Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019GL084305 |
Tracking Pyrometeors With Meteorological Radar Using Unsupervised Machine Learning | |
McCarthy, N. F.1; Guyot, A.2; Protat, A.3; Dowdy, A. J.3; McGowan, H.1 | |
2020-04-28 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS |
ISSN | 0094-8276 |
EISSN | 1944-8007 |
出版年 | 2020 |
卷号 | 47期号:8 |
文章类型 | Article |
语种 | 英语 |
国家 | Australia |
英文摘要 | Pyrometeors are the large (>2 mm) debris lofted above wildfires that are composed of the by-products of combustion of the fuels. One speciation of pyrometeor is firebrands, which are burning debris that lead to ignitions ahead of the surface fire and can be the dominant mechanism of fire spread and structure loss. Pyrometeors are observed by meteorological radar. To date, there have been no investigations into identification of pyrometeor speciation with radar. Here we present an unsupervised machine learning method (Gaussian mixture model) to classify pyrometeor modes using X-band radar data. The coherent features of the mode of pyrometeor identified most likely to transport firebrands were tracked in time and space. The radar classification and tracking method shows that wildfires do produce signatures in radar returns that could be used for spot fire risk prediction. In wildfires, different types of debris (known as pyrometeors) are lofted in the smoke plumes and transported downwind. Some types of pyrometeors may, when in the air, still be burning and capable of starting new wildfires. Here we investigate the potential for meteorological radar to classify different types of pyrometeors and to track them to determine their potential for starting new fires downwind of the main fire front. |
英文关键词 | Wildfire Radar Pyrometeor Machine Learning Gaussian Mixture Model Hydrometeor |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000530332600040 |
WOS关键词 | HYDROMETEOR CLASSIFICATION ; WEATHER RADAR ; DYNAMICS ; WILDFIRE ; PLUME |
WOS类目 | Geosciences, Multidisciplinary |
WOS研究方向 | Geology |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/279887 |
专题 | 气候变化 |
作者单位 | 1.Univ Queensland, Sch Earth & Environm Sci, Atmospher Observat Res Grp, Brisbane, Qld, Australia; 2.Monash Univ, Dept Civil Engn, Melbourne, Vic, Australia; 3.Australian Bur Meteorol, Melbourne, Vic, Australia |
推荐引用方式 GB/T 7714 | McCarthy, N. F.,Guyot, A.,Protat, A.,et al. Tracking Pyrometeors With Meteorological Radar Using Unsupervised Machine Learning[J]. GEOPHYSICAL RESEARCH LETTERS,2020,47(8). |
APA | McCarthy, N. F.,Guyot, A.,Protat, A.,Dowdy, A. J.,&McGowan, H..(2020).Tracking Pyrometeors With Meteorological Radar Using Unsupervised Machine Learning.GEOPHYSICAL RESEARCH LETTERS,47(8). |
MLA | McCarthy, N. F.,et al."Tracking Pyrometeors With Meteorological Radar Using Unsupervised Machine Learning".GEOPHYSICAL RESEARCH LETTERS 47.8(2020). |
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