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Characteristics of cloud Water Resource and Precipitation Efficiency of Hydrometeors over Northwest china

Journal of meteorological Research 2023年第3期37卷 353-369页

作者： Zhanyu YAO Lin AN Pei ZHANG Liangshu GAO Shuo JIA Weijian WANG Wenhui ZHAO China Meteorological Administration Cloud–Precipitation Physics and Weather Modification Key Laboratory Weather Modification CentreChina Meteorological AdministrationBeijing 100081

Understanding the characteristics of cloud water resource(CWR)and precipitation efficiency of hydrometeors(PEh)is imperative for the application of CWR in Northwest *** atmospheric precipitable water(PW)in all four seasons and clouds and PEh in summer were studied with ERA-5 and cloudSat data in this *** results show that topography,especially in the Tibetan Plateau,exerts significant impacts on the precipitation and PW in summer,since large amounts of clouds are distributed along the mountain *** study region is divided into four typical areas:the monsoon area in eastern Northwest china(NWE),the Qilian Mountains area(QM),the Tianshan Mountains area(TM),and the Source of Three Rivers area(STR).Over the four areas,cloud top height(6.3 km)and cloud base height(3.3 km)over NWE are higher,and precipitating clouds are thicker(7 km)in the single-layer *** water content decreases with increasing altitude,while the ice water content first increases and then *** water path is higher over NWE(0.11 kg m^(−2))than over TM and STR(0.05 kg m^(−2)),and the ice water path is mainly concentrated within the range of 0.025–0.055 kg m^(−2).The PEh values are distributed unevenly and affected evidently by the *** the PEh values in the four typical areas(0.3–0.6)are higher than those in other regions,the CWR is relatively abundant and has a higher exploitation ***,it is well-founded to exploit CWR for alleviating water shortages in these areas of Northwest china in summer.

关键词： cloud water resource(CWR) precipitation efficiency of hydrometeors(PEh) precipitable water(PW) cloud Northwest china

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Shape Classification of cloud Particles Recorded by the 2D-S Imaging Probe Using a Convolutional Neural Network

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Journal of meteorological Research 2023年第4期37卷 521-535页

作者： Rong ZHANG Haixia XIAO Yang GAO Haizhou SU Dongnan LI Lei WEI Junxia LI Hongyu LI Cloud–Precipitation Physics and Weather Modification Key Laboratory(CPML) China Meteorological AdministrationBeijing 100081 CMA Weather Modification Centre China Meteorological Administration(CMA)Beijing 100081 Key Laboratory of Transportation Meteorology of China Meteorological Administration Nanjing Joint Institute for Atmospheric SciencesNanjing 210041 Heilongjiang Weather Modification Office Harbin 150030

The airborne two-dimensional stereo(2D-S) optical array probe has been operating for more than 10 yr, accumulating a large amount of cloud particle image data. However, due to the lack of reliable and unbiased classification tools,our ability to extract meaningful morphological information related to cloud microphysical processes is limited. To solve this issue, we propose a novel classification algorithm for 2D-S cloud particle images based on a convolutional neural network(CNN), named CNN-2DS. A 2D-S cloud particle shape dataset was established by using the 2D-S cloud particle images observed from 13 aircraft detection flights in 6 regions of china(Northeast, Northwest, North,East, Central, and South china). This dataset contains 33,300 cloud particle images with 8 types of cloud particle shape(linear, sphere, dendrite, aggregate, graupel, plate, donut, and irregular). The CNN-2DS model was trained and tested based on the established 2D-S dataset. Experimental results show that the CNN-2DS model can accurately identify cloud particles with an average classification accuracy of 97%. Compared with other common classification models [e.g., Vision Transformer(ViT) and Residual Neural Network(ResNet)], the CNN-2DS model is lightweight(few parameters) and fast in calculations, and has the highest classification accuracy. In a word, the proposed CNN-2DS model is effective and reliable for the classification of cloud particles detected by the 2D-S probe.

