Integration of remote-sensing data with WRF to improve lake-effect precipitation simulations over the Great Lakes region

Authors

  • Lin Zhao,

    1. Department of Watershed Sciences, Utah State University, Logan, Utah, USA
    2. Department of Plants, Soils, and Climate, Utah State University, Logan, Utah, USA
    Search for more papers by this author
  • Jiming Jin,

    Corresponding author
    1. Department of Watershed Sciences, Utah State University, Logan, Utah, USA
    2. Department of Plants, Soils, and Climate, Utah State University, Logan, Utah, USA
    • Corresponding Author: J. Jin, Department of Watershed Sciences, Utah State University, 5210 Old Main Hill, Logan, UT 84341, USA. (jiming.jin@usu.edu)

    Search for more papers by this author
  • Shih-Yu Wang,

    1. Department of Plants, Soils, and Climate, Utah State University, Logan, Utah, USA
    2. Utah Climate Center, Utah State University, Logan, Utah, USA
    Search for more papers by this author
  • Michael B. Ek

    1. Environmental Modeling Center, National Centers for Environmental Prediction, National Weather Service, National Oceanic and Atmospheric Administration, Camp Springs, Maryland, USA
    Search for more papers by this author

Abstract

[1] In this study, remotely sensed lake surface temperature (LST) and lake ice cover (LIC) were integrated into the Advanced Research Weather Research and Forecasting (WRF) model version 3.2 to evaluate the simulation of lake-effect precipitation over the Great Lakes region. The LST was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), while the LIC was obtained from the National Ice Center (NIC). WRF simulations for the Great Lakes region were performed at 10 km grid spacing for the cold season from November 2003 through February 2008. Initial and lateral boundary conditions were provided by the North American Regional Reanalysis (NARR). Experiments were carried out to compare winter precipitation simulations with and without the integration of the satellite data. Results show that integration with MODIS LST and NIC LIC significantly improves simulation of lake-effect precipitation over the Great Lakes region by reduced latent heat and sensible heat fluxes. A composite analysis of lake-effect precipitation events further reveals that more accurately depicted low-level stability and vertical moisture transport forced by the observation-based LST and LIC contribute to the improved simulation of lake-effect precipitation.

Ancillary