Nonlinear dynamics and recurrence analysis of extreme precipitation for observed and general circulation model generated climates

Abstract

A statistical framework based on nonlinear dynamics theory and recurrence quantification analysis of dynamical systems is proposed to quantitatively identify the temporal characteristics of extreme (maximum) daily precipitation series. The methodology focuses on both observed and general circulation model (GCM) generated climates for present (1961–2000) and future (2061–2100) periods which correspond to 1xCO2 and 2xCO2 simulations. The daily precipitation has been modelled as a stochastic process coupled with atmospheric circulation. An automated and objective classification of daily circulation patterns (CPs) based on optimized fuzzy rules was used to classify both observed CPs and ECHAM4 GCM‐generated CPs for 1xCO2 and 2xCO2 climate simulations (scenarios). The coupled model ‘CP‐precipitation’ was suitable for precipitation downscaling. The overall methodology was applied to the medium‐sized mountainous Mesochora catchment in Central‐Western Greece. Results reveal substantial differences between the observed maximum daily precipitation statistical patterns and those produced by the two climate scenarios. A variable nonlinear deterministic behaviour characterizes all climate scenarios examined. Transitions’ patterns differ in terms of duration and intensity. The 2xCO2 scenario contains the strongest transitions highlighting an unusual shift between floods and droughts. The implications of the results to the predictability of the phenomenon are also discussed. Copyright © 2013 John Wiley & Sons, Ltd.

Compound Extremes in Hydroclimatology: A Review

“…Traditionally, studies on weather and climate extremes have mostly focused on the extremes from a single process or variable, such as heavy precipitation or maximum temperature. For example, a multitude of studies have shown increases in the severity, duration, and frequency of precipitation and temperature extremes [4,[16][17][18][19][20][21]. The extreme value theory (EVT) constitutes the basis for statistical modeling of univariate extremes in this regard, which can generally be achieved with the probability distribution of individual extremes, such as generalized extreme value (GEV) distribution or generalized Pareto distribution (GPD) based on the annual maxima or peak over threshold [22,23].…”

Recurrence quantification analysis of monthly rainfall time series in Pernambuco, Brazil

“…We use Recurrence Plot (RP) and the Recurrence Quantitative Analysis (RQA) methods that were developed for nonlinear analysis of temporal series, by visualizing the recurrences and calculating different complexity measures (Marwan, Romano, Thiel & Kurths, 2007). These methods were widely Research, Society and Development, v. 9, n. 9, e637997737, 2020 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v9i9.7737 5 used in physiology (Afsar, Tirnakli & Marwan, 2018), geophysics (Donner et al, 2019), climatology (Panagoulia & Vlahogianni, 2014) and finances (Bastos & Caiado, 2011). We apply RP and RQA on monthly time series recorded during the period from 1962 to 2012, in three representative stations, in order to compare characteristics of rainfall regime in Zona da Mata, Agreste and Sertão.…”

Chaotic signature of climate extremes

“…In this study, the threshold is taken as > 5σ. Recurrence plots and recurrence quantification analysis have been employed in several climate studies (Panagoulia and Vlahogianni 2014).…”

“…where i , || • || ,θ are the threshold for distance, Euclidean norm and Heaviside function respectively (Panagoulia and Vlahogianni 2014). Recurrence plots have small scale structures which can be used to quantify complexity.…”