Publication: Multidecadal variability of ENSO in a recharge oscillator framework
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2022-07-01
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IOP Publishing Ltd
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Abstract
We use a conceptual recharge oscillator model to identify changes in El Niño and the Southern Oscillation (ENSO) statistics and dynamics during the observational record. The variability of ENSO has increased during the 20th century. The cross-correlation between sea surface temperature (SST) and warm water volume (WWV) has also changed during the observational record. From the 1970s onwards, the SST drives WWV anomalies with a lead-time of ten months and the WWV feedbacks onto the SST with a lead-time of eight months. This is reminiscent of a recharge-discharge mechanism of the upper ocean heat content. The full recharge-discharge mechanism is only observed from the 1970s onwards. This could be the result of the degradation of the quality of observations in the early part of the 20th century. However, it may also be a consequence of decadal changes in the coupling between WWV and SST. Additional analysis fitting the recharge oscillator model to the coupled state-of-the-art climate models indicates that ENSO properties show little decadal changes in the climate models. The disagreement in changes in ENSO properties between the reanalysis and the climate models can be due to errors in the available observational data or due to the models missing the low frequency variability and decadal wind trends. Longer and more reliable observational records would be required to validate our results.
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© 2022 The Author(s). The work was supported by the European Union Seventh Framework Programme (EU-FP7/2007–2013) PREFACE (Grant Agreement No. 603521), the TRIATLAS H2020 project (Grant 817578), the ERC STERCP project (Grant 648982), the Spanish project PRE4CAST (CGL2017-86415-R) the ARC Centre of Excellence in Climate Extremes (CE170100023) and the ARC discovery project “Improving projections of regional sea level rise and their credibility (DP200102329). We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. The data archiving is underway and will be stored in the NIRD Research Data Archive repository (archive.norstore.no). We temporarily provide a copy of the output data of the ReOsc model as supporting information.