资源环境科技发展态势分析平台

Until recently, the El Nino-Southern Oscillation (ENSO) was considered a reliable source of winter precipitation predictability in the western US, with a historically strong link between extreme El Nino events and extremely wet seasons. However, the 2015-2016 El Nino challenged our understanding of the ENSO-precipitation relationship. California precipitation was near-average during the 2015-2016 El Nino, which was characterized by warm sea surface temperature (SST) anomalies of similar magnitude compared to the extreme 1997-1998 and 1982-1983 El Nino events. We demonstrate that this precipitation response can be explained by El Nino's spatial pattern, rather than internal atmospheric variability. In addition, observations and large-ensembles of regional and global climate model simulations indicate that extremes in seasonal and daily precipitation during strong El Nino events are better explained using the ENSO Longitude Index (ELI), which captures the diversity of ENSO's spatial patterns in a single metric, compared to the traditional Nino3.4 index, which measures SST anomalies in a fixed region and therefore fails to capture ENSO diversity. The physically-based ELI better explains western US precipitation variability because it tracks the zonal shifts in tropical Pacific deep convection that drive teleconnections through the response in the extratropical wave-train, integrated vapor transport, and atmospheric rivers. This research provides evidence that ELI improves the value of ENSO as a predictor of California's seasonal hydroclimate extremes compared to traditional ENSO indices, especially during strong El Nino events.