Search

Constraining the low-frequency (LF) behavior of general circulation models (GCMs) requires reliable observational estimates of LF variability. This two-part paper presents multiproxy reconstructions of Niño-3.4 sea surface temperature over the last millennium, applying two techniques [composite plus scale (CPS) and hybrid regularized expectation maximization (RegEM) truncated total least squares (TTLS)] to a network of tropical, high-resolution proxy records. This first part presents the data and methodology before evaluating their predictive skill using frozen network analysis (FNA) and pseudoproxy experiments. The FNA results suggest that about half of the Niño-3.4 variance can be reconstructed back to A.D. 1000, but they show little LF skill during certain intervals. More variance can be reconstructed in the interannual band where climate signals are strongest, but this band is affected by dating uncertainties (which are not formally addressed here). The CPS reliably estimates interannual variability, while LF fluctuations are more faithfully reconstructed with RegEM, albeit with inevitable variance loss. The RegEM approach is also tested on representative pseudoproxy networks derived from two millennium-long integrations of a coupled GCM. The pseudoproxy study confirms that reconstruction skill is significant in both the interannual and LF bands, provided that sufficient variance is exhibited in the target Niño-3.4 index. It also suggests that FNA severely underestimates LF skill, even when LF variability is strong, resulting in overly pessimistic performance assessments. The centennial-scale variance of the historical Niño-3.4 index falls somewhere between the two model simulations, suggesting that the network and methodology presented here would be able to capture the leading LF variations in Niño-3.4 for much of the past millennium, with the caveats noted above. [ABSTRACT FROM AUTHOR]

In this paper, an idealized framework based on a cloud-topped mixed layer model is developed for investigating feedbacks between subtropical stratocumulus (Sc) and global warming. The two principal control parameters are Sc-region sea surface temperature (SST) and intertropical convergence zone (ITCZ) SST (which controls the temperature and mean subsidence profiles above the Sc). The direct effect of CO2 doubling (leaving all other parameters fixed) is tested and found to somewhat reduce liquid water path; discussion of this effect on the SST-change simulations is included. The presence of a cold boundary layer is found to significantly affect the temperature and subsidence rate just above cloud top by enhancing lower-tropospheric diabatic cooling in this region. A simple representation of this effect (easily generalizable to a more realistic boundary layer model) is developed. Steady-state solutions are analyzed as a function of local and ITCZ SST. Two climate change scenarios are considered. The first scenario is an equal increase of local and ITCZ SSTs. In this case, predicted boundary layer depth and cloud thickness increase. This is found in a simplified context to result from subsidence and entrainment decreases due to increased static stability in a warmer climate. In the second case, local SST change is diagnosed from a surface energy balance under the assumption that ocean heat transport remains unchanged. In this case, predicted boundary layer depth decreases. Cloud continues to thicken with rising ITCZ SST, but at a rate much reduced in comparison to the equal-warming scenario. This cloud shading feedback keeps SST in the Sc region nearly constant as the ITCZ SST increases. Model sensitivity to aerosol indirect effects is also considered by varying the assumed droplet concentration. The resulting change in liquid water path is small, suggesting a weaker dependence on second indirect effect than found in previous studies. [ABSTRACT FROM AUTHOR]