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We analyze the historical simulations from 31 CGCMs participating in the CMIP6 (Table 1). Only one integration ensemble member is used for all models. Output of the monthly SST, wind, and ocean temperature from these models are remapped onto a 1° × 1° regular grid. The observational reanalysis of the monthly ocean temperature data is obtained from the Ocean Reanalysis System 4 (ORAS4) for 1958–2015 from the European Centre for Medium-Range Weather Forecasts (ECMWF) (Balmaseda et al., 2013), which is also remapped onto a 1° × 1° regular grid. ORAS4 has been widely used to study variability in the equatorial Indian Ocean (Deepa et al., 2019; Kakatkar et al., 2020; Mohapatra et al., 2020) and was found to be one of the best reanalysis products over the Indian Ocean (Karmakar et al., 2018). The monthly wind from 1958 to 1978 and from 1979 to 2015 are obtained from the ECMWF 40 reanalysis (ERA-40) and ECMWF interim reanalysis (ERA-Interim) (Uppala et al., 2005; Dee et al., 2011), respectively. Oceanic heat content anomalies (HCA) are defined as the mean ocean temperature anomalies multiplied by the density (1025 kg m–3) and the specific heat (3850 J kg–1 °C–1) of seawater for the upper 315 m of depth. The equatorial thermocline depth is defined by the depth of 20°C isotherm and the thermocline tilt is calculated as the difference in thermocline depth between the western (50°−70°E, 10°S−10°N) and eastern TIO (80°−95°E, 10°S−10°N).
NO. Model name Institute (country) 1 ACCESS-CM2 Commonwealth Scientific and Industrial Research Organisation and Bureau of Meteorology (Australia) 2 ACCESS-ESM1-5 Commonwealth Scientific and Industrial Research Organisation and Bureau of Meteorology (Australia) 3 BCC-CSM2-MR Beijing Climate Center (China) 4 BCC-ESM1 Beijing Climate Center (China) 5 CAMS-CSM1-0 Chinese Academy of Meteorological Sciences (China) 6 CanESM5 Canadian Centre for Climate Modelling and Analysis (Canada) 7 CanESM5-CanOE Canadian Centre for Climate Modelling and Analysis (Canada) 8 EC-Earth3 EC-Earth-Consortium 9 EC-Earth3-AerChem EC-Earth-Consortium 10 EC-Earth3-CC EC-Earth-Consortium 11 EC-Earth3-Veg EC-Earth-Consortium 12 EC-Earth3-Veg-LR EC-Earth-Consortium 13 E3SM-1-0 E3SM-Project 14 E3SM-1-1 E3SM-Project 15 E3SM-1-1-ECA E3SM-Project 16 FGOALS-f3-L Chinese Academy of Sciences (China) 17 FGOALS-g3 Chinese Academy of Sciences (China) 18 GFDL-CM4 Geophysical Fluid Dynamics Laboratory (USA) 19 GFDL-ESM4 Geophysical Fluid Dynamics Laboratory (USA) 20 GISS-E2-1-G NASA Goddard Institute for Space Studies (USA) 21 GISS-E2-1-H NASA Goddard Institute for Space Studies (USA) 22 GISS-E2-2-H NASA Goddard Institute for Space Studies (USA) 23 HadGEM3-GC31-LL Met Office Hadley Centre (UK) 24 HadGEM3-GC31-MM Met Office Hadley Centre (UK) 25 MCM-UA-1-0 University of Arizona (UA) 26 MPI-ESM-1-2-HAM Max Planck Institute for Meteorology (Germany) 27 MPI-ESM1-2-HR Max Planck Institute for Meteorology (Germany) 28 MPI-ESM1-2-LR Max Planck Institute for Meteorology (Germany) 29 MRI-ESM2-0 Meteorological Research Institute (Japan) 30 NESM3 Nanjing University of Information Science and Technology (China) 31 UKESM1-0-LL Met Office Hadley Centre (UK) Table 1. The CMIP6 models used in this study
