Internal climate variability encompasses processes ranging from daily weather fluctuations to multidecadal interactions within the climate system. A large component of internal variability on sub-seasonal to multi-decadal time scales is associated with recurring patterns or “climate modes”. In this study we provide an openly available dataset of eight major climate modes: Eastern Pacific El Niño (EP-El Niño), Central Pacific El Niño (CP-El Niño), Interdecadal Pacific Oscillation (IPO), Indian Ocean Dipole (IOD), Subsurface Dipole Mode (SDM), Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), and Southern Annular Mode (SAM). These modes were derived from 23 Coupled Model Intercomparison Project 6 (CMIP6) models, each with over 500 years of simulation data, ensuring robust statistical insights into their spatial and temporal structures. The datasets were validated against observational data, revealing broad-scale consistency and highlighting biases in regional features and amplitudes. However, regional discrepancies, like exaggerated warming or cooling in specific areas, were found. Despite these limitations, the datasets provide an important resource for understanding climate variability, conducting detection and attribution studies, and improving climate projections. All datasets are publicly accessible (Mohapatra et al. 2025; <a href="https://doi.org/10.5281/zenodo.17337105" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.17337105</a>), supporting future research and policy development to address climate variability and its implications for climate change adaptation and mitigation.