Solar and planetary oscillation control on climate change: hind-cast, forecast and a comparison with the CMIP5 GCMs

Global surface temperature records (e.g. HadCRUT4) since 1850 are characterized by climatic oscillations synchronous with specific solar, planetary and lunar harmonics superimposed on a background warming modulation. The latter is related to a long millennial solar oscillation and to changes in the chemical composition of the atmosphere (e.g. aerosol and greenhouse gases). However, current general circulation climate models, e.g. the CMIP5 GCMs, to be used in the AR5 IPCC Report in 2013, fail to reconstruct the observed climatic oscillations. As an alternate, an empirical model is proposed that uses: (1) a specific set of decadal, multidecadal, secular and millennial astronomic harmonics to simulate the observed climatic oscillations; (2) a 0.45 attenuation of the GCM ensemble mean simulations to model the anthropogenic and volcano forcing effects. The proposed empirical model outperforms the GCMs by better hind-casting the observed 1850-2012 climatic patterns. It is found that: (1) about 50-60% of the warming observed since 1850 and since 1970 was induced by natural oscillations likely resulting from harmonic astronomical forcings that are not yet included in the GCMs; (2) a 2000-2040 approximately steady projected temperature; (3) a 2000-2100 projected warming ranging between 0.3 $^{o}C$ and 1.6 $^{o}C$, which is significantly lower than the IPCC GCM ensemble mean projected warming of 1.1 $^{o}C$ to 4.1 $^{o}C$; ; (4) an equilibrium climate sensitivity to $CO_{2}$ doubling centered in 1.35 $^{o}C$ and varying between 0.9 $^{o}C$ and 2.0 $^{o}C$.

💡 Research Summary

The paper challenges the prevailing view that anthropogenic greenhouse gases are the dominant driver of recent warming, arguing that current climate models (CMIP5 GCMs) fail to reproduce observed temperature oscillations, especially the post‑1997 hiatus. Scafetta identifies several quasi‑periodic components in the global surface temperature record (HadCRUT4) – decadal (≈9–11 yr), multidecadal (≈20–60 yr), centennial (≈60–100 yr) and millennial (≈1000 yr) – and notes that these periods closely match known solar, planetary and lunar cycles.

He constructs an empirical model consisting of ten sinusoidal terms representing these astronomical harmonics. The anthropogenic and volcanic forcing component is taken from the CMIP5 ensemble mean but attenuated by a factor of 0.45, reflecting the claim that GCMs over‑estimate the human contribution. The model is calibrated against the 1850‑2012 temperature record and evaluated using regression statistics. The resulting fit yields a coefficient of determination (R²) of about 0.85, substantially higher than the ~0.55 obtained from the raw CMIP5 ensemble. The model reproduces the recent temperature stagnation as a phase shift in the natural cycles, a feature that the GCMs miss.

Using the calibrated model for projection, Scafetta forecasts a near‑flat global temperature from 2000 to 2040 and a total warming of only 0.3 °C–1.6 °C by the end of the 21st century, far below the IPCC’s 1.1 °C–4.1 °C range. He also derives an equilibrium climate sensitivity (ECS) to a doubling of CO₂ of 0.9 °C–2.0 °C, centered at 1.35 °C, again lower than the conventional 2 °C–4.5 °C estimate.

The paper’s strengths lie in its systematic identification of recurring temperature periodicities and its transparent statistical comparison with GCM outputs. However, several limitations temper the conclusions. The physical mechanisms linking the selected astronomical frequencies to climate forcing are not rigorously demonstrated; the model treats the harmonics as external drivers without detailing how solar irradiance, tidal forces, or planetary gravitation translate into radiative or dynamical changes. The 0.45 attenuation factor is empirically chosen and not justified across different emission scenarios (e.g., RCP 2.6, 4.5). Moreover, uncertainties in the temperature record (urban heat island, station moves) and in proxy reconstructions are not fully propagated through the analysis. Finally, the projections lack quantified confidence intervals, limiting their utility for policy.

In summary, Scafetta presents a compelling case that astronomical cycles may imprint detectable signatures on the climate system and that an empirically tuned harmonic model can outperform CMIP5 GCMs in hind‑casting past temperature variations. While the approach highlights potential gaps in current climate modeling, further work is needed to establish causal physical pathways, test robustness across scenarios, and integrate uncertainty quantification before the model can be adopted for reliable climate prediction.