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  • Other Sources  (22,493)
  • ASTROPHYSICS  (16,581)
  • Earth Resources and Remote Sensing  (5,912)
  • 1
    Publication Date: 2020-01-24
    Description: The NASA Global Imagery Browse Services (GIBS) and Worldview interactive mapping site leverage scientific and community best practices, open source software, and public standards to provide a scalable, compliant, and authoritative source for NASA Earth Observing System (EOS) Earth science data visualizations. GIBS and Worldview allow end users to easily and quickly interact with more than 800 full resolution pre-generated raster- and vector-based visualizations. This interactive discovery approach relies on visual observation and identification of phenomena that are not as simply identified otherwise. This eLightning presentation will exhibit the broad set of capabilities and visualization layers made possible through the GIBS and Worldview open source software. Specific dependencies on, and contributions to, open source software will be highlighted. Additionally, opportunities for future improvements for better interoperability and reuse through open source software will be discussed.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN76098 , American Geophysical Union (AGU) Fall Meeting 2019; Dec 09, 2019 - Dec 13, 2019; San Francisco, CA; United States
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  • 2
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    In:  CASI
    Publication Date: 2020-01-24
    Description: The Alpha Jet Atmospheric eXperiment (AJAX) airborne science project based out of NASA Ames Research Center performed eight science flights in coordination with the California Baseline Ozone Transport Study (CABOTS) campaign. Many of these flights included a series of vertical profiles (~ 0-5 km) distributed roughly along either a North/South or East/West transect. Some flights also connected the fixed-location measurements at Visalia (TOPAZ ozone lidar) and Bodega Bay (ozonesondes). AJAX measured ozone, carbon dioxide, methane, water vapor, and 3-D winds on each flight, and those in situ measurements are the basis of the data sets collected here. Trace gas data sets including time and aircraft position have been delivered as comma-separated-value text files. Meteorological data (temperature, pressure and 3-dimensional winds) are provided at 1 Hz in ICARTT-compliant text files.
    Keywords: Earth Resources and Remote Sensing
    Type: ARC-E-DAA-TN77025
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  • 3
    Publication Date: 2020-01-24
    Description: Northern peatlands are an integral part of the global carbon cyclea strong sink of atmospheric carbon dioxide and source of methane. Increasing anthropogenic carbon dioxide and methane in the atmosphere are thought to strongly impact these environments, and yet, peatlands are not routinely included in Earth system models. Here we present a quantification of the sink and stock of northern peat carbon from the last glacial period through the pre-industrial period. Additional data and new algorithms for reconstructing the history of peat carbon accumulation and the timing of peatland initiation increased the estimate of total northern peat carbon stocks from 545 Gt to 1,055 Gt of carbon. Further, the post-glacial increases in peatland initiation rate and carbon accumulation rate are more abrupt than previously reported. Peatlands have been a strong carbon sink throughout the Holocene, but the atmospheric partial pressure of carbon dioxide has been relatively stable over this period. While processes such as permafrost thaw and coral reef development probably contributed some additional carbon to the atmosphere, we suggest that deep ocean upwelling was the most important mechanism for balancing the peatland sink and maintaining the observed stability.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN74633 , Nature Geoscience (ISSN 1752-0894) (e-ISSN 1752-0908); 12; 11; 917–921
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  • 4
    Publication Date: 2020-01-24
    Description: Social media data can provide useful real-time and historical information relating to the natural world, but managing this data poses challenges. Scientists at GES DISC are exploring the potential of Twitter data to augment precipitation data from the Global Precipitation Measurement (GPM) mission. However, the format of Twitter data is unconventional in the context of NASA data centers, resulting in frustration for scientists who need to work with the data. This study investigated procedures and standards needed to properly manage Twitter data to make them compatible with these data centers. After comparing databases, the study found that the MongoDB database was best suited for the storage of raw Twitter data due to its flexibility, ability to be accessed by multiple users, and querying functionality. The study used the Python package Zarr to transform processed Twitter data into a gridded format similar to that of satellite data. Each Tweet was mapped onto a time-space grid; each grid location contained information about Tweet attributes and precipitation. The study developed a pipeline for downloading, storing, and gridding Twitter data and transformed Twitter data into an understandable format for users of NASA satellite data.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN76535 , AGU 2019 Fall Meeting; Dec 10, 2019