关键词： cloud particles particle shape 2D-S probe shape classification convolutional neural network

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Airborne Investigation of Riming:cloud and Precipitation Microphysics within a Weak Convective System in North china

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Advances in Atmospheric Sciences 2025年第3期42卷 515-526页

作者： Xiangfeng HU Hao HUANG Shaoyu HOU Kun ZHAO Chuanfeng ZHAO Yinghui LU Jiefang YANG Rong ZHANG Delong ZHAO Weiguo LIU Dan ZHANG Haixia XIAO Key Laboratory of Radar Meteorology and State Key Laboratory of Severe Weather China Meteorology AdministrationBeijing 100044China China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory Xiong'an New AreaHebei 071703China Hebei Provincial Weather Modification Center ShijiazhuangHebei 051430China School of Atmospheric Sciences Key Laboratory of Mesoscale Severe Weather/MOEand Frontiers Science Center for Critical Earth Material CyclingNanjing UniversityJiangsu 210023China Department of Atmospheric and Oceanic Sciences School of PhysicsPeking UniversityBeijing 100871China Laboratory of Cloud-Precipitation Physics and Severe Storms Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Cloud-Precipitation Physics and Weather Modification Key Laboratory China Meteorology AdministrationBeijing 100044China Beijing Weather Modification Center Beijing 100089China Nanjing Joint Institute for Atmospheric Sciences NanjingJiangsu 210000China

The process of riming significantly impacts the microphysical characteristics of *** study uses aircraft and radar observation data in stratiform clouds with convection embedded that occurred in the central and southern regions of North china on 22 May *** microphysical structural characteristics and processes near the embedded convection core and in the stratiform cloud are analyzed *** attention is given to the effect of riming on the microphysical properties near the upper boundary of the melting layer and to the factors influencing riming *** collaborative observations reveal that the particle size distributions observed near the convection core and in the stratiform region are close,while the particle properties like habit and riming degree are quite *** the melting layer,larger plate-like ice particles and supercooled water droplets(D>50μm)are more abundant near the convective core,leading to higher collision efficiencies between ice particles and supercooled water *** fluctuation amplitudes of vertical airflow near the convective core also contribute to the increased riming activity and the formation of more heavily rimed particles,such as ***,in situ measurements from airborne probes also revealed that above the melting layer,the riming process involves two stages:the mass of snow crystals grows as supercooled droplets merge internally without changing size,followed by external freezing that significantly enlarges the crystals.

关键词： riming collision efficiency airflow fluctuation particle habit aircraft measurement

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Operational Plan,Effect Verification,and key Technical Settings for a Stadium-Scale Artificial Rain Reduction Experiment

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Journal of meteorological Research 2023年第5期37卷 643-665页

作者： Yuquan ZHOU Siyao LIU Miao CAI Junlin LONG Jia WANG CMA Cloud–Precipitation Physics and Weather Modification Key Laboratory(CPML) Weather Modification CentreChina Meteorological Administration(CMA)Beijing 100081 School of Electronic Engineering Chengdu University of Information TechnologyChengdu 610225 College of Meteorological Observation Chengdu University of Information Technology/CMA Key Laboratory of Atmospheric SoundingChengdu 610225 Jiangsu Weather Modification Center Nanjing 210000

To explore the key technologies of artificial weather modification for specific targets(e.g.,a stadium)and improve the efficiency of artificial rainfall modification for major events,this study conducts an artificial rainfall reduction experiment for the closing ceremony of Nanjing Youth Olympic Games on 28 August *** retrievals,radar observations,sounding data,and other sources of information as well as cloud and Precipitation Accurate Analysis System(CPAS)are used in this *** main conclusions are as follows.(1)On 28 August 2014,a large-scale cumulus cloud system with mixed-phase stratocumulus and stratus precipitation was *** system was influenced by the weak shear of a low-level trough and the precipitation was dominated by cold clouds with dry layers between ***,we adopted the crystal-priming over-catalytic hypothesis and conducted a rocket-catalytic rain abatement operation at a certain distance(100–25 km)from the *** shootings of different intensities were implemented for two echoes that affected the stadium successively(two rounds of 15 rocket shootings within15 min for an isolated weak echo IA;multiple rounds of 156 rocket shootings within 80 min for a strong echo IB).Amazingly,after the shootings with the catalysis in the air,reflectivity of the two echoes was reduced at all altitudes with the most significant reduction at the 2-km altitude,and the time needed for the obvious reduction was 40 *** most obvious reduction of the two echoes then maintained for 60 and 53 min,respectively,and the operation time needed for the echo zone to recover after the stop of rocket shooting was 108 min for echo IA and 90 min for echo *** two echoes moving across the stadium during the time period of the closing ceremony(2000–2130 local time)were at their minimal strengths,with almost no echo over the target *** demonstrates that the rocket shooting strategy of over-crystallization catalysis is effective,and th

