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气象学报（英文版）
中国气象学会
气象学报（英文版）

中国气象学会

丁一汇

双月刊

0894-0525

cmsams@163.com

010-68407634

100081

北京中关村南大街46号

气象学报（英文版）/Journal Acta Meteorologica SinicaCSCDCSTPCD北大核心SCI
查看更多>>中国气象学会的官方刊物《气象学报》于1925年7月创刊。英文版于1987年9月创刊，1988年至2008年出版季刊，2009年改为双月刊。
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    Precipitation Evolution from Plain to Mountains during the July 2023 Extreme Heavy Rainfall Event in North China

    Mingxin LIJisong SUNFeng LIChong WU...
    635-651页
    查看更多>>摘要：North China experienced devastating rainfall from 29 July to 1 August 2023,which caused substantial flooding and damage.This study analyzed observations from surface rain gauges and S-band dual-polarization radars to reveal the following unique features of the precipitation evolution from the plain to the mountains during this event.(1)The total rainfall was found concentrated along the Taihang Mountains at elevations generally>200 m,and its spatiotem-poral evolution was closely associated with northward-moving low-level jets.(2)Storms propagated northwestward with southeasterly steering winds,producing continuous rainfall along the eastern slopes of the Taihang Mountains owing to mountain blocking,which resulted in the formation of local centers of precipitation maxima.However,most rainfall episodes with an extreme hourly rainfall rate(HRR),corresponding to large horizontal wind shear at low levels,actively occurred in the plain area to the east of the Taihang Mountains.(3)The western portion of the ex-treme heavy rain belt in the north was mainly caused by long-lasting cumulus-stratus mixed precipitation with HRR＜20 mm h-1;the eastern portion was dominated by short-duration convective precipitation with HRR>20 mm h-1.The contributions of convective precipitation and cumulus-stratus mixed precipitation to the total rainfall of the southern and middle rain belts were broadly equivalent.(4)The local HRR maxima located at the transition zone from the plain to the mountains were induced by moderate storm-scale convective cells with active warm-rain pro-cesses and large number of small-sized rain droplets.(5)During the devastating rainfall event,it was observed that the rainfall peaked at around 1800 local time(LT)every day over the upstream plain area(no diurnal cycle of rain-fall was observed in relation to the accumulated rainfall centers over mountain areas).This was attributable to con-vective activities along the storm propagation path,which was a result of the more unstable stratification with a suit-able steering mechanism that was related to afternoon solar heating and enhanced water vapor.The findings of this study improve our understanding and knowledge of the extreme precipitation that can develop from the plain to the mountains in North China.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Enhancing Tropical Cyclone Intensity Estimation from Satellite Imagery through Deep Learning Techniques

    Wen YANGJianfang FEIXiaogang HUANGJuli DING...
    652-663页
    查看更多>>摘要：This study first utilizes four well-performing pre-trained convolutional neural networks(CNNs)to gauge the in-tensity of tropical cyclones(TCs)using geostationary satellite infrared(IR)imagery.The models are trained and tested on TC cases spanning from 2004 to 2022 over the western North Pacific Ocean.To enhance the models per-formance,various techniques are employed,including fine-tuning the original CNN models,introducing rotation aug-mentation to the initial dataset,temporal enhancement via sequential imagery,integrating auxiliary physical informa-tion,and adjusting hyperparameters.An optimized CNN model,i.e.,visual geometry group network(VGGNet),for TC intensity estimation is ultimately obtained.When applied to the test data,the model achieves a relatively low mean absolute error(MAE)of 4.05 m s-1.To improve the interpretability of the model,the SmoothGrad combined with the Integrated Gradients approach is employed.The analyses reveal that the VGGNet model places significant emphasis on the distinct inner core region of a TC when estimating its intensity.Additionally,it partly takes into ac-count the configuration of cloud systems as input features for the model,aligning well with meteorological principles.The several improvements made to this model's performance offer valuable insights for enhancing TC intensity fore-casts through deep learning.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Machine Learning-Based Temperature and Wind Forecasts in the Zhangjiakou Competition Zone during the Beijing 2022 Winter Olympic Games

