Paleoclimate Reconstructions of Tropical Sea Surface Temperatures from Precipitation Proxies: Methods, Uncertainties, and Nonstationarity

Abstract

AbstractProxy-based paleoclimate reconstructions of tropical sea surface temperature (SST) fields may lead to better constraints of tropical climate variability in climate model projections. In this study, the authors quantify uncertainties associated with two popular SST anomaly reconstruction methods that have been applied over the last millennium. The first reconstruction method exploits the high correlation between the leading modes of variability of global precipitation and SSTs; the second method uses a multiregression model that exploits the multiple modes of covariability between precipitation and SSTs. Regardless of the proxy network density, the first method has skill only in the tropical eastern Pacific and misses some ENSO events. By contrast, the multiregression approach demonstrates high skill throughout the tropical Indo-Pacific region and predicts all ENSO events correctly. The advantage of the multiregression method lies in the second mode of covariability between SSTs and precipitation, which explains nearly 15% of the covariability between the two variables. However, when the period 1950–2000 is considered, the authors find that the nonstationarity in the second mode of covariability between SST and precipitation leads to a significant reduction of skill in the Indian Ocean and the warm pool region. This change suggests that the underlying stationarity assumption common in most climate field reconstruction methods needs to be treated more carefully, particularly in the tropics.