Natural Variability and Non-CO₂ Climate Drivers

Solar Cycles and Forcing Representation

Solar variability-including the Schwabe (11-year) and Gleissberg (~80-90 year) cycles-modulates total solar irradiance (TSI), affecting ozone, circulation, and possibly cloud cover. Most GCMs treat solar forcing as static, smoothing out short-term variability and feedbacks. This underrepresents the role of solar minima (e.g., Maunder Minimum) in decadal-to-centennial anomalies.

Major Ocean-Atmosphere Oscillations: AMO, PDO, ENSO

The Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and ENSO drive multi-decadal and interannual climate variability. Most models underrepresent their amplitude, phase, and teleconnections due to limited ocean data, coarse resolution, and ensemble averaging.

Observed vs. Modeled Decadal Variability

Empirical records reveal pronounced decadal swings (such as the 1940s-1970s cooling and the 1998-2014 “hiatus”) that GCMs struggle to replicate without tuning. This suggests overfitting to monotonic forcing and underweighting of internal variability.

Extremes and Mean-State Bias

Models calibrated to mean surface temperature miss the structure and drivers of extremes. Observations show rising frequency and intensity of heatwaves, floods, and droughts, even where the mean has changed little. GCMs lack resolution for subgrid triggers and compound events.

Synthesis and Policy Implications

  • Natural variability-solar, oceanic, and atmospheric-is systematically underrepresented in most climate models.
  • This leads to over-attribution of observed changes to CO₂ and narrows the interpretation of past and future trends.
  • Disentangling anthropogenic signals from natural variability requires higher-resolution models, better initialization, and pluralistic methods.
Research Priorities:
High-res decadal models
Expanded solar forcing
Ocean-atmosphere data
Empirical/stochastic frameworks
Policy Risks:
Overconfident attribution
Misallocated resilience investment
Premature mandates
Underestimated extremes
Data: IPCC AR6, NOAA, NASA, empirical variability studies (2024-2025).

Natural Variability and Non-CO₂ Drivers