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At least 271 records · Page 15

Improving NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA: The Research Access initiative is part of the agency's framework for increasing public access to scientific publications and digital scientific data. The initiative follows the release of White House Office of Science and Technology Policy's (OSTP) memorandum "Increasing Access to the Results of Federally Funded Research," to ensure federally funded research is available to the public within one year of publication. NASA answered the mandate by creating an agency plan entitled "NASA Plan for Increasing Access to the Results of Scientific Research" and associated policy, NPD 2230.1, Research Data and Publication Access. Principles in NASA SMD Strategic Plan for Scientific Data and Computing: Continued free and open access to scientific data for any use. Improved ease of use and discoverability. Enhanced science applications and new use cases. Incorporates best practices and "state of the art" through partnerships. Earth Data and Systems are Evolving: Increasing archive and file sizes. More complicated data structures. More user-friendly and data services. What is the future direction?

Liu, Zhong↗

Developing Data Services to Provide Data Quality Information for Global Satellite-Based Precipitation Products

Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide data on a global scale, especially in remote continents and over oceans. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As a data service provider, it is necessary to provide easy access to data quality information. However, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present such challenges and activities at the GES DISC to address precipitation data (other datasets as well) quality issues.

Liu, Z.↗

Providing Data Access and Analysis Capabilities to SERVIR’s Data-Sparse Regions

In developing regions of the world, the communications infrastructure pose enormous challenges for using Earth observation data. Limited internet bandwidth along with the high costs make it almost impossible to process and extract zonal statistics over large periods of time for even small geographic areas. In such cases, downloading daily rainfall data or dekadal series of NDVI data would take days and consume all the bandwidth allocated to an organization (for reference, internet connections in Niger would cost thousands of dollars per month at a maximum - and unreliable - bandwidth of just 10 Mbps). Running crop models or hydrological models typically require several years of historic data over the area of interest (AOI). In some cases, these AOIs are relatively small compared to the footprint of individual earth observation granules. Hence, systems that let the stakeholders subset the data to download to a user specified area, or even submit processing requests that let them download small result files for the AOI become critical. The SERVIR program has developed a tool to provide this type of access to help decision makers in developing regions use long time series of adjusted rainfall data (CHIRPS), NDVI values, seasonal weather forecasts, evaporative stress indices and others in a very efficient manner. This system, named ClimateSERV (https://climateserv.servirglobal.net) ingests the datasets in an automated fashion and allows interactive access (through a web application), or automated access through a simple API that developers can quickly incorporate in independent applications. This way, the extraction of daily averages of rainfall over a 50 square Km area through 30 years of archived data takes only a few seconds to process, and the results can be presented on an online chart or downloaded in a comma separated file that's only a few Kb.

Ashmall, William↗

The Atacama Cosmology Telescope: Summary of DR4 and DR5 Data Products and Data Access

Two recent large data releases for the Atacama Cosmology Telescope (ACT), called DR4 and DR5, are available for public access. These data include temperature and polarization maps that cover nearly half the sky at arcminute resolution in three frequency bands; lensing maps and component-separated maps covering ∼2100 deg 2 of sky; derived power spectra and cosmological likelihoods; a catalog of over 4000 galaxy clusters; and supporting ancillary products including beam functions and masks. The data and products are described in a suite of ACT papers; here we provide a summary. In order to facilitate ease of access to these data, we present a set of Jupyter IPython notebooks developed to introduce users to DR4, DR5, and the tools needed to analyze these data. The data products (excluding simulations) and the set of notebooks are publicly available on the NASA Legacy Archive for Microwave Background Data Analysis; simulation products are available on the National Energy Research Scientific Computing Center.

Maya Mallaby-Kay↗

Cloud Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) - Data Management - Data Products Catalog V4.94

The CALIPSO V2.00 Lidar Level 2 Polar Stratospheric Cloud data product is an updated version of an already order-able dat set. The changes were signed off by the CALIPSO Configuration Control Board, versioned, and the code uploaded to a code repository. There is no ITAR/SBU data or code associated with this product. Data will be publicly order-able at the NASA LaRC Atmospheric Sciences Data Center (ASDC). All documentation and web sites will be made public once the data product is released. The data is in HDF4 format and will be generated for majority of the mission (June 2006 - March 2021). The attached Data Products Catalog (v4.94) describes this new product in section 2.14, pp 115- 119.

