GSTDTAP
项目编号1564670
The Impact of Fire on Entrainment and Precipitation Efficiency Derived from Isotope Ratios
David Noone
主持机构Oregon State University
项目开始年2016
2016-08-01
项目结束日期2019-07-31
资助机构US-NSF
项目类别Standard Grant
项目经费587291(USD)
国家美国
语种英语
英文摘要Biomass burning in central and southern Africa produces some of the world's most dense layers of smoke. The smoke plumes and transported over the southern Atlantic Ocean where they merge with wide areas of low altitude stratocumulus clouds. The details of how smoke aerosol particles and stratocumulus clouds interact is inadequately understood, despite the disproportionally large role those types of clouds play in local and global climate. This project seeks to improve understanding of how smoke changes the way air circulates near clouds, how cloud droplets in polluted clouds evaporate at different rates from those in pristine clouds, and how drizzle is modified when smoke is present. Stable isotope ratios of oxygen and hydrogen in water vapor and cloud liquid will be measured from aircraft flights though smoke and cloud layers near Namibia to evaluate characteristics of atmospheric mixing, cloud evaporation and the fraction of clouds droplets which grow to produce rain. These characteristics are difficult to quantify from more traditional methods. Isotopic data will be used to evaluate entrainment and evaporation simulated by the NCAR Community Earth System Model to evaluate where new understanding from the experiment can improve model simulations.

Lack of knowledge about cloud-smoke interactions leads to crude treatment of processes in climate models, which consequently leads important unresolved uncertainties in climate model simulations. The isotopic study provides a sorely needed critical check on how clouds are depicted in models and gives specific guidance as to which mechanisms are incorrectly represented. The datasets collected enable several research groups to test and compare their models using isotopic constraints which will serve as a valuable legacy of the experiment. The data-model synthesis fosters collaboration that bridges between observation and modeling specialists and enables students training in combining expertise in modeling and data methods to achieve enhanced knowledge though synthesis. The project provides opportunities to engage learning at many levels though incorporation of research experiences in class room teaching at Oregon State University and in public outreach forums.
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条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/70013
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David Noone.The Impact of Fire on Entrainment and Precipitation Efficiency Derived from Isotope Ratios.2016.
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