| DOI: | 10.2172/1121262
|
| 报告号: | DOE-Final-Report-Wu-3011
|
| 报告题名: | Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations |
| 作者: | Wu, Xiaoqing
|
| 出版年: | 2014
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| 发表日期: | 2014-02-25
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| 国家: | 美国
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| 语种: | 英语
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| 中文主题词: | 对流
; 云
; 降水
; 高温
; 升温速率
|
| 主题词: | CONVECTION
; CLOUDS
; PRECIPITATION
; HEAT
; HEATING RATE
|
| 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. |
| URL: | http://www.osti.gov/scitech/servlets/purl/1121262
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| Citation statistics: |
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| 资源类型: | 研究报告
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/41600
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| Appears in Collections: | 过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响
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| 1121262.pdf（138KB） | 研究报告 | -- | 开放获取 | | View
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| Recommended Citation: | |
Wu, Xiaoqing. Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations. 2014-01-01.
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