Arid
DOI10.1016/j.aeolia.2017.09.005
Signal-adapted tomography as a tool for dust devil detection
Aguirre, C.1; Franzese, G.2,3; Esposito, F.2; Vazquez, Luis4; Caro-Carretero, Raquel5; Vilela-Mendes, Rui6; Ramirez-Nicolas, Maria; Cozzolino, F.2; Popa, C. I.2
通讯作者Caro-Carretero, Raquel
来源期刊AEOLIAN RESEARCH
ISSN1875-9637
EISSN2212-1684
出版年2017
卷号29页码:12-22
英文摘要

Dust devils are important phenomena to take into account to understand the global dust circulation of a planet. On Earth, their contribution to the injection of dust into the atmosphere seems to be secondary. Elsewhere, there are many indications that the dust devil’s role on other planets, in particular on Mars, could be fundamental, impacting the global climate. The ability to identify and study these vortices from the acquired meteorological measurements assumes a great importance for planetary science.


Here we present a new methodology to identify dust devils from the pressure time series testing the method on the data acquired during a 2013 field campaign performed in the Tafilalt region (Morocco) of the North-Western Sahara Desert. Although the analysis of pressure is usually studied in the time domain, we prefer here to follow a different approach and perform the analysis in a time signal-adapted domain, the relation between the two being a bilinear transformation, i.e. a tomogram. The tomographic technique has already been successfully applied in other research fields like those of plasma reflectometry or the neuronal signatures. Here we show its effectiveness also in the dust devils detection. To test our results, we compare the tomography with a phase picker time domain analysis. We show the level of agreement between the two methodologies and the advantages and disadvantages of the tomographic approach.


英文关键词Mars Dust devils Tomography technique Meteorology North-Western Sahara
类型Article
语种英语
国家Spain ; Italy ; Portugal
收录类别SCI-E
WOS记录号WOS:000418972000002
WOS关键词ELECTRIC-FIELD ; SALTATION ; MARS
WOS类目Geography, Physical
WOS研究方向Physical Geography
来源机构University of London
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/197065
作者单位1.Univ Autonoma Madrid, Escuela Politecn Super, Calle Francisco Tomas y Valiente 11, Madrid 28260, Spain;
2.INAF, Osservatorio Astron Capodimonte, Salita Moiariello 16, I-80131 Naples, Italy;
3.Univ Naples Federico II, Dept Phys E Pacini, Via Cinthia, I-80126 Naples, Italy;
4.Univ Complutense Madrid, Fac Informat, Calle Profesor Jose Garcia Santesmases 9, E-28040 Madrid, Spain;
5.Univ Pontificia Comillas Madrid, Escuela Tecn Super Ingn, ICAI, Calle Alberto Aguilera 25, Madrid 28015, Spain;
6.Univ Lisbon C6, Ctr Matemat & Aplicacoes Fundamentals, P-1749016 Lisbon, Portugal
推荐引用方式
GB/T 7714
Aguirre, C.,Franzese, G.,Esposito, F.,et al. Signal-adapted tomography as a tool for dust devil detection[J]. University of London,2017,29:12-22.
APA Aguirre, C..,Franzese, G..,Esposito, F..,Vazquez, Luis.,Caro-Carretero, Raquel.,...&Popa, C. I..(2017).Signal-adapted tomography as a tool for dust devil detection.AEOLIAN RESEARCH,29,12-22.
MLA Aguirre, C.,et al."Signal-adapted tomography as a tool for dust devil detection".AEOLIAN RESEARCH 29(2017):12-22.
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