RAPID RESEARCH: Particle Trajectories in Volcanic Plumes: Tracking the 2010 Eyjafjallajokull Plume
RAPID RESEARCH: Particle Trajectories in Volcanic Plumes: Tracking the 2010 Eyjafjallajokull Plume
批准号:
1041775
负责人:
Marcus Bursik
金额:
$7.65万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-06-01 至 2011-05-31
中文摘要
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英文摘要
This RAPID (Rapid Response) project is a collaborative effort by scientists from University at Buffalo (UB), the Geophysical Institute at the University of Alaska - Fairbanks (UAF-GI) and University to make an attempt to model the ash dispersal due to the volcanic eruption at Eyjafjallajokull, Iceland, that has wreaked havoc on European aviation since ash emissions began on 14 April 2010. The advecting downwind plume is thought to be a serious hazard to aircraft, with potential for damage to jet engines and abrasion of airplane leading edges. The proposed work could have important ramifications for air traffic over the next months, as past Eyjafjallajokull eruptions have continued for over one year.It is proposed to use ensemble forecasting to develop probabilistic ash cloud maps at different times. More specifically, the 'Puff' simulation code will be used to hindcast the motion of the Eyjafjallajokull ash cloud through time beginning on 14 April 2010. Variability in the height and loading of the eruption column will be introduced through the column model Bent. Windfield data from several sources and with differing resolutions will be used. Output variability due to uncertain input parameters and initial conditions, and random forcing, will be determined. The output will be validated through comparison with satellite data. The principal scientific goals of this project are: to understand how uncertain input variables and random forcing affect the output of Puff simulations of the Eyjafjallajokull cloud, to validate output against satellite data, and to explore the possibility of producing improved assessments of ash cloud hazards. It is expected that the work will have implications for ash cloud tracking as well as probabilistic hazards assessment and ensemble forecasting.
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