A statistical mass-balance model for reconstruction of LIA ice mass for glaciers in the European Alps

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Abstract
Stepwise linear regression models were calibrated against the measured mass balance of glaciers in the Austrian Alps for the prediction of specific annual net balance and summer balance from climatological and topographical input data. For estimation of winter mass balance, a simple ratio between the amount of winter precipitation and the measured winter balance was used. A ratio with a mean value of 2.0 and a standard deviation of 0.44 was derived from the sample of measured winter balances. Climate input data were taken from the HISTALP database which offers a homogenized data source that is outstanding in terms of its spatial and temporal coverage. Data from the Austrian glacier inventory were used as topographical input data. From the group of possible predictors summer air temperature, winter precipitation, summer snow precipitation and continentality (as defined from seasonal temperature variation) were selected as climatological driving forces in addition to lowest glacier elevation and area-weighted mean glacier elevation as topographical driving forces. Summer temperature explains 60% of the variance of summer mass balance and 39% of the variance of annual mass balance. Additional factors increase the explained variance by 22% for summer and 31% for annual net balance. The calibrated mass-balance model was used to reconstruct the mass balance of Hintereisferner and Vernagtferner back to 1800. Whereas the model performs well for Hintereisferner, it fails for some sub-periods for Vernagtferner due to the complicated flow dynamics of the glacier.