Subgrid-scale Microphysics in UCLA-LaRC SCM with IP-

HOC

Anning Cheng1 and Kuan-Man Xu 2

1. AS&M, Inc.

2. Science Directorate, NASA Langley Research Center

Outline

• Intermediately prognostic (IP) higher-order closure (HOC) model

• Results form UCLA-LaRC SCM, 3D-SAM LES and 2D-SAM LES with IP-HOC

• Subgrid-scale (SGS) microphysics scheme in UCLA-LaRC SCM

• Effects of the SGS microphysics scheme

2D-SAM LES (with IP-HOC) Configuration

• Domain size is 250 km• Horizontal grid size is 200 m• The 2D LES is aligned in either x

direction (Exp. U) or y direction (Exp. V)

• The rest of configuration is the same as in the 3D LES

Subgrid-scale Autoconversion

• The original Kessler’s autoconversion rate is simply proportional to the grid-mean cloud water mixing ratio, subject to a threshold value

• An integration of the Kessler’s formula multiplied by the subgrid-scale Double-Gaussian pdf found that subgrid-scale autoconversion is a function of mean, variance, and skewness of liquid water potential temperature and total water mixing ratio

What is the effect of including the new subgrid-scale autoconversion formulation?

Rain Water Collection Rate and Skewness of W

Summary and Discussion

• UCLA-LaRC SCM produces reasonable results for the RICO case although improvement is still needed

• Subgrid-scale microphysics is essential for the IP-HOC model to produce precipitation

• The cloud amount and cloud top height decreased drastically when subgrid-scale autoconversion rate was used

• Compared to 3D LES, the autoconversion rate is too high, but the collection rate is reasonable in the SCM simulation athough their formula are very simple

Thank You!