Measuring the sensitivity of southern Wisconsin lake ice to climate variations and lake depth using a numerical model

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Abstract
The sensitivity of lake ice phenology to climatic variations is tested using a numerical lake‐ice model (LIMNOS). The model simulates the evolution of ice and snow cover by time‐integrating equations of vertical heat conduction through ice and snow. The required input variables are mean lake depth, air temperature and moisture, wind speed, solar radiation, snowfall, and cloudiness.The model simulates the ice‐on and ice‐off dates of three southern Wisconsin lakes to within 1 week of their historical averages, despite large differences in mean depth. Using hourly meteorological data from 1961–1990 as inputs, LIMNOS simulates the annual ice‐on and ice‐off dates of Lake Mendota with a median absolute error of only 2 d and 4 d, respectively.The atmospheric variables are altered to determine the sensitivity of Lake Mendota ice phenology to climate change. The simulated ice‐off date shows stronger sensitivity than the ice‐on date to air temperature changes, and the sensitivity of both dates is greater for climatic warmings than coolings. Increased snowfall causes a monotonic delay in the breakup date, whereas decreased snowfall nonlinearly hastens ice decay.

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