The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflect...The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflectivity observed by GPM Ku PR is compared quantitatively against GR networks from CINRAD of China and NEXRAD of the United States,and the volume matching method is used for spatial matching.Additionally,a novel frequency correction method for all phases as well as precipitation types is used to correct the GPM Ku PR radar frequency to the GR frequency.A total of 20 GRs(including 10 from CINRAD and 10 from NEXRAD)are included in this comparative analysis.The results indicate that,compared with CINRAD matched data,NEXRAD exhibits larger biases in reflectivity when compared with the frequency-corrected Ku PR.The root-mean-square difference for CINRAD is calculated at 2.38 d B,whereas for NEXRAD it is 3.23 d B.The mean bias of CINRAD matched data is-0.16 d B,while the mean bias of NEXRAD is-2.10 d B.The mean standard deviation of bias for CINRAD is 2.15 d B,while for NEXRAD it is 2.29 d B.This study effectively assesses weather radar data in both the United States and China,which is crucial for improving the overall consistency of global precipitation estimates.展开更多
The North Pacific storm track(NPST)is a high-frequency area of extratropical cyclones and an important channel for water vapor and energy transfer between low and mid–high latitudes.Previous weather and dynamic studi...The North Pacific storm track(NPST)is a high-frequency area of extratropical cyclones and an important channel for water vapor and energy transfer between low and mid–high latitudes.Previous weather and dynamic studies in this region have made significant progress,but due to the lack of ocean surface rainfall observation data,there is a lack of statistical research on precipitation in this area.In this study,statistical research on the spatiotemporal distribution characteristics of NPST rainfall was conducted based on GPM DPR(Global Precipitation Measurement Dual-frequency Precipitation Radar)observation data and ERA5 atmospheric parameters,and analysis and explanations are provided based on the atmospheric parameters.The study found that,compared to low-pressure systems,pressure gradients have a greater impact on cyclone activity and rainfall distribution.This feature,along with the meridional distribution of high atmospheric water vapor in the North Pacific Ocean and low in the north,collectively leads to the offset of high-frequency rainfall areas relative to storm tracks.The distribution of sea surface temperatures in the North Pacific Ocean affects the zonal distribution of storm tracks,causing weather disturbances and precipitation along the storm tracks to exhibit a northward extension from west to east.This study deepens our understanding of the role of NPST in global-scale water vapor and energy balance,and is of great significance for improving the prediction accuracy of climate models with respect to rainfall generated by extratropical cyclones.展开更多
Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for...Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.展开更多
Understanding the structure of tropical cyclone(TC)hydrometeors is crucial for detecting the changes in the distribution and intensity of precipitation.In this study,the GMI brightness temperature and cloud-dependent ...Understanding the structure of tropical cyclone(TC)hydrometeors is crucial for detecting the changes in the distribution and intensity of precipitation.In this study,the GMI brightness temperature and cloud-dependent 1DVAR algorithm were used to retrieve the hydrometeor profiles and surface rain rate of TC Nanmadol(2022).The Advanced Radiative Transfer Modeling System(ARMS)was used to calculate the Jacobian and degrees of freedom(△DOF)of cloud water,rainwater,and graupel for different channels of GMI in convective conditions.The retrieval results were compared with the Dual-frequency Precipitation Radar(DPR),GMI 2A,and IMERG products.It is shown that from all channels of GMI,rain water has the highest△DOF,at 1.72.According to the radiance Jacobian to atmospheric state variables,cloud water emission dominates its scattering.For rain water,the emission of channels 1–4 dominates scattering.Compared with the GMI 2A precipitation product,the 1DVAR precipitation rate has a higher correlation coefficient(0.713)with the IMERG product and can better reflect the location of TC precipitation.Near the TC eyewall,the highest radar echo top indicates strong convection.Near the melting layer where Ka-band attenuation is strong,the double frequency difference of DPR data reflects the location of the melting.The DPR drop size distribution(DSD)product shows that there is a significant increase in particle size below the melting layer in the spiral rain band.Thus,the particle size may be one of the main reasons for the smaller rain water below the melting layer retrieved from 1DVAR.展开更多
在无线传感器网络中,延迟是影响实时服务质量的重要因素.为了减少分组在转发过程中的排队延迟,提出一种基于动态优先级的实时分组调度机制(Dynamic Priority Based Real-time Packet Scheduling简写DPRS).在DPRS中,节点的队列被分为三...在无线传感器网络中,延迟是影响实时服务质量的重要因素.为了减少分组在转发过程中的排队延迟,提出一种基于动态优先级的实时分组调度机制(Dynamic Priority Based Real-time Packet Scheduling简写DPRS).在DPRS中,节点的队列被分为三个优先级队列,分别存放紧急分组、延误分组以及普通分组,DPRS在三个队列之间采取优先级调度机制,且根据当前队列的拥塞程度在每个队列内部采取先到先服务(First Come First Service简写FCFS)或后到先服务(Last Come First Service简写LCFS)的调度机制.理论分析和实验对比验证结果表明DPRS能够提高无线传感器网络的实时性.展开更多
基金funded by the National Key Research and Development Program of China(Grant No.2023YFB3907500)the National Natural Science Foundation(Grant No.42330602)the“Fengyun Satellite Remote Sensing Product Validation and Verification”Youth Innovation Team of the China Meteorological Administration(Grant No.CMA2023QN12)。
文摘The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflectivity observed by GPM Ku PR is compared quantitatively against GR networks from CINRAD of China and NEXRAD of the United States,and the volume matching method is used for spatial matching.Additionally,a novel frequency correction method for all phases as well as precipitation types is used to correct the GPM Ku PR radar frequency to the GR frequency.A total of 20 GRs(including 10 from CINRAD and 10 from NEXRAD)are included in this comparative analysis.The results indicate that,compared with CINRAD matched data,NEXRAD exhibits larger biases in reflectivity when compared with the frequency-corrected Ku PR.The root-mean-square difference for CINRAD is calculated at 2.38 d B,whereas for NEXRAD it is 3.23 d B.The mean bias of CINRAD matched data is-0.16 d B,while the mean bias of NEXRAD is-2.10 d B.The mean standard deviation of bias for CINRAD is 2.15 d B,while for NEXRAD it is 2.29 d B.This study effectively assesses weather radar data in both the United States and China,which is crucial for improving the overall consistency of global precipitation estimates.
