Using Chaos theory fundamentals for analysing temperature, precipitation variability and trends in Northern Patagonia, Argentina

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 theNASA 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.