    Zhuo SUNJiangbo LIRuiqiang GUOYiran ZHANG...
    664-679页
    查看更多>>摘要：Weather forecasting for the Zhangjiakou competition zone of the Beijing 2022 Winter Olympic Games is a challen-ging task due to its complex terrain.Numerical weather prediction models generally perform poorly for cold air pools and winds over complex terrains,due to their low spatiotemporal resolution and limitations in the description of dy-namics,thermodynamics,and microphysics in mountainous areas.This study proposes an ensemble-learning model,named ENSL,for surface temperature and wind forecasts at the venues of the Zhangjiakou competition zone,by in-tegrating five individual models-linear regression,random forest,gradient boosting decision tree,support vector machine,and artificial neural network(ANN),with a ridge regression as meta model.The ENSL employs predictors from the high-resolution ECMWF model forecast(ECMWF-HRES)data and topography data,and targets from auto-matic weather station observations.Four categories of predictors(synoptic-pattern related fields,surface element fields,terrain,and temporal features)are fed into ENSL.The results demonstrate that ENSL achieves better perform-ance and generalization than individual models.The root-mean-square error(RMSE)for the temperature and wind speed predictions is reduced by 48.2％and 28.5％,respectively,relative to ECMWF-HRES.For the gust speed,the performance of ENSL is consistent with ANN(best individual model)in the whole dataset,whereas ENSL outper-forms on extreme gust samples(42.7％compared with 38.7％obtained by ECMWF-HRES in terms of RMSE reduc-tion).Sensitivity analysis of predictors in the four categories shows that ENSL fits their feature importance rankings and physical explanations effectively.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Ground Passive Microwave Remote Sensing of Atmospheric Profiles Using WRF Simulations and Machine Learning Techniques

    Lulu ZHANGMeijing LIUWenying HEXiangao XIA...
    680-692页
    查看更多>>摘要：Microwave radiometer(MWR)demonstrates exceptional efficacy in monitoring the atmospheric temperature and humidity profiles.A typical inversion algorithm for MWR involves the use of radiosonde measurements as the train-ing dataset.However,this is challenging due to limitations in the temporal and spatial resolution of available sound-ing data,which often results in a lack of coincident data with MWR deployment locations.Our study proposes an al-ternative approach to overcome these limitations by harnessing the Weather Research and Forecasting(WRF)model's renowned simulation capabilities,which offer high temporal and spatial resolution.By using WRF simulations that collocate with the MWR deployment location as a substitute for radiosonde measurements or reanalysis data,our study effectively mitigates the limitations associated with mismatching of MWR measurements and the sites,which enables reliable MWR retrieval in diverse geographical settings.Different machine learning(ML)algorithms includ-ing extreme gradient boosting(XGBoost),random forest(RF),light gradient boosting machine(LightGBM),extra trees(ET),and backpropagation neural network(BPNN)are tested by using WRF simulations,among which BPNN appears as the most superior,achieving an accuracy with a root-mean-square error(RMSE)of 2.05 K for temperat-ure,0.67 g m-3 for water vapor density(WVD),and 13.98％for relative humidity(RH).Comparisons of temperature,RH,and WVD retrievals between our algorithm and the sounding-trained(RAD)algorithm indicate that our al-gorithm remarkably outperforms the latter.This study verifies the feasibility of utilizing WRF simulations for deve-loping MWR inversion algorithms,thus opening up new possibilities for MWR deployment and airborne observa-tions in global locations.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    MGCPN:An Efficient Deep Learning Model for Tibetan Plateau Precipitation Nowcasting Based on the IMERG Data

