CAS Key Laboratory of Regional Climate-Environment for Temperate East Asia (RCE-TEA), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, and Key Open Laboratory of Arid Climate Change and Disaster Reduction of CMA, Institute of Arid Meteorology, CMA, Lanzhou 730020, China.
Sci Rep. 2017 Jan 17;7:40741. doi: 10.1038/srep40741.
The devastating North China drought in the summer of 2015 was roughly captured by a dynamical seasonal climate forecast model with a good prediction of the 2015/16 big El Niño. This raises a question of whether strong El Niños imply higher predictability of extreme droughts. Here we show that a strong El Niño does not necessarily result in an extreme drought, but it depends on whether the El Niño evolves synergistically with Eurasian spring snow cover reduction to trigger a positive summer Eurasian teleconnection (EU) pattern that favors anomalous northerly and air sinking over North China. The dynamical forecast model that only well represents the El Niño underpredicts the drought severity, while a dynamical-statistical forecasting approach that combines both the low- and high-latitudes precursors is more skillful at long lead. In a warming future, the vanishing cryosphere should be better understood to improve predictability of extreme droughts.
2015 年夏季重创华北地区的毁灭性干旱,大致可被一个动力季节气候预测模型捕捉到,该模型对 2015/16 年超强厄尔尼诺现象的预测非常准确。这就提出了一个问题,即强烈的厄尔尼诺现象是否意味着极端干旱的可预测性更高。在这里,我们表明,强烈的厄尔尼诺现象并不一定会导致极端干旱,而是取决于厄尔尼诺现象是否与欧亚大陆春季积雪减少协同演变,以引发有利于异常北风和空气下沉的正的欧亚夏季遥相关(EU)模式。仅能很好地代表厄尔尼诺现象的动力预测模型低估了干旱的严重程度,而结合低纬和高纬前兆的动力统计预测方法在提前较长时间预测时更有优势。在变暖的未来,应该更好地了解正在消失的冰冻圈,以提高对极端干旱的预测能力。