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Sun and hurricanes No robust link with the solar cycle

Correspondences

What is linked, what is not

Each arc joins two phenomena tested on this site. Green and animated: clear link (correlation significant at 5 % after correcting for autocorrelation, or a response outside chance in an event study). Grey: inconclusive test. A statistical link alone does not establish causation.

  • Clear link
  • Inconclusive
Hypotheses tested
16
Clear links
11
correlation p < 0.05 or epochs outside chance
Causation demonstrated
0
a correlation demonstrates none

Arc width from |r| of the stored result; several tests between the same phenomena are drawn as stacked arcs.

Hypothesis tested: A more active Sun would warm the upper tropical atmosphere and reduce the potential intensity of cyclones; a solar-cycle effect on hurricanes has been proposed (Elsner & Jagger, 2008). If it exists, it should show as a negative correlation with ACE.
Spearman correlation ρ
-0.10
95% interval [-0.30; 0.09] (block bootstrap)
Pearson correlation r (lag 2 year(s))
-0.20
at the strongest lag
Aligned points
74
effective n ≈ 50 (autocorrelation)
p-value
0.174
two-sided, Fisher z transform, effective n
Period analysed
1950 → 2025
computed on Oct 23, 2026 · engine v1.0
Aligned series (standard deviations, after preprocessing)
Show the data as a table
Correlation by lag (year(s))
Show the data as a table

Aligned series (CSV)

Method and sources

The yearly sunspot number (SILSO V2.0) is compared with the season’s ACE in HURDAT2 from 1950 to the last complete season, with lags from −3 to +3 years. The lag kept is that of the strongest correlation; the p-value accounts for autocorrelation (Bretherton effective N) and the Spearman interval comes from a 3-year block bootstrap.

Computation parameters
{
    "max_lag": 3,
    "bootstrap": {
        "seed": 20261023,
        "block": 3,
        "draws": 1000,
        "statistic": "spearman"
    },
    "from_year": 1950
}

Inputs : silso.ssn.yearly (326 pts, run #49) · hurdat2.ace.yearly (175 pts, run #21)

Reading this result
The correlation stays weak and not significant once autocorrelation is accounted for: the solar cycle does not predict a season’s activity. The effects proposed in the literature concern specific regions and intensities and remain debated. Picking the best of seven lags also raises the chance of finding a correlation by luck. Correlation is not causation: common factors (seasons, cycles, trends) or coincidence can produce it. The p-values account for autocorrelation (effective n) but not for preprocessing choices; the confidence interval comes from a block bootstrap. The limits of the source data apply.
SOURCES OF THIS PAGE
SILSO yearly mean total sunspot number V2.0
SILSO World Data Center. The International Sunspot Number, V2.0. Royal Observatory of Belgium, Brussels. · source page ↗
Licence : CC BY-NC 4.0 · retrieved on Oct 23, 2026 · SHA-256 0ccb2104b03f…
HURDAT2 Atlantic hurricane database (NOAA NHC)
Landsea, C. W., Franklin, J. L. (2013). Atlantic hurricane database uncertainty and presentation of a new database format. Monthly Weather Review 141, 3576–3592 (HURDAT2, NOAA NHC). · doi:10.1175/MWR-D-12-00254.1 · source page ↗
Licence : U.S. Government work, public domain · retrieved on Oct 23, 2026 · SHA-256 75202780ce56…
Elsner et al. (2008)
Elsner, J. B., & Jagger, T. H. (2008). United States and Caribbean tropical cyclone activity related to the solar cycle. Geophysical Research Letters, 35, L18705. · doi:10.1029/2008GL034431
Licence : Published literature; cited
Hodges et al. (2012)
Hodges, R. E., & Elsner, J. B. (2012). The spatial pattern of the sun–hurricane connection across the North Atlantic. ISRN Atmospheric Sciences, 2012, 351738. · doi:10.5402/2012/351738
Licence : Published literature; cited