摘要：The Split wildfire in July 2017, which was one of the most severe wildfires in the history of this Croatian World Heritage Site, is the focus in this study. The Split fire is a good example of a wildfire–urban interface, with unexpected fire behavior including rapid downslope spread to the coastal populated area. This study clarifies the meteorological conditions behind the fire event, those that have limited the effectiveness of firefighting operations, and the rapid escalation and expansion of the fire zones within 30 h. The Split fire propagation was first reconstructed using radio logs, interviews with firefighters and pilots involved in the intervention, eyewitness statements, digital photographs from fire detection cameras, media, and the monthly firefighting journal. Four phases of fire development have been identified.Then, weather observations and numerical simulations using an enhanced-resolution operational model are utilized to analyze the dynamics in each phase of the fire runs. The synoptic background of the event includes large surface pressure gradient between the Azores anticyclone accompanied by a cold front and a cyclone over the southeastern Balkan Peninsula. At the upper level, there was a deep shortwave trough extending from the Baltic Sea to the Adriatic Sea, which developed into a cut-off low. Such synoptic conditions have resulted in the maximum fire weather index in 2017. Combined with topography, they also locally provoke the formation of the strong northeasterly bura wind along the Adriatic coast, which has been accompanied by a low-level jet (LLJ). The bura (downslope wind), with mid- to low-level gravity-wave breaking and turbulence mixing (as in the hydraulic jump theory), also facilitated the subsidence of dry air from the upper troposphere and rapid drying at the surface.This study demonstrates that numerical guidance that indicates the spatial and temporal occurrence of a LLJ is highly capable of explaining the Split fire evolution from the ignition potential to its extinguishment stage. Thus, in addition to the conventional fire weather indices, such products are able to improve fire weather behavior forecasting and in general more effective decision-making in fire management.
