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

doi:10.2172/1121262

GSTDTAP > 地球科学

DOI	10.2172/1121262
报告编号	DOE-Final-Report-Wu-3011
来源ID	OSTI ID: 1121262
	Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations
	Wu, Xiaoqing
	2014-02-25
出版年	2014
语种	英语
国家	美国
领域	地球科学
英文摘要	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.
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来源平台	US Department of Energy (DOE)
引用统计
文献类型	科技报告
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/6749
专题	地球科学
推荐引用方式 GB/T 7714	Wu, Xiaoqing. Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations,2014.