关键词： target area artificial rainfall abatement radar monitoring weather modification plan effect analysis

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Leveraging Deep Learning to Extract Raindrop Size Gamma Distribution Parameters from Wind Profile Radar Data

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Journal of meteorological Research 2025年第2期39卷 404-414页

作者： Yu HUANG Zhiqun HU Lin LI Ru ZHOU Xu LU Mengyu HUANG Beijing Weather Modification Centre Field Experiment Base of Cloud and Precipitation Research in North China Chinese Academy of Meteorological Sciences China Meteorological Administration Beijing Meteorological Observation Centre Field Experiment Base of Cloud and Precipitation Research in North China China Meteorological Administration Key Laboratory of Smart Earth

Raindrop size distribution (DSD) is crucial in the study of precipitation microphysics, but the parameters that characterize the DSD is not easy to be derived accurately. Wind profile radar (WPR) provides rich data with high spatiotemporal resolution and low attenuation, and the previous studies using WPR power spectral distribution to extract DSD parameters demonstrate certain limitations. In this study, a WPR-based Gamma DSD parameter estimation network (WPR-DSDnet) combined with a neural network (NN) and a long short-term memory (LSTM) network is designed, and then a WPR-DSDnet-based model is trained to retrieve the Gamma DSD parameters including normalized intercept parameter (Nw) and mass-weighted average diameter (Dm) by means of the high-resolution WPR reflectivity factor and velocity spectral width as the inputs, and the spatiotemporal matching disdrometer data collected from 2017 to 2021 in Beijing as labels. Two precipitation cases are used to validate the performance of the model,and the results demonstrate that the model can retrieve the Gamma DSD parameters effectively, in which the ratio between the estimated and measured values of both lg Nw and Dm exceeds 99%. The estimation accuracy of lg Nw is slightly better than that of Dm due to smaller relative deviation of lg Nw although the absolute deviation between the estimated and true values of lg Nw is larger than that of Dm, which are probably caused by the larger distribution range of lg Nw. The vertical distributions of lg Nw closely aligns with variations in precipitation intensity, which hints it is a useful indicator for precipitation intensity change. On the other hand, the distribution of Dm is closely associated with the degree of convection, which is valuable for precipitation recognition and classification. The two parameters extracted by the deep learning-based model can facilitate further in-depth analysis on precipitation characteristics and mechanisms with WPR data.

关键词： deep learning disdrometer Gamma distribution parameter estimation wind profile radar

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Aircraft Observation and Simulation of the Supercooled Liquid Water Layer in a Warm Conveyor Belt over North china

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Advances in Atmospheric Sciences 2024年第3期41卷 529-544页

作者： Jiefan YANG Fei YAN Hengchi LEI Shuo JIA Xiaobo DONG Xiangfeng HU Key Laboratory of Cloud Physics and Severe Storms Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Weather modification office of Hebei Province Hebei Meteorology AdministrationShijiazhuang 050000China

This paper studied a snow event over North china on 21 February 2017,using aircraft in-situ data,a Lagrangian analysis tool,and WRF simulations with different microphysical schemes to investigate the supercooled layer of warm conveyor belts(WCBs).Based on the aircraft data,we found a fine vertical structure within clouds in the WCB and highlighted a 1-2 km thin supercooled liquid water layer with a maximum Liquid Water Content(LWC) exceeding0.5 g kg^(-1) during the vertical aircraft *** the main features of thermodynamic profiles were essentially captured by both modeling schemes,the microphysical quantities exhibited large diversity with different microphysics *** conventional Morrison two-moment scheme showed remarkable agreement with in-situ observations,both in terms of the thermodynamic structure and the supercooled liquid water ***,the microphysical structure of the WCB clouds,in terms of LWC and IWC,was not apparent in HUJI fast bin *** reduce such uncertainty,future work may focus on improving the representation of microphysics in bin schemes with in-situ data and using similar assumptions for all schemes to isolate the impact of physics.

