Inferred changes in El Niño–Southern Oscillation variance over the past six centuries

S Mcgregor,M H England,O Elison Timm,A Timmermann,A T Wittenberg

doi:10.5194/cp-9-2269-2013

Abstract

Abstract. It is vital to understand how the El Niño–Southern Oscillation (ENSO) has responded to past changes in natural and anthropogenic forcings, in order to better understand and predict its response to future greenhouse warming. To date, however, the instrumental record is too brief to fully characterize natural ENSO variability, while large discrepancies exist amongst paleo-proxy reconstructions of ENSO. These paleo-proxy reconstructions have typically attempted to reconstruct ENSO's temporal evolution, rather than the variance of these temporal changes. Here a new approach is developed that synthesizes the variance changes from various proxy data sets to provide a unified and updated estimate of past ENSO variance. The method is tested using surrogate data from two coupled general circulation model (CGCM) simulations. It is shown that in the presence of dating uncertainties, synthesizing variance information provides a more robust estimate of ENSO variance than synthesizing the raw data and then identifying its running variance. We also examine whether good temporal correspondence between proxy data and instrumental ENSO records implies a good representation of ENSO variance. In the climate modeling framework we show that a significant improvement in reconstructing ENSO variance changes is found when combining information from diverse ENSO-teleconnected source regions, rather than by relying on a single well-correlated location. This suggests that ENSO variance estimates derived from a single site should be viewed with caution. Finally, synthesizing existing ENSO reconstructions to arrive at a better estimate of past ENSO variance changes, we find robust evidence that the ENSO variance for any 30 yr period during the interval 1590–1880 was considerably lower than that observed during 1979–2009.

Highlights

The El Niño–Southern Oscillation (ENSO) is characterized by variations in sea surface temperature (SST) in the eastern tropical Pacific, causing changes in ocean currents and atmospheric circulation patterns globally
We find that a strong correlation between a common precipitation time series, identified by calculating the median time series from multiple simulated precipitation time series sourced from different locations, and simulated ENSO is a much better indicator for a high correlation between the common precipitation running variance and ENSO running variance (Fig. 3a) as compared to the case with simulated precipitation data sourced from only one location
The main goal of this study was to synthesize existing ENSO reconstructions to arrive at a better estimate of past ENSO variance changes

Summary

Introduction

The El Niño–Southern Oscillation (ENSO) is characterized by variations in sea surface temperature (SST) in the eastern tropical Pacific, causing changes in ocean currents and atmospheric circulation patterns globally. ENSO has been shown to exhibit significant multi-decadal variability in its strength and frequency throughout the instrumental period (Power, et al, 1999; Timmermann et al, 2003; Zhang et al, 1998), with additional longer-term variability reported in proxy data (Li et al, 2011; Wolff et al, 2011; Emile-Geay et al, 2013b). Characterizing ENSO’s long-term changes in frequency, magnitude and duration has been hampered by the fact that reliable instrumental records cover a period of less than 150 yr. This period is too brief to capture the range of longterm changes in ENSO frequency, magnitude and duration (Wittenberg, 2009). Multi-century paleo-climate reconstructions derived from monthly to annually resolved tree rings, ice cores, lake sediments and coral records can be used to extend the observational record and to further quantify ENSO’s

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