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荆现文, 张华. McICA云—辐射方案在国家气候中心全球气候模式中的应用与评估[J]. 大气科学, 2012, 36(5): 945-958. DOI: 10.3878/j.issn.1006-9895.2012.11155
引用本文: 荆现文, 张华. McICA云—辐射方案在国家气候中心全球气候模式中的应用与评估[J]. 大气科学, 2012, 36(5): 945-958. DOI: 10.3878/j.issn.1006-9895.2012.11155
JING Xianwen, ZHANG Hua. Application and Evaluation of McICA Cloud-Radiation Framework in the AGCM of the National Climate Center[J]. Chinese Journal of Atmospheric Sciences, 2012, 36(5): 945-958. DOI: 10.3878/j.issn.1006-9895.2012.11155
Citation: JING Xianwen, ZHANG Hua. Application and Evaluation of McICA Cloud-Radiation Framework in the AGCM of the National Climate Center[J]. Chinese Journal of Atmospheric Sciences, 2012, 36(5): 945-958. DOI: 10.3878/j.issn.1006-9895.2012.11155

McICA云—辐射方案在国家气候中心全球气候模式中的应用与评估

Application and Evaluation of McICA Cloud-Radiation Framework in the AGCM of the National Climate Center

  • 摘要: 本文将一种新的、可以灵活给出云的次网格结构的蒙特卡洛独立气柱近似 (McICA) 云—辐射方案应用于国家气候中心全球气候模式BCC_AGCM 2.0.1中;由于此方案会引入一定的随机误差,本文对随机误差的特征和对所模拟的气候场的影响进行了分析和评估.结果表明,McICA随机误差引起的模拟扰动很小,随机误差对所模拟的各种气候变量影响也很小,全球平均值与作为参考的精确独立气柱近似 (ICA) 计算的差别都在0.01%量级,模拟结果的纬向分布、垂直分布和典型区域内的分布等气候特征都基本上与ICA一致.因此,在国家气候中心全球气候模式BCC_AGCM 2.0.1中应用McICA云—辐射方案具有较高的可信度,模拟性能的提升仍然主要取决于模式物理过程、动力框架等方面,而不受随机误差的影响.考虑到McICA方案下云和辐射过程是各自独立的,云的结构调整和辐射模式的改进都更为简便,为模式在未来的进一步改进提供了很大便利和发展空间.

     

    Abstract: McICA, a new cloud-radiation framework that can easily define the sub-grid cloud structure, is incorporated into the National Climate Center’s Global Climate Model, called BCC_AGCM 2.0.1. As random noise is inevitably introduced by the scheme, it is important to evaluate and estimate how the noise behaves and whether the modeled climate will be degraded by the noise. Results show a minor perturbation of modeled climate within McICA samples, and the modeled climate fields are impacted very little by McICA noise, with the global mean bias at the order of 0.01% compared to the reference ICA (independent column approximation) results. Good agreement between McICA and ICA results is also illustrated from zonal mean, vertical, and domain distributions of variables. So, it is highly reliable to use the McICA cloud-radiation scheme in BCC_AGCM 2.0.1 to do climate researches. Because random noises have little impact on the modeling, the modeling ability of BCC_AGCM 2.0.1 still depends on its physical parameterization and dynamic framework improvements. Considering that cloud and radiation processes are separately coded in the new scheme, it is now very easy to make improvement and progress in both cloud and radiation codes themselves, which facilitates and allows more space for the further development of the model.

     

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