关键词： warm conveyor belt Microphysical properties supercooled liquid water microphysics schemes

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cloud Microphysical Processes and Atmospheric Water Budget during the 20 July 2021 Extreme Precipitation Event in Zhengzhou,china

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Journal of meteorological Research 2023年第5期37卷 722-742页

作者： Weixi SHU Danhong FU Hui XIAO Huiling YANG Yue SUN Xueliang GUO Yang ZHAO Jianfang DING Shujing SHEN Key Laboratory of Cloud–Precipitation Physics and Severe Storms(LACS) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 School of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049 School of Earth and Space Sciences University of Science and Technology of ChinaHefei 230026 Weather Modification Center of Henan Province Zhengzhou 450003 CMA Cloud–Precipitation Physics and Weather Modification Key Laboratory Weather Modification CentreChina Meteorological Administration(CMA)Beijing 100081

This study investigated the cloud microphysical processes and atmospheric water budget during the extreme precipitation event on 20 July 2021 in Zhengzhou of Henan Province,china,based on observations,reanalysis data,and the results from the high-resolution large-eddy simulation nested in the weather Research and Forecasting(WRF)model with assimilation of satellite and radar *** results show that the abundant and persistent southeasterly supply of water vapor,induced by Typhoons In-Fa and Cempaka,under a particular synoptic pattern featured with abnormal northwestward displacement of the western Pacific subtropical high,was conducive to warm rain processes through a high vapor condensation rate of cloud water and an efficient collision–coalescence process of cloud water to *** conditions were favorable for the formation and maintenance of the quasi-stationary warmsector heavy *** formation through the collision–coalescence process of cloud water to rainwater accounted for approximately 70%of the total,while the melting of snow and graupel accounted for only approximately 30%,indicating that warm cloud processes played a dominant role in this extreme rainfall ***,enhancement of cold cloud processes promoted by latent heat release also exerted positive effect on rainfall during the period of most intense hourly *** was also found that rainwater advection from outside of Zhengzhou City played an important role in maintaining the extreme precipitation event.

关键词： extreme precipitation event microphysical processes atmospheric water budget large-eddy simulation

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Improved forecasting via physics-guided machine learning as exemplified using“21·7”extreme rainfall event in Henan

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Science china Earth Sciences 2024年第5期67卷 1652-1674页

作者： Qi ZHONG Zhicha ZHANG Xiuping YAO Shaoyu HOU Shenming FU Yong CAO Linguo JING China Meteorological Administration Training Center Beijing 100081China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Zhejiang Meteorological Observatory Hangzhou 310017China Hebei Provincial Weather Modification Center Shijiazhuang 050020China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China National Meteorological Center Beijing 100081China School of Computer Science Chengdu University of Information TechnologyChengdu 610225China

As a natural disaster,extreme precipitation is among the most destructive and influential,but predicting its occurrence and evolution accurately is very challenging because of its rarity and *** the example of the“21·7”extreme precipitation event(17–21 July 2021)in Henan Province,this study explores the potential of using physics-guided machine learning to improve the accuracy of forecasting the intensity and location of extreme *** physics-guided ways of embedding physical features,fusing physical model forecasts and revised loss function are used,i.e.,(1)analyzing the anomalous circulation and thermodynamical factors,(2)analyzing the multi-model forecast bias and the associated underlying reasons for it,and(3)using professional forecasting knowledge to design the loss function,and the corresponding results are used as input for machine learning to improve the forecasting *** results indicate that by learning the relationship between anomalous physical features and heavy precipitation,the forecasting of precipitation intensity is improved significantly,but the location is rarely adjusted and more false alarms *** reasons for this are as *** anomalous features used here mainly contain information about large-scale systems and factors which are consistent with the model precipitation deviation;moreover,the samples of extreme precipitation are sparse and so the algorithm used here is ***,by combining“good and different”multi models with machine learning,the advantages of each model are extracted and then the location of the precipitation center in the forecast is improved ***,by combining the appropriate anomalous features with multi-model fusion,an integrated improvement of the forecast of the rainfall intensity and location is ***,this study is a novel exploration to improve the refined forecasting of heavy precipitation with extreme intensity and high variability,

