DOI: 10.1002/jgrd.50237
论文题名: Statistical decision analysis for flight decision support: The SPartICus campaign
作者: Hanlon C.J. ; Stefik J.B. ; Small A.A. ; Verlinde J. ; Young G.S.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 10 起始页码: 4679
结束页码: 4688
语种: 英语
英文关键词: algorithm
; decision analysis
; field campaign
; resource allocation
Scopus关键词: Algorithms
; Clouds
; Conformal mapping
; Decision support systems
; Decision theory
; Forecasting
; Heuristic methods
; Resource allocation
; Tools
; Atmospheric radiation measurements
; Atmospheric science
; Field campaign
; Global forecast systems
; Optimization procedures
; Probabilistic forecasts
; Southern great plains
; Statistical decision
; Decision making
; aircraft
; cirrus
; data acquisition
; decision analysis
; decision support system
; flight
; optimization
; relative humidity
; resource allocation
; season
; Great Plains
英文摘要: Field campaigns in atmospheric science typically require making challenging decisions about how best to deploy limited resources, especially aircraft flight hours. Algorithmic decision tools have shown the potential to outperform traditional heuristic approaches to allocating limited flight hours in field campaigns. The present study examines the utility of algorithmic decision tools in an application to the Atmospheric Radiation Measurement (ARM) Small Particles in Cirrus (SPartICus) campaign, which sampled cirrus clouds over the ARM Southern Great Plains (SGP) site between January and June 2010. Probabilistic forecasts of suitable data collection conditions were generated using relative humidity forecasts from the Global Forecast System (GFS) and self-organizing maps. An optimization procedure based on dynamic programming was then used to generate day-ahead fly/no-fly decisions for research flights over the SGP site. The quality of flight decisions thus generated were compared with those made by the SPartICus science team. Results showed that the algorithmic decision tool would have delivered 11% more optimal data while shortening the length of the campaign season by 29 days and reducing the per-day expenditure of investigator time on activities of forecasting and decision-making. Key pointsAlgorithmic decision tools show promise in field campaign resource allocation.The SPartICus campaign measured cirrus clouds using aircraft.An algorithmic tool could have saved resources, yielded more data. ©2013. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63735
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
There are no files associated with this item.
作者单位: Department of Meteorology, Pennsylvania State University, 503 Walker Building, University Park, PA 16802, United States; Risk Management Solutions, Hoboken NJ, United States; Venti Risk Management, State College PA, United States
Recommended Citation:
Hanlon C.J.,Stefik J.B.,Small A.A.,et al. Statistical decision analysis for flight decision support: The SPartICus campaign[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(10)