Advancing the capabilities for efficient hurricane-centric simulations with the atmospheric model ICON

Abstract. Global storm-resolving simulations with kilometer resolution are increasingly replacing traditional climate modeling approaches and show particular potential for resolving the dynamics and effects of deep moist convection. These modern modeling methods are moving toward sub-km scales, leading to extremely high energy and resource requirements. This makes iterations, parameter optimizations, and sensitivity studies no longer easily feasible. For the class of propagating, large-scale weather phenomena such as hurricanes, high-resolution limited-area approaches in combination with Lagrangian methods are therefore of interest, in which refined grids are shifted along the path of the phenomenon under consideration. To create this capacity for the ICON atmospheric model, this study develops a flexible workflow toolkit to enable efficient simulations of hurricanes on a sub-km scale. Our approach leverages the flexibility that ICON offers through the ability to create custom grids. The concept divides hurricane tracks into overlapping temporal windows of 12–24 h and generates customized grid segments that follow the hurricane's movement. The technical implementation automates key components of the workflow, including hurricane tracking, flexible grid generation, and preparation and merging of initial conditions across successive segments. The application of the workflow is demonstrated using Hurricane Paulette (2020) as an example, for which high-resolution simulations with grid spacings down to 300 m were performed using different segment configurations. The results show that the hurricane track remains consistent with the base run and depends mainly on the across-track width of the chosen configuration, while intensity metrics such as minimum pressure and maximum wind speed show significant sensitivities to resolution in our multi-nested setups. The efficiency gains are significant compared to traditional approaches with fixed limited-area domains: replacing a fixed domain with a track-following tube reduces resource requirements by factors of 2–8, and segmenting the tube into short, frequently re-initialized intervals adds a further factor of 2–6. Analysis of re-initialization effects shows systematic but manageable impacts during segment transitions. Nevertheless, the efficiency gains achieved by our method are so substantial that they justify the acceptance of the re-initialization effects. Our segment-based approach in the hurricane-centric reference system now allows for more flexible regional hurricane simulations with the ICON model and more efficient investigation of new research questions regarding the sensitivity of hurricane cloud systems at very high resolutions.