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Tropical Cyclone Research and Review 2012年第3期1卷 331-339页

作者： M.MOHAPATRA D.P.NAYAK B.K.BANDYOPADHYAY india meteorological department Mausam Bhavan

india meteorological department(IMD) introduced cone of uncertainty(COU) in cyclonic disturbances(CDs) alongwith the 72 hr track forecast over the north india Ocean(NIO) in 2009. The track forecast for CDs is issued for +6, +12, +18, +24, +36, +48, +60 and +72 hrs time period from the stage of deep depression onwards. An attempt is made to evaluate COU forecast issued by IMD during 2009-2011(3 years). The size of the cone is deduced from climatological track forecast errors. The accuracy of COU forecast has been analysed with respect to basin of formation, season of formation, intensity and type of track(climatological/straight moving and recurving/looping type) of CDs by calculating percentage of total number of forecasts in each category lying within COU. The observed track lies within the forecast COU in about 60% of the cases over the NIO. The accuracy of COU forecast is about 66% in post-monsoon season and about 50% in pre-monsoon season. The observed track lies within the forecast COU in 90% cases of climatological/straight moving CDs and 39% cases of recurving/looping CDs. The observed track lies within COU forecast in about 71% cases of severe cyclonic storm and 37% cases of cyclonic storm/deep depression.

关键词： Tropical cyclone North indian Ocean Cone of uncertainty Track

Exploring changes of precipitation extremes under climate change through global variable-resolution modeling

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Science Bulletin 2024年第2期69卷 237-247页

作者： Wei Sun Jian Li Rucong Yu Nina Li Yi Zhang State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Institute of Tibetan Plateau Meteorology China Meteorological AdministrationChengdu 610072China department of Atmospheric Science Yunnan UniversityKunming 650091China National meteorological Center China Meteorological AdministrationBeijing 100081China 2035 Future Laboratory PIESAT Information Technology Co.Ltd.Beijing 100105China

Understanding the responses of precipitation extremes to global climate change remains limited owing to their poor representations in models and complicated interactions with multi-scale systems.Here we take the record-breaking precipitation over China in 2021 as an example,and study its changes under three different climate scenarios through a developed pseudo-global-warming(PGW)experimental framework with 60-3 km variable-resolution global ensemble modeling.Compared to the present climate,the precipitation extreme under a warmer(cooler)climate increased(decreased)in intensity,coverage,and total amount at a range of 24.3%-37.8%(18.7%-56.1%).With the help of the proposed PGW experimental framework,we further reveal the impacts of the multi-scale system interactions in climate change on the precipitation extreme.Under the warmer climate,large-scale water vapor transport converged from double typhoons and the subtropical high marched into central China,enhancing the convective energy and instability on the leading edge of the transport belt.As a result,the mesoscale convective system(Mcs)that directly contributed to the precipitation extreme became stronger than that in the present climate.On the contrary,the cooler climate displayed opposite changing characteristics relative to the warmer climate,ranging from the large-scale systems to local environments and to the Mcs.In summary,our study provides a promising approach to scientifically assess the response of precipitation extremes to climate change,making it feasible to perform ensemble simulations while investigating the multi-scale system interactions over the globe.

关键词： Precipitation extreme Climate change Pseudo-global-warming experiment Variable-resolution modeling Multi-scale system interaction

Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during the Monsoon Season. Part Ⅰ:Pre-storm Environment and Storm Evolution

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Advances in Atmospheric Sciences 2024年第6期41卷 1115-1131页

作者： Lanqiang BAI Dan YAO Zhiyong MENG Yu ZHANG Xianxiang HUANG Zhaoming LI Xiaoding YU Foshan Tornado Research Center and China Meteorological Administration Tornado Key LaboratoryGuangdong Meteorological Serviceand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Guangdong 528000China meteorological Observation Centre CMABeijing 100081China department of Atmospheric and Oceanic Sciences and China Meteorological Administration Tornado Key LaboratorySchool of PhysicsPeking UniversityBeijing 100871China Guangzhou meteorological Observatory CMAGuangdong 511430China Foshan Tornado Research Center and China Meteorological Administration Tornado Key LaboratoryCMAGuangdong 528000China China meteorological Administration Training Center CMABeijing 528000China

