Abstract
Precipitation is the main climatic variable that is used for modeling risks indices for natural disasters. We investigated nonlinear dynamics of monthly rainfall temporal series recorded from 1962 to 2012, at three stations in Pernambuco state, Brazil, located in regions with different rainfall regime (Zona da Mata, Agreste and Sertão), provided by the Meteorological Laboratory of the Institute of Technology of Pernambuco (Laboratório de Meteorologia do Instituto de Tecnologia de Pernambuco – LAMEP/ITEP). The objective of this work is to contribute to a better understanding of the spatiotemporal distribution of rainfall in the state of Pernambuco. We use the methodology from nonlinear dynamics theory, Recurrence plot (RP) that allows to distinguish between different types of underlying processes. The results showed that rainfall regime in deep inland semiarid Sertão region is characterized by weaker and less complex deterministic behavior, comparing to Zona da Mata and Agreste, where we identified transitions between chaotic and nonstationary type of dynamics. For transitional Agreste region rainfall dynamics showed stronger memory with longer mean prediction time, while for sub humid Zona da Mata rainfall dynamics is characterized by laminar (slowly changing) states.
Highlights
Precipitation is the main climatic variable that is used for modeling risks indices for natural disasters that are consequences of luck or excess of rain, such as aridity index, flash floods and landslides vulnerability indices (Marengo & Bernasconi, 2015; Debortoli, Camarinha, Marengo & Rodrigues, 2017)
We investigated nonlinear dynamics of monthly rainfall temporal series recorded from 1962 to 2012, at three stations in Pernambuco state, Brazil, located in regions with different rainfall regime (Zona da Mata, Agreste and Sertão), provided by the Meteorological Laboratory of the Institute of Technology of Pernambuco (Laboratório de Meteorologia do Instituto de Tecnologia de Pernambuco – LAMEP/ITEP)
We use the methodology from nonlinear dynamics theory, Recurrence plot (RP) that allows to distinguish between different types of underlying processes
Summary
Precipitation is the main climatic variable that is used for modeling risks indices for natural disasters that are consequences of luck or excess of rain, such as aridity index, flash floods and landslides vulnerability indices (Marengo & Bernasconi, 2015; Debortoli, Camarinha, Marengo & Rodrigues, 2017). 2. Methodology In this work we use the methodology Recurrence plot originated from network theory, which transforms the time series into network, by analyzing dynamics system trajectories in the phase space. Methodology In this work we use the methodology Recurrence plot originated from network theory, which transforms the time series into network, by analyzing dynamics system trajectories in the phase space It includes both qualitative and quantitative approaches (Pereira, Shitsuka, Parreira & Shitsuka, 2018) which permit to distinguish between different types of nonlinear dynamics. The data used in this work are monthly series of precipitation recorded at three meteorological stations (Figure 1) in the state of Pernambuco, Brazil during the period from 1962 to 2012. Single, isolated points occur if states are rare and persist only for a very short time, diagonal lines parallel with the LOI occur when the evolution of states is similar at different times, and vertical (horizontal) lines occur when the system is in a state that does not change or changes very slowly (laminar states) (Marwan et al, 2007)
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