Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations

Technical Report · Tue Feb 25 04:00:00 EST 2014

DOI:https://doi.org/10.2172/1121262· OSTI ID:1121262

Wu, Xiaoqing ^[1]

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1. Iowa State Univ., Ames, IA (United States). Dept. of Geological and Atmospheric Sciences; Iowa State University

The works supported by this ASR project lay the solid foundation for improving the parameterization of convection and clouds in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and ARM observations to produce thermodynamically and dynamically consistent multi-year cloud and radiative properties; improve the GCM simulations of convection, clouds and radiative heating rate and fluxes using the ARM observations and CRM simulations; and understand the seasonal and annual variation of cloud systems and their impacts on climate mean state and variability. We conducted multi-year simulations over the ARM SGP site using the CRM with multi-year ARM forcing data. The statistics of cloud and radiative properties from the long-term CRM simulations were compared and validated with the ARM measurements and value added products (VAP). We evaluated the multi-year climate simulations produced by the GCM with the modified convection scheme. We used multi-year ARM observations and CRM simulations to validate and further improve the trigger condition and revised closure assumption in NCAR GCM simulations that demonstrate the improvement of climate mean state and variability. We combined the improved convection scheme with the mosaic treatment of subgrid cloud distributions in the radiation scheme of the GCM. The mosaic treatment of cloud distributions has been implemented in the GCM with the original convection scheme and enables the use of more realistic cloud amounts as well as cloud water contents in producing net radiative fluxes closer to observations. A physics-based latent heat (LH) retrieval algorithm was developed by parameterizing the physical linkages of observed hydrometeor profiles of cloud and precipitation to the major processes related to the phase change of atmospheric water.

• Research Organization: Iowa State Univ., Ames, IA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: FG02-08ER64559
• OSTI ID: 1121262
• Report Number(s): DOE-Final-Report-Wu--3011
• Country of Publication: United States
• Language: English

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