On the Estimation of Internal Climate Variability During the Preindustrial Past Millennium

Abstract

We use an ensemble of simulations of a coupled model (NCAR Community Earth System Model) driven by natural radiative forcing estimates over the pre‐industrial past millennium to test the efficacy of methods designed to remove forced variability from proxy‐based climate reconstructions and estimate residual internal variability (e.g., a putative “Atlantic Multidecadal Oscillation”). Within the framework of these experiments, the forced component of surface temperature change can be estimated accurately from the ensemble mean, and the internal variability of each of the independent realizations can be accurately assessed by subtracting off that estimate. We show in this case, where the true internal variability is known, that regression‐based methods of removing the forced component from proxy reconstructions will, in the presence of uncertainties in the underlying natural radiative forcing, fail to yield accurate estimates thereof, incorrectly attributing unresolved forced features (and multidecadal spectral peaks associated with them) to internal variability.

Changes of Atlantic Multidecadal Variability During the Medieval Climate Anomaly and Little Ice Age and Associated Causes

“…First, the internal components of the AMV exhibit periods of 25–50 years during the MCA and LIA, but few of them are significant at the 90% confidence level (Figures 3e and 3f, Figures S5 and S6 in Supporting Information ). The results are similar to those derived from whole millennium, which are consistent with previous studies (Mann et al., 2021, 2022). The relatively weak power spectrum may be partly due to the CESM model's underestimation of the observed AMV's peaks (Figure 1b).…”

“…In addition, the AMV‐related SST anomalies are more uniform and larger during the LIA than those during the MCA. Note that, the above‐mentioned studies achieve the internally generated component of the AMV by linearly detrending SST or subtracting global mean SST before calculating the AMV index, which may be not skillful to yield accurate estimation on internal variability within a background changing climate (Deser & Phillips, 2021; Mann et al., 2022). Thus, how the internally generated and externally forced parts of the AMV change during the MCA and LIA is still unclear.…”

Recruitment regime shifts and nonstationarity are widespread phenomena in harvestable stocks experiencing pronounced climate fluctuations

“…Overall, recruitment success in the Northeast Atlantic stocks appears to be linked to large‐scale climate variability patterns, primarily AMO and the subpolar gyre (Zimmermann et al., 2019). However, it should be noted that recent studies argue that AMO under on‐going climate change fails to isolate the true internal variability in Northern Hemisphere mean temperature (Mann et al., 2014, 2022). So, although AMO functioned as an effective driver for several stocks, its current relevance might be less than before.…”

Separating internal and externally-forced contributions to global temperature variability using a Bayesian stochastic energy balance framework

“…Different methods have been developed to isolate forced and internal variations based on detrending 86 , single-model ensembles 5,[87][88][89] , and deterministic EBMs 90,91 , among others. The application of a Bayesian energy balance framework to the timescale-dependent quantification of forced and internal variance is novel.…”