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Sub-Seasonal Predictability of the Northeast China Cold Vortex in BCC and ECMWF S2S Model Forecasts for 2006-2021

Journal of meteorological Research 2024年第3期38卷 453-468页

作者： Yiqiu YU Jie WU Yihe FANG Chunyu ZHAO Zongjian KE Yitong LIN Liaoning provincial Climate Centre Liaoning Provincial Meteorological AdministrationShenyang110166China Key Opening Laboratory for Northeast China Cold Vortex Research China Meteorological AdministrationShenyang110166China Panjin National Climate observatory Panjin124000China China meteorological Administration Key Laboratory for Climate Prediction Studies National Climate CentreChina Meteorological AdministrationBeijing100081China Jilin provincial Climate Centre Jilin Provincial Meteorological AdministrationChangchun130062China

As an important atmospheric circulation system in the mid-high latitudes of East Asia,the Northeast China cold vortex(NCCV)substantially influences weather and climate in this *** far,systematic assessment on the performance of numerical prediction of the NCCVs has not been carried *** on the Beijing Climate Centre(BCC)and the ECMWF model hindcast and forecast data that participated in the Sub-seasonal to Seasonal(S2S)Prediction Project,this study systematically examines the performance of both models in simulating and forecasting the NCCVs at the sub-seasonal *** results demonstrate that the two models can effectively capture the seasonal variations in the intensity,active days,and spatial distribution of NCCVs;however,the duration of NCCVs is shorter and the intensity is weaker in the models than in the *** analysis shows that the differences in the intensity and location of the East Asian subtropical westerly jet and the wave train pattern from North Atlantic to East Asia may be responsible for the deficient simulation of NCCV events in the S2S ***,in the deterministic forecasts,BCC and ECMWF provide skillful prediction on the anomalous numbers of NCCV days and intensity at a lead time of 4-5(5-6)pentads,and the skill limit of the ensemble mean is 1-2 pentads longer than that of individual *** the probabilistic forecasts of daily NCCV activities,BCC and ECMWF exhibit a forecasting skill of approximately 7 and 11 days,respectively;both models show seasonal dependency in the simulation performance and forecast skills of NCCV events,with better performance in winter than in *** results from this study provide helpful references for further improvement of the S2S prediction of NCCVs.

关键词： Northeast China cold vortex(NCCV) predictability sub-seasonal to seasonal(S2S)prediction deterministic forecast probabilistic forecast

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Growth and Interactions of Multi-Source Perturbations in Convection-Allowing Ensemble Forecasts

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Journal of Tropical Meteorology 2024年第2期30卷 118-131页

作者：张璐闵锦忠庄潇然王世璋魏莉青 Key Laboratory of meteorological Disaster of Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of meteorological Disasters Nanjing University of Information Science and TechnologyNanjing 210044 China jiangsu meteorological observatory Jiangsu Meteorological ServiceNanjing 210008 China Nanjing Joint Institute for Atmospheric Sciences Nanjing 210000 China

This study investigated the growth of forecast errors stemming from initial conditions(ICs),lateral boundary conditions(LBCs),and model(MO)perturbations,as well as their interactions,by conducting seven 36 h convectionallowing ensemble forecast(CAEF)*** cases,one with strong-forcing(SF)and the other with weak-forcing(WF),occurred over the Yangtze-Huai River basin(YHRB)in East China,were selected to examine the sources of uncertainties associated with perturbation growth under varying forcing backgrounds and the influence of these backgrounds on *** perturbations exhibited distinct characteristics in terms of temporal evolution,spatial propagation,and vertical distribution under different forcing backgrounds,indicating a dependence between perturbation growth and forcing background.A comparison of the perturbation growth in different precipitation areas revealed that IC and LBC perturbations were significantly influenced by the location of precipitation in the SF case,while MO perturbations were more responsive to convection triggering and dominated in the WF *** vertical distribution of perturbations showed that the sources of uncertainties and the performance of perturbations varied between SF and WF cases,with LBC perturbations displaying notable case ***,the interactions between perturbations were considered by exploring the added values of different source *** the SF case,the added values of IC,LBC,and MO perturbations were reflected in different forecast periods and different source uncertainties,suggesting that the combination of multi-source perturbations can yield positive *** the WF case,MO perturbations provided a more accurate estimation of uncertainties downstream of the Dabie Mountain and need to be prioritized in the research on perturbation development.

