The representation of stable boundary layers (SBLs) still challenges turbulence parameterizations implemented in current weather or climate models. The present work assesses whether these model deficiencies reflect calibration choices or intrinsic limits in currently‐used turbulence parameterization formulations and implementations. This question is addressed for the CNRM atmospheric model ARPEGE‐Climat 6.3 in a single‐column model/large‐eddy simulation (SCM/LES) comparison framework, using the history matching with iterative refocusing statistical approach. The GABLS4 case, which samples a nocturnal strong SBL observed at Dome C, Antarctic Plateau, is used. The standard calibration of the ARPEGE‐Climat 6.3 turbulence parameterization leads to a too deep SBL, a too high low‐level jet and misses the nocturnal wind rotation. This behavior is found for low and high vertical resolution model configurations. The statistical tool then proves that these model deficiencies reflect a poor parameterization calibration rather than intrinsic limits of the parameterization formulation itself. In particular, the role of two lower bounds that were heuristically introduced during the parameterization implementation to increase mixing in the free troposphere and to avoid runaway cooling in snow‐ or ice‐covered region is emphasized. The statistical tool identifies the space of the parameterization free parameters compatible with the LES reference, accounting for the various sources of uncertainty. This space is non‐empty, thus proving that the ARPEGE‐Climat 6.3 turbulence parameterization contains the required physics to capture the GABLS4 SBL. The SCM framework is also used to validate the statistical framework and a few guidelines for its use in parameterization development and calibration are discussed.

中文翻译：

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使用GCM湍流参数化对GABLS4强稳定边界层建模：参数灵敏度还是固有极限？

稳定边界层（SBL）的表示仍对当前天气或气候模型中实施的湍流参数化提出了挑战。本工作评估这些模型缺陷是否反映了当前使用的湍流参数化公式和实现中的校准选择或固有极限。在单列模型/大涡模拟（SCM / LES）比较框架中，CNRM大气模型ARPEGE-Climat 6.3使用历史记录和迭代重聚焦统计方法进行了解决。使用了GABLS4案例，该案例对在南极高原Dome C上观察到的夜间强SBL进行了采样。ARPEGE-Climat 6.3湍流参数化的标准校准会导致SBL太深，低空急流太高而错过了夜间风的旋转。对于低和高垂直分辨率模型配置，可以找到此行为。统计工具然后证明这些模型缺陷反映了较差的参数化校准，而不是参数化公式本身的固有限制。特别要强调的是，强调了在参数化实施过程中试探性引入的两个下限的作用，以增加自由对流层中的混合并避免积雪或冰雪覆盖地区的失控冷却。统计工具确定了与LES参考兼容的无参数化参数的空间，并考虑了各种不确定性来源。该空间是非空的，因此证明ARPEGE-Climat 6.3湍流参数化包含捕获GABLS4 SBL所需的物理原理。