Terrestrial Climate Records

Previous statistical detection methods based partially on climate model simulations indicate that, globally, the observed  warming lies very probably  outside the natural variations. We use a more simple approach  to assess recent warming at different spatial scales without making explicit use of climate simulations. It  considers the likelihood that the observed recent clustering of  warm record-breaking mean temperatures at global, regional and local scales may occur by chance in a  stationary climate. Under two statistical null-hypotheses, autoregressive and  long-memory,  this probability turns to be  very low: for the global records lower than $p=0.001$, and  even lower for some regional records. The picture for the individual long station records is not as clear, as the number of recent record years is not as large as for the spatially averaged temperatures.