Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMiranda, Francisco O.-
dc.contributor.authorRamos, Fernando Manuel-
dc.contributor.authorRandow, Celso Von-
dc.contributor.authorDias Júnior, Cléo Quaresma-
dc.contributor.authorChamecki, Marcelo-
dc.contributor.authorFuentes, José D.-
dc.contributor.authorManzi, Antônio Ocimar-
dc.contributor.authorde Oliveira, Marceliano E.-
dc.contributor.authorSouza, Cledenilson Mendonça de-
dc.description.abstractWe apply different methods for detection of extreme phenomena (EP) in air-turbulent time series measured in the nocturnal boundary layer above the Amazon forest. The methods used were: (a) a Morlet complex wavelet transform, which is often used in analysis of non-linear application processes. Through the use of the wavelet, it is possible to observe a phase singularity that involves a strong interaction between an extensive range of scales; (b) recurrence plot tests, which were used to identify a sudden change between different stable atmospheric states. (c) statistical analysis of early-warning signals, which verify simultaneous increases in the autocorrelation function and in the variance in the state variable; and (d) analysis of wind speed versus turbulent kinetic energy to identify different turbulent regimes in the stable boundary layer. We found it is adequate to use a threshold to classify the cases of strong turbulence regime, as a result of the occurrence of EP in the tropical atmosphere. All methods used corroborate and indicate synergy between events that culminate in what we classify as EP of the stable boundary layer above the tropical forest. © 2020 by the authors.en
dc.relation.ispartofVolume 11, Número 9pt_BR
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Brazil*
dc.subjectExtreme phenomenaen
dc.subjectNocturnal Boundary Layeren
dc.subjectTurbulence regimesen
dc.titleDetection of extreme phenomena in the stable boundary layer over the Amazonian forestpt_BR
Appears in Collections:Artigos

Files in This Item:
File Description SizeFormat 
artigo-inpa.pdf9,44 MBAdobe PDFThumbnail

This item is licensed under a Creative Commons License Creative Commons