The Pearl River Delta(PRD),a tornado hotspot,forms a distinct trumpet-shaped coastline that concaves toward the South China Sea.During the summer monsoon season,low-level southwesterlies over the PRD’s sea surface tend to be turned toward the west coast,constituting a convergent wind field along with the landward-side southwesterlies,which influences regional convective weather.This two-part study explores the roles of this unique land–sea contrast of the trumpet-shaped coastline in the formation of a tornadic mesovortex within monsoonal flows in this region.Part I primarily presents observational analyses of pre-storm environments and storm evolutions.The rotating storm developed in a lowshear environment(not ideal for a supercell)under the interactions of three air masses under the influence of the land–sea contrast,monsoon,and storm cold outflows.This intersection zone(or“triple point”)is typically characterized by local enhancements of ambient vertical vorticity and convergence.Based on a rapid-scan X-band phased-array radar,finger-like echoes were recognized shortly after the gust front intruded on the triple point.Developed over the triple point,they rapidly wrapped up with a well-defined low-level mesovortex.It is thus presumed that the triple point may have played roles in the mesovortex genesis,which will be demonstrated in Part II with multiple sensitivity numerical simulations.The findings also suggest that when storms pass over the boundary intersection zone in the PRD,the expected possibility of a rotating storm occurring is relatively high,even in a low-shear environment.Improved knowledge of such environments provides additional guidance to assess the regional tornado risk.

关键词： tornado mesovortex surface boundary land–sea contrast monsoon

Predicting PM_(2.5) Concentration in the Yangtze River Delta Region Using Climate System Monitoring Indices and Machine Learning

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Journal of meteorological Research 2024年第2期38卷 249-261页

作者： Jinghui MA Shiquan WAN Shasha XU Chanjuan WANG Danni QIU Shanghai Typhoon Institute Shanghai Meteorological ServiceShanghai 200030 Key Laboratory of Polar Atmosphere-Ocean-Iice System for Weather and Climate Ministry of EducationDepartment of Atmospheric and Oceanic SciencesFudan UniversityShanghai 200438 Shanghai Key Laboratory of Meteorology and Health Shanghai Meteorological ServiceShanghai 200030 Yangzhou meteorological Office Yangzhou 225001 department of Physics Yangzhou UniversityYangzhou 225003

Changing meteorological conditions during autumn and winter have considerable impact on air quality in the Yangtze River Delta(YRD)region.External climatic factors,such as sea surface temperature and sea ice,together with the atmospheric circulation,directly affect meteorological conditions in the YRD region,thereby modulating the variation in atmospheric PM_(2.5) concentration.This study used the evolutionary modeling machine learning technique to investigate the lag relationship between 144 climate system monitoring indices and autumn/winter PM_(2.5) concentration over 0-12 months in the YRD region.After calculating the contribution ratios and lagged correlation coefficients of all indices over the previous 12 months,the top 36 indices were selected for model training.Then,the nine indices that contributed most to the PM_(2.5) concentration in the YRD region,including the decadal oscillation index of the Atlantic Ocean and the consistent warm ocean temperature index of the entire tropical indian Ocean,were selected for physical mechanism analysis.An evolutionary model was developed to forecast the average PM_(2.5) concentration in major cities of the YRD in autumn and winter,with a correlation coefficient of 0.91.In model testing,the correlation coefficient between the predicted and observed PM_(2.5) concentrations was in the range of 0.73-0.83 and the root-mean-square error was in the range of 9.5-11.6μg m-3,indicating high predictive accuracy.The model performed exceptionally well in capturing abnormal changes in PM_(2.5) concentration in the YRD region up to 50 days in advance.

关键词： PM_(2.5)concentration machine learning evolutionary modeling seasonal prediction

Synergistic Effects of Bay of Bengal Tropical Cyclones and Tibetan Plateau Vortices on Water Vapor Transport over the Tibetan Plateau in Early Summer

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Journal of meteorological Research 2024年第2期38卷 383-398页

作者： Jialu LIN Ying LI Beiyao LIU Pengchao AN State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 University of Chinese Academy of Sciences Beijing 100049 department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200433

The Bay of Bengal(BoB)tropical cyclones(TCs)and the Tibetan Plateau vortices(TPVs)are two crucial weather systems influencing the Tibetan Plateau(TP).Their synergistic effects can lead to widespread heavy precipitation events on the TP.In this study,we employ the Hybrid Single-Particle Lagrangian Integrated Trajectory(HYSPLIT)model to track the trajectory of water vapor transport during three large-scale precipitation events on the TP under the combined influence of BoB TCs and TPVs.The results indicate that low-level water vapor from the BoB under the influence of BoB TCs was cyclonically entangled into the cyclonic circulation,lifted and transported northward by southwesterly flow to the southeastern part of the TP,which contributes to the moistening of the entire troposphere there.Additionally,convergence of the cyclonic circulation of the TPVs on the northern TP further transports water vapor collected in the southeastern TP northward,conducive to the maintenance and development of precipitation systems,thus inducing widespread heavy precipitation events over the TP.

