Water temperature estimates from multiple models were evaluated by comparing predictions to observed water temperatures. The performance metric of root-mean square error (in degrees C) is calculated for each lake and each model type, and matched values for predicted and observed temperatures are also included to support more specific error estimation methods (for example, calculating error in a particular month). Errors for the process-based model are compared to predictions as shared in <a href="https://www.sciencebase.gov/catalog/item/5e5d0bb9e4b01d50924f2b36">Model Predictions</a> data since these models were not calibrated. Errors for the process-guided deep learning models were calculated from validation folds and therefore differ from the comparisons to <a href="https://www.sciencebase.gov/catalog/item/5e5d0bb9e4b01d50924f2b36">Model Predictions</a> because those final models were trained on all available data.