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Trans-Tasman Sea climate variability since ad 1740 inferred from middle to high latitude tree-ring data

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Abstract

The limited length and spatial coverage of instrumental climate data for many areas of the Southern Hemisphere impedes the study of atmosphere-ocean dynamics prior to the past century. Such analyses are important for understanding interannual to decadal variation of the Southern Hemisphere circulation and whether recent changes are related to anthropogenic effects rather than natural variability. We use a middle- to high-latitude tree-ring width data set (from Tasmania, New Zealand and Tierra del Fuego) to reconstruct sea-level pressure (SLP) variability spanning the Tasman Sea and vicinity since ad 1740. The variables reconstructed are austral summer (November–March) SLP for Hobart, Tasmania (43°S, 147°E) and the Chatham Islands, New Zealand (44°S, 177°E), as well as a meridional circulation index (Hobart-Chatham Islands index) which measures the pressure gradient between these two stations. The three reconstructions are well verified statistically and capture between 40 and 48% of the variance in the SLP data. The instrumental and estimated SLP show similar spatial patterns of correlation with the sea surface temperature (SST) field for the Pacific. Statistically significant (above 95% level) 3–3.5 year spectral peaks are identified in the three reconstructions using multitaper spectral analysis, and a significant 4–5 year peak is found in both the Chatham Islands and Hobart-Chatham Islands SLP reconstructions. These two modes are within the bandwidth of the El Nino-Southern Oscillation. Although very speculative, they may also correspond to a proposed Antarctic circumpolar wave of SLP, SST, wind and sea-ice extent, believed to play a key role in atmosphere-ocean circulation for the Southern Hemisphere.

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Received: 30 November 1998 / Accepted: 13 December 1999

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D'Arrigo, R., Cook, E., Villalba, R. et al. Trans-Tasman Sea climate variability since ad 1740 inferred from middle to high latitude tree-ring data. Climate Dynamics 16, 603–610 (2000). https://doi.org/10.1007/s003820000070

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  • DOI: https://doi.org/10.1007/s003820000070

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