Corrected surface water temperatures using Gaussian Regression Process and process-based hydrodynamic models

This dataset provides corrected predictions of surface water temperature of Lake Harsha (Ohio, US) for year 2019. Corrected predictions are provided by a hybrid modeling approach that combines (a) a process-based hydrodynamic model of the lake and (b) a Gaussian Process Regression model that predicts errors of the process-based models. The Gaussian Process Regression model was trained on simulation errors provided by the process-based model during the period 2015-2018.

Parameter: Surface water temperature (^oC )

Spatial resolution	Temporal resolution
60 m	Daily

2015 – 2019