A statistical analysis of sea temperature dataA statistical analysis of sea temperature data

The paper analyzes sea temperature series measured at two geographical locations along the coast of Norway. We address the question whether the series are stable over the sample period 1936–2012 and whether we can measure any signal of climate change in the regional data. We use nonstandard supF, OLS-based CUSUM, RE, and Chow tests in combination with the Bai-Perron’s structural break test to identify potential changes in the temperature. The augmented Dickey-Fuller, the KPSS, and the nonparametric Phillips-Perron tests are in addition applied in the evaluation of the stochastic properties of the series. The analysis indicates that both series undergo similar structural instabilities in the form of small shifts in the temperature level. The temperature at Lista (58° 06′ N, 06° 38′ E) shifts downward about 1962 while the Skrova series (68° 12′ N, 14° 10′ E) shifts to a lower level about 1977. Both series shift upward about 1987, and after a period of increasing temperature, both series start leveling off about the turn of the millennium. The series have no significant stochastic or deterministic trend. The analysis indicates that the mean temperature has moved upward in decadal, small steps since the 1980s. The result is in accordance with recent analyses of sea temperatures in the North Atlantic. The findings are also related to the so-called hiatus phenomenon where natural variation in climate can mask global warming processes. The paper contributes to the discussion of applying objective methods in measuring climate change.