We present version 2 of the Berkeley Earth Surface Temperature dataset, a global observational temperature record that now features enhanced spatial resolution (0.25° × 0.25°) and a new regression Kriging framework that incorporates physically informed predictive fields. The land analysis uses 58,311 weather stations, updated to reflect the latest source archives, and includes separate reconstructions for TAVG (1750–present), TMAX, and TMIN (both 1850–present). Sea surface temperatures are derived from HadSST4, with spatial detail improved using predictors from the ORAS5 ocean reanalysis. The land and ocean fields are merged into a unified product with a refined coastal blending method. A new uncertainty ensemble is introduced to quantify reconstruction and coverage uncertainty, enabling propagation of errors into derived metrics. The resulting Berkeley Earth Surface Temperature – High-Resolution (BEST-HR) dataset offers a globally complete, monthly resolved temperature product suitable for applications ranging from global trend analysis to regional climate impact assessments. The current BEST-HR dataset described in this paper has been archived at Zenodo DOI: <a href="https://doi.org/10.5281/zenodo.20428381" target="_blank" rel="noopener">10.5281/zenodo.20428381</a> alongside the merged weather station data used to generate it DOI: <a href="https://doi.org/10.5281/zenodo.20427092" target="_blank" rel="noopener">10.5281/zenodo.20427092</a>. Monthly updates to these datasets will be provided primarily through the Berkeley Earth website.