This is an exploratory investigation to search for the presence of an acceleration in global sea surface temperature rise, which is essential to identify anthropogenic contributions to the climate change during the 20...This is an exploratory investigation to search for the presence of an acceleration in global sea surface temperature rise, which is essential to identify anthropogenic contributions to the climate change during the 20 th century. A weighted statistical model with an acceleration parameter was built progressively to reconstruct the variations in the global sea surface temperature data considering statistically significant confounders and autoregressive disturbances in the process. From the preliminary residual analysis of a weighted regression model, emerged a parsimonious model with first order autoregressive disturbances with a deterministic trend, acceleration and periodicity of 69 yr and its 138 yr subharmonic. The final model solution, selected from 29 alternative combinations of the model parameters using Mallows' s Cp metric, revealed a statistically significant deterministic trend, 0.40 ± 0.03C/c(p < 0.01), and acceleration, 0.67 ± 0.11C/c^2(p < 0.01) explaining 33% of the global sea surface temperature variations. The combined yearly trend and acceleration in global sea surface temperature as predicted by the model,exhibit a strong correlation with the yearly increase in the global CO^2 concentrations observed during the 20th century.展开更多
文摘This is an exploratory investigation to search for the presence of an acceleration in global sea surface temperature rise, which is essential to identify anthropogenic contributions to the climate change during the 20 th century. A weighted statistical model with an acceleration parameter was built progressively to reconstruct the variations in the global sea surface temperature data considering statistically significant confounders and autoregressive disturbances in the process. From the preliminary residual analysis of a weighted regression model, emerged a parsimonious model with first order autoregressive disturbances with a deterministic trend, acceleration and periodicity of 69 yr and its 138 yr subharmonic. The final model solution, selected from 29 alternative combinations of the model parameters using Mallows' s Cp metric, revealed a statistically significant deterministic trend, 0.40 ± 0.03C/c(p < 0.01), and acceleration, 0.67 ± 0.11C/c^2(p < 0.01) explaining 33% of the global sea surface temperature variations. The combined yearly trend and acceleration in global sea surface temperature as predicted by the model,exhibit a strong correlation with the yearly increase in the global CO^2 concentrations observed during the 20th century.