关键词： Bay of Bengal(BoB) tropical cyclones(TCs) Tibetan Plateau vortices(TPVs) trajectory tracing water vapor transport

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 uniqueness.Taking 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 precipitation.Three 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 accuracy.The 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 appear.Possible reasons for this are as follows.The 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 simple.However,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 significantly.Therefore,by combining the appropriate anomalous features with multi-model fusion,an integrated improvement of the forecast of the rainfall intensity and location is achieved.Overall,this study is a novel exploration to improve the refined forecasting of heavy precipitation with extreme intensity and high variability,and provides a reference for the deep fusion of

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

Anomalies of Precipitation over China on Days with Tropical Cyclone Activity over the Bay of Bengal: Role of Moisture Transport

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Journal of meteorological Research 2024年第2期38卷 368-382页

作者： Na WEI Ying LI Xiaoting FAN Nanjing Joint Institute for Atmospheric Sciences Nanjing 210041 State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081 department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200433

Tropical cyclones over the Bay of Bengal(BoBTC)affect the precipitation over China,with distinct seasonal and daily variabilities.This study quantitatively examines the daily standardized precipitation anomalies(SPAs)over China on the days with BoBTC activities(storm-days)and related circulations,based on rainfall measurements at surface meteorological stations and ECMWF reanalysis data on a 0.25°×0.25°resolution during 1979-2019.Significant positive SPA is found over the stations in the two adjacent regions around BoB(Southwest China in May/November and southern Tibetan Plateau in October)and three distant regions(Southeast China and the northeastern boundary of the Qinghai-Tibet Plateau in May,and central North China in October).The SPA distributions are remarkably consistent with the integrated water vapor transport(IVT)anomalies.Enhanced IVT is found associated with the interaction between southwesterly(southerly)of the BoBTC circulation and low-level monsoonal flow in May(midlevel westerly in winter months).The probabilities of extreme precipitation(EP)occurrences over the above regions all increase on storm-days.For adjacent regions,EP is significantly correlated with the northward IVT anomalies to the east of BoBTC circulation,which strengthen the water vapor input through the southern border.Such IVT anomalies are stronger in May,benefited by the deep monsoonal southwesterlies than those in November.For distant regions,EP is more closely related to the IVT anomaly extending back from BoB.Enhanced moisture from BoB concentrates along a local low-level convergence line over Southeast China,being further facilitated by coexistence of the BoBTC depression and midlevel westerly trough in midlatitudes.Our results highlight the interactions between BoBTCs and local weather systems that influence the general precipitation anomalies and occurrence of EP over China,especially over distant regions.

关键词： tropical cyclone Bay of Bengal precipitation anomaly moisture transport

Amebic liver abscess: An update

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World Journal of Hepatology 2024年第3期16卷 316-330页

作者： Ramesh Kumar Rishabh Patel Rajeev Nayan Priyadarshi Ruchika Narayan Tanmoy Maji Utpal Anand Jinit R Soni department of Gastroenterology All India Institute of Medical SciencesPatna 801507India department of Radiodiagnosis All India Institute of Medical SciencesPatna 801507India department of Surgical Gastroenterology All India Institute of Medical SciencesPatna 801507India

Amebic liver abscess(ALA)is still a common problem in the tropical world,where it affects over three-quarters of patients with liver abscess.It is caused by an anaerobic protozoan Entamoeba hystolytica,which primarily colonises the cecum.It is a non-suppurative infection of the liver consisting primarily of dead hepatocytes and cellular debris.People of the male gender,during their reproductive years,are most prone to ALA,and this appears to be due to a poorly mounted immune response linked to serum testosterone levels.ALA is more common in the right lobe of the liver,is strongly associated with alcohol consumption,and can heal without the need for drainage.While majority of ALA patients have an uncomplicated course,a number of complications have been described,including rupture into abdomino-thoracic structures,biliary fistula,vascular thrombosis,bilio-vascular compression,and secondary bacterial infection.Based on clinico-radiological findings,a classification system for ALA has emerged recently,which can assist clinicians in making treatment decisions.Recent research has revealed the role of venous thrombosis-related ischemia in the severity of ALA.Recent years have seen the development and refinement of newer molecular diagnostic techniques that can greatly aid in overcoming the diagnostic challenge in endemic area where serology-based tests have limited accuracy.Metronidazole has been the drug of choice for ALA patients for many years.However,concerns over the resistance and adverse effects necessitate the creation of new,safe,and potent antiamebic medications.Although the indication of the drainage of uncomplicated ALA has become more clear,high-quality randomised trials are still necessary for robust conclusions.Percutaneous drainage appears to be a viable option for patients with ruptured ALA and diffuse peritonitis,for whom surgery represents a significant risk of mortality.With regard to all of the aforementioned issues,this article intends to present an updated review of ALA.

