Modeling the duration of intermittent ice cover on a lake for climate‐change studies

Abstract

A generalized empirical approach to the problem of the prediction of intermittent lake ice cover for climate‐change studies is presented and applied to historical ice data from Muggelsee, a shallow lake in northern Germany that experiences either no ice cover, intermittent ice cover, or continuous ice cover, depending on the severity of the winter. The approach presented allows the total duration of ice cover in any winter to be estimated in terms of an air‐temperature probability function. Advantages over traditional empirical methods based on the mean air temperature during a fixed period or on the computed number of negative degree‐days are: (1) it is valid for both continuous and intermittent ice cover; (2) it is not necessary to specify a fixed time period for integration in advance; (3) the results emerge in time units, allowing them to be directly compared with the measured duration of ice cover without prior calibration; and (4) it is based on statistical properties of the ambient air temperature that are routinely forecast by climate models, making it easy to apply predictively. Regional climate model forecasts for northern Germany imply that for Muggelsee, the percentage of ice‐free winters will increase from ≪2% to over 60% by the end of the current century.