Impact of Turbulent Mixing in the Stratocumulus-Topped Boundary Layer on Numerical Weather Prediction

  • Eun-Hee LeeEmail author
  • Eunjung Lee
  • Raeseol Park
  • Young Cheol Kwon
  • Song-You Hong


The impact of enhanced turbulent mixing induced by radiative cooling at the top of the stratocumulus-topped boundary layer (STBL) on numerical weather prediction is examined. An additional term involving top-down turbulent mixing via in-cloud radiative cooling is applied to the Yonsei University (YSU) planetary boundary layer (PBL) parameterization scheme using a top-down diffusivity profile and cloud-top entrainment. The modified scheme is evaluated in an advection fog case over the Yellow Sea of Korea using the Weather Research and Forecasting (WRF) model and in global medium-range forecasts using the Global/Regional Integrated Model system (GRIMs). In the fog case simulation, consideration of the additional top-down mixing parameterization in the YSU PBL simulates less formation and more rapid dispersion of the fog. As a result, the modified scheme simulates a drier and warmer boundary layer and a moister and cooler layer above the PBL. The modified algorithm also improves surface temperature prediction over the Yellow Sea accompanying early dissipation of the fog. In the global medium-range forecast experiment, the modified scheme simulates overall enhanced PBL mixing over the STBL in the tropics and subtropical ocean, showing drier and warmer regions near the surface and moister and cooler regions above the PBL, resulting in prediction of reduced low level cloud amount and increased downward shortwave radiation at the surface. The modified scheme appears to improve systematic bias in temperature and humidity in the lower troposphere compared to the control simulation.

Key words

Fog dissipation numerical weather prediction planetary boundary layer parameterization stratocumulus-topped boundary layer 


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Copyright information

© Korean Meteorological Society and Springer Nature B.V. 2018

Authors and Affiliations

  • Eun-Hee Lee
    • 1
    • 2
    Email author
  • Eunjung Lee
    • 1
  • Raeseol Park
    • 1
  • Young Cheol Kwon
    • 1
  • Song-You Hong
    • 1
  1. 1.Korea Institute of Atmospheric Prediction Systems (KIAPS)SeoulKorea
  2. 2.Korea Institute of Atmospheric Prediction SystemsSeoulKorea

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