Editorial Type:
Article
Article Type:
Research Article

Mesoscale Boundary Layer and Heat Flux Variations over Pack Ice–Covered Lake Erie

Mathieu R. Gerbush Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

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David A. R. Kristovich Center for Atmospheric Science, Illinois State Water Survey, Illinois Department of Natural Resources, Champaign, Illinois

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Neil F. Laird Department of Geoscience, Hobart and William Smith Colleges, Geneva, New York

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Print Publication:
01 Feb 2008
DOI:
https://doi.org/10.1175/2007JAMC1479.1
Page(s):
668–682
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Abstract

The development of extensive pack ice fields on the Great Lakes significantly influences lake-effect storms and local airmass modification, as well as the regional hydrologic cycle and lake water levels. The evolution of the ice fields and their impacts on the atmospheric boundary layer complicates weather forecasters’ ability to accurately predict late-season lake-effect snows. The Great Lakes Ice Cover–Atmospheric Flux (GLICAF) experiment was conducted over Lake Erie during February 2004 to investigate the surface–atmosphere exchanges that occur over midlatitude ice-covered lakes. GLICAF observations taken by the University of Wyoming King Air on 26 February 2004 show a strong mesoscale thermal link between the lake surface and the overlying atmospheric boundary layer. Mesoscale atmospheric variations that developed over the lake in turn influenced heat exchanges with the surface. Boundary layer sensible and latent heat fluxes exhibited different relationships to variations in surface pack ice concentration. Turbulent sensible heat fluxes decreased nonlinearly with increases in underlying lake-surface ice concentration such that the largest decreases occurred when ice concentrations were greater than 70%. Latent heat fluxes tended to decrease linearly with increasing ice concentration and had a reduced correlation. Most current operational numerical weather prediction models use simple algorithms to represent the influence of heterogeneous ice cover on heat and moisture fluxes. The GLICAF findings from 26 February 2004 suggest that some currently used and planned approaches in numerical weather prediction models may significantly underestimate sensible heat fluxes in regions of high-concentration ice cover, leading to underpredictions of the local modification of air masses and lake-effect snows.

* Current affiliation: Office of the New Jersey State Climatologist, Rutgers, The State University of New Jersey, Piscataway, New Jersey

Corresponding author address: Dr. David A. R. Kristovich, 2204 Griffith Dr., Champaign, IL 61820-7495. Email: dkristo@uiuc.edu

Abstract

The development of extensive pack ice fields on the Great Lakes significantly influences lake-effect storms and local airmass modification, as well as the regional hydrologic cycle and lake water levels. The evolution of the ice fields and their impacts on the atmospheric boundary layer complicates weather forecasters’ ability to accurately predict late-season lake-effect snows. The Great Lakes Ice Cover–Atmospheric Flux (GLICAF) experiment was conducted over Lake Erie during February 2004 to investigate the surface–atmosphere exchanges that occur over midlatitude ice-covered lakes. GLICAF observations taken by the University of Wyoming King Air on 26 February 2004 show a strong mesoscale thermal link between the lake surface and the overlying atmospheric boundary layer. Mesoscale atmospheric variations that developed over the lake in turn influenced heat exchanges with the surface. Boundary layer sensible and latent heat fluxes exhibited different relationships to variations in surface pack ice concentration. Turbulent sensible heat fluxes decreased nonlinearly with increases in underlying lake-surface ice concentration such that the largest decreases occurred when ice concentrations were greater than 70%. Latent heat fluxes tended to decrease linearly with increasing ice concentration and had a reduced correlation. Most current operational numerical weather prediction models use simple algorithms to represent the influence of heterogeneous ice cover on heat and moisture fluxes. The GLICAF findings from 26 February 2004 suggest that some currently used and planned approaches in numerical weather prediction models may significantly underestimate sensible heat fluxes in regions of high-concentration ice cover, leading to underpredictions of the local modification of air masses and lake-effect snows.

* Current affiliation: Office of the New Jersey State Climatologist, Rutgers, The State University of New Jersey, Piscataway, New Jersey

Corresponding author address: Dr. David A. R. Kristovich, 2204 Griffith Dr., Champaign, IL 61820-7495. Email: dkristo@uiuc.edu

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Journal of Applied Meteorology and Climatology

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