4.7 Article

Improving Climate Sensitivity of Deep Lakes within a Regional Climate Model and Its Impact on Simulated Climate

Journal

JOURNAL OF CLIMATE
Volume 27, Issue 8, Pages 2886-2911

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-13-00110.1

Keywords

Regional models; Model comparison; Hydrologic models; Air-sea interaction; Atmosphere-land interaction; Inland seas/lakes

Funding

  1. University of Michigan
  2. National Oceanic and Atmospheric Administration [NA07OAR4320006]

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Regional climate models aim to improve local climate simulations by resolving topography, vegetation, and land use at a finer resolution than global climate models. Lakes, particularly large and deep lakes, are local features that significantly alter regional climate. The Hostetler lake model, a version of which is currently used in the Community Land Model, performs poorly in deep lakes when coupled to the regional climate of the International Centre for Theoretical Physics (ICTP) Regional Climate Model, version 4 (RegCM4). Within the default RegCM4 model, the lake fails to properly stratify, stifling the model's ability to capture interannual variability in lake temperature and ice cover. Here, the authors improve modeled lake stratification and eddy diffusivity while correcting errors in the ice model. The resulting simulated lake shows improved stratification and interannual variability in lake ice and temperature. The lack of circulation and explicit mixing continues to stifle the model's ability to simulate lake mixing events and variability in timing of stratification and destratification. The changes to modeled lake conditions alter seasonal means in sea level pressure, temperature, and low-level winds in the entire model domain, highlighting the importance of lake model selection and improvement for coupled simulations. Interestingly, changes to winter and spring snow cover and albedo impact spring warming. Unsurprisingly, regional climate variability is not significantly altered by an increase in lake temperature variability.

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