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 s...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 high-intensity 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(now-casting)and early warning of weather disasters.展开更多
Given that floods continue to cause yearly significant worldwide human and material damages, flood risk mitigation is a key issue and a permanent challenge in developing policies and strategies at various spatial scal...Given that floods continue to cause yearly significant worldwide human and material damages, flood risk mitigation is a key issue and a permanent challenge in developing policies and strategies at various spatial scales. Therefore, a basic phase is elaborating hazard and flood risk maps, documents which are an essential support for flood risk management. The aim of this paper is to develop an approach that allows for the identification of flash-flood and flood-prone susceptible areas based on computing and mapping of two indices： FFPI （Flash-Flood Potential Index） and FPI （Flooding Potential Index）. These indices are obtained by integrating in a GIS environment several geographical variables which control runoff（in the case of the FFPI） and favour flooding （in the case of the FPI）. The methodology was applied in the upper （mountainous） and middle （hilly） catchment of the Prahova River, a densely populated and socioeconomically well-developed area which has been affected repeatedly by water-related hazards over the past decades. The resulting maps showing the spatialization of the FFPI and FPI allow for the identification of areas with high susceptibility to flash- floods and flooding. This approach can provide useful mapped information, especially for areas （generally large） where there are no flood/hazard risk maps. Moreover, the FFPI and FPI maps can constitute a preliminary step for flood risk and vulnerability assessment.展开更多
By using the high-resolution observation data and MM5 model simulation data,the analysis on the 12 June 2008 Guangxi flash-flood rainstorm shows that the associated major mesoscale weather system of this event is a qu...By using the high-resolution observation data and MM5 model simulation data,the analysis on the 12 June 2008 Guangxi flash-flood rainstorm shows that the associated major mesoscale weather system of this event is a quasi-stationary mesoscale vortex,which resulted from the interaction between the midlatitude synoptic-scale waves in the westerly belt and the low-latitude warm-moist flow under the terrain effect.The genesis,development,and movement of the mesoscale vortex have significant impacts on the intensity and persistence of the severe precipitation from the Guangxi flash-flood rainstorm.This vortex is characterized by the coexistence of strong vorticity and divergence with the same order of magnitude.Well organized,deep,and moist convection was observed for a long period of time,and was produced by the interaction between the mesoscale vortex and the gravity waves.The latter was generated by the terrain effect and the ageostrophic effect of high winds in the low-level jet.According to the quasi-balanced dynamical theory,quasi-balanced flow must have existed in the mesoscale motions with both divergent and rotational winds.Thus,based on the diagnosis of the quasi-balanced flow,the PV-ω inversion method is employed to analyze the organized moist convection.The results show that 50%-70% of the vertical circulation in the rainstorm areas was quasi-balanced,so the quasi-balanced flow could well reflect features of the strong vertical motions associated with the coexistence of vorticity and divergence during this event.展开更多
Floods remain one of the most devastating weather-induced disastersworldwide, resulting in numerous fatalities each year and severelyimpacting socio-economic development and the environment.Therefore, the ability to p...Floods remain one of the most devastating weather-induced disastersworldwide, resulting in numerous fatalities each year and severelyimpacting socio-economic development and the environment.Therefore, the ability to predict flood-prone areas in advance is crucialfor effective risk management. The objective of this research is to assessand compare three convolutional neural networks, U-Net, WU-Net, andU-Net++, for spatial prediction of pluvial flood with a case study at atropical area in the north of Vietnam. They are relative new convolutionalgorithms developed based on U-shaped architectures. For this task, ageospatial database with 796 historical flood locations and 12 floodindicators was prepared. For training the models, the binary crossentropywas employed as the loss function, while the Adaptive momentestimation (ADAM) algorithm was used for the optimization of themodel parameters, whereas, F1-score and classification accuracy (Acc)were used to assess the performance of the models. The results unequivocally highlight the high performance of the three models,achieving an impressive accuracy rate of 96.01%. The flood susceptibility maps derived from this research possess considerable utility for local authorities, providing valuable insights and informationto enhance decision-making processes and facilitate the implementation of effective risk management strategies.展开更多
文摘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 high-intensity 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(now-casting)and early warning of weather disasters.
