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The Short-Duration Heavy Rainfall in Different Quadrants of Northeast China Cold Vortices

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Journal of meteorological Research 2024年第2期38卷 321-338页

作者： Lei YANG Yongguang ZHENG Liaoning meteorological Disaster Monitoring and Early Warning center Shenyang 110166 National meteorological Centre China Meteorological AdministrationBeijing 100081 China meteorological Administration Tornado Key Laboratory Foshan 528315

The Northeast China cold vortex(NCCV)is one of the main synoptic-scale systems causing short-duration heavy rainfall(SDHR)in Northeast China.Environmental conditions(e.g.,water vapor,instability,and vertical wind shear)are known to be distinctly different over the four quadrants of NCCVs,rendering prediction of the SDHR related to NCCVs(NCCV_SDHR)more challenging.Based on 5-yr hourly rainfall observations from 3196 automatic weather stations and ERA5 reanalysis data,10,232 NCCV_SDHR events were identified and divided into four quadrant groups according to their relative position to the center of the NCCV(CVC).The results show that the southeast quadrant features the highest frequency of SDHR,with stronger intensity,longer duration,and wider coverage;and the SDHR in different quadrants presents different formation mechanisms and varied temporal evolution.A new coordinate system is established relative to the CVC that uses the CVC as the origin and the radius of the NCCV(r CV)as the unit distance.In this new coordinate system,all of the NCCV_SDHR events in the 5-yr study period are synthesized.It is found that the occurrence frequency of NCCV_SDHR initially increases and then decreases with increasing distance from the CVC.The highest frequency occurs mainly between 0.8 and 2.5 times r CV from the CVC in the southeast quadrant.This can be attributed to the favorable conditions,such as convergence of the low-level shear line and abundant water vapor,which are concentrated in this region.Furthermore,high-frequency NCCV_SDHR larger than 50 mm(NCCV_SDHR50)is observed to be closer to the CVC.When NCCV_SDHR50occurs,the NCCV is in closer proximity to the subtropical high,resulting in stronger low-level convergence and more abundant water vapor.Additionally,there are lower lifting condensation levels and stronger 0-6-and 0-1-km vertical wind shears in these environments.These findings provide a valuable reference for more accurate prediction of NCCV_SDHR.

关键词： Northeast China cold vortex short-duration heavy rainfall statistical characteristics environmental conditions

Changes in extreme high temperature warning indicators over China under different global warming levels

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Science China Earth Sciences 2024年第6期67卷 1895-1909页

作者： Yuxia ZHANG Ying SUN Ting HU Chinese Academy of meteorological Sciences Beijing 100081China National Climate center Laboratory for Climate StudiesChina Meteorological AdministrationBeijing 100081China

High temperature warning indicators play a pivotal role in meteorological departments,serving as crucial criteria for issuing warnings that guide both social production and daily life.Despite their importance,limited studies have explored the relationship between different global warming levels and changes in high temperature warning indicators.In this study,we analyze data from 2,419 meteorological stations over China and utilize the Coupled Model Intercomparison Project Phase 6(CMIP6)models to examine historical changes in high temperature warning indicators used by the China meteorological Administration.We evaluate model performance and estimate future changes in these indicators using an annual cycle bias correction method.The results indicate that since 1961,the number of high temperature days(TX35d and TX40d)and length of season(TX40d and TX40l)with daily maximum temperature reaching or exceeding 35℃ and 40℃ have increased over China.The intensity of high temperatures(TXx)has strengthened and the geographical extent affected by high temperatures has expanded.In 2022,the occurrence of 40℃ high temperatures surges,with Eastern China experiencing a two-day increase in TX40d and an extended seasonal length in TX40l by over five days.While CMIP6 models have underestimated the high temperature indictors associated with 35℃ during historical periods,notable difference is not observed between the models and observations for TX40d and TX40l,given their rare occurrence.However,future projections,after bias correction,indicate that the increasing trends for 35℃ and 40℃ high temperature days and length of season become more pronounced than the raw projection,suggesting a more severe increase than that anticipated originally.As global warming intensifies,the high temperature days and length of season are projected to increase non-linearly,while the intensity of high temperatures is expected to increase linearly.For every 1℃ increase in global temperature,the intensity is projected to rise by approximately 1.4℃.The impa

关键词： Extreme high temperatures meteorological warning CMIP6 Global warming levels Future projection

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

Analysis on characteristics of extreme precipitation indices and atmospheric circulation in Northern Shanxi

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Research in Cold and Arid Regions 2024年第2期16卷 84-97页

作者： Xia Cai Yan Song Lin Cai Xin Su GuiHua Liang YanMing Xu Shuozhou meteorological Bureau of Shanxi Province China meteorological Administration Training center Heze University of Shandong Province Huafeng meteorological Media Group Shuocheng meteorological Bureau

This article utilizes daily precipitation data from 28 national meteorological stations in northern Shanxi Province spanning from 1972 to 2020, and the US NCEP/NCAR monthly average reanalysis and ERA5 monthly average reanalysis data. The study employs techniques such as empirical orthogonal function(EOF) decomposition, MannKendall mutation and other methods to investigate the spatiotemporal distribution of extreme precipitation index in northern Shanxi and their correlation with atmospheric circulation. The research results show that: the absolute index, relative index, intensity index and sustained dry period index(CDD) in the continuous index appear from southwest to northeast. The spatial distribution characteristics of the central region decrease, while the continuous wet period(CWD) decreases from the central to the east and west. The three indices Rx1day, Rx5day, and CWD mutated in 1978, 1975, and 1983 respectively, and other extreme precipitation indices all appeared in a sudden change from a low-value period to a high-value period occurred around 2010. In the high-value years of the summer extreme precipitation index, there is a significant negative anomaly in the height field in the mid-high latitude regions of Eurasia. Northern Shanxi is controlled by a broad low-pressure trough in the Lake Baikal area.Water vapor transported via the east, west, and south routes converges in the northern Shanxi region and encounters cold air from the north. There is a strong upward motion anomaly at 500 hPa in the troposphere, and the dynamic conditions of upper-level divergence and lower-level convergence lead to more summer extreme precipitation in the northern Shanxi region. Conversely, in the low-value years of the summer extreme precipitation index, northern Shanxi is affected by a strong high-pressure ridge north of Lake Baikal. There is a downward motion anomaly at 500 hPa, and the northern Shanxi region lacks water vapor. The cold and warm air cannot converge, and both the water vapor conditions and dynamic cond

