A preprint posted to arXiv in April 2026 (not yet peer-reviewed) examines the Atlantic Meridional Mode (AMM) index and monthly sunspot counts from 1951 to 2017. Researchers led by Cleber Souza Correa used wavelet and cross-wavelet transforms to identify shared cycles. These statistical tools detect periodic signals in noisy time-series data; the authors report prominent 11-year periodicity (matching the Schwabe solar cycle), plus 2.66- and 5.33-year beats. The sea-surface-temperature portion of the AMM also showed a weak 21.33-year signal. Sample size is 67 years of monthly observations (roughly 800 points), adequate for decadal cycles but marginal for robust multidecadal claims.

The study further tested non-parametric rank correlations between sunspot anomalies and temperature anomalies at five stations: Belém, São Luís, Fortaleza, Fernando de Noronha, and Natal. In four of the five locations, minimum monthly temperature anomalies correlated negatively with sunspots, meaning higher solar activity tended to coincide with cooler nights. Average and maximum temperatures showed weaker or inconsistent links. The authors cautiously note an 'apparent degree of memory' in the climate indices tied to solar variability.

These statistical associations matter for North and Northeast Brazil, a region where small shifts in Atlantic sea-surface temperatures and the position of the Intertropical Convergence Zone determine whether the semiarid interior receives enough rain for subsistence crops and cattle pasture. Severe droughts in 2012–2018 displaced millions and slashed yields of beans, cassava, and corn. Conventional reporting and policy documents overwhelmingly attribute such extremes to anthropogenic greenhouse gases and deforestation. This preprint, and the regional patterns it highlights, reveal an under-examined natural pacemaker.

Mainstream coverage routinely misses the amplitude of solar influence on Atlantic Meridional Mode variability. While the IPCC AR6 assigns only modest radiative forcing to total solar irradiance changes since 1750, it acknowledges that indirect dynamical pathways (stratospheric ozone response, UV-driven circulation shifts, cosmic-ray cloud microphysics) remain active areas of research. A 2010 review by Gray et al. in Reviews of Geophysics ('Solar Influences on Climate') catalogued exactly these pathways and noted that regional responses can exceed global averages. Likewise, Kayano and Capistrano (2014) documented strong Atlantic SST control over Northeast Brazilian rainfall on decadal scales but stopped short of solar attribution. The current preprint supplies the missing solar link.

The negative correlation with minimum temperatures is especially intriguing. Higher sunspot counts often coincide with slightly elevated total solar irradiance and altered cosmic-ray flux; both can modulate low-level cloudiness. Fewer nighttime clouds would normally allow more radiative cooling, yet the observed pattern is cooler minima during solar maxima—an apparent contradiction that invites mechanistic follow-up involving changes in meridional circulation or soil-moisture memory.

Agricultural implications are immediate and under-appreciated. Brazil's Northeast is already a climate-vulnerability hotspot. If roughly one-third of the decadal rainfall variance is traceable to solar-modulated Atlantic patterns, then seasonal forecasts could be sharpened by folding in sunspot progression and polar magnetic-field precursors. Current models used by Brazil's National Institute for Space Research (INPE) emphasize ENSO and anthropogenic trends; adding solar memory could reduce forecast error during solar-cycle peaks and troughs.

Limitations must be stated clearly. The dataset spans only six 11-year cycles, limiting confidence in 'multidecadal' robustness. Wavelet analysis can produce spurious periodicities if long-term trends are not fully removed. Correlation is not causation; a plausible physical chain (solar UV → stratospheric heating → tropospheric jet shifts → Atlantic SST anomalies) exists but was not tested here. Being a preprint, the work has not yet survived community scrutiny.

Still, the paper arrives at a useful moment. As global policy fixates on net-zero targets, regional planners in vulnerable drylands need every usable signal. Solar cycles are predictable decades ahead, whereas greenhouse-gas concentrations respond slowly to mitigation. A fuller synthesis that respects both anthropogenic forcing and natural solar-climate rhythms would improve adaptation decisions for millions of Brazilian smallholders—an insight largely absent from today's dominant climate narratives.