Padrón Ryan S, Gudmundsson Lukas, Seneviratne Sonia I
Institute for Atmospheric and Climate Science, Department of Environmental Systems Science ETH Zurich Zurich Switzerland.
Geophys Res Lett. 2019 Jan 28;46(2):736-744. doi: 10.1029/2018GL080521. Epub 2019 Jan 16.
Future changes in multidecadal mean water availability, represented as the difference between precipitation and evapotranspiration, remain highly uncertain in ensemble simulations of climate models. Here we identify a physically meaningful relationship between present-day mean precipitation and projected changes in water availability. This suggests that the uncertainty can be reduced by conditioning the ensemble on observed precipitation, which is achieved through a novel probabilistic approach that uses Approximate Bayesian Computation. Comparing the constrained with the full ensemble shows that projected extreme changes in water availability, denoted by the 5th and 95th percentile of the full ensemble, are less likely over 73% and 63% of land, respectively. There is also an overall shift toward wetter conditions over Europe, Southern Africa, and Western North America, whereas the opposite occurs over the Amazon. Finally, the constrained projections support adaptation to shifts in regional water availability as imposed by different global warming levels.
在气候模型的集合模拟中，以降水与蒸发散之差表示的多年代平均水资源可用性的未来变化仍具有高度不确定性。在此，我们确定了当前平均降水量与预计水资源可用性变化之间具有物理意义的关系。这表明，通过以观测到的降水量为条件对集合进行限制，可以降低不确定性，这是通过一种使用近似贝叶斯计算的新型概率方法实现的。将受限集合与完整集合进行比较表明，分别在超过73%和63%的陆地上，完整集合中第5和第95百分位数所表示的预计水资源可用性极端变化可能性较小。欧洲、南部非洲和北美西部总体上也朝着更湿润的条件转变，而亚马逊地区则相反。最后，受限预测支持适应不同全球变暖水平所带来的区域水资源可用性变化。
