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THE MEDIUM-RANGE NUMERICAL WEATHER PREDICTION OPERATION SYSTEM IN THE CHINA national meteorological center

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Acta meteorologica Sinica 1995年第3期9卷 373-384页

作者：李泽椿 national meteorological center Beijing 100081

It is not only meteorological problems for the medium-range numerical weather prediction (NWP) research to be in operation,but also engineering and technological problems.Here we gener- ally described the results of research,engineering construction,operation information and testing,in the course of set-up of medium-range NWP operation system in the China national meteorological center.

关键词： medium-range numerical weather prediction operation system China national meteorological center

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

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

Tropical Cyclone Monitoring and Analysis Techniques: A Review

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Journal of meteorological Research 2024年第2期38卷 351-367页

作者： Chuanhai QIAN Ying LI Yinglong XU Xin WANG Zenghai ZHANG Gaozhen NIE Da LIU Shiwen ZHANG Institute for Development and Programme Design China Meteorological AdministrationBeijing 100081 Chinese Academy of meteorological Sciences China Meteorological AdministrationBeijing 100081 national meteorological Centre China Meteorological AdministrationBeijing 100081 national Satellite meteorological Centre China Meteorological AdministrationBeijing 100081

Tropical cyclones(TCs),including tropical depressions and different categories of typhoons,hurricanes,and cyclonic storms,mostly originate over the oceans in the absence of direct observations.Thus,detailed monitoring and analysis of TCs has always been an unsolved problem.In the recent 20 years,great changes have taken place in domestic and foreign TC monitoring techniques,imposing a significant impact on TC operations and research.Some new technologies and products gradually emerge to support operations,with improved monitoring accuracy.In this paper,the progress on TC monitoring and analysis via meteorological satellites,radars,and airplanes in China and the world is reviewed,compared,and summarized,with special focuses on multisatellite fusion observations,in situ aircraft measurements,and some unconventional observation equipment such as rockets,saildrones,and underwater gliders.On this basis,the paper points out future directions for improving TC monitoring and analysis in aid of better TC forecast and early warning.

关键词： tropical cyclone(TC) monitoring and analysis meteorological satellite aircraft reconnaissance

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

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

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

Characteristics of Lightning Activity in Southeast China and its Relation to the Atmospheric Background

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Journal of Tropical Meteorology 2024年第1期30卷 76-88页

作者：支树林朱杰刘岩毛梦妮 Jiangxi meteorological Observatory Nanchang 330096 China Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites National Satellite Meteorological Center(National Center for Space Weather)China Meteorological AdministrationBeijing 100081 China Shanghai Typhoon Institute China Meteorological AdministrationShanghai 200030 China Innovation center for FengYun meteorological Satellite(FYSIC) Beijing 100081 China Key Laboratory of Transportation Meteorology of China meteorological Administration Nanjing Joint Institute for Atmospheric SciencesNanjing 210041 China Key Laboratory of meteorological Disaster(KLME) Ministry of Education&Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CICFEMD)Nanjing University of Information Science&TechnologyNanjing 210041 China Jiujiang Observatory JiujiangJiangxi 332000 China

Based on the lightning observation data from the Fengyun-4A(FY-4A)Lightning Mapping Imager(FY-4A/LMI)and the Lightning Imaging Sensor(LIS)on the International Space Station(ISS),we extract the“event”type data as the lightning detection results.These observations are then compared with the cloud-to-ground(CG)lightning observation data from the China meteorological Administration.This study focuses on the characteristics of lightning activity in Southeast China,primarily in Jiangxi Province and its adjacent areas,from April to September,2017–2022.In addition,with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis data,we further delved into the potential factors influencing the distribution and variations in lightning activity and their primary related factors.Our findings indicate that the lightning frequency and density of the FY-4A/LMI,ISS-LIS and CG data are higher in southern and central Jiangxi,central Fujian Province,and western and central Guangdong Province,while they tend to be lower in eastern Hunan Province.In general,the high-value areas of lightning density for the FY-4A/LMI are located in inland mountainous areas.The lower the latitude is,the higher the CG lightning density is.High-value areas of the CG lightning density are more likely to be located in eastern Fujian and southeastern Zhejiang Province.However,the high-value areas of lightning density for the ISS-LIS are more dispersed,with a scattered distribution in inland mountainous areas and along the coast of eastern Fujian.Thus,the mountainous terrain is closely related to the high-value areas of the lightning density.The locations of the high-value areas of the lightning density for the FY-4A/LMI correspond well with those for the CG observations,and the seasonal variations are also consistent.In contrast,the distribution of the high-value areas of the lightning density for the ISS-LIS is more dispersed.The positions of the peak frequency of the FY-4A/LMI lightning and CG lightning contrast with local altitudes

关键词： lightning satellite and ground detections atmospheric background Southeast China

Construction and Application of a Regional Kilometer-Scale Carbon Source and Sink Assimilation Inversion System(CCMVS-R)

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Engineering 2024年第2期33卷 263-275页

作者： Lifeng Guo Xiaoye Zhang Junting Zhong Deying Wang Changhong Miao Licheng Zhao Zijiang Zhou Jie Liao Bo Hu Lingyun Zhu Yan Chen Monitoring and Assessment center for GHGs and Carbon Neutrality&Key Laboratory of Atmospheric Chemistry of CMA Chinese Academy of Meteorological SciencesBeijing 100081China Laboratory of Climate Change Mitigation and Carbon Neutrality Henan UniversityZhengzhou 450001China national meteorological Information center Beijing 100081China Shanxi meteorological Administration Taiyuan 030002China Shanxi Provincial Institute of meteorological Sciences Taiyuan 030002China Jiangsu Provincial Climate center Nanjing 210000China

CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in S

关键词： CCMVS-R Regional carbon assimilation system Anthropogenic carbon emissions CO_(2) POD 4DVar