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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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NASA NTRS1965

Meteorological satellites.

Launch vehicle, spacecraft, command and data station and data utilization for meteorological satellite systems, satellite stabilization and orbit types

SPACECRAFT STABILITY↗
NASA NTRS2014

Applied Meteorology Unit (AMU) Quarterly Report First Quarter FY-14

NASA's LSP and other programs at Vandenberg Air Force Base (VAFB) use wind forecasts issued by the 30th Operational Support Squadron (30 OSS) to determine if they need to limit activities or protect property such as a launch vehicle due to the occurrence of warning level winds at VAFB in California. The 30 OSS tasked the AMU to provide a wind forecasting capability to improve wind warning forecasts and enhance the safety of their customers' operations. This would allow 30 OSS forecasters to evaluate pressure gradient thresholds between pairs of regional observing stations to help determine the onset and duration of warning category winds. Development of such a tool will require that solid relationships exist between wind speed and the pressure gradient of one or more station pairs. As part of this task, the AMU will also create a statistical climatology of meteorological observations from the VAFB wind towers.

Forecasting↗
NASA NTRS2016

Estimation of Daily PM(sub 10) Concentrations in Italy (2006-2012) Using Finely Resolved Satellite Data, Land Use Variables and Meteorology

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM10=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM10levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Particulate Matter/analysis↗