Based on the 30-year global hourly sea surface temperature (SST) dataset (MLSST) produced by the National Marine Environmental Forecasting Center, Ministry of Natural Resources of China, we analyzed the variability of diurnal sea surface temperature amplitude (DSST) of the tropical Indian Ocean at multiple time scales, as well as its influencing factors. The results show that the DSST in the Arabian Sea, Bay of Bengal, and equatorial Indian Ocean exhibits a bimodal seasonal variation with a semi-annual cycle, while the DSST in the southern Indian Ocean shows an annual cycle. The seasonal variation of DSST is mainly influenced by factors such as sea surface wind speed, shortwave solar radiation, and precipitation. The DSST in the equatorial Indian Ocean is generally higher during El Niño years compared to La Niña years. At the intraseasonal scale, the large standard deviation of DSST in boreal winter is mainly distributed in the southern hemisphere, while the large standard deviation of DSST in boreal summer shifts northward. The intraseasonal variation amplitude of DSST in boreal winter of the tropical Indian Ocean is greater than that in boreal summer. The DSST in the tropical Indian Ocean exhibits significant variation characteristics at multi-time scales. This study provides reference for numerical simulation of air-sea interaction patterns in the tropical Indian Ocean, as well as improvement of short-term climate prediction.

Currently, the “spring predictability barrier” (SPB) is still a controversial problem in many atmosphere–ocean coupled models and has significant impacts on degrading the El Niño–Southern Oscillation (ENSO) predictions across the boreal spring. In this study, unlike previous studies that viewed the SPB issue from the perspective of sea surface temperature (SST), based on the Bjerknes feedback theory and the decadal variations in Walker circulation over the tropical Pacific, a new perspective of the SPB is revealed by the seasonal variations in the observed zonal sea level pressure (SLP) gradient, which can reflect the stability and variability of the atmosphere–ocean interactions during the ENSO’s evolution. More importantly, a significant decadal variation of SPB strength (SPBS) is exhibited in the last 3 decades, from 1991 to 2020, which is strongly controlled by the dominant patterns of sea surface temperature (SST) and Walker circulation, and associated with the background mean atmosphere–ocean states. That is to say, the atmosphere–ocean interaction pattern over the tropical Pacific has undergone decadal variations over the past 3 decades which determine the decadal variations in SPBS. International Research Institute for Climate and Society/Climate Prediction Center (IRI/CPC) multi-models show stronger SPBS during 2001–2010 than during 2011–2020, indicating that the decadal variations in SPBS from statistical analysis also exist in actual model predictions, which further confirms the rationality of this perspective of SPB based on the zonal SLP gradient.