    Mingyue LUZhiyu HUANGManzhu YUHui LIU...
    693-707页
    查看更多>>摘要：The sparse and uneven placement of rain gauges across the Tibetan Plateau(TP)impedes the acquisition of precise,high-resolution precipitation measurements,thus challenging the reliability of forecast data.To address such a chal-lenge,we introduce a model called Multisource Generative Adversarial Network-Convolutional Long Short-Term Memory(GAN-ConvLSTM)for Precipitation Nowcasting(MGCPN),which utilizes data products from the Integ-rated Multi-satellite Retrievals for global precipitation measurement(IMERG)data,offering high spatiotemporal res-olution precipitation forecasts for upcoming periods ranging from 30 to 300 min.The results of our study confirm that the implementation of the MGCPN model successfully addresses the problem of underestimating and blurring precipitation results that often arise with increasing forecast time.This issue is a common challenge in precipitation forecasting models.Furthermore,we have used multisource spatiotemporal datasets with integrated geographic ele-ments for training and prediction to improve model accuracy.The model demonstrates its competence in generating precise precipitation nowcasting with IMERG data,offering valuable support for precipitation research and forecast-ing in the TP region.The metrics results obtained from our study further emphasize the notable advantages of the MGCPN model;it outperforms the other considered models in the probability of detection(POD),critical success in-dex,Heidke Skill Score,and mean absolute error,especially showing improvements in POD by approximately 33％,19％,and 8％compared to Convolutional Gated Recurrent Unit(ConvGRU),ConvLSTM,and small Attention-UNet(SmaAt-UNet)models.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Recent Enhanced Deep Troposphere-to-Stratosphere AirMass Transport Accompanying the Weakening Asian Monsoon

    Bin CHENJianzhong MAWei ZHANGJianchun BIAN...
    708-719页
    查看更多>>摘要：The Asian monsoon(AM)region is a well-known region with prevailing stratosphere-troposphere exchange(STE).However,how the STE across this region changes with the weakening AM remains unclear.Here,we particu-larly diagnose the air mass transport between the planetary boundary layer(PBL)and the stratosphere over the AM region during 1992-2017 using the Lagrangian particle dispersion model FLEXPART based on the ERA-Interim reanalysis data.The results show that both the downward and upward deep STEs exhibit a detectable increasing trend,while the latter,namely,the deep troposphere-to-stratosphere transport(DTST),is relatively more significant.Further analysis reveals that the long-term trend of DTST over the AM region could be partly attributed to changes in the Pacific Walker circulation and the air temperature(especially at upper levels).Additionally,it is found that DTST increases markedly over the tropical oceanic regions,while the increasing DTST into the stratosphere can be attrib-uted to the enhanced air masses originated from the PBL over the terrestrial regions,where large amounts of pollut-ant emissions occur.The results imply that the influence of the DTST on the chemical composition and the climate of the stratosphere over the AM region is expected to become increasingly important,and is thereby of relevance to cli-mate projection in an evolving climate.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Interdecadal Change of the Relationship between Early Summer Precipitation over Northeast China and Spring Land Surface Thermal Anomalies in West Asia

    Hongjun SUNHaishan CHENXinguan DUYinshuo DONG...
    720-732页
    查看更多>>摘要：Recent studies have suggested a close relationship between early summer precipitation over Northeast China and spring land surface thermal anomalies in West Asia.However,is this relationship the same over the multidecadal timescale?This study aims to identify the long-term variation in this relationship and the accompanying atmospheric circulation anomalies by using singular value decomposition,correlation analysis,and linear regression based on the ECMWF Reanalysis v5(ERA5)atmospheric data,ERA-Land reanalysis,and CN05 gridded observations during 1961-2020(60 yr).It is found that an interdecadal transition of the relationship between the spring surface temperat-ure/thermal anomalies in West Asia and early summer precipitation over Northeast China occurred around 1990,and the temperature-rainfall relationship intensified after 1990.Based on the Mann-Kendall test,the study period was di-vided into Pl(1961-1990)and P2(1991-2020).Further analysis indicated significant differences in the correspond-ing atmospheric circulation before and after the interdecadal transition.During P2,spring land surface warming in West Asia corresponded to a significantly enhanced early summer Circumglobal Teleconnection(CGT),which in turn suppressed the Northeast China cold vortex(NECV).The changes in circulation patterns further resulted in weakened moisture transport,strengthened subsidence,reduced precipitation triggering,and eventually,weakened precipitation.Additionally,the results suggest that the interdecadal transition of the relationship and the changes in the corresponding atmospheric circulation may be related to activities of the westerly jet stream.The second princi-pal component(PC2)mode of empirical orthogonal function(EOF)of zonal wind in June over Asia demonstrated a pattern similar to that of the atmospheric circulation corresponding to land surface thermal anomalies.In addition,during P2,the PC2 mode of the westerly jet stream in June showed a strong positive correlation with the NECV,thereby suppressing precipitation over Northeast China.Therefore,it is concluded that the westerly jet stream may have affected the interdecadal transition of the temperature-rainfall relationship around 1990.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Impacts of Winter Eurasian Snow Cover Anomalies on the Surface Air Temperature Variability over West Asia

