Shallow Cumulus in WRF Parameterizations Evaluated against LASSO Large-Eddy Simulations
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Shallow Cumulus in WRF Parameterizations Evaluated against LASSO Large-Eddy Simulations
  • Published Date:

    2018

  • Source:
    Monthly Weather Review, 146(12), 4303-4322.
Filetype[PDF-2.37 MB]


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  • Personal Author:
  • Description:
    Representation of shallow cumulus is a challenge for mesoscale numerical weather prediction models. These cloud fields have important effects on temperature, solar irradiance, convective initiation, and pollutant transport, among other processes. Recent improvements to physics schemes available in the Weather Research and Forecasting (WRF) Model aim to improve representation of shallow cumulus, in particular over land. The DOE LES ARM Symbiotic Simulation and Observation Workflow (LASSO) project provides several cases that we use here to test the new physics improvements. The LASSO cases use multiple large-scale forcings to drive large-eddy simulations (LES), and the LES output is easily compared to output from WRF single-column simulations driven with the same initial conditions and forcings. The new Mellor-Yamada-Nakanishi-Niino (MYNN) eddy diffusivity mass-flux (EDMF) boundary layer and shallow cloud scheme produces clouds with timing, liquid water path (LWP), and cloud fraction that agree well with LES over a wide range of those variables. Here we examine those variables and test the scheme's sensitivity to perturbations of a few key parameters. We also discuss the challenges and uncertainties of single-column tests. The older, simpler total energy mass-flux (TEMF) scheme is included for comparison, and its tuning is improved. This is the first published use of the LASSO cases for parameterization development, and the first published study to use such a large number of cases with varying cloud amount. This is also the first study to use a more precise combined infrared and microwave retrieval of LWP to evaluate modeled clouds.
  • DOI:
    http://dx.doi.org/10.1175/mwr-d-18-0115.1
  • Document Type:
    Journal Article
  • Collection(s):
    NOAA Cooperative Institutes
    Office of Oceanic and Atmospheric Research (OAR)
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