关键词： convection-allowing ensemble forecast forcing background perturbation growth interactions added value

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Microphysical Insights into a Tornadic Supercell from Dual-Polarization Radar Observations in jiangsu, China on 14 May 2021

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Journal of meteorological Research 2024年第2期38卷 303-320页

作者： Chao YUAN Yang BAI Pengfei SUN Hua BAI Lu XIA China meteorological Administration Tornado Key Laboratory Foshan 528315 Institute of Atmospheric Environment China Meteorological AdministrationShenyang 110166 Panjin National Climate observatory Panjin 124010 Yangzhou meteorological Bureau of jiangsu Province Yangzhou 225100 Yichun meteorological Bureau of Heilongjiang Province Yichun 153000

Tornadoes are incredibly powerful and destructive natural events,yet the microphysical characteristics of the parent storm and its effects on tornadogenesis remain *** study analyzed polarization radar data of a tornadic supercell that occurred in jiangsu Province of China on 14 May 2021,in comparison with another tornadic supercell and two non-tornadic supercells that occurred in the same region in *** two tornadic supercells exhibited lower differential reflectivity(ZDR)in the hook echo region compared with the non-tornadic supercells,indicating smaller median drop sizes.A distinct increase in ZDR from the melting of frozen hydrometeors,observed between2.5-and 4.0-km altitude in the non-tornadic storms,was absent in the tornadic *** non-tornadic supercells also displayed substantially higher specific differential phase(KDP)below the melting level,likely aroused from enhanced melting and *** findings suggest fundamental microphysical contrasts between tornadic and nontornadic ***,tornadic supercells have smaller droplets and may reduce melting in hook ***,greater separation between the ZDR arc and the KDP foot was observed during *** vertical gradient of KDP related to the cooling pool strength of the hook echo,regulating rear-flank downdraft *** the limited number of cases investigated,the findings of this study indicate that monitoring ZDR,KDP,and drop size distribution trends could assist with tornado prediction and warnings.

关键词： tornado polarimetric radar supercell hook echo drop size distribution

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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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Comparative Analysis of Energy Characteristics of Two Southwest Vortices in Sichuan Under Similar Circulation Backgrounds

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Journal of Tropical Meteorology 2024年第2期30卷 168-179页

作者：周春花张驹肖红茹 Sichuan meteorological Disaster Prevention Technology Center Chengdu 610072 China Chengdu meteorological Bureau Chengdu 610072 China Sichuan meteorological observatory Chengdu 610072 China

Based on ERA5 reanalysis data,the present study analyzed the thermal energy development mechanism and kinetic energy conversion characteristics of two extreme rainstorm processes in relation to the shallow southwest vortex in the warm-sector during a“rain-generated vortex”process and the deep southwest vortex in a“vortex-generated rain”*** findings were as follows:(1)During the extreme rainstorm on August 11,2020(hereinafter referred to as the“8·11”process),intense surface heating and a high-energy unstable environment were *** mesoscale convergence system triggered convection to produce heavy rainfall,and the release of latent condensation heat generated by the rainfall promoted the formation of a southwest *** significant increase(decrease)in atmospheric diabatic heating and kinetic energy preceded the increase(decrease)in *** contrast,the extreme rainstorm on August 16,2020(hereinafter referred to as the“8·16”process)involved the generation of southwest vortex in a low-energy and highhumidity *** dynamic uplift of the southwest vortex triggered rainfall,and the release of condensation latent heat from rainfall further strengthened the development of the southwest *** significant increase(decrease)in atmospheric diabatic heating and kinetic energy exhibited a delayed progression compared to the increase(decrease)in vorticity.(2)The heating effect around the southwest vortex region was non-uniform,and the heating intensity varied in different *** the“8·11”process,the heating effect was the strongest in the initial stage,but weakened during the vortex's *** the contrary,the heating effect was initially weak in the“8·16”process,and intensified during the development stage.(3)The available potential energy of the“8·11”process significantly increased in kinetic energy converted from rotational and divergent winds through baroclinic action,and the divergent wind energy continued to convert into rotatio

关键词： southwest vortex similar circulation background diabatic heating kinetic energy spatial non-uniform heating effect

