Simulation and observation of ice formation (freeze-over) in a lake

Xing Fang, Christopher R. Ellis, Heinz G. Stefan

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

The date on which a lake freezes over has significance for the safety of winter lake recreation, for winterkill of fish and for the water quality of ice-covered lakes. This paper describes the development and application of a new algorithm to predict the date of ice formation on a lake. It uses a full heat budget equation to estimate surface cooling, quantifies the effect of forced convective (wind) mixing and includes the latent heat removed by ice formation. The algorithm has a fine spatial resolution near the water surface where temperature gradients before freeze-over are the greatest. Detailed field measurements of water temperatures and local weather data leading to freeze-over of Ryan Lake, Minnesota, are reported and used to verify the algorithm development. Inverse temperature stratification occurs in the near-surface water several hours before ice formation. The new algorithm is combined with a year-round temperature model and tested against observations in Ryan Lake and eight other Minnesota lakes for multiple (9-36) years. The difference between the simulated and observed permanent ice formation dates is less than 6 days for all lakes studied.

Original languageEnglish (US)
Pages (from-to)129-145
Number of pages17
JournalCold Regions Science and Technology
Volume24
Issue number2
DOIs
StatePublished - May 1996

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