Multiple Linear Regression Analysis for Lake Ice and Lake Temperature Characteristics

Shaobai Gao, Heinz G. Stefan

Research output: Book/ReportOther report

Abstract

Lake ice and lake temperature characteristics are all dependent on climate and morphometric lake characteristics. Simulation results of water temperature and ice characteristics of ten large lakes in Minnesota (Gao and Stefan, 1997) were used for multiple linear regressions. Some equations were obtained for predicting lake ice and lake temperature characteristics from climate parameters, geographic location, lake surface area and depth. Some of these regression equations were employed to predict the ice~on dates, ice~off dates, ice cover duration, and maximum ice thicknesses for several freshwater lakes in the U.S. and Canada. The predictions were also compared with observed data, which were assembled by Adams and Stefan (1997). The results show that the predictions by regression equations were in good agreement with the observed data. The standard errors between observed and predicted ice-on dates, ice-off dates, ice cover duration, and maximum ice thicknesses range from 4 to 7 days, 6 to 10 days, 7 to 10 days, and 0.06 to 0.13 m, respectively. Because the ten lakes used to do the multiple linear regressions are all in Minnesota, and the lakes used to verify the regression equations are in the northern u.s. and one in Canada, the regression equations are considered only applicable to lakes in the northern U.s. and southern Canada.
Original languageEnglish (US)
StatePublished - Jun 1998

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