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Representation of Lake–Atmosphere Interactions and Lake-Effect Snowfall in the Laurentian Great Lakes Basin among HighResMIP Global Climate Models

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  • 1 aNelson Institute Center for Climatic Research, University of Wisconsin–Madison, Madison, Wisconsin
  • | 2 bGreat Lakes Integrated Sciences and Assessments, University of Michigan, Ann Arbor, Michigan
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Abstract

Credible modeling, tools, and guidance, regarding the changing Laurentian Great Lakes and the climatic impacts, are needed by local decision-makers to inform their management and planning. The present study addresses this need through a model evaluation study of the representation of lake–atmosphere interactions and resulting lake-effect snowfall in the Great Lakes region. Analysis focuses on an extensive ensemble of 74 historical simulations generated by 23 high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP). The model assessment addresses the modeling treatment of the Great Lakes, the spatial distribution and seasonality of climatological snowfall, the seasonal cycle of lake-surface temperatures and overlake turbulent fluxes, and the lake-effect ratio between upwind and downwind precipitation. A deeper understanding of model performance and biases is achieved by partitioning results between HighResMIP GCMs that are 1) coupled to 1D lake models versus GCMs that exclude lake models, 2) between prescribed-ocean model configurations versus fully coupled configurations, and 3) between deep Lake Superior versus relatively shallow Lake Erie. While the HighResMIP GCMs represent the Great Lakes by a spectrum of approaches that include land grid cells, ocean grid cells (with lake surface temperature and ice cover boundary conditions provided by the Met Office Hadley Center Sea Ice and Sea Surface Temperature Dataset), and 1D lake models, the current investigation demonstrates that none of these rudimentary approaches adequately represent the complex nature of seasonal lake temperature and ice cover evolution and its impact on lake–atmosphere interactions and lake-effect precipitation in the Great Lakes region.

Significance Statement

The purpose of this study is to evaluate the capability of high-resolution global climate models to simulate lake–atmosphere interactions and lake-effect snowfall in the Great Lakes region, given the critical influence of the lakes on regional climate and vast societal and environmental impacts of lake-effect snowfall. It is determined that the models inadequately represent lake temperatures and ice cover, often leading to insufficient annual snowfall in the lake-effect zones. More advanced, three-dimensional lake models need to be coupled to climate models to support greater credibility in regional lake and climate simulations and future climate projections.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding Author: Michael Notaro, mnotaro@wisc.edu

Abstract

Credible modeling, tools, and guidance, regarding the changing Laurentian Great Lakes and the climatic impacts, are needed by local decision-makers to inform their management and planning. The present study addresses this need through a model evaluation study of the representation of lake–atmosphere interactions and resulting lake-effect snowfall in the Great Lakes region. Analysis focuses on an extensive ensemble of 74 historical simulations generated by 23 high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP). The model assessment addresses the modeling treatment of the Great Lakes, the spatial distribution and seasonality of climatological snowfall, the seasonal cycle of lake-surface temperatures and overlake turbulent fluxes, and the lake-effect ratio between upwind and downwind precipitation. A deeper understanding of model performance and biases is achieved by partitioning results between HighResMIP GCMs that are 1) coupled to 1D lake models versus GCMs that exclude lake models, 2) between prescribed-ocean model configurations versus fully coupled configurations, and 3) between deep Lake Superior versus relatively shallow Lake Erie. While the HighResMIP GCMs represent the Great Lakes by a spectrum of approaches that include land grid cells, ocean grid cells (with lake surface temperature and ice cover boundary conditions provided by the Met Office Hadley Center Sea Ice and Sea Surface Temperature Dataset), and 1D lake models, the current investigation demonstrates that none of these rudimentary approaches adequately represent the complex nature of seasonal lake temperature and ice cover evolution and its impact on lake–atmosphere interactions and lake-effect precipitation in the Great Lakes region.

Significance Statement

The purpose of this study is to evaluate the capability of high-resolution global climate models to simulate lake–atmosphere interactions and lake-effect snowfall in the Great Lakes region, given the critical influence of the lakes on regional climate and vast societal and environmental impacts of lake-effect snowfall. It is determined that the models inadequately represent lake temperatures and ice cover, often leading to insufficient annual snowfall in the lake-effect zones. More advanced, three-dimensional lake models need to be coupled to climate models to support greater credibility in regional lake and climate simulations and future climate projections.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding Author: Michael Notaro, mnotaro@wisc.edu

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