Precipitation Characteristics in the Community Atmosphere Model and Their Dependence on Model Physics and Resolution
Precipitation Characteristics in the Community Atmosphere Model and Their Dependence on Model Physics and Resolution
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DOI：
10.1029/2018ms001536
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发表时间：
2019-08-01
影响因子：
6.8
通讯作者：
Dai, Aiguo
中科院分区：
文献类型：
--
作者：
Chen, Di;Dai, Aiguo
降水量(A)、频率(F)、强度(I)和持续时间(D)是降水的重要属性，但它们的估计对数据分辨率很敏感。本研究通过分析社区大气模式（CAM）第4版（CAM4）和第5版（CAM5）在类似于0.25至2.0度的不同网格尺寸下的模拟结果，探讨了这种分辨率依赖性以及不同模式物理特性的影响。结果表明，CAM4和CAM5在所有分辨率下都大大高估了F和D，而低估了I。这些偏差的部分原因是参数化（对流）降水过多，F和D高，而I低。对流和非对流降水的A、F、I和D对栅格尺寸减小的反应不同，导致总降水的F和D大幅减小，而I随着模式分辨率的增加而增加。这种分辨率依赖性来自于更大面积降水的概率增加（面积聚集效应，小于观测值）和模式物理在分辨率变化下的不同表现（模式调整效应），这大致增强了聚集诱导的依赖性。更细的网格尺寸不仅增加了分辨降水的强度，从而提高了CAM的整体降水强度，而且降低了区域聚集效应。因此，气候模式中长期存在的毛毛雨问题可以通过提高模式分辨率和修改模式物理来抑制参数化的对流降水和增强可分辨的非对流降水来缓解。
Precipitation amount (A), frequency (F), intensity (I), and duration (D) are important properties of precipitation, but their estimates are sensitive to data resolution. This study investigates this resolution dependence, and the influences of different model physics, by analyzing simulations by the Community Atmospheric Model (CAM) version 4 (CAM4) and version 5 (CAM5) with varying grid sizes from similar to 0.25 to 2.0 degrees. Results show that both CAM4 and CAM5 greatly overestimate F and D but underestimate I at all resolutions, despite realistic A. These biases partly result from too much parameterized (convective) precipitation with high F and D but low I. Different cloud microphysics schemes contribute to the precipitation differences between CAM4 and CAM5. The A, F, I, and D of convective and nonconvective precipitation react differently to grid-size decreases, leading to the large decreases in F and D but increases in the I for total precipitation as model resolution increases. This resolution dependence results from the increased probability of precipitation over a larger area (area aggregation effect, which is smaller than in observations) and the varying performance of model physics under changing resolution (model adjustment effect), which roughly enhances the aggregation-induced dependence. Finer grid sizes not only increase resolved precipitation, which has higher intensity and thus improves overall precipitation intensity in CAM, but also reduce the area aggregation effect. Thus, the long-standing drizzling problem in climate models may be mitigated by increasing model resolution and modifying model physics to suppress parameterized convective precipitation and enhance resolved nonconvective precipitation.