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Study on Quantitative Precipitation Estimation by Polarimetric Radar Using Deep Learning

Advances in Atmospheric Sciences 2024年第6期41卷 1147-1160页

作者： Jiang huANGFU zhiqun hu Jiafeng ZHENG Lirong WANG Yongjie Zhu State Key Lab of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Meteorological observatory of Jiangxi Province Nanchang 330096China Hebei Meteorological Disaster Prevention and Environmental Meteorological Center Shijiazhuang 050021China School of Atmospheric Sciences Chengdu University of Information TechnologyChengdu 610225China

Accurate radar quantitative precipitation estimation(QPE)plays an essential role in disaster prevention and mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The dataset includes Shijiazhuang S-band dual polarimetric radar(CINRAD/SAD)data and rain gauge data within the radar’s 100-km detection range during the flood season of 2021 in North China.Considering that the specific propagation phase shift(KDP)has a roughly linear relationship with the precipitation intensity,KDP is set to 0.5°km^(-1 )as a threshold value to divide all the rain data(AR)into a heavy rain(HR)and light rain(LR)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The results suggest that the effects of QPE after distinguishing rainfall intensity are better than those without distinguishing,and the effects of using SLF are better than those that used MSE as a loss function.A Z-R relationship and a ZH-KDP-R synthesis method are compared with deep learning-based QPE.The mean relative errors(MRE)of AR models using SLF are improved by 61.90%,51.21%,and 56.34%compared with the Z-R relational method,and by 38.63%,42.55%,and 47.49%compared with the synthesis method.Finally,the models are further evaluated in three precipitation processes,which manifest that the deep learning-based models have significant advantages over the traditional empirical formula methods.

关键词： polarimetric radar quantitative precipitation estimation deep learning single-parameter network multi-parameter network

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Identification of Convective and Stratiform Clouds Based on the Improved DBSCAN Clustering Algorithm

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Advances in Atmospheric Sciences 2022年第12期39卷 2203-2212页

作者： Yuanyuan ZUO zhiqun hu Shujie YUAN Jiafeng ZHENG Xiaoyan YIN Boyong LI State Key Lab of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China School of Atmospheric Sciences Chengdu University of Information TechnologyChengdu 610225China

A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise(DBSCAN)algorithm.To identify convective and stratiform clouds in different developmental phases,two-dimensional(2D)and three-dimensional(3D)models are proposed by applying reflectivity factors at 0.5°and at 0.5°,1.5°,and 2.4°elevation angles,respectively.According to the thresholds of the algorithm,which include echo intensity,the echo top height of 35 dBZ(ET),density threshold,andεneighborhood,cloud clusters can be marked into four types:deep-convective cloud(DCC),shallow-convective cloud(SCC),hybrid convective-stratiform cloud(HCS),and stratiform cloud(SFC)types.Each cloud cluster type is further identified as a core area and boundary area,which can provide more abundant cloud structure information.The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing,Xuzhou,and Qingdao.The results show that cloud clusters can be intuitively identified as core and boundary points,which change in area continuously during the process of convective evolution,by the improved DBSCAN algorithm.Therefore,the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification.Because density thresholds are different and multiple elevations are utilized in the 3D model,the identified echo types and areas are dissimilar between the 2D and 3D models.The 3D model identifies larger convective and stratiform clouds than the 2D model.However,the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds.In addition,the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.

关键词： improved DBSCAN clustering algorithm cloud identification and classification 2D model 3D model weather radar

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Improvement of X-Band Polarization Radar Melting Layer Recognition by the Bayesian Method and ITS Impact on Hydrometeor Classification

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Advances in Atmospheric Sciences 2020年第1期37卷 105-116页

作者： Jianli MA zhiqun hu Meilin YANG Siteng LI Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China

Using melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBBhunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB

关键词： X-band polarimetric radar Bayesian method melting layer identification hydrometeor classification

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萍乡古代寺产纠纷案初考——以显华寺碑刻所录案例为中心

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萍乡学院学报 2024年第2期41卷 46-53页

作者：邓里胡志群萍乡博物馆江西萍乡337000

古代,萍乡地区的寺庙因田产与村民发生纠纷的案件,地方文献不见有相关资料记载。近年,萍乡博物馆对全市庙宇文物进行调查时,在显华寺内发现数通碑刻,其中清同治二年(1863)重立的《永远遵守》碑和光绪四年(1878)刊立的《千秋永賴》碑涉... 详细信息

