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Using the Fire Weather Index (FWI) to improve the estimation of fire emissions from fire radiative power (FRP) observations

机译:使用消防天气指数(FWI)来改善火灾辐射功率(FRP)观测的消防排放量

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摘要

The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation System (GFAS). The GFAS is a global system and converts fire radiative power (FRP) observations from MODIS satellites into smoke constituents. Missing observations are filled in using persistence, whereby observed FRP values from the previous day are progressed in time until a new observation is recorded. One of the consequences of this assumption is an increase of fire duration, which in turn translates into an increase of emissions estimated from fires compared to what is available from observations. In this study persistence is replaced by modelled predictions using the Canadian Fire Weather Index (FWI), which describes how atmospheric conditions affect the vegetation moisture content and ultimately fire duration. The skill in predicting emissions from biomass burning is improved with the new technique, which indicates that using an FWI-based model to infer emissions from FRP is better than persistence when observations are not available.
机译:欧洲哥白尼大气监测服务(CAMS)的大气成分分析和预测依赖于全球防火系统(GFAS)的生物质燃烧消防估计。 GFA是全球系统,并将来自Modis卫星的火辐射功率(FRP)观察转换为烟雾成分。使用持久性填写缺失的观察结果,从而观察到前一天的FRP值随时间进行,直到记录新的观察。这种假设的后果是导致火持续时间的增加,而导致从火灾估计的排放量增加,而与从观察结果中获得的内容。在本研究中,持久性通过使用加拿大火灾天气指数(FWI)的建模预测所取代,该预测描述了大气条件如何影响植被水分含量和最终火灾持续时间。利用新技术提高了从生物质燃烧预测排放的技能,这表明使用基于FWI的模型从FRP的推断出来的优于持久性,而当观察不可用。

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