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An index representing the Sub-IOD (SDI) is defined as the normalized difference in the area-mean HCA between the western (50°–70°E, 5°S–5°N) and eastern (80°–100°E, 5°S–5°N) TIO (e.g., Rao et al. 2002 and their Fig. 3; Kakatkar et al. 2020 and their Fig.1; Song et al. 2021 and their Fig. 10). Following Saji et al. (1999), the IOD index is defined as the normalized SSTA difference between the western (50°–70°E, 10°S–10°N) and southeastern (90°–110°E, 10°S–0°) TIO. Sub-IOD (IOD) events are defined when the three-month running mean normalized SDI (DMI) exceeds its 0.9 (1.0) standard deviation. It should be pointed out that the IOD index defined from ORAS4 is highly consistent with that from the gridded SST products HadISST (correlation coefficient up to 0.81 and significant at the 99% confidence level). Therefore, we use the ORAS4 as the observational reanalysis dataset. As for ENSO, the Niño-3, Niño-3.4, and Niño-4 indices are defined as the area-mean SSTA respectively over the (5°N–5°S, 150°–90°W), the (5°N–5°S, 170°–120°W), and the (5°N–5°S, 160°E–150°W). In general, we use the Niño-3.4 index to describe the evolution and strength of ENSO and further define an index for CP ENSO (CPI) as:
where
$ \alpha=0.4 $ when$\mathrm{N}\mathrm{i}\tilde{\mathrm{n}}\mathrm{o}4$ ×$\mathrm{N}\mathrm{i}\tilde{\mathrm{n}}\mathrm{o}3\gg 0$ and$ \alpha =0 $ when$\mathrm{N}\mathrm{i}\tilde{\mathrm{n}}\mathrm{o}4$ ×$\text{Ni}\tilde{\mathrm{n}}\mathrm{o}3\ll 0$ (Ren and Jin, 2011). Similarly, a positive (negative) three-month running mean, CPI normalized to be greater than 1.0 standard deviation indicates a CP El Niño (La Niña) event.
NO. | Model name | Institute (country) |
1 | ACCESS-CM2 | Commonwealth Scientific and Industrial Research Organisation and Bureau of Meteorology (Australia) |
2 | ACCESS-ESM1-5 | Commonwealth Scientific and Industrial Research Organisation and Bureau of Meteorology (Australia) |
3 | BCC-CSM2-MR | Beijing Climate Center (China) |
4 | BCC-ESM1 | Beijing Climate Center (China) |
5 | CAMS-CSM1-0 | Chinese Academy of Meteorological Sciences (China) |
6 | CanESM5 | Canadian Centre for Climate Modelling and Analysis (Canada) |
7 | CanESM5-CanOE | Canadian Centre for Climate Modelling and Analysis (Canada) |
8 | EC-Earth3 | EC-Earth-Consortium |
9 | EC-Earth3-AerChem | EC-Earth-Consortium |
10 | EC-Earth3-CC | EC-Earth-Consortium |
11 | EC-Earth3-Veg | EC-Earth-Consortium |
12 | EC-Earth3-Veg-LR | EC-Earth-Consortium |
13 | E3SM-1-0 | E3SM-Project |
14 | E3SM-1-1 | E3SM-Project |
15 | E3SM-1-1-ECA | E3SM-Project |
16 | FGOALS-f3-L | Chinese Academy of Sciences (China) |
17 | FGOALS-g3 | Chinese Academy of Sciences (China) |
18 | GFDL-CM4 | Geophysical Fluid Dynamics Laboratory (USA) |
19 | GFDL-ESM4 | Geophysical Fluid Dynamics Laboratory (USA) |
20 | GISS-E2-1-G | NASA Goddard Institute for Space Studies (USA) |
21 | GISS-E2-1-H | NASA Goddard Institute for Space Studies (USA) |
22 | GISS-E2-2-H | NASA Goddard Institute for Space Studies (USA) |
23 | HadGEM3-GC31-LL | Met Office Hadley Centre (UK) |
24 | HadGEM3-GC31-MM | Met Office Hadley Centre (UK) |
25 | MCM-UA-1-0 | University of Arizona (UA) |
26 | MPI-ESM-1-2-HAM | Max Planck Institute for Meteorology (Germany) |
27 | MPI-ESM1-2-HR | Max Planck Institute for Meteorology (Germany) |
28 | MPI-ESM1-2-LR | Max Planck Institute for Meteorology (Germany) |
29 | MRI-ESM2-0 | Meteorological Research Institute (Japan) |
30 | NESM3 | Nanjing University of Information Science and Technology (China) |
31 | UKESM1-0-LL | Met Office Hadley Centre (UK) |