文摘Given that floods continue to cause yearly significant worldwide human and material damages, flood risk mitigation is a key issue and a permanent challenge in developing policies and strategies at various spatial scales. Therefore, a basic phase is elaborating hazard and flood risk maps, documents which are an essential support for flood risk management. The aim of this paper is to develop an approach that allows for the identification of flash-flood and flood-prone susceptible areas based on computing and mapping of two indices： FFPI （Flash-Flood Potential Index） and FPI （Flooding Potential Index）. These indices are obtained by integrating in a GIS environment several geographical variables which control runoff（in the case of the FFPI） and favour flooding （in the case of the FPI）. The methodology was applied in the upper （mountainous） and middle （hilly） catchment of the Prahova River, a densely populated and socioeconomically well-developed area which has been affected repeatedly by water-related hazards over the past decades. The resulting maps showing the spatialization of the FFPI and FPI allow for the identification of areas with high susceptibility to flash- floods and flooding. This approach can provide useful mapped information, especially for areas （generally large） where there are no flood/hazard risk maps. Moreover, the FFPI and FPI maps can constitute a preliminary step for flood risk and vulnerability assessment.
基金Supported by the National Nature Science Foundation of China under Grant Nos. 40905022 and 40830958National Key Basic Research Program under Grant No. 2009CB421500
文摘By using the high-resolution observation data and MM5 model simulation data,the analysis on the 12 June 2008 Guangxi flash-flood rainstorm shows that the associated major mesoscale weather system of this event is a quasi-stationary mesoscale vortex,which resulted from the interaction between the midlatitude synoptic-scale waves in the westerly belt and the low-latitude warm-moist flow under the terrain effect.The genesis,development,and movement of the mesoscale vortex have significant impacts on the intensity and persistence of the severe precipitation from the Guangxi flash-flood rainstorm.This vortex is characterized by the coexistence of strong vorticity and divergence with the same order of magnitude.Well organized,deep,and moist convection was observed for a long period of time,and was produced by the interaction between the mesoscale vortex and the gravity waves.The latter was generated by the terrain effect and the ageostrophic effect of high winds in the low-level jet.According to the quasi-balanced dynamical theory,quasi-balanced flow must have existed in the mesoscale motions with both divergent and rotational winds.Thus,based on the diagnosis of the quasi-balanced flow,the PV-ω inversion method is employed to analyze the organized moist convection.The results show that 50%-70% of the vertical circulation in the rainstorm areas was quasi-balanced,so the quasi-balanced flow could well reflect features of the strong vertical motions associated with the coexistence of vorticity and divergence during this event.
基金The authors would like to thank the Spanish Ministry of Science and Innovation for the support under the projects PID2020-117954RB-C21 and TED2021-131311B-C22.
文摘Floods remain one of the most devastating weather-induced disastersworldwide, resulting in numerous fatalities each year and severelyimpacting socio-economic development and the environment.Therefore, the ability to predict flood-prone areas in advance is crucialfor effective risk management. The objective of this research is to assessand compare three convolutional neural networks, U-Net, WU-Net, andU-Net++, for spatial prediction of pluvial flood with a case study at atropical area in the north of Vietnam. They are relative new convolutionalgorithms developed based on U-shaped architectures. For this task, ageospatial database with 796 historical flood locations and 12 floodindicators was prepared. For training the models, the binary crossentropywas employed as the loss function, while the Adaptive momentestimation (ADAM) algorithm was used for the optimization of themodel parameters, whereas, F1-score and classification accuracy (Acc)were used to assess the performance of the models. The results unequivocally highlight the high performance of the three models,achieving an impressive accuracy rate of 96.01%. The flood susceptibility maps derived from this research possess considerable utility for local authorities, providing valuable insights and informationto enhance decision-making processes and facilitate the implementation of effective risk management strategies.
