Very early warning of next El Niño

Abstract

The most important driver of climate variability is the El Niño Southern Oscillation, which can trigger disasters in various parts of the globe. Despite its importance, conventional forecasting is still limited to 6 mo ahead. Recently, we developed an approach based on network analysis, which allows projection of an El Niño event about 1 y ahead. Here we show that our method correctly predicted the absence of El Niño events in 2012 and 2013 and now announce that our approach indicated (in September 2013 already) the return of El Niño in late 2014 with a 3-in-4 likelihood. We also discuss the relevance of the next El Niño to the question of global warming and the present hiatus in the global mean surface temperature.dynamic networks | ENSO | spring barrier

El Niño and the shifting geography of cholera in Africa

“…However, here we show clear evidence for a shift in the distribution of cholera incidence throughout regions of Africa in El Niño compared with non-El Niño years, likely mediated by El Niño's impact on local climatic factors. Recent ENSO forecasting models warn of developing El Niño conditions up to 12 mo in advance (31). As predictive ability of ENSO anomalies improves (31,32), our findings provide hope that we may be able to provide early cholera-risk forecasts.…”

Network analysis reveals strongly localized impacts of El Niño

“…This phenomenon is evident by inspecting the emergent teleconnections between the ENB and localized regions. Such a large-scale cooperative mode helps us to forecast El Niño events (15,16). Our results also indicate that the El Niño/La Niña events influence different regions with different magnitudes during different events; still, by determining the network community structure, our results suggest that similarities exist among some of the El Niño (La Niña) events.…”

“…35. The climate network approach has been found to be useful in improving our understanding of El Niño (8,(23)(24)(25) and in forecasting it (15,16). However, that approach has not been developed and applied to study systematically the global impact of El Niño, and that is what we try to achieve in quantitative terms here.…”

“…These networks have been used successfully to analyze, model, understand, and even predict climate phenomena (6-16). Specific examples of climate network studies include the investigation of the interaction structure of coupled climate subnetworks (17), the multiscale dependence within and among climate variables (18), the temporal evolution and teleconnections of the North Atlantic Oscillation (19,20), the finding of the dominant imprint of Rossby waves (21), the optimal paths of teleconnection (22), the influence of El Niño on remote regions (8,23,24), the distinction of different types of El Niño events (25), and the prediction of these events (15,16). A network is composed of nodes and links; in a climate network, the nodes are the geographical locations, and the links are the correlations between them.…”

Unified functional network and nonlinear time series analysis for complex systems science: Thepyunicornpackage

“…20 It has been already successfully used in a wide variety of applications, ranging from the complex structure of teleconnections in the climate system, 15,18,49 including backbones and bottlenecks, 19,89 to dynamics and predictability of the El Niño-Southern Oscillation (ENSO). 66,92,93 Climate networks (class climate.ClimateNetwork) represent strong statistical interrelationships between time series and are typically reconstructed by thresholding the matrix of a statistical similarity measure S (Fig. 8) …”