| description abstract | AbstractRegional hydroclimate changes on decadal time scales contain substantial natural variability. This presents a challenge for the detection of anthropogenically forced hydroclimate changes on these spatiotemporal scales because the signal of anthropogenic changes is modest, compared to the noise of natural variability. However, previous studies have shown that this signal-to-noise ratio can be greatly improved in a large model ensemble where each member contains the same signal but different noise. Here, using multiple state-of-the-art large ensembles from two climate models, the authors quantitatively assess the detectability of anthropogenically caused decadal shifts in precipitation-minus-evaporation (PmE) mean state against natural variability, focusing on North America during 2000?50. Anthropogenic forcing is projected to cause detectable (signal larger than noise) shifts in PmE mean state relative to the 1950?99 climatology over 50%?70% of North America by 2050. The earliest detectable signals include, during November?April, a moistening over northeastern North America and a drying over southwestern North America and, during May?October, a drying over central North America. Different processes are responsible for these signals. Changes in submonthly transient eddy moisture fluxes account for the northeastern moistening and central drying, while monthly atmospheric circulation changes explain the southwestern drying. These model findings suggest that despite the dominant role of natural internal variability on decadal time scales, anthropogenic shifts in PmE mean state can be detected over most of North America before the middle of the current century. | |
