Flash floods pose a significant risk to infrastructure in Kosovo, particularly in urban and riverine areas. This research focuses on an intense river flood event that took place on January 19, 2023, in the Skenderaj catchment. The study’s main goal was to establish a flash flood early warning system by combining sophisticated atmospheric modeling, hydrological evaluation, and rainfall hazard analysis. The ARW model with 2-km resolution effectively captured rainfall intensity and local flood occurrences, particularly around Skenderaj and Istog, whereas the 4-km NMM model better represented wider spatial precipitation patterns. Hydrological results demonstrated that precipitation strongly dictated river discharge and runoff dynamics, with the highest flows recorded in northern Albania. To validate and enhance forecast accuracy for flash flood warnings, datasets from the Global Flood Awareness System (GloFAS), the European Flood Awareness System (EFAS), and ERA5 reanalysis were incorporated. These resources prov ided essential information on antecedent conditions, such as soil moisture and snowmelt, which substantially influenced runoff and flood magnitude. The ECMWF Copernicus framework also contributed by supplying 24-hour river discharge forecasts for Kosovo’s basins, aiding in timely and spatially detailed flood alerts. The Novel Thunderstorm Alert System (NOTHAS) was updated to integrate crucial hydrological variables - including surface and convective runoff, snow water equivalent, soil moisture, and slope - thereby enhancing the precision of flood warnings. This improved system enabled effective classification of flood risk zones, thus identifying areas vulnerable to flash floods and landslides. The study highlights the crucial role of high-resolution weather modeling, hydrological insights, and integrated early warning systems in enhancing flash flood prediction and mitigation efforts.
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This study examines the severe flash flood event that hit Kosovo on June 24, 2023, resulting in an extraordinary 54 mm of rainfall within a single hour. Utilizing a state-of-the-art three-dimensional nonhydrostatic cloud resolving model, the research clarifies the atmospheric mechanisms driving such extreme precipitation events. Key findings highlight the development of high altitude cumulonimbus clouds, the crucial role of strong updrafts in facilitating intense microphysical vertical transfer, and the subsequent formation of wet downbursts. Model validation against radar data demonstrates accuracy in replicating observed precipitation patterns, bolstering confidence in its predictive capabilities. These insights enhance our understanding of extreme weather events and suggest potential improvements in forecasting and risk mitigation strategies.
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This research investigates the efficacy of the cloud-resolving Weather Research and Forecasting (WRF) model in reproducing convective cells associated with flash-flooding heavy rainfall near Peja, Northeast Kosovo, on June 24, 2023. Employing two distinct dynamical cores and a unique numerical setup for the Kosovo domain, numerical experiments were conducted. The study employed a triply nested WRF-ARW model with a high resolution of 3 km horizontal grid spacing, integrating conventional analysis data. Additionally, experiments using the WRF-NMM core with 3 km for a larger domain covering Southeast Europe and Kosovo domain were executed to simulate the specific event. The WRF model accurately simulated the initiation of isolated thunderstorms, convective band formation, cloud cluster, and squall line at the opportune time. While precipitation distribution was reasonably replicated, there was a slight underestimation in the amount. Hydrological analysis of precipitation, including river discharge rates provided from ECMWF ERA5 reanalysis, identified a unique storm category with intense precipitation production, registering an intensity of approximately 54.6 mm in 1 h, leading to sudden flash flooding.
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Climate changes are accelerating and leading to climate and weather extremes with the most destructive impacts and negative consequences on the planet. For these reasons, precise forecasting, and announcement of weather disasters of a convective nature, from local to synoptic scales, is very important. The Novel Thunderstorm Alert System (NOTHAS) has shown outstanding results in forecasting and early warning of different modes of convection, including local hazards in mid-latitudes. In this study, an attempt has been made to apply this tool in the prediction of different atmospheric systems that occur in different climatic regions. The upgraded prognostic and diagnostic algorithm with adjusted complex parameters and criteria representative of tropical storms and tropical cyclones showed good coincidence with the available observations. NOTHAS showed skill and success in assessing the dynamics and intensity of Hurricane Ian, which hit the west coast of Florida on 30 September 2022 and caused great material damage and human losses. This advanced tool also detected the most intense-extreme Level-5 on 1 September 2021, over New York, when catastrophic flooding occurred within the remnants of Hurricane Ida. Likewise, the upgraded model configuration very correctly predicted the trajectory, modifications, and strength of super typhoon Nanmadol over Japan (19 September 2022), 24-48 h in advance, and super typhoon Noru over the Philippines (25 September 2022). The system showed the temporal and spatial accuracy of the location of the heavy rainfall and flash flood. In general, the obtained results for all evaluated cases are encouraging and provide a good basis for further testing, verification, and severe weather warnings and guidance for weather services worldwide.
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The present study examines the ability of the forecast (WRF) model to reproduce a heavy rainfall flash-flood event that hit the urban area of Skopje City, on August 6, 2016. A series of numerical experiments were carried out to evaluate the model’s performance in the simulation of this catastrophic event, which caused great material damage and the loss of 23 human lives. The simulations with the triple-nested WRF-ARW runs as well as the experiment using WRF-NMM dynamic core with the initial data of FNL GDAS showed better skills in a more precise qualitative and quantitative assessment of the total 24-h accumulated precipitation, the location and the relative intensities of rainfall. Explicit treatment of convection without parameterization significantly improves forecast accuracy and reduces forecast errors. The verification results, using standard tests, showed the model’s ability to reproduce the occurred flood. The correlation coefficient is higher for runs with explicit cumulus convection and 4 km resolution with the Yonsei PBL scheme and Thomson microphysics with aerosol climatology. In addition to the influence of the thermodynamic characteristics of the atmosphere, orographic forcing on the development of a strong mesosystem is of great importance for the intensification of convective cells and the production of large amounts of precipitation.
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