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Human influence on the duration of extreme temperature events in Asia's hotspot regions

Advances in Climate Change Research 2024年第2期15卷 312-326页

作者： Zi-Meng WANG Hong-Yun MA Wei LI Hai-Shan CHEN Collaborative Innovation center on Forecast and Evaluation of meteorological Disasters(CIC-FEMD)/Key Laboratory of meteorological Disaster Ministry of Education(KLME)Nanjing University of Information Science and TechnologyNanjing 210044China

Observations and models indicate that human activities exert a considerable impact on the frequency and intensity of extreme temperature events,which are associated with global warming.However,changes in the duration of extreme temperature events and their association with human influence have not been considered in most studies.Thus,the possible relationship between the observed changes in the warm and cold spell duration(WSDI and CSDI)in hotspot regions during 1960-2014 and human influence was investigated based on the NCEP/NCAR reanalysis version 1 and Coupled Model Inter-comparison Project Phase 6(CMIP6)data.Constraint projection based on these attribution results was also performed.The optimal fingerprinting technique was used to compare observed changes in WSDI and CSDI to simulated changes averaged across eight CMIP6 models.Results show that anthropogenic(ANT)forcing contributed to the observed increase in WSDI in the three hotspot regions(West Asia,South Asia and Southeast Asia),with the majority of the changes being attributed to greenhouse gas forcing.However,a generally weak ANT signal can be observed in the decreasing trend of CSDI and can be detected in South and Southeast Asia.The influence of aerosol forcing remains undetected in either WSDI or CSDI,which differs from the results for frequency and intensity of extreme temperatures.The attribution results revealed that the constrained projection of WSDI is lower than the raw projection for 2015-2100 in West Asia and Southeast Asia.However,no differences in future CSDI changes are found in Southeast Asia between the constrained and raw projections.

关键词： Extreme temperature events Duration Detection attribution Constraint projection Hotspot regions

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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 mitigation.In this paper,two deep learning-based QPE networks including a single-parameter network and a multi-parameter network are designed.Meanwhile,a self-defined loss function(SLF)is proposed during modeling.The 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 China.Considering 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)dataset.Subsequently,12 deep learning-based QPE models are trained according to the input radar parameters,the precipitation datasets,and whether an SLF was adopted,respectively.The 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 QPE.The 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 method.Finally,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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Consistency of Tropospheric Water Vapor between Reanalyses and Himawari-8/AHI Measurements over East Asia

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Advances in Atmospheric Sciences 2024年第1期41卷 19-38页

作者： Di DI Jun LI Yunheng XUE Min MIN Bo LI Zhenglong LI Collaborative Innovation center on Forecast and Evaluation of meteorological Disasters Nanjing University of Information Science and TechnologyNanjing 210044China Key Laboratory for Aerosol-Cloud-Precipitation China Meteorological AdministrationSchool of Atmospheric PhysicsNanjing University of Information Science and TechnologyNanjing 210044China FYSIC National Satellite Meteorological CenterChina Meteorological AdministrationBeijing 100081China Chengdu University of information Science and Technology Chengdu 610225China School of Atmospheric Sciences and Guangdong Province Key laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen University and Southern Laboratory of Ocean Science and EngineeringZhuhai 519082China Cooperative Institute for meteorological Satellite Studies University of Wisconsin–MadisonMadison WI 53706WisconsinUSA Wuxi University Wuxi 214105China

High spatiotemporal resolution radiances from the advanced imagers onboard the new generation of geostationary weather satellites provide a unique opportunity to evaluate the abilities of various reanalysis datasets to depict multilayer tropospheric water vapor(WV),thereby enhancing our understanding of the deficiencies of WV in reanalysis datasets.Based on daily measurements from the Advanced Himawari Imager(AHI)onboard the Himawari-8 satellite in 2016,the bias features of multilayer WV from six reanalysis datasets over East Asia are thoroughly evaluated.The assessments show that wet biases exist in the upper troposphere in all six reanalysis datasets;in particular,these biases are much larger in summer.Overall,we find better depictions of WV in the middle troposphere than in the upper troposphere.The accuracy of WV in the ERA5 dataset is the highest,in terms of the bias magnitude,dispersion,and pattern similarity.The characteristics of the WV bias over the Tibetan Plateau are significantly different from those over other parts of East Asia.In addition,the reanalysis datasets all capture the shift of the subtropical high very well,with ERA5 performing better overall.

