Using Chaos theory fundamentals for analysing temperature, precipitation variability and trends in Northern Patagonia, Argentina
Grethel García Bu Bucogen
A * , María Cintia Piccolo B , Vanesa Yael Bohn C and Gabriel Eduardo Huck A
+ Author Affiliations
- Author Affiliations
A Instituto Argentino de Oceanografía (CONICET-UNS), Bahía Blanca, Buenos Aires, Argentina.
B Instituto Argentino de Oceanografía (CONICET-UNS)–Departamento de Geografía y Turismo, Universidad Nacional del Sur (UNS), Bahía Blanca, Buenos Aires, Argentina.
C Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)–Departamento de Geografía y Turismo, UNS, Bahía Blanca, Buenos Aires, Argentina.
* Correspondence to: grethelgbb@gmail.com
Journal of Southern Hemisphere Earth Systems Science 72(3) 179-190 https://doi.org/10.1071/ES22009
Submitted: 23 March 2022 Accepted: 26 September 2022 Published: 18 October 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of BoM. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
The fundamentals of Chaos theory allow the study of climatic conditions and long-term modifications produced by changes in their spatial and temporal scales. The aim of this work is to analyse the variability and changes produced in the annual cycles of temperature and precipitation in Northern Patagonia, Argentina, applying multifractal analysis as a practical mathematical tool of Chaos theory. Data from the NASA POWER Project (2021) was implemented as an alternative dataset for carrying out climatological studies in the area. Annual mean temperature and precipitation time-series data (1981–2019) were analysed at 72 grid points with 1° of spatial resolution. The Mann–Kendall test was used to calculate the trends through the annual cycles of the meteorological variables. Fractal dimension values were calculated using Multifractal Detrended Fluctuation Analysis. The Hurst exponent, complexity and asymmetry were the multifractal dimensions describing the persistence of time-series trends and climatic variability. The results showed changes in the annual cycles of both variables during the study period. The most significant finding was a large area in the centre and north of the study area, where the decrease in the rainfall regime was persistent. The Hurst exponent detected a sector in the Patagonian Andes mountain range where the temperature increase was constant. This work demonstrates that fractal geometry is useful to describe meteorological variability and obtain better short-, medium- and long-term forecasts.
Keywords: annual cycles, climatic variability, heating, hydric stress, melting, multifractal dimensions, Northern Patagonia, precipitation, temperature, trends.
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