Short-duration heavy rainfall(SHR),as delineated by the National Meteorological Center of the China Me-teorological Administration,is characterized by hourly rainfall amounts no less than 20.0 mm.SHR is one of the mos...Short-duration heavy rainfall(SHR),as delineated by the National Meteorological Center of the China Me-teorological Administration,is characterized by hourly rainfall amounts no less than 20.0 mm.SHR is one of the most common convective weather phenomena that can cause severe damage.Short-range forecasting of SHR is an important part of operational severe weather prediction.In the present study,an improved objective SHR forecasting scheme was developed by adopting the ingredients-based methodology and using the fuzzy logic approach.The 1.0°×1.0°National Centers for Environmental Prediction(NCEP)final analysis data and the ordinary rainfall(0.1-19.9 mm h-1)and SHR observational data from 411 stations were used in the improved scheme.The best lifted index,the total precipitable water,the 925 hPa specific humidity(Q 925),and the 925 hPa divergence(DIV 925)were selected as predictors based on objective analysis.Continuously distributed membership functions of predictors were obtained based on relative frequency analysis.The weights of predictors were also objectively determined.Experiments with a typhoon SHR case and a spring SHR case show that the main possible areas could be captured by the improved scheme.Verification of SHR forecasts within 96 hours with NCEP global forecasts 1.0°×1.0°data initiated at 08:00 Beijing Time during the warm seasons in 2015 show the results were improved from both deterministic and probabilistic perspectives.This study provides an objectively feasible choice for short-range guidance forecasts of SHR.The scheme can be applied to other convective phenomena.展开更多
在车载网络(VANETs,vehicular Ad Hoc networks)中,车辆以动态节点方式与其他车辆通信。由于车辆数量的变化和高速移动,通信管理并建立稳定网络成为VANETs最有挑战的项目。因此,簇技术成为解决此挑战的可靠方案之一。利用簇技术将车辆...在车载网络(VANETs,vehicular Ad Hoc networks)中,车辆以动态节点方式与其他车辆通信。由于车辆数量的变化和高速移动,通信管理并建立稳定网络成为VANETs最有挑战的项目。因此,簇技术成为解决此挑战的可靠方案之一。利用簇技术将车辆划分不同的群,使得网络更强健。为此,提出基于模糊逻辑的簇头选择算法,记为COHORT算法。在COHORT算法中,车辆利用关于平均速度、邻居密度和链路质量的模糊逻辑评估自己成为簇头的资格,具有最高资格的车辆被选为簇头。仿真结果表明,提出的COHORT算法提高了簇头的生命周期和稳定性。展开更多
基金Key R&D Program of Xizang Autonomous Region(XZ202101ZY0004G)National Natural Science Foundation of China(U2142202)+1 种基金National Key R&D Program of China(2022YFC3004104)Key Innovation Team of China Meteor-ological Administration(CMA2022ZD07)。
文摘Short-duration heavy rainfall(SHR),as delineated by the National Meteorological Center of the China Me-teorological Administration,is characterized by hourly rainfall amounts no less than 20.0 mm.SHR is one of the most common convective weather phenomena that can cause severe damage.Short-range forecasting of SHR is an important part of operational severe weather prediction.In the present study,an improved objective SHR forecasting scheme was developed by adopting the ingredients-based methodology and using the fuzzy logic approach.The 1.0°×1.0°National Centers for Environmental Prediction(NCEP)final analysis data and the ordinary rainfall(0.1-19.9 mm h-1)and SHR observational data from 411 stations were used in the improved scheme.The best lifted index,the total precipitable water,the 925 hPa specific humidity(Q 925),and the 925 hPa divergence(DIV 925)were selected as predictors based on objective analysis.Continuously distributed membership functions of predictors were obtained based on relative frequency analysis.The weights of predictors were also objectively determined.Experiments with a typhoon SHR case and a spring SHR case show that the main possible areas could be captured by the improved scheme.Verification of SHR forecasts within 96 hours with NCEP global forecasts 1.0°×1.0°data initiated at 08:00 Beijing Time during the warm seasons in 2015 show the results were improved from both deterministic and probabilistic perspectives.This study provides an objectively feasible choice for short-range guidance forecasts of SHR.The scheme can be applied to other convective phenomena.
文摘在车载网络(VANETs,vehicular Ad Hoc networks)中,车辆以动态节点方式与其他车辆通信。由于车辆数量的变化和高速移动,通信管理并建立稳定网络成为VANETs最有挑战的项目。因此,簇技术成为解决此挑战的可靠方案之一。利用簇技术将车辆划分不同的群,使得网络更强健。为此,提出基于模糊逻辑的簇头选择算法,记为COHORT算法。在COHORT算法中,车辆利用关于平均速度、邻居密度和链路质量的模糊逻辑评估自己成为簇头的资格,具有最高资格的车辆被选为簇头。仿真结果表明,提出的COHORT算法提高了簇头的生命周期和稳定性。
