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  • Earth Resources and Remote Sensing  (2)
  • 2005-2009  (2)
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  • 1
    Publication Date: 2019-07-19
    Description: Data obtained from the OTD (April 1995 to March 2000) and LIS (December 1997 to December 2005) satellites (70 and 35 degree inclination low earth orbits, respectively) are used to statistically determine the number of flashes in the diurnal cycle both as a function of local and universal time. Also included are global flash density maps. The data are further subdivided by season, continental versus oceanic, night time versus day time, northern versus southern hemisphere, and other regions of interest. The data include corrections for detection efficiency and instrument view time. The data are compared with both the "Carnegie Curve" and the diurnal global thunderstorm contributions from thunderday statistics from different continents, and are found to agree closely in phase and amplitude with the global thunderday statistics. The analysis also indicates that the southern hemisphere spring (September to November) has larger amplitude than the southern hemisphere fall (March to May). This may be due to differences in the contribution from the Brazilian rain forest during these periods. In general, as highlighted by a difference analysis, more lightning is observed in local springtime than the fall for continental locations, while oceanic regions display an opposite effect. For some areas of the world, the peak of diurnal curve appears to be shifted to later in the evening.
    Keywords: Earth Resources and Remote Sensing
    Type: International Conferences on Atmospheric Electricity (ICAE); Aug 13, 2007 - Aug 17, 2007; Beijing; China|International Commission on Atmospheric Electricity; Aug 13, 2007 - Aug 17, 2007; Beijing; China
    Format: text
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  • 2
    Publication Date: 2019-07-13
    Description: NASA seeks on-demand data processing and analysis of Earth science observations to facilitate timely decision-making that can lead to the realization of the practical benefits of satellite instruments, airborne and surface remote sensing systems. However, a significant challenge exists in accessing and integrating data from multiple sensors or platforms to address Earth science problems because of the large data volumes, varying sensor scan characteristics, unique orbital coverage, and the steep "learning curve" associated with each sensor, data type, and associated products. The development of sensor web capabilities to autonomously process these data streams (whether real-time or archived) provides an opportunity to overcome these obstacles and facilitate the integration and synthesis of Earth science data and weather model output.
    Keywords: Earth Resources and Remote Sensing
    Type: NASA Science Technology Conference; Jun 19, 2007 - Jun 21, 2007; Adelphi, MD; United States
    Format: application/pdf
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