Response of glacier modelling parameters to time, space, and model complexity: Examples from eastern slopes of...

Mountain glaciers are at risk of rapid retreat and require an accurate prediction of their melt and evolution. However, there is a great deal of hassle with mountain glacier melt modelling at a regional scale. Most advanced physical process-based models require an ample amount of high-resolution measurements, while widely-used empirical models suffer from parameter transferability. We developed a glacier melt, mass balance, and evolution modelling framework using three temperature index melt modelling approaches. We performed 24 model scenarios to examine the response of 19 empirical parameters to the effects of: (1) two time periods, for understanding how parameter response can vary with time period considered for the simulation; (2) two glaciers located at the eastern slopes of the Canadian Rocky Mountains, for understanding the effects of glaciers hydro-climate and geographic setting; and (3) two levels of complexity in the model structure including melt and mass balance models coupled with (complex) and without (simple) glacier evolution modules. The results showed that the best optimal melt parameter sets vary temporally and spatially for both simple and complex models, indicating that they are not transferable from one period to another and across glaciers. The variations of ice melt parameters are greater than the snowmelt parameters. The spatiotemporal variations of parameters are resulted from the geographical and local climatic settings and energy balance components, including albedo parameterization on the glacier surface, the altitudinal variations of the glaciers, and the slope and aspects to which glaciers are exposed. For all models, the most sensitive parameter is temperature Lapse rate (LR), but with increasing model complexity, the parameter responses vary depending on the melt model structure and input data. Our study provides important information for modelling glacier melt and evolution at a regional scale.