Detecting Atlantic MOC Changes in an Ensemble of Climate Change Simulations

S. S. Drijfhout Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands

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W. Hazeleger Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands

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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.

Corresponding author address: S. S. Drijfhout, Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE De Bilt, Netherlands. Email: drijfhou@knmi.nl

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.

Corresponding author address: S. S. Drijfhout, Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE De Bilt, Netherlands. Email: drijfhou@knmi.nl

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