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A storm modeling system as an advanced tool in prediction of well organized slowly moving convective cloud system and early warning of severe weather risk

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Abstract

Short-range prediction of precipitation is a critical input to flood prediction and hence the accuracy of flood warnings. Since most of the intensive processes come from convective clouds-the primary aim is to forecast these small-scale atmospheric processes. One characteristic pattern of organized group of convective clouds consist of a line of deep convection resulted in the repeated passage of heavy-rain-producing convective cells over NW part of Macedonia along the line. This slowly moving convective system produced extreme local rainfall and hailfall in urban Skopje city. A 3-d cloud model is used to simulate the main storm characteristic (e.g., structure, intensity, evolution) and the main physical processes responsible for initiation of heavy rainfall and hailfall. The model showed a good performance in producing significantly more realistic and spatially accurate forecasts of convective rainfall event than is possible with current operational system. The output results give a good initial input for developing appropriate tools such as flooding indices and potential risk mapping for interpreting and presenting the predictions so that they enhance operational flood prediction capabilities and warnings of severe weather risk of weather services. Convective scale model-even for a single case used has proved significant benefits in several aspects (initiation of convection, storm structure and evolution and precipitation). The storm-scale model (grid spacing-1 km) is capable of producing significantly more realistic and spatially accurate forecasts of convective rainfall events than is possible with current operational systems based on model with grid spacing 15 km.

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Spiridonov, V., Curic, M. A storm modeling system as an advanced tool in prediction of well organized slowly moving convective cloud system and early warning of severe weather risk. Asia-Pacific J Atmos Sci 51, 61–75 (2015). https://doi.org/10.1007/s13143-014-0060-3

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