The rate of global precipitation increase under future warming (hydrologic sensitivity, HS) is highly uncertain among climate models. Here, we show that it may be constrained by using El Niño and La Niña events centered in the Central equatorial Pacific as an observable analogue in the historical climate.
Climate models all appear to underestimate HS, meaning that global precipitation is likely to intensify at a greater rate than previously predicted. With the observational record of precipitation anomalies under El Niño and La Niña events ever increasing, we will be able to predict this rate of intensification more robustly.
Large uncertainty exists in hydrologic sensitivity (HS), the global-mean precipitation increase per degree of warming, among global climate models. Meanwhile, global precipitation is sensitive to variations of surface temperature under El Niño and La Niña events, collectively known as the El Niño Southern Oscillation (ENSO). Here we show in phase 6 of the Coupled Model Intercomparison Project (CMIP6) that the strength of HS under ENSO is predictive of HS in the climate change context (r = 0.56). This correlation increases to 0.62 when only El Niño and La Niña events with maximum anomalies in the Central Pacific are considered, meaning that they are a better proxy for HS under future warming than East-Paciﬁc ENSO events. Observations of HS under ENSO suggest that it is signiﬁcantly underestimated by the climate models, with the lower bound of observational uncertainty almost double even the highest-HS models. Climate models with greater HS are associated with greater transformation of the tropical atmospheric circulation than those with lower HS. This ENSO-related transformation of the tropical circulation holds clues into how the models may be improved in order to more reliably simulate future hydrological-cycle intensiﬁcation.