The 11-year solar cycle is associated with a roughly 1Wm-2 trough-to-peak variation in total solar irradiance and is expected to produce a global temperature response. The sensitivity of this response is, however, contentious. Empirical best estimates of global surface temperature sensitivity to solar forcing range from 0.08 to 0.18 K [W m-2 ]-1. In comparison, best estimates from general circulation models forced by solar variability range between 0.03-0.07 K [W m-2]-1, prompting speculation that physical mechanisms not included in general circulation models may amplify responses to solar variability. Using a lagged multiple linear regression method, we find a sensitivity of globalaverage surface temperature ranging between 0.02-0.09 K [W m-2]-1, depending on which predictor and temperature datasets are used. On the basis of likelihood maximization, we give a best estimate of the sensitivity to solar variability of 0.05 K [W m-2]-1 (0.03-0.09 K, 95% c.i.). Furthermore, through updating a widely-used compositing approach to incorporate recent observations, we revise prior global temperature sensitivity best estimates of 0.12 to 0.18 K [W m-2]-1 downwards to 0.07 to 0.10 K [W m-2]-1. The finding of a most-likely global temperature response of 0.05 K [W m-2]-1 supports a relatively modest role for solar cycle variability in driving global surface temperature variations over the 20th century and removes the need to invoke processes that amplify the response relative to that exhibited in general circulation models.

Differences among total solar irradiance (TSI) estimates are most pronounced during the so-called “ACRIM Gap” of 1989–1991, when available satellite observations disagree in trend and no observations exist from satellites with on-board calibration. Different approaches to bias-correcting noisy satellite observations lead to discrepancies of up to 0.7 W/m in the change in TSI during the Gap. Using a Bayesian hierarchical model for Total Solar Irradiance (BTSI), we jointly infer TSI during the ACRIM Gap from satellite observations and proxies of solar activity. In addition, BTSI yields estimates of noise and drift in satellite observations and calibration for proxy records. We find that TSI across the ACRIM Gap changes by only 0.01 W/m, with a 95% confidence interval of [-0.07, 0.09] W/m. Our results are consistent with the PMOD CPMDF and Community Consensus TSI reconstructions and inconsistent with the 0.7 W/m trend reported in the ACRIM composite reconstruction. Constraints on the trend across the ACRIM Gap are primarily obtained through constraints on the drift in the Nimbus-7 satellite that are afforded by overlapping satellite and proxy observations.

Differences among total solar irradiance (TSI) estimates are most pronounced during the so‐called “ACRIM Gap” of 1989–1991, when available satellite‐based observations disagree in trend and no observations exist from satellites with on‐board calibration. Different approaches to bias‐correcting noisy satellite‐based observations lead to discrepancies of up to 0.7 W/m2 in the change in TSI during the Gap. Using a Bayesian hierarchical model for TSI (BTSI), we jointly infer TSI during the ACRIM Gap from satellite‐based observations and proxies of solar activity. In addition, BTSI yields estimates of noise and drift in satellite‐based observations and calibration for proxy records. We find that TSI across the ACRIM Gap changes by only 0.01 W/m2, with a 95% confidence interval of [−0.07, 0.09] W/m2. Our results are consistent with the PMOD CPMDF and Community Consensus TSI reconstructions and inconsistent with the 0.7 W/m2 trend reported in the ACRIM composite reconstruction. Constraints on the trend across the ACRIM Gap are primarily obtained through constraints on the drift in the Nimbus‐7 satellite that are afforded by overlapping satellite and proxy observations.