Abstract

The time at which the climate change signal emerges from the noise of natural climate variability is known as Time of Emergence (ToE), and has become relevant for impact assessment studies and the implementation of adaptation strategies. Traditionally, the ToE has been estimated using the time at which the ratio between the General Circulation Model (GCM) signal and its noise (variability) exceeds a particular threshold (such as 1 or 2). This approach neither considers the noise of the local climate, nor a probabilistic assessment of the ToEits occurrence. This work proposes a methodology to estimate with a certain probability the ToE for precipitation and temperature at a local scale. (i.e. meteorological gauge). The probabilistic evaluation of ToE on a specific location is performed by combining the stochastic generation of annual climate data representing the local natural variability, and the identification of probabilistic long-term statistical properties obtained from the group of Coupled Model Intercomparison Project Phase 5 (CMIP5) GCMs. The On this study ToE on this study is identified by the generation of several realizations of two sets of synthetic climate time series. One set incorporates the GCM trend and the other replicates the local climate. The ToE is estimated as the time at which both sets of data are not statistically the same. We applied the method to three Chilean river basins located in a semiarid, dry and normal Mediterranean climate (Limarí, Maipo and Maule)) a dry Mediterranean climate (Maipo) and a Mediterranean climate (Maule). For the three basins, the ToE of temperature takes places earlier than that of precipitation. Our method suggests that the ToE of temperatures already occurred, while there is a probability larger than 50% that the ToE of precipitation occurs prior to ~2030 for RCPs 4.5, 6.0 and 8.5. Overall, the proposed method is an attractive tool for risk assessment at the local scale, able to estimate the probability of having a certain precipitation reduction or increase and the corresponding ToE of these changes.