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Raindrop Size Distributions in the Zhengzhou Extreme Rainfall Event on 20 July 2021:Temporal-Spatial Variability and Implications for Radar QPE

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Journal of meteorological Research 2024年第3期38卷 489-503页

作者： Liman CUI Haoran LI Aifang SU Yang ZHANG Xiaona LYU Le XI Yuanmeng ZHANG Henan Key Laboratory of Agrometeorological Support and Applied Technique China Meteorological AdministrationZhengzhou450003China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing100081China Henan meteorological observatory Zhengzhou450003China

In this study,a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is employed to investigate the temporal-spatial variability of raindrop size distributions(DSDs)in the Zhengzhou extreme rainfall event on 20 July *** rain rates observed by disdrometers and rain gauges from six operational sites are in good agreement,despite significant site-to-site variations of 24-h accumulated rainfall ranging from 198.3 to 624.1 *** Parsivel OTT observations show prominent temporal-spatial variations of DSDs,and the most drastic change was registered at Zhengzhou Station where the record-breaking hourly rainfall of 201.9 mm over 1500-1600 LST(local standard time)was *** hourly rainfall is characterized by fairly high concentrations of large raindrops,and the mass-weighted raindrop diameter generally increases with the rain rate before reaching the equilibrium state of DSDs with the rain rate of about 50 mm h^(−1).Besides,polarimetric radar observations show the highest differential phase shift(K_(dp))and differential reflectivity(Z_(dr))near surface over Zhengzhou Station from 1500 to 1600 *** light of the remarkable temporal-spatial variability of DSDs,a reflectivity-grouped fitting approach is proposed to optimize the reflectivity-rain rate(Z-R)parameterization for radar quantitative precipitation estimation(QPE),and the rain gauge measurements are used for *** results show an increase of mean bias ratio from 0.57 to 0.79 and a decrease of root-mean-square error from 23.69 to 18.36 for the rainfall intensity above 20.0 mm h^(−1),as compared with the fixed Z-R *** study reveals the drastic temporal-spatial variations of rain microphysics during the Zhengzhou extreme rainfall event and warrants the promise of using reflectivity-grouped fitting Z-R relationships for radar QPE of such events.

关键词： extreme rainfall raindrop size distribution radar quantitative precipitation estimation(QPE)

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Characterization and Application of S-Band Polarimetric Radar and X-Band Phased Array Radar for a Tornadic Storm Event on June 16,2022

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Journal of Tropical Meteorology 2024年第2期30卷 189-199页

作者：陈炳洪傅佩玲张羽苏冉田聪聪陈超 Guangzhou meteorological observatory Guangzhou 511430 China China meteorological Administration Tornado Key Laboratory Guangdong Meteorological ServiceFoshanGuangdong 528010 China Collaborative Innovation Center for Smart Meteorology of Guangzhou Guangzhou 511430 China Guangdong meteorological observatory Guangzhou 510640 China

The X-band phased array radar offers faster scanning speed and higher spatial resolution compared to the S-band radar,making it capable of enhancing tornado monitoring and early warning *** study analyzed the characteristics and nowcasting signals of a tornado case that occurred on June 16,2022 in the Guangzhou *** findings indicate that the violent contraction of rotation radius and the dramatic increase in rotation speed were important signal characteristics associated with tornado *** X-band phased array radar,with its high temporal and spatial resolution,provided an opportunity to capture early warning signals from polarimetric *** X-band phased array radar demonstrated noteworthy ability to identify apparent tornado vortex signature(TVS)features in a 10-minute lead time,surpassing the capabilities of the CINRAD/SA ***,due to its higher scanning frequency,the Xband phased-array radar was capable of consistently identifying TVS with shorter intervals,enabling a more precise tracking of the tornado's *** application of professional radars,in this case,provides valuable insights for the monitoring of evolutions of severe local storms and even tornadoes and the issuance of early warning signals.

