South America is expanding solar generation faster than it can verify forecasts. Brazil increased its installed photovoltaic capacity by 1351.5% in a single year, and Chile has mandated that 20% of energy come from renewables by 2025. Meanwhile, the region sits under the El Niño–La Niña seesaw, which reshapes cloud cover, precipitation, and wind every 3–7 years. Related papers in the archive have already shown that solar cycles and space weather affect terrestrial processes, and analysis of the solar corona helps predict flares. This paper stands apart: it looks not at the Sun itself, but at how Pacific oscillations modulate incoming radiation on a continental scale.
The authors collected 3-hourly accumulated solar radiation data from 31 weather stations: 25 in Brazil's solar belt and 6 in Chile. They selected three full years: La Niña (June 2010 – June 2011), neutral (June 2013 – June 2014), and El Niño (June 2015 – June 2016). For each series, they applied detrended fluctuation analysis (DFA): the signal is integrated, divided into windows of varying sizes, a local polynomial trend is subtracted, and the root mean square deviation is computed. The slope of the fluctuation-versus-window-size relationship yields the self-similarity exponent α. Additionally, using the second derivative of the curve, they identified crossover points at approximately 27 hours and 10 days, which split the analysis into three scale ranges.
During the neutral period in Brazil, nearly all stations showed a persistent signal (α > 0.5) at scales longer than 10 days. El Niño statistically significantly increased α compared to neutral and La Niña periods, especially in the northern part of the country. In Chile, all cities showed antipersistence at scales from 27 hours to 10 days, while at larger scales during La Niña, two southern cities transitioned from a subdiffusive to a persistent regime. The city of Coxim in Brazil showed the largest spread: from antipersistence during El Niño to subdiffusion during La Niña and persistence in the neutral year. Corumbá, in contrast, was the most stable: the spread in α did not exceed 0.05 across all periods.
This work is the first to show that ENSO phases alter not only mean radiation values but also the very nature of its temporal variability across a large region of South America. This distinguishes it from neighboring studies that focused on solar cycles or local effects. The subdiffusive regime found in some cities points to a transitional atmospheric state, where forecasts based on a typical meteorological year can be systematically off. For energy planners, this means measurements taken during an El Niño or La Niña year cannot be directly extrapolated to the station's 10-year service life without adjustments.
Next steps include examining cross-correlations between solar radiation, temperature, humidity, and wind over the same periods. This could reveal which atmospheric mechanisms transmit the ENSO signal to the radiation regime. Also, models could be built to adjust certified output estimates based on the ENSO phase. Another direction is analyzing longer time series to separate the influence of global warming from natural variability.
The results directly affect the design and financing of solar power plants in Brazil and Chile. They are also useful for climatologists studying regional responses to ENSO.
Conduct cross-correlation analysis of radiation with temperature, humidity, and wind for each station. Develop correction factors for the typical meteorological year depending on the ENSO phase.
The paper touches on the fundamental problem of atmospheric predictability: how long-term memory in radiation series persists under external climate forcings. This echoes the open question about the boundary between weather and macroweather, where the transition around 10 days is still only empirically explained.
The city of Coxim in Brazil switched regimes three times in three years: antipersistent during El Niño, subdiffusive during La Niña, and persistent in the neutral year. Such variability is comparable to a person who in some years predictably repeats their habits and in others behaves chaotically.