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  • 5
    Publication Date: 2020-01-24
    Description: No abstract available
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN76317 , American Geoscience Union (AGU) Fall Meeting; Dec 09, 2019 - Dec 13, 2020; San Francisco, CA; United States
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  • 6
    Publication Date: 2020-01-23
    Description: No abstract available
    Keywords: Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN76011 , AGU 2019 Fall Meeting; Dec 09, 2019 - Dec 13, 2019; San Francisco, CA; United States
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  • 7
    Publication Date: 2020-01-23
    Description: No abstract available
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN76529 , AGU 2019 Fall Meeting; Dec 09, 2019 - Dec 13, 2019; San Francisco, CA; United States
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  • 8
    Publication Date: 2020-01-23
    Description: Spaceborne lidar observations have great potential to provide accurate global estimates of the aerosol direct radiative effect (DRE) in both clear and cloudy conditions. However, comparisons between observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) and multiple years of Atmospheric Radiation Measurement (ARM) programs ground-based Raman lidars (RL) show that CALIPSO does not detect all radiatively significant aerosol, i.e. aerosol that directly modifies the Earths radiation budget. We estimated that using CALIPSO observations results in an underestimate of the magnitude of the global mean aerosol DRE by up to 54%. The ARM RL datasets along with NASA Langley airborne high spectral resolution lidar (HSRL) data from multiple field campaigns are used to compute the detection sensitivity required to accurately resolve the aerosol DRE. This shows that a lidar with a backscatter coefficient detection sensitivity of about 12x10(exp -4)km(exp -1)sr(exp -1) at 532nm would resolve all the aerosol needed to derive the DRE to within 1%.
    Keywords: Earth Resources and Remote Sensing
    Type: NF1676L-27456 , Geophysical Research Letters; 44; 17; 9059-9067
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  • 9
    Publication Date: 2020-01-23
    Description: Adjoint models are powerful tools that can be used to estimate the impact of observations on a chosen norm for numerical weather prediction forecasts. In this study, the Global Modeling and Assimilation Office (NASA/GMAO) Observing System Simulation Experiment framework is employed to investigate the behavior of the adjoint tool in an environment where the 'true' state of the atmosphere is fully known. This allows for the calculation of adjoint estimates of observation impact for very short forecast times including the zero-hour analysis state. The adjoint calculations using self-analysis verification can also be compared to adjoint calculations using the 'truth' as verification in order to characterize the robustness of adjoint estimations in the operational setting. Results from a experiments exploring various aspects of performance of the adjoint tool will be presented.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN76951 , AMS Annual Meeting; Jan 12, 2020 - Jan 16, 2020; Boston, MA; United States
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  • 10
    Publication Date: 2020-01-23
    Description: Some of the most intense thunderstorms on the planet occur in the Hindu Kush Himalaya (HKH) region of South-Central Asia. NASA/SERVIR Applied Sciences Team competitive project to develop capacity of severe thunderstorm monitoring and forecasting tool for HKH. Project Goal: Use [NASA] modeling and remote-sensing assets to build early warning capabilities and facilitate timely disaster response for high impact weather events in the HKH region. Specific objectives: 1. Prototype and transition High-Impact Weather Assessment Toolkit (HIWAT) 2. Jointly develop HIWAT capabilities & training with SERVIRs hub in Kathmandu, Nepal: International Centre for Integrated Mountain Development (ICIMOD) 3. Demonstrate capacity in end-user environment 4. Transition HIWAT system to ICIMOD for future maintenance.
    Keywords: Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN76785 , AMS Annual Meeting; Jan 12, 2020 - Jan 16, 2020; Boston, MA; United States
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