Oertel Annika, Schemm Sebastian
Institute for Atmospheric and Climate Science ETH Zürich Zürich Switzerland.
Present address: A. Oertel, Institute for Meteorology and Climate Research Karlsruhe Institute of Technology (KIT) Karlsruhe Germany.
Q J R Meteorol Soc. 2021 Apr;147(736):1752-1766. doi: 10.1002/qj.3992. Epub 2021 Feb 22.
The complex coupling between the large-scale atmospheric circulation, which is explicitly resolved in modern numerical weather and climate models, and cloud-related diabatic processes, which are parameterized, is an important source of error in weather predictions and climate projections. To quantify the interactions between clouds and the large-scale circulation, a method is employed that attributes a far- and near-field circulation to the cloud system. The method reconstructs the cloud-induced flow based on estimates of vorticity and divergence over a limited domain and does not require the definition of a background flow. It is subsequently applied to 12- and 2-km simulations of convective clouds, which form within the large-scale cloud band ahead of the upper-level jet associated with an extratropical cyclone over the North Atlantic. The cloud-induced circulation is directed against the jet, reaches up to 10 m·s, and compares well between both simulations. The flow direction is in agreement with what can be expected from a vorticity dipole that forms in the vicinity of the clouds. Hence, in the presence of embedded convection, the wind speed does not steadily decrease away from the jet, as it does in cloud-free regions, but exhibits a pronounced negative anomaly, which can now be explained by the cloud-induced circulation. Furthermore, the direction of the reconstructed circulation suggests that the cloud induces a flow that counteracts its advection by the jet. Convective clouds therefore propagate more slowly than their surroundings, which may affect the distribution of precipitation. The method could be used to compare cloud-induced flow at different resolutions and between different parameterizations.
在现代数值天气和气候模型中能够明确解析的大尺度大气环流与采用参数化处理的云相关非绝热过程之间的复杂耦合,是天气预报和气候预测中误差的一个重要来源。为了量化云与大尺度环流之间的相互作用,采用了一种方法,该方法将远场和近场环流归因于云系统。该方法基于有限区域内涡度和散度的估计来重建云诱导流,并且不需要定义背景流。随后将其应用于对对流云的12公里和2公里模拟,这些对流云形成于与北大西洋温带气旋相关的高空急流前方的大尺度云带内。云诱导环流与急流方向相反,可达10米·秒,并且在两次模拟之间具有良好的一致性。流动方向与在云附近形成的涡度偶极子所预期的一致。因此,在存在嵌入式对流的情况下,风速不像在无云区域那样远离急流稳定减小,而是呈现出明显的负异常,现在这可以由云诱导环流来解释。此外,重建环流的方向表明云诱导了一股与急流对其平流作用相反的气流。因此,对流云的传播速度比其周围环境慢,这可能会影响降水分布。该方法可用于比较不同分辨率以及不同参数化情况下的云诱导流。