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Наслов: Ensemble cloud model application in simulating the catastrophic heavy rainfall event
Authors: Spiridonov, Vlado 
Curic, Mladjen
Grcic, Marija
Jakimovski, Boro 
Keywords: WRF triple nested model
Convective cloud model
Ensemble initialization
3-D nerical simulation
Flash-flood event
Super-cell storm
Issue Date: 30-ное-2022
Journal: Journal of Atmospheric Science Research
Abstract: An attempt has been made in the present research to simulate a deadly flash-flood event over the City of Skopje, Macedonia on 6 August 2016. A cloud model ensemble forecast method is developed to simulate a super-cell storm’s initiation and evolutionary features. Sounding data are generated using an ensemble approach, that utilizes a triple-nested WRF model. A three-dimensional (3-D) convective cloud model (CCM) with a very fine horizontal grid resolution of 250-m is initialized, using the initial representative sounding data, derived from the WRF 1-km forecast outputs. CCM is configured and run with an open lateral boundary conditions LBC, allowing explicit simulation of convective scale processes. This preliminary study showed that the ensemble approach has some advantages in the generation of the initial data and the model initialization. The applied method minimizes the uncertainties and provides a more qualitative-quantitative assessment of super-cell storm initiation, cell structure, evolutionary properties, and intensity. A high-resolution 3-D run is capable to resolve detailed aspects of convection, including highintensity convective precipitation. The results are significant not only from the aspect of the cloud model’s ability to provide a qualitative-quantitative assessment of intense precipitation but also for a deeper understanding of the essence of storm development, its vortex dynamics, and the meaning of micro-physical processes for the production and release of large amounts of precipitation that were the cause of the catastrophic flood in an urban area. After a series of experiments and verification, such a system could be a reliable tool in weather services for very short-range forecasting (nowcasting) and early warning of weather disasters.
URI: http://hdl.handle.net/20.500.12188/27413
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles

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