古代,萍乡地区的寺庙因田产与村民发生纠纷的案件,地方文献不见有相关资料记载。近年,萍乡博物馆对全市庙宇文物进行调查时,在显华寺内发现数通碑刻,其中清同治二年(1863)重立的《永远遵守》碑和光绪四年(1878)刊立的《千秋永賴》碑涉及有关寺产纠纷方面的内容,尤其是《千秋永賴》碑刻比较详细地记录了一件萍乡显华寺寺产纠纷案的整个发生过程和最终处理结果,为我们研究清代该时期寺产纠纷案的处理及其衍生问题,提供了一手资料。

关键词：显华寺清代碑刻寺产纠纷案

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Recent Progress in Dual-Polarization Radar Research and Applications in China

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Advances in Atmospheric Sciences 2019年第9期36卷 961-974页

作者： Kun ZHAO Hao huANG Mingjun WANG Wen-Chau LEE Gang CHEN Long WEN Jing WEN Guifu ZHANG Ming XUE Zhengwei YANG Liping LIU Chong WU zhiqun hu Sheng CHEN Key Laboratory of Mesoscale Severe Weather of Ministry of Education and School of Atmospheric Sciences Nanjing University163 Xianlin RoadNanjing 210023China State Key Laboratory of Severe Weather and Joint Center for Atmospheric Radar Research of China Meteorological Administration and Nanjing University Chinese Academy of Meteorological SciencesBeijing 100081China National Center for Atmospheric Research BoulderColorado 80301USA School of Meteorology and Advanced Radar Research Center University of OklahomaNormanOklahoma 73019USA School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster StudiesSun Yat-sen UniversityGuangzhou 510006China

Dual-polarization(dual-pol)radar can measure additional parameters that provide more microphysical information of precipitation systems than those provided by conventional Doppler radar.The dual-pol parameters have been successfully utilized to investigate precipitation microphysics and improve radar quantitative precipitation estimation(QPE).The recent progress in dual-pol radar research and applications in China is summarized in four aspects.Firstly,the characteristics of several representative dual-pol radars are reviewed.Various approaches have been developed for radar data quality control,including calibration,attenuation correction,calculation of specific differential phase shift,and identification and removal of non-meteorological echoes.Using dual-pol radar measurements,the microphysical characteristics derived from raindrop size distribution retrieval,hydrometeor classification,and QPE is better understood in China.The limited number of studies in China that have sought to use dual-pol radar data to validate the microphysical parameterization and initialization of numerical models and assimilate dual-pol data into numerical models are summarized.The challenges of applying dual-pol data in numerical models and emerging technologies that may make significant impacts on the field of radar meteorology are discussed.

关键词： dual-polarization radar quantitative precipitation estimation precipitation microphysics drop size distribution numerical model

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利用卷积神经网络开展偏振雷达定量降水估测研究

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热带气象学报 2024年第1期40卷 64-74页

作者：蔡康龙胡志群谭浩波黄锦灿张伟强张晶晶植江玲佛山市龙卷风研究中心/中国气象局龙卷风重点开放实验室广东佛山528000 中国气象科学研究院灾害天气国家重点实验室北京100081 广东省气象局广东广州510080 高明区气象局广东佛山528000

利用偏振升级改造后的广州新一代天气雷达(CINRAD/SAD)水平反射率ZH、差分传播相移率KDP、差分反射率因子ZDR和广东佛山219个地面气象自动站雨量数据,形成不同偏振量组合的8个数据集。基于卷积神经网络(CNN),建立雷达定量降水估测网络架... 详细信息

