资源环境科技发展态势分析平台

The contribution of the subsurface precursor, defined as the buildup of heat content in theequatorial subsurface prior to El Nino-Southern Oscillation (ENSO) events, to ENSO amplitude and predictability has been unclear for some time. To address the issue, this study implements a careful experimental design to construct three March-initialized precursor ensembles using CCSM4, one ensemble with ENSO-neutral initial conditions, one with a warm precursor in the subsurface, and one with a cold precursor. The initial precursors within each respective ensemble, although generated via identical wind forcing, differ slightly due to intrinsic sources of noise in the ocean and atmosphere. The ensembles are then integrated fully-coupled to produce a distribution of outcomes per each type of initial condition. Results show that a precursor is not essential to produce moderate El Nino and the full range of La Nina events, whereas a warm precursor is a necessary condition to generate extreme El Nino. The findings imply that extreme El Nino and the coldest La Nina events are fundamentally different. Presence of a warm (cold) precursor in the initial condition results in a warm (cold) shift and narrowing of the distribution of outcomes, suggesting increased predictability of El Nino (La Nina). Although the cold precursor is not necessary to produce La Nina, its presence in the initial condition reduces La Nina spread more than the warm precursor reduces El Nino spread. Despite the smaller ensemble spread for La Nina, signal-to-noise ratios indicate that El Nino may be more predictable than La Nina.