关键词： AHI reanalysis dataset multilayer water vapor assessment radiative transfer model

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Atlantic blocking events in a simplified nonlinear baroclinic model for local finite-amplitude wave activity

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Atmospheric and Oceanic Science Letters 2024年第4期17卷 41-45页

作者： Ning Shi Bamidele Abiodun Paul Wencai Liu Collaborative Innovation center on Forecast and Evaluation of meteorological Disasters School of Atmospheric SciencesNanjing University of Information Science and TechnologyNanjingChina Nigerian meteorological Agency AbujaNigeria

为研究北大西洋阻高的形成机制,本文在局部有限振幅波活动(LWA)框架下进行了一系列数值实验.采用的数值模型能显式地描绘出两种重要的大气内部动力过程,即非线性纬向位涡通量和Rossby波包传播.模拟结果显示,这两种动力学过程均是形成大... 详细信息

为研究北大西洋阻高的形成机制,本文在局部有限振幅波活动(LWA)框架下进行了一系列数值实验.采用的数值模型能显式地描绘出两种重要的大气内部动力过程,即非线性纬向位涡通量和Rossby波包传播.模拟结果显示,这两种动力学过程均是形成大西洋阻高的重要机理.具体地,非线性纬向位涡通量和Rossby波包传播,分别是大西洋阻高南部和北部LWA形成的主导因子.因此,本研究综合了前人关于大西洋阻高的研究成果,为其形成机理提供了新的认识.

关键词：斜压模式局地有限振幅波活动罗斯贝波传播非线性效应

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Record-breaking summer-autumn drought in southern China in 2022:Roles of tropical sea surface temperature and Eurasian warming

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Science China Earth Sciences 2024年第2期67卷 420-431页

作者： Yuepeng HU Botao ZHOU Huijun WANG Dapeng ZHANG 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 TechnologyNanjing210044China School of Atmospheric Sciences Nanjing University of Information Science and TechnologyNanjing210044China

From summer to autumn in 2022,a severe drought lasted in southern China,posing serious effects on economic growth and ecological systems.This study explored the atmospheric circulations accounting for this persistent drought event.It shows that the drought in southern China during the summer of 2022 was strongly linked to the divergence of water vapor flux and descending motions,which were respectively caused by the anomalous anticyclone over the western North Pacific and the northward movement of the East Asian subtropical jet(EASJ).Differently,the atmospheric background responsible for the sustained drought in autumn is manly featured by a cyclonic circulation anomaly over the region from the Bay of Bengal to the South China Sea,which led to decreased moisture and descending motions in southern China.Further investigation suggests that the rarely strong surface warming over northern Eurasia and the extreme La Nina-like pattern over the tropical Pacific jointly resulted in the anomalous anticyclone over the western North Pacific and the northward shift of the EASJ in the summer of 2022,while the cyclonic circulation anomaly prevailing over the region from the Bay of Bengal to the South China Sea in autumn was largely attributed to the extremely negative anomalies of the tropical Indian Ocean sea surface temperature.

关键词： Summer-autumn drought Southern China Tropical sea surface temperature Eurasian warming

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Spatial and Temporal Distribution Characteristics of Solar Energy Resources in Tibet

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Energy Engineering 2024年第1期121卷 43-57页

作者： Yanbo Shen Yang Gao Yueming Hu Xin Yao Wenzheng Yu Yubing Zhang Public meteorological Service center China Meteorological AdministrationBeijing100081China center forWind and Solar Energy Resources China Meteorological AdministrationBeijing100081China School of Applied Meteorology Nanjing University of Information Science&TechnologyNanjing210044China School of Geographical Sciences Nanjing University of Information Science&TechnologyNanjing210044China