关键词： Amebic liver abscess Amebiasis Ruptured liver abscess Percutaneous drainage Metronidazole

Predictability of the 7·20 extreme rainstorm in Zhengzhou in stochastic kinetic-energy backscatter ensembles

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Science China Earth Sciences 2024年第7期67卷 2226-2241页

作者： Min YANG Peilong YU Lifeng ZHANG Xiaobing PAN Quanjia ZHONG Yunying LI College of Meteorology and Oceanography National University of Defense TechnologyChangsha 410073China Key Laboratory of High Impact Weather(Special) China Meteorological AdministrationChangsha 410073China Collaborative Innovation Center on Forecast and Evaluation of meteorological Disasters/Key Laboratory of meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjing 210044China department of Ocean Science Hong Kong University of Science and TechnologyHong Kong 999077China

The scale-dependent predictability of the devastating 7·20 extreme rainstorm in Zhengzhou,China in 2021 was investigated via ensemble experiments,which were perturbed on different scales using the stochastic kinetic-energy backscatter(SKEB)scheme in the WRF model,with the innermost domain having a 3-km grid spacing.The daily rainfall(RAIN24h)and the cloudburst during 1600-1700 LST(RAIN1h)were considered.Results demonstrated that with larger perturbation scales,the ensemble spread for the rainfall maximum widens and rainfall forecasts become closer to the observations.In ensembles with mesoscale or convective-scale perturbations,RAIN1h loses predictability at scales smaller than 20 km and RAIN24h is predictable for all scales.Whereas in ensembles with synoptic-scale perturbations,the largest scale of predictability loss extends to 60 km for both RAIN1h and RAIN24h.Moreover,the average positional error in forecasting the heaviest rainfall for RAIN24h(RAIN1h)was 400 km(50-60)km.The southerly low-level jet near Zhengzhou was assumed to be directly responsible for the forecast uncertainty of RAIN1h.The rapid intensification in low-level cyclonic vorticity,mid-level divergence,and upward motion concomitant with the jet dynamically facilitated the cloudburst.Further analysis of the divergent,rotational and vertical kinetic spectra and the corresponding error spectra showed that the error kinetic energy at smaller scales grows faster than that at larger scales and saturates more quickly in all experiments.Larger-scale perturbations not only boost larger-scale error growth but are also conducive to error growth at all scales through a downscale cascade,which indicates that improving the accuracy of larger-scale flow forecast may discernibly contributes to the forecast of cloudburst intensity and position.

关键词： Stochastic kinetic-energy backscatter(SKEB) Extreme rainfall Ensemble forecast Predictability

Analysis and Optimization of Operational and Pollutant Attributes of Diesel Engine with CNT-Infused Orange Peel Biodiesel-Diesel Blend Fuel

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Journal of Thermal Science 2024年第2期33卷 761-778页

作者： Ranjeet RAI R.R.SAHOO Mechanical Engineering department GLA UniversityMathura281406India Mechanical Engineering department IIT(BHU)Varanasi221005India

The current study is performed to find sustainable solutions for the future of transportation and environmental well-being.Both conventional methods and experimental design table(L16 Orthogonal Array)techniques have been employed to examine and optimize a diesel-powered engine's operational and pollutant parameters.The L16 Orthogonal Array is obtained through Taguchi's experimental design approach using Minitab 16 software.The experimental design incorporated three control variables,namely engine speed,fuel type,and engine load,each with four levels.The operational parameters,namely brake thermal efficiency(BTE)and brake specific fuel consumption(BSFC),as well as the emission characteristics,including hydrocarbon(HC),carbon monoxide(CO),nitrogen oxide(NO),and smoke emissions,were acquired using the L16 orthogonal array(OA) and subsequently examined.The utilization of methodologies such as signal-to-noise(S/N) ratio and grey analysis was employed to determine the optimal operational state of the engine to achieve maximum performance while minimizing emissions.The engine's ideal state of operation,in terms of BTE and BSFC,was determined to be at 75% engine load,1000 r/min engine speed,and using 10^(-4)(in vol) carbon nanotube incorporated 20% orange peel biodiesel(OPB20CNT100) blended fuel(A3-B1-C4).The study indicated that engine load significantly influenced BTE and BSFC,with 84.05% and 87.79% contribution factors,respectively.At 25% engine load,1000 r/min,and OPB20CNT100 fuel(A1-B1-C4) CO,smoke,NO,and HC emissions were the lowest.Engine load affects emissions the most.Engine BSFC increased 3.10% and NO emissions 1.77%.BTE,CO,smoke,and HC emissions decreased by 1.9%,12.29%,47.05%,and 47.22%,respectively,at optimal operating conditions concerning diesel fuel.This study shows that Taguchi-Grey's experimental design optimizes diesel engine operational and pollutant attributes.The outcomes revealed that orange peel biodiesel infused with CNT can replace diesel fuel in an environmentally friendly way.This alternative

关键词： Taguchi-Grey method OPB20CNT100 transesterification S/N ratio GRG HC CO and NO