Impact of Cold Tongue Bias on Indian Ocean Dipole Prediction Skills

Abstract In this study, we employ the Model‐based Analog Forecast approach to conduct Indian Ocean Dipole (IOD) hindcasts from 1982 to 2017, using 18 CMIP6 models. We focus on the skill diversity among different climate models, with particular attention to how the cold tongue bias affects IOD predictions. Our findings reveal a significant diversity in IOD prediction skills across the CMIP6 models. Skillful predictions are observed for lead times ranging from 1 to 4 months, depending on the model. Also, this study identifies a direct relationship between cold tongue bias and IOD prediction skills. Models that exhibit a more pronounced cold tongue bias tend to show weaker El Niño‐Southern Oscillation influences over the tropical Indian Ocean, which in turn leads to a reduction in IOD prediction skills. This study provides valuable insights into the factors driving the diversity in IOD predictions and highlights the potential for improving IOD forecasting skills.