• climate modelling;
  • precipitation change

[1] Evidence is strong that the changes observed in the Earth's globally averaged temperature over the past half-century are caused to a large degree by human activities. Efforts to document accompanying precipitation changes in observations have met with limited success, and have been primarily focussed on large-scale regions in order to reduce the relative impact of the natural variability of precipitation as compared to any potential forced change. Studies have not been able to identify statistically significant changes in observed precipitation on small spatial scales. General circulation climate models offer the possibility to extend the analysis of precipitation changes into the future, to determine when simulated changes may emerge from the simulated variability locally as well as regionally. Here we estimate the global temperature increase needed for the precipitation “signal” to emerge from the “noise” of interannual variability within various climatic regions during their wet season. The climatic regions are defined based on cluster analysis. The dry season is not included due to poor model performance as compared to measurements during the observational period. We find that at least a 1.4°C warmer climate compared with the early 20th century is needed for precipitation changes to become statistically significant in any of the analysed climate regions. By the end of this century, it is likely that many land regions will experience statistically significant mean precipitation changes during wet season relative to the early 20th century based on an A1B scenario.