关键词： tornadoes X-band phased array radar mesocyclone rotation radius

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An Evaluation of Tropical Cyclone Genesis Forecast over the Western North Pacific and the South China Sea from the CMA-TRAMS

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Journal of Tropical Meteorology 2024年第1期30卷 20-28页

作者：李梦婕陈子通戴光丰田群梁卓轩林青张艳霞 Guangzhou Institute of Tropical and Marine Meteorology/Guangdong provincial Key Laboratory of Regional Numerical Weather Prediction CMAGuangzhou 510641 China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081 China Guangdong meteorological observatory Guangzhou 510641 China

Tropical cyclone(TC) genesis forecasting is essential for daily operational practices during the typhoon *** updated version of the Tropical Regional Atmosphere Model for the South China Sea(CMA-TRAMS) offers forecasters reliable numerical weather prediction(NWP) products with improved configurations and fine resolution. While traditional evaluation of typhoon forecasts has focused on track and intensity, the increasing accuracy of TC genesis forecasts calls for more comprehensive evaluation methods to assess the reliability of these predictions. This study aims to evaluate the effectiveness of the CMA-TRAMS for cyclogenesis forecasts over the western North Pacific and South China Sea. Based on previous research and typhoon observation data over five years, a set of localized, objective criteria has been proposed. The analysis results indicate that the CMA-TRAMS demonstrated superiority in cyclogenesis forecasts, predicting 6 out of 22 TCs with a forecast lead time of up to 144 h. Additionally, over 80% of the total could be predicted 72 h in advance. The model also showed an average TC genesis position error of 218.3 km, comparable to the track errors of operational models according to the annual evaluation. The study also briefly investigated the forecast of Noul(2011). The forecast field of the CMA-TRAMS depicted thermal and dynamical conditions that could trigger typhoon genesis, consistent with the analysis field. The 96-hour forecast field of the CMA-TRAMS displayed a relatively organized threedimensional structure of the typhoon. These results can enhance understanding of the mechanism behind typhoon genesis,fine-tune model configurations and dynamical frameworks, and provide reliable forecasts for forecasters.

关键词： CMA-TRAMS cyclogenesis numerical weather prediction tropical cyclone

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Study on Quantitative Precipitation Estimation by Polarimetric Radar Using Deep Learning

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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 *** this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are ***,a self-defined loss function(SLF)is proposed during *** 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 *** 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)***,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,*** 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 *** 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 ***,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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Impact of EnKF assimilating Himawari-8 all-sky infrared radiance on the forecasting of a warm-sector rainstorm event

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Science China Earth Sciences 2024年第10期67卷 3110-3127页

作者： Shanshan LOU Lei ZHU Xuexing QIU Guangzhou CHEN Song YUAN Shengnan ZHOU Anhui meteorological observatory Hefei 230031China Key Laboratory of meteorological Disaster Ministry of Education(KLME)Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Joint International Research Laboratory of Climate and Environment Change(ILCEC)Nanjing University of Information Science&TechnologyNanjing 210044China Huaihe River Basin meteorological Center Hefei 230031China Shouxian National Climatology observatory Huaihe River Basin Typical Farm Eco-Meteorological Experiment Field of CMAShouxian National Comprehensive Meteorological Observation Special Experimental OutfieldShouxian 232200China Anhui Province Key Laboratory of Atmospheric Science and Satellite Remote Sensing Hefei 230031China

Warm-sector rainstorms are highly localized events, with weather systems and triggering mechanisms are not obvious,leading to limited forecasting capabilities in numerical models. Based on the ensemble Kalman filter(PSU-En KF) assimilation system and the regional mesoscale model WRF, this study conducted a simulation experiment assimilating all-sky infrared(IR)radiance for a warm-sector rainstorm in East China and investigated the positive impact of assimilating the Himawari-8 moisture channel all-sky IR radiance on the forecast of the rainstorm. Results indicate that hourly cycling assimilation of all-sky IR radiance can significantly improve the forecast accuracy of this warm-sector rainstorm. There is a notable increase in the Threat Score(TS), with the simulated location and intensity of the 3-hour precipitation aligning more closely with observations. These improvements result from the assimilation of cloud-affected radiance, which introduces more mesoscale convective information into the model's initial fields. The adjustments include enhancements to the moisture field, such as increased humidity and moisture transport, and modifications to the wind field, including the intrusion of mid-level cold air and the strengthening of lowlevel convergent shear. These factors are critical in improving the forecast of this warm-sector rainstorm event.

关键词： Ensemble Kalman filter WRF model Himawari-8 All-sky radiance Warm-sector rainstorm

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