Air2water model with nine parameters for lake surface temperature assessment

The air2water model is a physically-based model in which major physical processes are parameterized. It allows to predict the surface lake temperature based solely on the time series of the air temperature. Due to its simplicity and very limited data requirements, it has found numerous applications around the globe. The air2water model defines the normalized depth of the well-mixed surface layer using a fixed parameter. This parameter is a threshold value that is set to 4 degrees C - the temperature of water with maximum density - for dimictic lakes, and to the minimum or to the maximum water temperature for warm or cold monomictic lakes, respectively. In this paper we propose to calibrate the threshold value as the ninth parameter of the model, instead of setting it fixed. We test the proposed approach on a set of 30-years long daily data from 22 lakes located in the lowland part of Poland and 25-years long daily data from the two Great Lakes - Huron and Eire. The proposed modification is very simple and improves the performance of the model, especially for winter-spring season, for the vast majority of lakes not only for the calibration, but also for the independent 8-10 years long validation data.

Automated summary

The study proposes a simple modification to improve the performance of the air2water model by calibrating a threshold value parameter and tests it on multiple lake datasets.