Brewer Dobson Circulation trends from Age of Air in models

Given the couplings between the circulation of the stratosphere and its composition, tracking the evolution of both is crucial. At present however, much remains to be learned about long term trends in the composition of the stratosphere, and there is still little to no agreement between the modeled trends in the Brewer Dobson Circulation and their observational counterparts; while models indicate that the BDC is accelerating at a pace of 2-3 %/decade, observational estimates suggest that the BDC is slowing down. These shortcomings are attributable in part to the relatively short length of the historical record and in part to difficulty characterizing the BDC using observations.

To alleviate these shortcomings, we propose to re-visit historical and projected BDC trends using the metric time of emergence (ToE), defined as the length of record needed to separate long-term trends from internal variability with a chosen degree of statistical confidence. We use ToE as it enables the evaluation of current observational capabilities for the detection and validation of BDC trends predicted by models. ToE also provides tangible motivation for the continued monitoring of the composition of the stratosphere by space borne platforms, a topic recently brought to light by the planned decommissioning of the Aura satellite in the absence of a follow-up flight mission.

ToE is calculated using two methods, for which results are compared: a) classic bootstrapping based on a reference CMIP6 run (a pre-industrial run, or a run with fixed contemporary greenhouse gas concentrations), and b) an analytical method published by Li et al. (2017) that does not require a very long reference run. We focus the analysis on a comparison of ToE for trends in a) the diabatic circulation, taken as reference for the “true” BDC, and b) the BDC metric based on age of air developed by Linz et al. (2016), used as a proxy for observational trend estimates. The results shed light on how internal variability shapes our understanding of long term trends, and provide minimum requirements for the robust detection of trends in the BDC using observations. 

Li, J., Thompson, D.W., Barnes, E.A. and Solomon, S., 2017. Quantifying the lead time required for a linear trend to emerge from natural climate variability. J. of Climate.

Linz, M., Plumb, R.A., Gerber, E.P. and Sheshadri, A., 2016. The relationship between age of air and the diabatic circulation of the stratosphere. JAS.