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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Geostationary Operational Environmental Statellite(GEOS-N report)

The Advanced Missions Analysis Office (AMAO) of GSFC has completed a study of the Geostationary Operational Environmental Satellites (GOES-N) series. The feasibility, risks, schedules, and associated costs of advanced space and ground system concepts responsive to National Oceanic and Atmospheric Administration (NOAA) requirements were evaluated. The study is the first step in a multi-phased procurement effort that is expected to result in launch ready hardware in the post 2000 time frame. This represents the latest activity of GSFC in translating meteorological requirements of NOAA into viable space systems in geosynchronous earth orbits (GEO). GOES-N represents application of the latest spacecraft, sensor, and instrument technologies to enhance NOAA meteorological capabilities via remote and in-situ sensing from GEO. The GOES-N series, if successfully developed, could become another significant step in NOAA weather forecasting space systems, meeting increasingly complex emerging national needs for that agency's services.

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Evaluation of Time-Series Gap-Filling Methods for Solar Irradiance Applications

A complete solar resource data set is essential for any stage of a solar energy project - from feasibility studies to daily operations. But measured or modeled solar resource data are prone to data gaps and data quality issues. To mitigate these issues, a data imputation process should be implemented to obtain a complete and reliable temporal and spatial data series. This study focused on imputing temporal scales by applying random and artificial data gaps and then implementing eight imputation methods, including the Kalman filtering and smoothing and stine interpolations. These methods were implemented on 1-minute to half hourly irradiance data for 1 year using a few locations from the National Solar Radiation Database (NSRDB) and ground measurement data set. The results demonstrated that some of the simpler methods, such as the stine and linear interpolation methods, were the relatively best models based on the statistical metrics for imputing NSRDB and ground measurement data, respectively.

14 SOLAR ENERGY↗