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GCE-Cloud Resolving Model

Coupling of Clouds and Precipitation to Land Surface

Clouds and precipitation are highly coupled with land surface on the timescales of days to months, which challenges current weather and climate prediction models. High-resolution cloud models, coupled with land surface models, can address this process explicitly. Recently, the GCE (Goddard Cumulus Ensemble) model is coupled with LIS (Land Information System), and model results are evaluated with observations.

 

ARM observed cloud amount
Modeled cloud amount with ARM surface fluxes as input

 

Modeled cloud amount with LIS surface fluxes as input

 

Zeng, X., W.-K. Tao, M. Zhang, C. Peters-Lidard, S. Lang, J. Simpson, S. Kumar, S. Xie, J. L. Eastman, C.-L. Shie and J. V. Geiger, 2007: Evaluating clouds in long-term cloud-resolving model simulations with observational data. J. Atmos. Sci. (in press).

 

Improving the Simulation of Convective Cloud Systems: Higher resolution and more realistic ice physics

The Goddard Cumulus Ensemble (GCE) model is a cloud-resolving model developed at NASA Goddard by Dr. W.-K. Tao to simulate convective cloud systems.

High resolution simulation of 23 Feb 1999 TRMM LBA case Image by J. Williams (Scientific Visualization Studio)

 

Improvements to the cloud microphysics results in less high-density ice and more realistic hydrometeor profiles for use in satellite retrievals

 

Higher horizontal model resolution leads to a more realistic, gradual transition from shallow to deep convection

 

 

Lang, S., W.-K. Tao, R. Cifelli, W. Olson, J. Halverson, S. Rutledge, and J. Simpson, 2007: Improving simulations of convective systems from TRMM LBA: Easterly and westerly regimes. J. Atmos. Sci., 64, 1141-1164.

Impact of Aerosol on Precipitation Processes

OBJECTIVE:

Use Goddard Cloud Ensemble Model with spectral-bin microphys to asses the impact of atmospheric aerosol concentration on deep convections.

Dirty (or high) CCN can either suppress or enhance precipitation processes, depending on environmental conditions and cloud dynamics/microphysics interactions; Clean (Low) CCN produces earlier rain onset and enhances surface rain only at initial stages;CCN variations can modulate surface rainfall characteristics, e.g. stratiform area and intensity.

 

 

Tao, W.-K., X. Li, A. Khain, T. Matsui, S. Lang, and J. Simpson, 2007: The role of atmospheric aerosol concentration on deep convective precipitation: Cloud-resolving model simulations. J. Geophys. Res., submitted.