摘要：How the pattern of the Earth’s surface warming will change under global warming represents a
fundamental question for our understanding of the climate system with implications for regional
projections. Despite the importance of this problem there have been few analyses of nonlinear local
temperature change as a function of global warming. Individual climate models project nonlinearities,
but drivers of nonlinear local change are poorly understood. Here, I present a framework for the
identification and quantification of local nonlinearities using a time-slice analysis of a multi-model
ensemble. Accelerated local warming is more likely over land than ocean per unit global warming. By
examining changes across the model ensemble, I show that models that exhibit summertime drying
over mid-latitude land regions, such as in central Europe, tend to also project locally accelerated
warming relative to global warming, and vice versa. A case study illustrating some uses of this
framework for nonlinearity identification and analysis is presented for north-eastern Australia. In this
region, model nonlinear warming in summertime is strongly connected to changes in precipitation,
incoming shortwave radiation, and evaporative fraction. In north-eastern Australia, model
nonlinearity is also connected to projections for El Niño. Uncertainty in nonlinear local warming
patterns contributes to the spread in regional climate projections, so attempts to constrain projections
are explored. This study provides a framework for the identification of local temperature
nonlinearities as a function of global warming and analysis of associated drivers under prescribed
global warming levels.
关键词：climate change; El Niño; CMIP5; Paris agreement; nonlinear change; regional projections
