Toward low‐cloud‐permitting cloud superparameterization with explicit boundary layer turbulence

Toward low‐cloud‐permitting cloud superparameterization with explicit boundary layer turbulence
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实现具有显式边界层湍流的低云允许云超参数化

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发表时间：
2017
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通讯作者：
M. Khairoutdinov
M. Khairoutdinov
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文献类型：
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作者：
H. Parishani;M. Pritchard;C. Bretherton;M. Wyant;M. Khairoutdinov

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边界层（BL）云表示的系统偏差是气候预测中不确定性的主要来源。超参数化（SP）的一个变体被称为“超参数化”（UP），其中云分辨模式（CRM）的网格间距足够细（250 × 20 m），可以在一个能够进行多年模拟的全球气候模式中明确地捕捉到BL湍流、相关云和卷吸。UP在社区大气模式中使用2°分辨率（14，000个嵌入式CRM）和一阶矩微物理学实现。通过使用小域和平均状态加速，UP在今天的计算上是可行的，并且有希望用于兆级计算机。短持续时间的全球UP后报与SP和卫星观测的大气层顶辐射和云垂直结构进行了比较。最令人鼓舞的改进是更深的BL和更真实的副热带层积云（Sc）的垂直结构，由于更强的垂直涡动，促进夹带。从90天的积分结果显示气候误差是竞争力与SP，海上Sc液态水的日周期有显着改善。当前UP实施的持续关注包括近海岸Sc的暗淡偏差，这在SP中也不太突出，以及热带大陆深对流区的明亮偏差。然而，UP使全球涡动允许模拟成为一种可行和有趣的替代方案，以研究BL云气候和云气溶胶反馈的常规参数化GCM或SP-GCM与湍流参数化。
Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud‐resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (∼14,000 embedded CRMs) with one‐moment microphysics. By using a small domain and mean‐state acceleration, UP is computationally feasible today and promising for exascale computers. Short‐duration global UP hindcasts are compared with SP and satellite observations of top‐of‐atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near‐coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy‐permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP‐GCMs with turbulence parameterizations for studying BL cloud‐climate and cloud‐aerosol feedback.