In our study, we present a purely statistical observations-based model-free analysis that provides evidence about Granger causality (GC) from long-lived radiative forcings (LLRFs) to the climate trend (CT). This relies on having locally ordered breaks in the slopes of the trend functions of LLRF and the CT, with the break for LLRF occurring before that of the CT and with the slope changes being of the same sign. The empirical evidence indicates that these conditions are satisfied empirically using standard global surface temperature series and an aggregate measure of LLRF (carbon dioxide, nitrous oxide, and chlorofluorocarbons). We also discuss why the presence of broken trends can lead one to conclude in favor of GC when using standard methods even if the noise function in LLRF is negligible.
Keywords: attribution; causality; climate change; econometric methods; time series.
© 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.