Detection of Extreme Phenomena in the Stable Boundary Layer over the Amazonian Forest

Francisco O Miranda,Francisco O Miranda,Cléo Q Dias-Júnior,Jose D Fuentes,Marceliano E De Oliveira,Cledenilson M De Souza,Celso Von Randow,Cléo Q Dias-Júnior,Antônio O Manzi,Marcelo Chamecki,Antônio O Manzi,Fernando M Ramos

doi:10.3390/atmos11090952

Abstract

We 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.

Highlights

Many of the techniques used for the analysis of micrometeorological data do not take into account situations where extreme phenomena (EP) are manifested
Experimental data measured in the nocturnal boundary layer, above the Amazon rainforest, were used to analyze strong variations that occur simultaneously in time series
One of them analyzed early-warning signals, where there was an increase in the autocorrelation function and in the variance of the state variables immediately before the onset of an extreme phenomena

Summary

Introduction

Many of the techniques used for the analysis of micrometeorological data do not take into account situations where extreme phenomena (EP) are manifested. The occurrence of an EP might be characterized as an emergent phenomenon in non-linear processes as discussed in a general way by [11,12,13] and in specific applications by [14,15,16], among others. Such processes are often associated with the emergence of critical slowing down, where a system is close to a critical tipping point and recovery rates of equilibrium states decrease, which have been observed in distinct scientific domains. Weng and Lau, and Lau and Weng [17,18]

Methods

Results

Conclusion