Quantifying the circulation induced by convective clouds in kilometer-scale simulations

• Main Authors: Oertel, Annika, Schemm, Sebastian
• Format: Article in Journal/Newspaper
• Language: English
• Published: John Wiley and Sons 2021
• Subjects: ddc:550; Earth sciences; info:eu-repo/classification/ddc/550; North Atlantic
• Online Access: https://publikationen.bibliothek.kit.edu/1000130526; https://publikationen.bibliothek.kit.edu/1000130526/106600873; https://doi.org/10.5445/IR/1000130526

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 ms$^{-1}$, 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.