The Tibet Plateau is one of the regions with the richest solar energy resources in the world.In the process of achieving carbon neutrality in China,the development and utilization of solar energy resources in the region will play an important role.In this study,the gridded solar resource data with 1km resolution in Tibet were obtained by spatial correction and downscaling of SMARTS model.On this basis,the spatial and temporal distribution characteristics of solar energy resources in the region in the past 30 years(1991–2020)are finely evaluated,and the annual global horizontal radiation resource is calculated.The results show that:1)The average annual global horizontal radiation amount in Tibet is 1816 kWh/m^(2).More than 60%of the area belongs to the“Most abundant”(GHI≥1750 kWh/m^(2))area of China’s solar energy resources category A,and nearly 40%belongs to the“Quite abundant”(1400≤GHI<1750)area of China’s solar energy resource category B.2)In space,the solar energy resources in Tibet increased gradually from north to south and from east to west.Lhasa,Central and Eastern Shigatse,Shannan,and Southwestern Ali are the most abundant cities,with a maximum annual radiation level of 2189 kWh/m2.3)In terms of time,the total horizontal radiation in Tibet was the highest in May and the lowest in December.74%of the total area belongs to the“Very stable”(R_(w)≥0.47)area of solar resource stability category A,and 26%belongs to the“stable”(0.36≤R_(w)<0.47)area of solar resource stability category B.Solar energy resources in the region show the characteristics of both strong and stable.Average solar energy resources in the region have shown a fluctuating downward trend over the past 30 years,with an average decline of about 12.86(kWh/m2)per decade.4)In terms of solar radiation resources reaching the earth’s surface,the theoretical total amount of annual horizontal radiation in Tibet is about 240.07 billion tons of standard coal or 222.91 billion kilowatts on average.

关键词： Tibet solar resource spatiotemporal distribution

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Mesoscale and Microphysical Characteristics of a Double Rain Belt Event in South China on May 10–13,2022

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Journal of Tropical Meteorology 2024年第1期30卷 61-75页

作者：郭照华谌芸肖天贵曾智琳 School of Atmospheric Sciences Chengdu University of Information TechnologyChengdu 610225 China national meteorological center Beijing 100081 China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiGuangdong 519082 China Guangdong meteorological Observatory Guangzhou 510640 China

A second rain belt sometimes occurs ahead of a frontal rain belt in the warm sector over coastal South China,leading to heavy precipitation.We examined the differences in the mesoscale characteristics and microphysics of the frontal and warm sector rain belts that occurred in South China on May 10–13,2022.The southern rain belt occurred in an environment with favorable mesoscale conditions but weak large-scale forcing.In contrast,the northern rain belt was related to low-level horizontal shear and the surface-level front.The interaction between the enhanced southeasterly winds and the rainfall-induced cold pool promoted the persistent growth of convection along the southern rain belt.The convective cell propagated east over the coastal area,where there was a large temperature gradient.The bow-shaped echo in this region may be closely related to the rear-inflow jet.By contrast,the initial convection of the northern rain belt was triggered along the front and the region of low-level horizontal shear,with mesoscale interactions between the enhanced warm-moist southeasterly airflow and the cold dome associated with the earlier rain.The terrain blocked the movement of the cold pool,resulting in the stagnation of the frontal convective cell at an early stage.Subsequently,a meso-γ-scale vortex formed during the rapid movement of the convective cell,corresponding to an enhancement of precipitation.The representative raindrop spectra for the southern rain belt were characterized by a greater number and higher density of raindrops than the northern rain belt,even though both resulted in comparable hourly rainfalls.These results help us better understand the characteristics of double rain belts over South China.

关键词： double rain belts in South China mesoscale rainstorm cyclonic shear line cold pool bow-shaped echo microphysical characteristics

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Differences in Variations of Long-Lived and Short-Lived Summer Heat Waves during1981–2020 over Eastern China and Their Corresponding Large-Scale Circulation Anomalies

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Journal of meteorological Research 2024年第3期38卷 414-436页

作者： Liqun JI Haishan CHEN Collaborative Innovation center on Forecast and Evaluation of meteorological Disasters/Key Laboratory of meteorological Disaster Ministry of Education Nanjing University of Information Science & Technology School of Atmospheric Sciences Nanjing University of Information Science & Technology