利用偏振升级改造后的广州新一代天气雷达(CINRAD/SAD)水平反射率ZH、差分传播相移率KDP、差分反射率因子ZDR和广东佛山219个地面气象自动站雨量数据,形成不同偏振量组合的8个数据集。基于卷积神经网络(CNN),建立雷达定量降水估测网络架构QPEnet,并将该架构用于雷达定量降水估测(QPE),评估结果表明:数据集通道数N的增加可降低QPEnet的定量降雨估测的均方根误差(RMSE),并提高相关系数(CORR);对于由ZH形成的数据集Z、Z_1~3 km和Z_6 min,随着通道数N的增加,数据集Z、Z_1~3 km和Z_6 min的性能逐步得到提高,数据集Z_1~3 km和Z_6 min的均方根误差(RMSE)分别是4.71和3.78,比数值集Z分别降低了1.3%和18.7%;数据集Z_1~3 km和Z_6 min的CORR分别是0.82和0.88,比数据集Z分别提高了2.5%和10.0%;对于ZH、KDP和ZDR偏振量组成的数据集里面,数据集Z_ZDR_KDP的拟合性能最好,RMSE为3.97,比数据集Z的RMSE降低了14.6%,CORR是0.86,比数据集Z提高了7.5%;分别对0.6~5 mm、5~10 mm、10~20 mm、20~30 mm、30~40 mm、40~50 mm和50 mm以上的7个降水量级的均方根误差(RMSE)、平均偏差比(MBR)、平均误差(AE)和相对误差(RE)等的统计结果表明,数据集Z_6 min降雨精度最高。

关键词：定量降水估测卷积神经网络 S波段双偏振雷达测雨精度

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Applications of Wavelet Analysis in Differential Propagation Phase Shift Data De-noising

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Advances in Atmospheric Sciences 2014年第4期31卷 825-835页

作者： hu zhiqun LIU Liping State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences

Using numerical simulation data of the forward differential propagation shift （ΦDP） of polarimetric radar,the principle and performing steps of noise reduction by wavelet analysis are introduced in detail.Profiting from the multiscale analysis,various types of noises can be identified according to their characteristics in different scales,and suppressed in different resolutions by a penalty threshold strategy through which a fixed threshold value is applied,a default threshold strategy through which the threshold value is determined by the noise intensity,or a ΦDP penalty threshold strategy through which a special value is designed for ΦDP de-noising.Then,a hard-or soft-threshold function,depending on the de-noising purpose,is selected to reconstruct the signal.Combining the three noise suppression strategies and the two signal reconstruction functions,and without loss of generality,two schemes are presented to verify the de-noising effect by dbN wavelets：（1） the penalty threshold strategy with the soft threshold function scheme （PSS）; （2） the ΦDP penalty threshold strategy with the soft threshold function scheme （PPSS）.Furthermore,the wavelet de-noising is compared with the mean,median,Kalman,and finite impulse response （FIR） methods with simulation data and two actual cases.The results suggest that both of the two schemes perform well,especially when ΦDP data are simultaneously polluted by various scales and types of noises.A slight difference is that the PSS method can retain more detail,and the PPSS can smooth the signal more successfully.

关键词： polarimetric radar wavelet analysis differential propagation phase shift de-noising

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The Tibetan Plateau Surface–Atmosphere Coupling System and Its Weather and Climate Effects: The Third Tibetan Plateau Atmospheric Science Experiment

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Journal of Meteorological Research 2019年第3期33卷 375-399页

作者： Ping ZHAO Yueqing LI Xueliang GUO Xiangde XU Yimin LIU Shihao TANG Wenming XIAO Chunxiang SHI Yaoming MA Xing YU huizhi LIU La JIA Yun CHEN Yanju LIU Jian LI Dabiao LUO Yunchang CAO Xiangdong ZHENG Junming CHEN An XIAO Fang YUAN Donghui CHEN Yang PANG zhiqun hu Shengjun ZHANG Lixin DONG Juyang hu Shuai HAN Xiuji ZHOU State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences China Meteorological Administration Beijing 100081 National Climate Center China Meteorological Administration Beijing 100081 Meteorological Observation Center China Meteorological Administration Beijing 100081 Jiangxi Meteorological Observatory Nanchang 330096 Chengdu Institute of Plateau Meteorology of the China Meteorological Administration Chengdu 610072 Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 National Satellite Meteorological Center China Meteorological Administration Beijing 100081 National Meteorological Information Center China Meteorological Administration Beijing 100081 Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing 100101 Meteorological Institute of Shaanxi Province Xi'an 710014 Meteorological Observatory of Tibet Autonomous Region Lhasa 850000 National Meteorological Centery China Meteorological Administration Beijing 100081

