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Evaluating ENSO teleconnections using observations and CMIP5 models

Roy, I, Gagnon, AS and Siingh, D (2018) Evaluating ENSO teleconnections using observations and CMIP5 models. Theoretical and Applied Climatology. ISSN 0177-798X

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Abstract

Bias correction of global and regional climate models is essential for credible climate change projections. This study examines the bias of the models of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) in their simulation of the spatial pattern of sea surface temperature (SSTs) in different phases of the El Niño Southern Oscillation (ENSO) and their teleconnections—highlighting the strengths and weaknesses of the models in different oceanic sectors. The comparison between the model outputs and the observations focused on the following three features: (i) the typical horseshoe pattern seen in the Pacific Ocean during ENSO events with anomalies in SSTs opposite to the warm/cool tongue, (ii) different signature in the tropical Pacific Ocean from that of the North and tropical Atlantic Ocean, and (iii) spurious signature in the southern hemisphere beyond 45° S. Using these three cases, it was found that the model simulations poorly matched the observations, indicating that more attention is needed on the tropical/extratropical teleconnections associated with ENSO. More importantly, the observed SST coupling between the tropical Pacific Ocean and the Atlantic Ocean is missing in almost all models, and differentiating the models between high/low top did not improve the results. It also found that SSTs in the tropical Pacific Ocean are relatively well simulated when compared with observation. This work has improved our understanding of the simulation of ENSO and its teleconnections in the CMIP5 models and has raised awareness of the bias existing in the models, which requires further attention by climate modellers. © 2018 The Author(s)

Item Type: Article
Uncontrolled Keywords: 0401 Atmospheric Sciences
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Divisions: Natural Sciences and Psychology
Publisher: Springer
Date Deposited: 07 Jan 2019 11:22
Last Modified: 07 Jan 2019 19:05
DOI or Identification number: 10.1007/s00704-018-2536-z
URI: http://researchonline.ljmu.ac.uk/id/eprint/9883

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