Testing for Deterministic Trends in Global Sea Surface Temperature

Abstract

ong-term variability in global sea surface temperature (SST) is often quantified by the slope from a linear regression fit. Attention is then focused on assessing the statistical significance of the derived slope parameter, but the adequacy of the linear model itself, and the inherent assumption of a deterministic linear trend, is seldom tested. Here, a parametric statistical test is applied to test the hypothesis of a linear deterministic trend in global sea surface temperature. The results show that a linear slope is not adequate for describing the long-term variability of sea surface temperature over most of the earth?s surface. This does not mean that sea surface temperature is not increasing, rather that the increase should not be characterized by the slope from a linear fit. Therefore, describing the long-term variability of sea surface temperature by implicitly assuming a deterministic linear trend can give misleading results, particularly in terms of uncertainty, since the actual increase could be considerably larger than the one predicted by a deterministic linear model.