Using daily maximum temperature(Tmax) data from 516 observation stations in eastern China from 1981 to 2020,this study employed a relative threshold method to define short-and long-lived heat waves（HWs） by considering regional climate differences to investigate the spatial characteristics and evolution of large-scale circulation during summer HWs. The results demonstrated spatial disparities in the frequency distribution of HWs of different durations and differences in the magnitude of duration and intensity between short-and long-lived HWs. Empirical orthogonal function analysis revealed three dominant spatial modes for both short-and long-lived HWs. The first mode showed that short-lived HWs occur prominently in both northern and southern regions, whereas long-lived HWs mainly occur in the northern region. The second mode was characterized by a meridional dipole pattern in both cases.The third mode exhibited a quadrupole pattern for short-lived HWs and a tripole pattern for long-lived HWs. Differences in the center locations of anomalies in the 500-hPa geopotential height and 850-hPa wind fields significantly influenced the temperature and precipitation anomaly distribution of typical HWs by affecting the warm column in the lower troposphere, cloud distribution, and moisture transport. Moreover, the atmospheric circulation evolution processes of typical HWs associated with the different modes of long-and short-lived HWs were linked to distinct teleconnection patterns. During the three modes of long-lived（short-lived） HWs, there was stronger（weaker） wave flux activity with multiple（single） propagation paths. Stronger westward Atlantic wave train activity at 300 hPa triggered the synergistic action of meridional and zonal wave fluxes, favoring the strengthening and maintenance of positive anomalies in geopotential height of 500 hPa. This may have contributed to the formation of long-lived HWs.These findings provide valuable insights to enhance our understanding and prediction of summer HWs.

关键词： short-lived heat waves (HWs) long-lived HWs empirical orthogonal function (EOF) modes large-scale atmospheric circulation

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Characteristics and Mechanisms of Persistent Wet–Cold Events with Different Cold-air Paths in South China

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Advances in Atmospheric Sciences 2024年第6期41卷 1171-1183页

作者： Xiaojuan SUN Li CHEN Chuhan LU Panxing WANG Key Laboratory of meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China School of Atmospheric Sciences Nanjing University of Information Science and TechnologyNanjing 210044China Qianxinan Bouyei and Miao Autonomous Prefecture meteorological Bureau of Guizhou Province Xingyi 562400China

We investigate the characteristics and mechanisms of persistent wet–cold events(PWCEs)with different types of coldair paths.Results show that the cumulative single-station frequency of the PWCEs in the western part of South China is higher than that in the eastern part.The pattern of single-station frequency of the PWCEs are“Yangtze River(YR)uniform”and“east–west inverse”.The YR uniform pattern is the dominant mode,so we focus on this pattern.The cold-air paths for PWCEs of the YR uniform pattern are divided into three types—namely,the west,northwest and north types—among which the west type accounts for the largest proportion.The differences in atmospheric circulation of the PWCEs under the three types of paths are obvious.The thermal inversion layer in the lower troposphere is favorable for precipitation during the PWCEs.The positive water vapor budget for the three types of PWCEs mainly appears at the southern boundary.

关键词： persistent wet–cold events cold-air paths circulation characteristics water vapor

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A Deep Learning Approach for Forecasting Thunderstorm Gusts in the Beijing–Tianjin–Hebei Region

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Advances in Atmospheric Sciences 2024年第7期41卷 1342-1363页

作者： Yunqing LIU Lu YANG Mingxuan CHEN Linye SONG Lei HAN Jingfeng XU Faculty of information Science and Engineering Ocean University of ChinaQingdao 266100China Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089China Collaborative Innovation center on Forecast and Evaluation of meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China

Thunderstorm gusts are a common form of severe convective weather in the warm season in North China,and it is of great importance to correctly forecast them.At present,the forecasting of thunderstorm gusts is mainly based on traditional subjective methods,which fails to achieve high-resolution and high-frequency gridded forecasts based on multiple observation sources.In this paper,we propose a deep learning method called Thunderstorm Gusts TransU-net(TGTransUnet)to forecast thunderstorm gusts in North China based on multi-source gridded product data from the Institute of Urban Meteorology(IUM)with a lead time of 1 to 6 h.To determine the specific range of thunderstorm gusts,we combine three meteorological variables:radar reflectivity factor,lightning location,and 1-h maximum instantaneous wind speed from automatic weather stations(AWSs),and obtain a reasonable ground truth of thunderstorm gusts.Then,we transform the forecasting problem into an image-to-image problem in deep learning under the TG-TransUnet architecture,which is based on convolutional neural networks and a transformer.The analysis and forecast data of the enriched multi-source gridded comprehensive forecasting system for the period 2021–23 are then used as training,validation,and testing datasets.Finally,the performance of TG-TransUnet is compared with other methods.The results show that TG-TransUnet has the best prediction results at 1–6 h.The IUM is currently using this model to support the forecasting of thunderstorm gusts in North China.

关键词： thunderstorm gusts deep learning weather forecasting convolutional neural network transformer

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