<p>This study investigated the seasonal variation of the optimal initial perturbations responsible for the fastest growth of the prediction error of the tropical Indian Ocean (IO) sea surface temperature (SST) and wind components using the climate-relevant singular vector method. With a lead time of 6 months, the spatial patterns of the optimal initial perturbations and the corresponding final patterns exhibited a significant seasonal variation. Furthermore, the growth rate of the prediction perturbation, as measured by the leading singular values, also displayed seasonal variations, with higher values for the initial month of the boreal spring and autumn and lower values for the initial months of the boreal winter. For different initial seasons, different regions in the IO were responsible for the fastest growth of prediction errors, which can be attributed to the different dynamical processes in these regions. For the initial month of April, the development of the optimal initial perturbations was primarily influenced by linear vertical upwelling terms, including the wind-induced Ekman feedback and thermocline feedback with the surface latent heat flux playing a secondary role. For the initial month of October, the perturbation in the southern IO grew the fastest and was mainly controlled by the zonal linear advection and surface heat flux. Furthermore, this investigation emphasized the critical role played by the tropical Pacific Ocean in the prediction error growth of the tropical IO, evidencing the important impact of the tropical Pacific Ocean on the predictability of the tropical IO SST anomalies.</p>