关键词： Extreme precipitation event Refined assessment Anomalous physical features Multi-model fusion Machine learning

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Assessment of Geostationary Satellite cloud Effective Radius over East china with In Situ Aircraft Measurements

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Journal of meteorological Research 2025年第2期39卷 240-251页

作者： Qiuli ZHANG Chao LIU Rong ZHANG Jing YANG Junxia LI Bo LI Feng LU Yan YIN Hongchun JIN Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/China Meteorological Administration (CMA) Aerosol–Cloud–Precipitation Key Laboratory School of Atmospheric PhysicsNanjing University of Information Science&Technology CMA Weather Modification Centre CMA Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites National Satellite Meteorological Centre (National Centre for Space Weather) and Innovation Centre for Fengyun Meteorological Satellite (FYSIC)CMA Ku Weather Science and Technology Co.Ltd.

cloud effective radius (CER) is a fundamental microphysical property of clouds,critical for understanding cloud formation and radiative *** spectral imagers,widely utilized in passive remote sensing,facilitate the monitoring of cloud characteristics,including CER,over extended time periods and spatial *** observational methods have been employed to evaluate satellite cloud property products;however,in situ measurement evaluations of CER remain limited,particularly for products over *** study utilized aircraft observations provided by the china meteorological administration weather modification Centre to evaluate the CER retrieved by Fengyun-4A Advanced Geosynchronous Radiation Imager (AGRI) and Himawari-8 Advanced Himawari Imager (AHI).Three flights were selected from the aircraft dataset for evaluation,involving flights through non-precipitating stratiform clouds with stable,high-quality *** data selection and collocation procedures were employed to ensure a comprehensive *** retrievals from heterogeneous cloud fields were excluded,and representative in-cloud aircraft measurements were identified through multi-parameter *** flight trajectory was adjusted to account for horizontal cloud movement corresponding to time differences between observations from different ***,in situ measurements from different vertical layers were adjusted to a comparable position near the cloud *** indicate that CER retrieved from satellites is generally overestimated compared to in situ *** AGRI,the average difference (AD) is 2.90μm,with a root mean square difference (RMSD) of 3.53μ*** AHI,the AD is 2.92μm,and the RMSD is 3.59μ*** enhance future validation and evaluation of remote sensing results,factors such as instrument calibration,flight patterns,and cloud conditions will be carefully *** the number of cases should further reduce errors associated

关键词： cloud effective radius cloud microphysics in situ measurements satellite retrievals

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Recent Enhanced Deep Troposphere-to-Stratosphere Air Mass Transport Accompanying the Weakening Asian Monsoon

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Journal of meteorological Research 2024年第4期38卷 708-719页

作者： Bin CHEN Jianzhong MA Wei ZHANG Jianchun BIAN Tianliang ZHAO Xiangde XU State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing100081China Department of Plants Soils and ClimateUtah State UniversityUT84322USA Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological AdministrationNanjing University of Information Science&TechnologyNanjing 210044China

The Asian monsoon(AM) region is a well-known region with prevailing stratosphere–troposphere exchange(STE).However,how the STE across this region changes with the weakening AM remains ***,we particularly diagnose the air mass transport between the planetary boundary layer(PBL) and the stratosphere over the AM region during 1992–2017 using the Lagrangian particle dispersion model FLEXPART based on the ERA-Interim reanalysis *** results show that both the downward and upward deep STEs exhibit a detectable increasing trend,while the latter,namely,the deep troposphere-to-stratosphere transport(DTST),is relatively more *** analysis reveals that the long-term trend of DTST over the AM region could be partly attributed to changes in the Pacific Walker circulation and the air temperature(especially at upper levels).Additionally,it is found that DTST increases markedly over the tropical oceanic regions,while the increasing DTST into the stratosphere can be attributed to the enhanced air masses originated from the PBL over the terrestrial regions,where large amounts of pollutant emissions *** results imply that the influence of the DTST on the chemical composition and the climate of the stratosphere over the AM region is expected to become increasingly important,and is thereby of relevance to climate projection in an evolving climate.

关键词： stratosphere–troposphere exchange(STE) air mass transport deep troposphere-to-stratosphere transport(DTST) Asian monsoon(AM) pollution

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