Chlorophyll is a crucial climate variable and remotely sensed satellite chlorophyll estimates are essential to understanding large-scale biological processes. Current ocean color chlorophyll algorithms, however, are less accurate in optically complex inland and coastal waters. As a result, remote sensing algorithms are not able to fully resolve chlorophyll concentrations in optically complex coastal regions leading to greater uncertainty in regions of high productivity. This can further lead to errors in regional biogeochemical models and hinder fisheries and ecosystem monitoring and research. In order to develop more accurate coastal chlorophyll retrievals, <em>in situ</em> chlorophyll measurements are needed for algorithm calibration and validation. Here the methods used to develop a single cohesive standardized <em>in situ</em> chlorophyll, chromophoric dissolved organic matter (CDOM), and remote sensing reflectance (R<sub>rs</sub>) dataset from multiple public data repositories are described. The final product is a North American dataset of quality controlled chlorophyll measurements and associated metadata. The dataset includes more than 700,000 chlorophyll values with coincidental CDOM and R<sub>rs</sub> data when available. Methodological flags such as chlorophyll measurement method, triplicate samples, and <em>in vitro</em>/<em>in vivo</em> flags distinguish between data collection methods. The dataset includes regularly formatted metadata across all sources to ensure due credit to the programs collecting the samples. The resulting dataset is then matched to satellite chlorophyll data to examine the difference in chlorophyll retrievals across multiple water types and regions. This dataset is currently being used to validate a new coastal chlorophyll algorithm in development and to assess chlorophyll retrievals. All methods and data are publicly available at <a href="https://doi.org/10.5281/zenodo.20140178" target="_blank" rel="noopener">doi.org/10.5281/zenodo.20140178</a> (Milton et al., 2026).