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Global Navigation Satellite System (GNSS) Final Clock Product (30 second resolution, daily files, generated weekly) from NASA CDDIS
data.nasa.gov | Last Updated 2023-02-28T19:25:26.000ZThis derived product set consists of Global Navigation Satellite System Final Satellite and Receiver Clock Product (30-second granularity, daily files, generated weekly) from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. Analysis Centers (ACs) of the International GNSS Service (IGS) retrieve GNSS data on regular schedules to produce GNSS satellite and ground receiver clock values. The IGS Analysis Center Coordinator (ACC) uses these individual AC solutions to generate the official IGS final combined satellite and receiver clock products. The final products are considered the most consistent and highest quality IGS solutions; they consist of daily orbit files, generated on a weekly basis with a delay up to 13 (for the last day of the week) to 20 (for the first day of the week) days. All satellite and receiver clock solution files utilize the clock RINEX format and span 24 hours from 00:00 to 23:45 UTC.
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NEW HORIZONS SDC JUPITER ENCOUNTER CALIBRATED V4.0
data.nasa.gov | Last Updated 2023-01-26T20:41:44.000ZThis data set contains Calibrated data taken by the New Horizons Student Dust Counter instrument during the Jupiter encounter mission phase. This is VERSION 4.0 of this data set. For the Jupiter encounter mission phase, SDC collected no science data during the Jupiter flyby, as the requisite spacecraft configuration prevented SDC from operating. There were some very sparse data taken from December, 2006 through April, 2007, and some of very short (or zero) duration after the Jupiter flyby from April, 2007 through June, 2007. The changes in Version 4.0 were re-running of the ancillary data in the data product, updated geometry from newer SPICE kernels, minor editing of the documentation, catalogs, etc., and resolution of liens from the December, 2014 review, plus those from the May, 2016 review of the Pluto Encounter data sets. No new observations were added with Version 4.0.
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ASO L4 Lidar Snow Water Equivalent 50m UTM Grid V001
data.nasa.gov | Last Updated 2022-01-17T05:08:23.000ZThis data set contains 50 m gridded snow water equivalent (SWE) values collected as part of the NASA/JPL Airborne Snow Observatory (ASO) aircraft survey campaigns. The data were derived from the <a href="https://nsidc.org/data/aso_50m_sd">ASO L4 Lidar Snow Depth 50m UTM Grid</a> data product and from modeled snow density.
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Contribution to High Asia Runoff from Ice and Snow (CHARIS) Melt Model Output, 2001 - 2014, Version 1
data.nasa.gov | Last Updated 2022-01-17T05:15:59.000ZThis data set contains input and output data for temperature index (TI) model runs completed for the Contributions to High Asia Runoff from Ice and Snow (CHARIS) project at NSIDC in 2018 and 2019. The input data are the area of snow on land, snow on ice, and exposed glacier ice as well as surface air temperature. These inputs are used to model the volumes of melt runoff from the snow on land, snow on ice, and exposed glacier ice in certain areas of High Mountain Asia.
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VIIRS/NPP BRDF/Albedo Snow Status Daily L3 Global 30ArcSec CMG V001
data.nasa.gov | Last Updated 2024-05-27T13:06:38.000ZThe NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Bidirectional Reflectance Distribution Function (BRDF) and Albedo Snow Status product (VNP43D52) is produced daily using 16 days of data at 30 arc second (1,000 meter) resolution. Data are temporally weighted to the ninth day, which is reflected in the file name. The VNP43D product suite is provided in a Climate Modeling Grid (CMG), which covers the entire globe for use in climate simulation models. Due to the large file size, each VNP43D product contains just one data layer for each of the parameters included in the VNP43MA2 (https://doi.org/10.5067/VIIRS/VNP43MA2.001) product. VNP43D40 through VNP43D53 are the 30 arc second BRDF/Albedo Quality values, the Local Solar Noon values, the Valid Observations of the moderate resolution bands (M1 through M5, M7, M8, M10, and M11) plus the Day/Night Band (DNB), the Snow Status, and the Uncertainty. Details regarding methodology are available on the VNP43MA2 product page and in the Algorithm Theoretical Basis Document (ATBD). VNP43D52 contains the snow status quality layer, which identifies each pixel as either “Snow-free Albedo Retrieved” or “Snow Albedo Retrieved” for the acquisition period.
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High Mountain Asia UCLA Daily Snow Reanalysis V001
data.nasa.gov | Last Updated 2022-01-17T05:28:32.000ZSnowpack plays a significant role in the hydrologic cycle over High Mountain Asia (HMA). As a vital water resource, the distribution of snowpack volume also impacts the water availability for downstream populations. To assess the regional water balance, it is important to characterize the spatio-temporal distribution of water storage in the HMA snowpack. This HMA snow reanalysis data set contains daily estimates of posterior snow water equivalent (SWE), fractional snow covered area (fSCA), snow depth (SD), etc.