The Tibetan Plateau(TP) is a key area affecting forecasts of weather and climate in China and occurrences of extreme weather and climate events over the world. The China Meteorological Administration, the National Natural Science Foundation of China, and the Chinese Academy of Sciences jointly initiated the Third Tibetan Plateau Atmospheric Science Experiment(TIPEX-Ⅲ) in 2013, with an 8–10-yr implementation plan. Since its preliminary field measurements conducted in 2013, routine automatic sounding systems have been deployed at Shiquanhe, Gaize, and Shenzha stations in western TP, where no routine sounding observations were available previously. The observational networks for soil temperature and soil moisture in the central and western TP have also been established. Meanwhile, the plateau-scale and regional-scale boundary layer observations, cloud–precipitation microphysical observations with multiple radars and aircraft campaigns, and tropospheric–stratospheric air composition observations at multiple sites, were performed. The results so far show that the turbulent heat exchange coefficient and sensible heat flux are remarkably lower than the earlier estimations at grassland, meadow, and bare soil surfaces of the central and western TP. Climatologically, cumulus clouds over the main body of the TP might develop locally instead of originating from the cumulus clouds that propagate northward from South Asia. The TIPEX-Ⅲ observations up to now also reveal diurnal variations, macro-and microphysical characteristics, and water-phase transition mechanisms, of cumulus clouds at Naqu station. Moreover, TIPEX-Ⅲ related studies have proposed a maintenance mechanism responsible for the Asian "atmospheric water tower" and demonstrated the effects of the TP heating anomalies on African, Asian, and North American climates. Additionally, numerical modeling studies show that the Γ distribution of raindrop size is more suitable for depicting the TP raindrop characteristics compared to the M–P distribution, the overestimation o

关键词： Tibetan Plateau field observation data processing weather and climate numerical forecasting

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Improving throughput through dynamically tuning contention window size in dense wireless network

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The Journal of China Universities of Posts and Telecommunications 2017年第4期24卷 27-33页

作者： Lin Shangjuan Wen Xiangming hu zhiqun Lu Zhaoming School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing 100876 China Beijing Key Laboratory of Network System Architecture and Convergence Beijing University of Posts and Telecommunications Beijing 100876 China Beijing Laboratory of Advanced Information Networks Beijing University of Posts and Telecommunications Beijing 100876 China

With the boom of wireless devices, the number of wireless users under wireless local area networks （WLANs） has increased dramatically. However, the standard baekoff mechanism in IEEE 802.11 adopts fixed initial contention window （CW） size without considering changes of network load, which leads to a high collision probability and low channel utilization in bursty arrivals. In this paper, a novel CW dynamic adjustment scheme is proposed to achieve high throughput performance in dense user environment. In the proposed scheme, the initial CW size is dynamically adjusted to optimum according to the measured packet collision probability. Simulation results show that the proposed scheme can significantly improve the throughput performance.

关键词： wireless local area network （WLAN） dense user environment contention window （CW） dynamic optimization

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QoE based power control scheme for interference mitigation in high-density WLANs

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The Journal of China Universities of Posts and Telecommunications 2016年第2期23卷 24-30页

作者： Wang Yiqing Wen Xiangming hu zhiqun Lu Zhaoming School of Telecommunication Engineering Beijing University of Posts and Telecommunications

Mobile data traffic is going through an explosive growth recently as mobile smart devices become more and more ubiquitous, causing huge pressure on cellular network. Taking advantage of its low cost and easy-to-deploy feature, wireless local-area networks（WLAN） becomes increasingly popular to offload data streams from cellular network, followed by higher and higher density of its deployment. However, the high density of WLAN will cause more interference, which results in degradation of its performance. Therefore, in order to enhance the performance of the network, we aim to minimize the interference caused by high density of WLAN. In this paper, we propose a novel power control scheme to achieve the above aim. We use the quality of experience（QoE） evaluation to coordinate the power of each access point（AP） and finally realize the optimization of the entire network. According to the simulation results, our scheme improves the performance of the network significantly in many aspects, including throughput and QoE.

关键词： power control high-density WLAN interference mitigation QoE

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