Gao Meng, Sherman Peter, Song Shaojie, Yu Yueyue, Wu Zhiwei, McElroy Michael B
Department of Geography, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China.
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Sci Adv. 2019 Jul 17;5(7):eaav4157. doi: 10.1126/sciadv.aav4157. eCollection 2019 Jul.
As China makes every effort to control air pollution, India emerges as the world's most polluted country, receiving worldwide attention with frequent winter (boreal) haze extremes. In this study, we found that the interannual variability of wintertime aerosol pollution over northern India is regulated mainly by a combination of El Niño and the Antarctic Oscillation (AAO). Both El Niño sea surface temperature (SST) anomalies and AAO-induced Indian Ocean Meridional Dipole SST anomalies can persist from autumn to winter, offering prospects for a prewinter forecast of wintertime aerosol pollution over northern India. We constructed a multivariable regression model incorporating El Niño and AAO indices for autumn to predict wintertime AOD. The prediction exhibits a high degree of consistency with observation, with a correlation coefficient of 0.78 ( < 0.01). This statistical model could allow the Indian government to forecast aerosol pollution conditions in winter and accordingly improve plans for pollution control.
在中国全力控制空气污染之际，印度成为世界上污染最严重的国家，其冬季（北方）频繁出现极端雾霾，受到全球关注。在本研究中，我们发现印度北部冬季气溶胶污染的年际变率主要受厄尔尼诺和南极涛动（AAO）共同调控。厄尔尼诺海表面温度（SST）异常以及AAO引发的印度洋经向偶极SST异常都能从秋季持续到冬季，为印度北部冬季气溶胶污染的冬季前预报提供了可能。我们构建了一个包含秋季厄尔尼诺和AAO指数的多变量回归模型来预测冬季气溶胶光学厚度（AOD）。该预测与观测结果高度一致，相关系数为0.78（<0.01）。这种统计模型可以让印度政府预测冬季的气溶胶污染状况，并据此改进污染控制计划。