Mark Vaughan↗

Assessment of Geo-Kompsat-2A Atmospheric Motion Vector Data and Its Assimilation Impact in the GEOS Atmospheric Data Assimilation System

Korea’s second geostationary meteorological satellite, Geo-Kompsat-2A (Geostationary-Korean Multi-Purpose Satellite-2A, GK2A), was successfully launched on 4 December 2018. GK2Agenerates Atmospheric Motion Vectors (AMVs) every 10 min in the full disk area. This data hasbeen disseminated via Global Telecommunication System (GTS) since 25 October 2019. This articleevaluates the quality of GK2A AMVs in the Goddard Earth Observing System (GEOS) atmosphericdata assimilation system (ADAS). The data show slow wind speed biases at 200–300 hPa and 600–800hPa in the northern and southern hemispheres. These biases are caused by observation heightassignment errors near jet streams. The Equivalent Blackbody Temperature (EBBT) method of GK2Atends to assign clouds at higher altitude, which mainly causes slow wind speed biases, especially inthe lower atmosphere. The IR/WV intercept method of GK2A assigns clouds slightly lower in theatmospheric layers below the altitude of 400 hPa, which causes positive biases. Quality control (QC)criteria to select the most suitable GK2A AMV data for assimilation are presented based on thesequality assessments. A new QC criterion utilizing height errors within the GEOS ADAS is introducedto exclude data with slow wind speed biases and large errors. GEOS forecast accuracy is slightlyimproved after assimilating GK2A AMVs along with other conventional, radiance, and satellitewinds which include AMVs made by the Himawari-8 satellite in nearly the same observational areaof GK2A. Additionally, the present work shows that GEOS forecasts can be significantly improved,especially in the tropics and southern hemisphere after assimilating GK2A data in the absence ofHimawari-8 AMVs. This study demonstrates that GK2A AMV data is a valuable data source toenhance the robustness of GEOS ADAS.

Atmospheric Motion Vectors↗

North American Land Data Assimilation (NLDAS) Data and Services at NASA GES DISC

The North American Land Data Assimilation System (NLDAS, https://ldas.gsfc.nasa.gov/nldas) integrates a large quantity of observation-based and model reanalysis data to drive offline (not coupled to the atmosphere) land surface models (LSMs) to produce fields of soil moisture, snow, and surface fluxes. The NLDAS-2 data sets currently archived at, and distributed by, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC, https://disc.gsfc.nasa.gov) have been updated to NLDAS Version 2.0 (NLDAS-2.0). This presentation provides an overview of the updated NLDAS-2.0 data at NASA GES DISC and discusses the methods for the public to access the data as well as the data services available.

Ashley Heath↗

NASA planetary data: applying planetary satellite remote sensing data in the classroom

NASA supports several data archiving and distribution mechanisms that provide a means whereby scientists can participate in education and outreach through the use of technology for data and information dissemination. The Planetary Data System (PDS) is sponsored by NASA's Office of Space Science. Its purpose is to ensure the long-term usability of NASA data and to stimulate advanced research. In addition, the NASA Regional Planetary Image Facility (RPIF), an international system of planetary image libraries, maintains photographic and digital data as well as mission documentation and cartographic data.

Regional Plaentary Image Facility RPIF Planetary D↗

Kepler Data Validation I: Architecture, Diagnostic Tests, and Data Products for Vetting Transiting Planet Candidates

The Kepler Mission was designed to identify and characterize transiting planets in the Kepler Field of View and to determine their occurrence rates. Emphasis was placed on identification of Earth-size planets orbiting in the Habitable Zone of their host stars. Science data were acquired for a period of four years. Long-cadence data with 29.4 min sampling were obtained for approx. 200,000 individual stellar targets in at least one observing quarter in the primary Kepler Mission. Light curves for target stars are extracted in the Kepler Science Data Processing Pipeline, and are searched for transiting planet signatures. A Threshold Crossing Event is generated in the transit search for targets where the transit detection threshold is exceeded and transit consistency checks are satisfied. These targets are subjected to further scrutiny in the Data Validation (DV) component of the Pipeline. Transiting planet candidates are characterized in DV, and light curves are searched for additional planets after transit signatures are modeled and removed. A suite of diagnostic tests is performed on all candidates to aid in discrimination between genuine transiting planets and instrumental or astrophysical false positives. Data products are generated per target and planet candidate to document and display transiting planet model fit and diagnostic test results. These products are exported to the Exoplanet Archive at the NASA Exoplanet Science Institute, and are available to the community. We describe the DV architecture and diagnostic tests, and provide a brief overview of the data products. Transiting planet modeling and the search for multiple planets on individual targets are described in a companion paper. The final revision of the Kepler Pipeline code base is available to the general public through GitHub. The Kepler Pipeline has also been modified to support the Transiting Exoplanet Survey Satellite (TESS) Mission which is expected to commence in 2018.

data analysis↗

Water quality parameters of harbors of Charlotte Amalie, St. Thomas, Virgin Islands: Acquisition of in situ water data, intercorrelation of selected water parameters, and initial correlation of these in situ biological, chemical and physical data with ERTS-1 bulk CCT MSS band 5 data

The author has identified the following significant results. Remote sensing by the ERTS-1 satellite was compared with selected water quality parameters including pH, salinity, conductivity, dissolved oxygen, water depth, water temperature, turbidity, plankton concentration, current variables, chlorophylla, total carotenoids, and species diversity of the benthic community. Strong correlation between turbidity and MSS-sensed radiance was recorded and less strong correlations between the two plankton pigments and radiance. Turbidity and benthic species diversity were highly correlated furnishing an inferential tie between an easily sensed water quality variable and a sensitive indicator of average water quality conditions.

Coulbourn, W. C.↗