the team for a new web services application. In early 2018, the use of Agile was expanded to the whole team and all the software, but we had to fulfill the NASA SW development requirements. And we needed to do this while still remaining true to the key Agile elements of transparency, inspection and adaption. In order to do this, the team worked very closely with the Software Process Improvement (SPI) team at NASA Goddard, as well as NASA engineering manageme

Beech, Theresa W.↗

Observing the Earth from Afar with NASA's Worldview

NASA's Worldview interactive web map application delivers global, near real-time imagery from NASA's fleet of Earth Observing System (EOS) satellites. Within hours of satellite overpass, discover where the latest wildfires, severe storms, volcanic eruptions, dust and haze, ice shelves calving as well as many other events are occurring around the world. Near real-time imagery is made available in Worldview through the Land, Atmosphere Near real-time Capability for EOS (LANCE) via the Global Imagery Browse Services (GIBS). This poster will explore new near real-time imagery available in Worldview, the current ways in which the imagery is used in research, the news and social media and future improvements to Worldview that will enhance the availability and viewing of NASA EOS imagery.

web applicatio↗

NASA Goddard Giovanni Support for YOTC

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.

Ostrenga, Dana↗

Addressing Usability for Discrete User Goals When Adding New Features to the Worldview Application

The Worldview (https://worldview.earthdata.nasa.gov/) application from NASA's Earth Observing System Data and Information System (EOSDIS) provides a low friction solution for users of different scientific backgrounds to access near real-time satellite imagery and data products. Worldview credits its successful growth by displaying new imagery from the Global Imagery Browse Services (GIBS), which has an increasing archive of 700+ products serving full-resolution satellite imagery from NASA's Earth observing fleet. NASA promotes the open sharing of all data with researchers, private industry, academia, and the general public. Worldview encourages this open data policy. Numerous general news publications feature Worldview for its unique imagery. Worldview also helps scholarly research in identifying field research locations, mapping thermal hotspots of active burning fires, and visualizing theoretical models of weather storm systems.

web application↗

Weather from 250 Miles Up: Visualizing Precipitation Satellite Data (and Other Weather Applications) Using CesiumJS

Geospatial weather visualization remains predominately a two-dimensional endeavor. Even popular advanced tools like the Nullschool Earth display 2-dimensional fields on a 3-dimensional globe. Yet much of the observational data and model output contains detailed three-dimensional fields. In 2014, NASA and JAXA (Japanese Space Agency) launched the Global Precipitation Measurement (GPM) satellite. Its two instruments, the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) observe much of the Earth's atmosphere between 65 degrees North Latitude and 65 degrees South Latitude. As part of the analysis and visualization tools developed by the Precipitation Processing System (PPS) Group at NASA Goddard, a series of CesiumJS [Using Cesium Markup Language (CZML), JavaScript (JS) and JavaScript Object Notation (JSON)] -based globe viewers have been developed to improve data acquisition decision making and to enhance scientific investigation of the satellite data. Other demos have also been built to illustrate the capabilities of CesiumJS in presenting atmospheric data, including model forecasts of hurricanes, observed surface radar data, and gridded analyses of global precipitation. This talk will present these websites and the various workflows used to convert binary satellite and model data into a form easily integrated with CesiumJS.

web applications↗

RadLab: Graphical and Programming Interfaces for Interrogation of Space Telemetry Data

Sensors on multiple spacecraft in and beyond low Earth orbit continuously monitor and collect space radiation data and transmit it back to Earth. These data are of vast importance to space biology research, as ionizing radiation affects living organisms—astronauts and non-human experiment subjects alike—placing them at higher risk of carcinogenesis, degenerative diseases, and radiation sickness. Therefore, knowledge of the biological effects of space radiation is essential for planning future crewed missions beyond low Earth orbit. The RadLab project, initiated by GeneLab and ALSDA (the Open Science Data Repository; OSDR) and sponsored by the NASA Human Research Program, is a new effort aimed at connecting dosimetry data from radiation detectors located on the International Space Station (ISS), as well as other spacecraft. To date, access to these data has been fragmented across space agencies and databases; to address this issue, we have developed an application programming interface (API) and an associated graphical user interface (GUI) designed to provide a single point of access to the data. As of now, OSDR has focused on the detectors located on the ISS, with the long-term goal to establish a self-sustained portal receiving continuous updates through APIs connecting to multiple radiation databases of varying scope, as well as individual investigator contributions. The RadLab API implements a request syntax enabling users to query data by craft, sensor type, timespan, etc, allowing for arbitrary combinations of original source data, thus providing programmatic access for use in computational pipelines, while the GUI facilitates data visualization and exploration, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

radiation↗

RadLab: A Comprehensive Database and Analysis Toolkit for Space Radiation Measurements Relevant to Space Radiation Biology

RadLab, a new addition to the NASA Open Science Data Repository (OSDR), is a public platform for space radiation data relevant to human space exploration. RadLab consists of a database, a submission portal, and user-friendly visualization and data analysis tools, including a graphical user interface (GUI) and an application programming interface (API). Investigators from ISS partners including Germany, Italy, Canada, Hungary, the Czech Republic, Russia, Japan have committed to providing data from their instruments. RadLab will also include data from other spacecraft in LEO: the Space Shuttle, the Mir space station, biosatellites; and beyond LEO: the lunar and the Martian surface, the heliocentric orbit at 1 AU, Mars orbit, and Earth-Mars space. Once fully operational, RadLab will provide open, centralized access to space radiation physics data relevant to human space exploration; a platform for submission of data by agencies and research institutions responsible for radiation detectors deployed in space; analysis tools to facilitate detector and dataset intercomparison to better understand space habitat radiation environments; capabilities for space biology investigators to determine the radiation environment to which samples were exposed. A RadLab Working Group (RLWG) has been formed, modeled on the GeneLab Analysis Working Groups and comprised of data contributors and users. RLWG tasks include identifying data sources, normalizing data from diverse detectors, expanding the analysis toolkit and, perhaps most importantly, sharing ideas for research exploiting capabilities of RadLab. We will provide an overview of RadLab data and capabilities and discuss examples of its potential as a resource for open science.

radiation↗