GREAT LAKES ICE THICKNESS PREDICTION

Weekly ice thickness data, collected from 24 bay, harbor, and river sites on the Great Lakes, were correlated with freezing degree-day accumulations to develop regression equations between ice thickness and freezing degree-days. The data base at ice measurement sites was 3 to 8 winters in length. The standard error of estimate varied for individual regression equations and averaged between 7 and 8 cm for five forms of regression equations. Because the regression equations are empirical, the range of input data used to predict ice thickness should be limited to the range of values used in the derivation.

• Corporate Authors:

  International Assoc for Great Lakes Research

  1300 Elmwood Avenue
  Buffalo, NY  United States  14222
• Authors:
  • Assel, R A
• Publication Date: 1976

Media Info

• Features: References;
• Pagination: p. 248-255
• Serial:
  • Journal of Great Lakes Research
  • Volume: 2
  • Issue Number: 2
  • Publisher: State University College

Subject/Index Terms

• TRT Terms: Ice; Ice formations; Lakes; Mathematical models; Measurement; Navigation; Seasons; Statistical analysis; Thickness
• Geographic Terms: Great Lakes
• Old TRIS Terms: Ice thickness measurement
• Subject Areas: Data and Information Technology; Marine Transportation;

Filing Info

• Accession Number: 00170122
• Record Type: Publication
• Source Agency: Engineering Index
• Files: TRIS
• Created Date: Mar 7 1978 12:00AM