基金funded by the National Natural Science Foundation of China(Grant Nos.42275140,42230612,91837310,41675041,and 92037000)the Second Tibetan Plateau Scientific Expedition and Research(STEP)program(Grant No.2019QZKK0104)。
文摘The North Pacific storm track(NPST)is a high-frequency area of extratropical cyclones and an important channel for water vapor and energy transfer between low and mid–high latitudes.Previous weather and dynamic studies in this region have made significant progress,but due to the lack of ocean surface rainfall observation data,there is a lack of statistical research on precipitation in this area.In this study,statistical research on the spatiotemporal distribution characteristics of NPST rainfall was conducted based on GPM DPR(Global Precipitation Measurement Dual-frequency Precipitation Radar)observation data and ERA5 atmospheric parameters,and analysis and explanations are provided based on the atmospheric parameters.The study found that,compared to low-pressure systems,pressure gradients have a greater impact on cyclone activity and rainfall distribution.This feature,along with the meridional distribution of high atmospheric water vapor in the North Pacific Ocean and low in the north,collectively leads to the offset of high-frequency rainfall areas relative to storm tracks.The distribution of sea surface temperatures in the North Pacific Ocean affects the zonal distribution of storm tracks,causing weather disturbances and precipitation along the storm tracks to exhibit a northward extension from west to east.This study deepens our understanding of the role of NPST in global-scale water vapor and energy balance,and is of great significance for improving the prediction accuracy of climate models with respect to rainfall generated by extratropical cyclones.
基金financially supported by the National Council for Scientific and Technological Development(CNPq,Brazil),Swedish-Brazilian Research and Innovation Centre(CISB),and Saab AB under Grant No.CNPq:200053/2022-1the National Council for Scientific and Technological Development(CNPq,Brazil)under Grants No.CNPq:312924/2017-8 and No.CNPq:314660/2020-8.
文摘Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFC3004202)the National Natural Science Foundation of China(Grant Nos.U2142212 and 42105136)。
文摘Understanding the structure of tropical cyclone(TC)hydrometeors is crucial for detecting the changes in the distribution and intensity of precipitation.In this study,the GMI brightness temperature and cloud-dependent 1DVAR algorithm were used to retrieve the hydrometeor profiles and surface rain rate of TC Nanmadol(2022).The Advanced Radiative Transfer Modeling System(ARMS)was used to calculate the Jacobian and degrees of freedom(△DOF)of cloud water,rainwater,and graupel for different channels of GMI in convective conditions.The retrieval results were compared with the Dual-frequency Precipitation Radar(DPR),GMI 2A,and IMERG products.It is shown that from all channels of GMI,rain water has the highest△DOF,at 1.72.According to the radiance Jacobian to atmospheric state variables,cloud water emission dominates its scattering.For rain water,the emission of channels 1–4 dominates scattering.Compared with the GMI 2A precipitation product,the 1DVAR precipitation rate has a higher correlation coefficient(0.713)with the IMERG product and can better reflect the location of TC precipitation.Near the TC eyewall,the highest radar echo top indicates strong convection.Near the melting layer where Ka-band attenuation is strong,the double frequency difference of DPR data reflects the location of the melting.The DPR drop size distribution(DSD)product shows that there is a significant increase in particle size below the melting layer in the spiral rain band.Thus,the particle size may be one of the main reasons for the smaller rain water below the melting layer retrieved from 1DVAR.
文摘在无线传感器网络中,延迟是影响实时服务质量的重要因素.为了减少分组在转发过程中的排队延迟,提出一种基于动态优先级的实时分组调度机制(Dynamic Priority Based Real-time Packet Scheduling简写DPRS).在DPRS中,节点的队列被分为三个优先级队列,分别存放紧急分组、延误分组以及普通分组,DPRS在三个队列之间采取优先级调度机制,且根据当前队列的拥塞程度在每个队列内部采取先到先服务(First Come First Service简写FCFS)或后到先服务(Last Come First Service简写LCFS)的调度机制.理论分析和实验对比验证结果表明DPRS能够提高无线传感器网络的实时性.
