Detecting Atlantic MOC changes in an ensemble of climate change simulations

16Citations
Citations of this article
49Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Signal-to-noise patterns for the meridional overturning circulation (MOC) have been calculated for an ensemble of greenhouse scenario runs. The greenhouse-forced signal has been defined as the linear trend in ensemble-mean MOC, after year 2000. It consists of an overall decrease and shoaling of the MOC, with maximum amplitudes of 10 Sv (Sv = 106 m3 s-1) per century. In each member the internal variability is defined as the anomaly with respect to the ensemble-mean signal. The interannual variability of the MOC is dominated by a monopole with a maximum amplitude of 2 Sv at 40°N. This variability appears to be driven by the North Atlantic Oscillation (NAO), mainly through NAO-induced variations in the wind field. The signal-to-noise ratio was estimated for various time spans, all starting in 1950 or later. Different noise estimates were made, both with and without intra-annual variability, relevant for episodic and continuous monitoring, respectively, and with and without an estimate of the observational error. Detection of a greenhouse-forced MOC signal on the basis of episodic measurements is impossible before 2055. With continuous monitoring, detection becomes possible after 35 years of observation. The main motivation for calculating signal-to-noise ratios and detection times is their usefulness for local monitoring strategies and detection methods. The two-dimensional pattern of detection times of a MOC change supports the rationale for deploying a sustained monitoring array on at 26°N. © 2007 American Meteorological Society.

Cite

CITATION STYLE

APA

Drijfhout, S. S., & Hazeleger, W. (2007). Detecting Atlantic MOC changes in an ensemble of climate change simulations. Journal of Climate, 20(8), 1571–1582. https://doi.org/10.1175/JCLI4104.1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free