Satellite remote sensing is critical for monitoring global inland water quality, yet the complexity and volume of raw data archives often hinder their widespread application. Here, we present a standardized, accessible dataset of <em>concurrent</em> daily water quality statistics for 5,551 lakes worldwide from 2002 to 2022. Derived from the European Space Agency’s Lakes Climate Change Initiative (ESA Lakes_cci), this dataset provides lake-wide statistics—including estimates of mean, ranges and extremes, and spatial coverage—for three relevant water quality parameters: chlorophyll-<em>a</em> (Chl-<em>a</em>), lake surface water temperature (LSWT), and turbidity. Distinctively, these records are harmonized to retain only days on which all three parameters are simultaneously valid, facilitating robust multivariate analysis. The data were extracted using HydroLAKES polygon boundaries and introduce a novel multi-tiered quality assurance flagging scheme to identify spatial inhomogeneities and temporal anomalies, providing a new analytical dimension. By transforming massive, multidimensional NetCDF files into easily-accessible tabular formats, this resource eliminates steep computational barriers, supporting researchers and other end users in conducting macro-scale limnological studies, training machine learning models, and assessing climate change impacts on lake water quality and aquatic ecosystems. The dataset and developed codes are openly accessible at <a href="https://doi.org/10.5281/zenodo.20347115" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.20347115</a> (Shahvaran <em>et al.</em>, 2026)