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  • Other Sources  (1,447)
  • Earth Resources and Remote Sensing  (1,447)
  • 2020-2022  (5)
  • 2000-2004  (1,434)
  • 1900-1904  (8)
  • 1
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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
    Format: application/pdf
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  • 2
    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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  • 3
    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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  • 4
    Publication Date: 2020-01-23
    Description: No abstract available
    Keywords: Earth Resources and Remote Sensing
    Type: MSFC-E-DAA-TN76637 , AMS Annual Meeting; Jan 12, 2020 - Jan 16, 2020; Boston, MA; United States
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  • 5
    Publication Date: 2020-01-15
    Description: No abstract available
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN76438 , ESIP Winter Meeting; Jan 07, 2020 - Jan 09, 2020; Bethesda, MD; United States
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  • 6
    Publication Date: 2019-08-28
    Description: Below is the 1st year progress report for NAG5-13435 "New Retrieval Algorithms for Geophysical Products from GLI and MODIS Data". Activity on this project has been coordinated with our NASA DB project NAG5-9604. For your convenience, this report has six sections and an Appendix. Sections I - III discuss specific activities undertaken during the past year to analyze/use MODIS data. Section IV formally states our intention to no longer pursue any research using JAXA's (formerly NASDA's) GLI instrument which catastrophically failed very early after launch (also see the Appendix). Section V provides some indications of directions for second year activities based on our January 2004 telephone discussions and email exchanges. A brief summary is given in Section VI.
    Keywords: Earth Resources and Remote Sensing
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  • 7
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    In:  CASI
    Publication Date: 2019-08-28
    Description: This document is concentrates on a couple of the missions where the Spacelab hardware was used to do Earth science. The Atmospheric Laboratory for Applications and Science (ATLAS) series of missions and the Lidar in-Space Technology Experiment (LITE) mission, the ATLAS being a series of three Shuttle missions that were very much Spacelab missions, are described. A little bit about the history, what the missions were, some of the instruments that were on them, and results are given.
    Keywords: Earth Resources and Remote Sensing
    Type: The Spacelab Accomplishments Forum; 67-90; NASA/CP-2000-210332
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  • 8
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    In:  Other Sources
    Publication Date: 2019-08-26
    Description: An assessment of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) laboratory and in-flight uniformity is presented in this Slide presentation. The ideal uniform system is described, being a system where every spectrum is intercomparable to every other spectrum. Two types of failures to achieve this uniformity are described. Graphs showing measured spectral upwelling radiance, the expanded spectral convolution, the radiometric error from spectral error, the results from the hyperion Arizaro calibration experiment and a AVIRIS cross-track uniformity are among those presented. The reasons why uniformity matters are presented.
    Keywords: Earth Resources and Remote Sensing
    Type: AVIRIS Workshop; May 24, 2005 - May 27, 2005; California; United States
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  • 9
    Publication Date: 2019-08-26
    Description: Increasing numbers of space assets can enable coordinated measurements of flooding phenomena to enhance tracking of extreme events. We describe the use of space and ground measurements to target further measurements as part of a flood monitoring system in Thailand. We utilize rapidly delivered MODIS data to detect major areas of flooding and the target the Earth Observing One Advanced Land Imager sensor to acquire higher spatial resolution data. Automatic surface water extent mapping products delivered to interested parties. We are also working to extend our network to include in-situ sensing networks and additional space assets.
    Keywords: Earth Resources and Remote Sensing
    Type: 34th International Symposium on Remote Sensing of Environment; Apr 10, 2011 - Apr 15, 2011; Sydney; Australia
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  • 10
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    In:  Other Sources
    Publication Date: 2019-08-17
    Description: The Land Surface data include bihemispherical and directional-hemispherical reflectances (albedo), hemispherical directional and bidirectional reflectance factors (BRF), BRF model parameters, leaf-area index (LAI), fraction of photosynthetically active radiation (FPAR), and normalized difference vegetation index (NDVI) on a 1.1 km grid. The land surface data include hemispherical directional reflectance factor, bihemispherical reflectance (i.e., albedo), bidirectional reflectance factor, directional hemispherical reflectance, BRF model parameters, FPAR, and terrain-referenced view and illumination angles. [Location=GLOBAL LAND] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km - 17.6 km; Longitude_Resolution=1.1 km - 17.6 km; Horizontal_Resolution_Range=1 km - 〈 10 km or approximately .01 degree - 〈 .09 degree; Temporal_Resolution=about 15 orbits/day].
    Keywords: Earth Resources and Remote Sensing
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