Evaluation of ENSO simulations in CMIP5 models: A new perspective based on percolation phase transition in complex networks

Zhenghui Lu,Lin Chen,Zuntao Fu,Naiming Yuan,Lijuan Hua

doi:10.1038/s41598-018-33340-y

Abstract

In this study, the performance of CMIP5 models in simulating the El Niño-Southern Oscillation (ENSO) is evaluated by using a new metric based on percolation theory. The surface air temperatures (SATs) over the tropical Pacific Ocean are constructed as a SAT network, and the nodes within the network are linked if they are highly connected (e.g., high correlations). It has been confirmed from reanalysis datasets that the SAT network undergoes an abrupt percolation phase transition when the influences of the sea surface temperature anomalies (SSTAs) below are strong enough. However, from simulations of the CMIP5 models, most models are found incapable of capturing the observed phase transition at a proper critical point Pc. For the 15 considered models, four even miss the phase transition, indicating that the simulated SAT network is too stable to be significantly changed by the SSTA below. Only four models can be considered cautiously with some skills in simulating the observed phase transition of the SAT network. By comparing the simulated SSTA patterns with the node vulnerabilities, which is the chance of each node being isolated during a ENSO event, we find that the improperly simulated sea-air interactions are responsible for the missing of the observed percolation phase transition. Accordingly, a careful study of the sea-air couplers, as well as the atmospheric components of the CMIP5 models is suggested. Since the percolation phase transition of the SAT network is a useful phenomenon to indicate whether the ENSO impacts can be transferred remotely, it deserves more attention for future model development.

Highlights

El Niño-Southern Oscillation (ENSO), the dominant mode of inter-annual climate variability, is one of the most important ocean-atmosphere coupled phenomena
The percentage of isolated nodes P is defined as the fraction of isolated nodes over the total nodes[40], which is a quantity that measures the intensity of the influences of ENSO on the upper surface air temperatures (SATs) network
We evaluated the ability of 15 CMIP5 models to simulate ENSO from a new perspective, namely as a climate network

Summary

Introduction

El Niño-Southern Oscillation (ENSO), the dominant mode of inter-annual climate variability, is one of the most important ocean-atmosphere coupled phenomena. In the studies of complex networks, percolation theory is one of the most important findings[32,33,34,35] It indicates the existence of a critical point Pc, such that above Pc the phase state of the network may convert abruptly from stable to unstable or metastable (see Methods)[34,35]. As long as the fraction of isolated nodes (nodes with no links with any other node of the network) in the SAT network is higher than a threshold Pc = 0.48, the SAT network will abruptly be divided into many small isolated clusters, indicating a conversion of the network state[37,38] This abrupt percolation phase transition means that the anomalous SST warming/cooling in the tropical central eastern Pacific has significantly changed the SAT field, which may further transport the influences of ENSO to remote regions via an atmospheric bridge. The fraction of isolated nodes P was conjectured to be a new index to determine whether the influences of ENSO can be transported remotely

Objectives

Methods

Results

Conclusion