关键词： Northern Shanxi Extreme precipitation indices Spatio-temporal distribution and evolution Mutations Atmospheric circulation anomaly

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

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

Fusion SST from Infrared and Microwave Measurement of FY-3D meteorological Satellite

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Journal of Tropical Meteorology 2024年第1期30卷 89-96页

作者：张淼徐娜陈林 National Satellite meteorological center/National center for Space Weather Beijing 100081 China Innovation center for Fengyun meteorological Satellite(FYSIC) Beijing 100081 China Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites China Meteorological AdministrationBeijing 100081 China

Sea surface temperature(SST)is one of the important parameters of global ocean and climate research,which can be retrieved by satellite infrared and passive microwave remote sensing instruments.While satellite infrared SST offers high spatial resolution,it is limited by cloud cover.On the other hand,passive microwave SST provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall,coastal effects,and high wind speeds.To achieve high-precision,comprehensive,and high-resolution SST data,it is essential to fuse infrared and microwave SST measurements.In this study,data from the Fengyun-3D(FY-3D)medium resolution spectral imager II(MERSI-II)SST and microwave imager(MWRI)SST were fused.Firstly,the accuracy of both MERSIII SST and MWRI SST was verified,and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI SST.After pretreatment and quality control of MERSI SST and MWRI SST,a Piece-Wise Regression method was employed to correct biases in MWRI SST.Subsequently,SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date.Finally,an optimal interpolation method was applied to fuse the FY-3D MERSI-II SST and MWRI SST.The results demonstrated a significant improvement in spatial coverage compared to MERSI-II SST and MWRI SST.Furthermore,the fusion SST retained true spatial distribution details and exhibited an accuracy of–0.12±0.74℃compared to OSTIA SST.This study has improved the accuracy of FY satellite fusion SST products in China.

关键词： SST data fusion FY3 infrared microwave

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

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Advances in Atmospheric Sciences 2024年第1期41卷 173-187页

作者： Lei ZHU Chunsong LU Xiaoqi XU Xin HE Junjun LI Shi LUO Yuan WANG Fan WANG Collaborative Innovation center on Forecast and Evaluation of meteorological Disasters(CIC-FEMD)and Key Laboratory for Aerosol-Cloud-Precipitation of China meteorological Administration Nanjing University of Information Science and TechnologyNanjing 210044China Nanjing Joint Institute for Atmospheric Sciences Nanjing 210019China College of aviation Meteorology Civil Aviation Flight University of ChinaGuanghan 618307China Collaborative Innovation center for Western Ecological Safety Lanzhou UniversityLanzhou 730000China Department of Geography Hong Kong Baptist UniversityHong Kong SAR 999077China

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

关键词： large-eddy simulation cumulus clouds entrainment rate probability density functions spatial and temporal distribution

Impact of Sky Conditions on Net Ecosystem Productivity over a “Floating Blanket” Wetland in Southwest China

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Advances in Atmospheric Sciences 2024年第2期41卷 355-368页

作者： Yamei SHAO Huizhi LIU Qun DU Yang LIU Jihua SUN Yaohui LI Jinlian LI State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100029China Yunnan meteorological Observatory Kunming 530100China College of aviation Meteorology Civil Aviation Flight University of ChinaGuanghan 618307China meteorological Bureau of Tengchong County Baoshan 679100China

Based on eddy covariance(EC) measurements during 2016–20, the effects of sky conditions on the net ecosystem productivity(NEP) over a subtropical “floating blanket ” wetland were investigated. Sky conditions were divided into overcast, cloudy, and sunny conditions. On the half-hourly timescale, the daytime NEP responded more rapidly to the changes in the total photosynthetic active radiation(PARt) under overcast and cloudy skies than that under sunny skies. The increase in the apparent quantum yield under overcast and cloudy conditions was the greatest in spring and the least in summer. Additionally, lower atmospheric vapor pressure deficit(VPD) and moderate air temperature were more conducive to enhancing the apparent quantum yield under cloudy skies. On the daily timescale, NEP and the gross primary production(GPP) were higher under cloudy or sunny conditions than those under overcast conditions across seasons. The daily NEP and GPP during the wet season peaked under cloudy skies. The daily ecosystem light use efficiency(LUE) and water use efficiency(WUE) during the wet season also changed with sky conditions and reached their maximum under overcast and cloudy skies, respectively. The diffuse photosynthetic active radiation(PAR_d) and air temperature were primarily responsible for the variation of daily NEP from half-hourly to monthly timescales, and the direct photosynthetic active radiation(PAR_b) had a secondary effect on NEP. Under sunny conditions, PAR_b and air temperature were the dominant factors controlling daily NEP. While daily NEP was mainly controlled by PAR_d under cloudy and overcast conditions.

关键词： diffuse radiation eddy covariance NEP controlling factors wetland path analysis