Abstract
Accurately representing the Indian Ocean Dipole (IOD) is crucial for reliable climate predictions and future projections. However, El Niño-Southern Oscillation (ENSO) and IOD interact, making it necessary to evaluate ENSO and IOD simultaneously. Using the historical simulation from 32 fifth phase of Coupled Model Intercomparison Project (CMIP5) models and 34 CMIP6 models, here we find that there are some modest changes in the basic characteristics of the IOD and ENSO from CMIP5 to CMIP6. Firstly, there is a slight shift in the seasonality of IOD toward an earlier peak in September in CMIP6, from November in CMIP5. Secondly, inter-model spread in the frequency of ENSO and the IOD has reduced in CMIP6 relative to CMIP5. ENSO asymmetry is still underestimated in CMIP6, based on the skewness of the Niño3 index, while the IOD skewness has degraded from CMIP5. Finally, mean state SST biases impact on the strength of the IOD; the Pacific cold tongue mean state is important in CMIP5, but in CMIP6 the Pacific warm pool mean state is more important.
Highlights
Representing the Indian Ocean Dipole (IOD) is crucial for reliable climate predictions and future projections
CMIP5 and CMIP6 show relative skill in simulating this seasonal phase locking as exhibited in Fig. 1a,b which shows the standard deviation of Dipole Mode Index (DMI) and Niño 3.4 for each month
In light of a previous suggestion that an extreme El Niño could be a result of El Niño-Southern Oscillation (ENSO)-IOD interaction[44 ], our analysis found no concrete evidence in CMIP5 and CMIP6 that ENSO is enhanced by IOD events
Summary
Representing the Indian Ocean Dipole (IOD) is crucial for reliable climate predictions and future projections. The IOD peaks around September–November, with its positive phase (pIOD) characterised by anomalously cool sea surface off Java and Sumatra, and anomalous warming in the tropical western Indian Ocean; vice versa for the negative phase (nIOD). Co-occurrences of pIOD with La Niña, and nIOD with El Niño are rare in observations[4,5] Given their pronounced impact on global and regional climate, accurate representation of ENSO and IOD in climate models is crucial to produce reliable climate forecasts and future projections. Spatial diversity in the IOD is shown to exist, with an ‘IOD Modoki’ characterised by SST anomalies in the central IO26 This suggests that the IOD has a complex behaviour that results from a combination of internal processes in the Indian Ocean and remote influences such as ENSO, potentially presenting further challenges in modelling the IOD. We focus on IOD diversity only in terms of its co-occurrence with ENSO, that is, examining ENSO-independent and ENSO co-occurring IOD events
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