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Global Navigation Satellite System (GNSS) IGS Clock Combination Product from Real-Time AC Submissions from NASA CDDIS
data.nasa.gov | Last Updated 2022-01-17T05:22:33.000ZThis derived product set consists of Global Navigation Satellite System satellite and receiver clock combination product (30-second granularity, daily files, generated daily) from the real-time IGS analysis center submissions available from NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. The CDDIS provides access to products generated from real-time data streams in support of the IGS Real-Time Service. The real-time observation data from a global permanent network of ground-based receivers are transmitted from the CDDIS in 1 to multi-second intervals in raw receiver or RTCM (Radio Technical Commission for Maritime Services) format. These real-time data are utilized to generate near real-time product streams. The real-time products consist of GNSS satellite orbit and clock corrections to the broadcast ephemeris. These correction streams are formatted according to the RTCM SSR standard for State Space Representation and are broadcast using the NTRIP protocol. IGS analysis centers (ACs) access GNSS real-time data streams to produce GNSS satellite and ground receiver clock values in real-time. The product streams are combination solutions generated by processing individual real-time solutions from participating IGS Real-time ACs. The IGS Real-Time Analysis Center Coordinator (RTACC) uses these individual AC solutions to generate this real-time IGS combined satellite and receiver clock product. The effect of combining the different AC solutions is a more reliable and stable performance than that of any single AC's product. This clock solution is a batch combination based on daily clock submissions by these IGS real-time analysis centers and have been provided since February 2009, shortly after real-time streams were routinely available through the IGS Real-Time Pilot Project and prior to the availability of real-time product streams. Clock solution files consist of decoded clock results from the real time stream at 30-second intervals. This combination is a daily solution available approximately one to three days after the end of the previous UTC day. All satellite and receiver clock solution files utilize the clock RINEX format and span 24 hours from 00:00 to 23:45 UTC.
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SnowEx17 Boise State University Terrestrial Laser Scanner (TLS) Point Cloud V001
data.nasa.gov | Last Updated 2022-01-17T05:55:02.000ZThis data set contains terrestrial laser scanner (TLS) point cloud data collected as part of the 2017 SnowEx campaign in Grand Mesa, Colorado. Data were collected under both snow-off (September 2016) and snow-on (February 2017) conditions, at both open and forested locations. Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i). These TLS data can be used to determine snow depth and explore the interactions between snow and vegetation.
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Global Navigation Satellite System (GNSS) Rapid Clock Product (30 second resolution, daily files, generated daily) from NASA CDDIS
data.nasa.gov | Last Updated 2023-02-28T19:25:38.000ZThis derived product set consists of Global Navigation Satellite System Rapid Satellite and Receiver Clock Product (30-second granularity, daily files, generated daily) from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. Analysis Centers (ACs) of the International GNSS Service (IGS) retrieve GNSS data on regular schedules to produce GNSS satellite and ground receiver clock values. The IGS Analysis Center Coordinator (ACC) uses these individual AC solutions to generate the official IGS rapid combined satellite and receiver clock products. The rapid combination is a daily solution available approximately 17 hours after the end of the previous UTC day. All satellite and receiver clock solution files utilize the clock RINEX format and span 24 hours from 00:00 to 23:45 UTC. For most applications the user of IGS products will not notice any significant differences between results obtained using the IGS Final and the IGS Rapid products.
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Classification of Aeronautics System Health and Safety Documents
data.nasa.gov | Last Updated 2020-01-29T01:57:57.000ZMost complex aerospace systems have many text reports on safety, maintenance, and associated issues. The Aviation Safety Reporting System (ASRS) spans several decades and contains over 700 000 reports. The Aviation Safety Action Plan (ASAP) contains over 12 000 reports from various airlines. Problem categorizations have been developed for both ASRS and ASAP to enable identification of system problems. However, repository volume and complexity make human analysis difficult. Multiple experts are needed, and they often disagree on classifications. Even the same person has classified the same document differently at different times due to evolving experiences. Consistent classification is necessary to support tracking trends in problem categories over time. A decision support system that performs consistent document classification quickly and over large repositories would be useful. We discuss the results of two algorithms we have developed to classify ASRS and ASAP documents. The first is Mariana---a support vector machine (SVM) with simulated annealing, which is used to optimize hyperparameters for the model. The second method is classification built on top of nonnegative matrix factorization (NMF), which attempts to find a model that represents document features that add up in various combinations to form documents. We tested both methods on ASRS and ASAP documents with the latter categorized two different ways. We illustrate the potential of NMF to provide document features that are interpretable and indicative of topics. We also briefly discuss the tool that we have incorporated Mariana into in order to allow human experts to provide feedback on the document categorizations.