Haboobs, dust storms generated by the cold pool outflow from moist convection, are a major dust uplift mechanism, especially over northern Africa in boreal summer. However, systematic model investigations of haboob properties and their contribution to total dust emissions remain limited. Such studies require not only computationally expensive convection-permitting models with an online dust cycle to explicitly simulate haboobs and their associated dust emissions, but also a reliable method to detect haboobs in model output. Here we develop HITRA (Haboob Identification, Tracking and Dust-emission Attribution Algorithm) v1.0, an automated algorithm to detect and characterize haboobs. We apply HITRA to a one-year simulation for 2011 with the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) including online dust at approximately 3 km resolution over North Africa and the Middle East. This allows us to assess both the algorithm performance and the realism of the simulated haboob characteristics. After filtering short-lived events and coastal and orographic artefacts, the diagnostic identified 3,371 haboob events during the simulation year. The resulting event catalogue shows that MONARCH captures key haboob features, including Sahelian hotspots, boreal-summer seasonality, afternoon-to-evening occurrence, mesoscale sizes, and lifetimes of a few hours. Haboobs account for 6.65 % of annual domain-total dust emission and 9.72 % in JJA, with local contributions exceeding 50 % in parts of the Sahel. These results demonstrate that convection-permitting modeling is able to represent haboobs overall realistically and HITRA provides a systematic framework for systematically identifying and characterizing haboobs and quantifying their contribution to dust emissions in convection-permitting simulations.