    Jiarong HESiguang ZHUHaishan CHENZehua QIAO...
    733-748页
    查看更多>>摘要：Previous research has shown that land surface thermal anomalies in West Asia(WA)can impact regional and global climate,particularly affecting China through the eastward propagation of wave trains.However,the factors driving these anomalies in WA have not been extensively studied.Based on the observation data,this work focuses on ex-amining the impacts of Eurasian winter snow cover on winter surface air temperature(SAT)variability over WA from 1978/1979 to 2017/2018 and explores the underlying physical mechanisms.The results indicate that a crucial snow anomaly area extending from the Baltic Sea to eastern Ural significantly influences the winter SAT anomaly in WA.An anomalous increase(decrease)in winter snow cover in this key area corresponds to the anomalously warmer(cooler)SAT in WA.This relationship is primarily driven by the albedo effects of snow cover,where more(less)snow cover induces cooling(warming)of the overlying air,altering upper-level geopotential height and influencing the intensity,duration,and frequency of local blocking events.Additionally,changes in the air temperature above the key area modify the meridional temperature gradient(MTG)between high and low latitudes,affecting the mean zonal flow in the midlatitude.Diagnosis of the thermodynamic energy equation for SAT reveals that the combined effects of variations in blocking events in high latitudes and mean zonal flow in midlatitudes alter the advection of climatolo-gical temperature by anomalous winds,which is caused by the anomalous increase(decrease)of snow cover in the key area.Consequently,this leads to changes in cold advection transported to WA,contributing to the occurrence of a warmer(colder)SAT over WA in winter.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    Evaluation of CLDAS and GPM Precipitation Products over the Tibetan Plateau in Summer 2005-2021 Based on Hourly Rain Gauge Observations

    Qiaohua LIUXiuping YAO
    749-767页
    查看更多>>摘要：Accurate,reliable,and high spatiotemporal resolution precipitation products are essential for precipitation research,hydrological simulation,disaster warning,and many other applications over the Tibetan Plateau(TP).The Global Precipitation Measurement(GPM)data are widely recognized as the most reliable satellite precipitation product for the TP.The China Meteorological Administration(CMA)Land Data Assimilation System(CLDAS)precipitation fu-sion dataset(CLDAS-Prcp),hereafter referred to as CLDAS,is a high-resolution,self-developed precipitation product in China with regional characteristics.Focusing on the TP,this study provides a long-term evaluation of CL-DAS and GPM from various aspects,including characteristics on different timescales,diurnal variation,and eleva-tion impacts,based on hourly rain gauge data in summer from 2005 to 2021.The results show that CLDAS and GPM are highly effective alternatives to the rain gauge records over the TP.They both perform well for precipitation amount and frequency on multiple timescales.CLDAS tends to overestimate precipitation amount and underestimate precipitation frequency over the TP.However,GPM tends to overestimate both precipitation amount and frequency.The difference between them mainly lies in the trace precipitation.CLDAS and GPM effectively capture rainfall events,but their performance decreases significantly as intensity increases.They both show better accuracy in diurnal variation of precipitation amount than frequency,and their performance tends to be superior during nighttime com-pared to the daytime.Nevertheless,there are some differences of the two against rain gauge observations in diurnal variation,especially in the phase of the diurnal variation.The performance of CLDAS and GPM varies at different el-evations.They both have the best performance over 3000-3500 m.The elevation dependence of CLDAS is relatively minor,while GPM shows a stronger elevation dependence in terms of precipitation amount.GPM tends to overestim-ate the precipitation amount at lower elevations and underestimate it at higher elevations.CLDAS and GPM exhibit unique strengths and weaknesses;hence,the choice should be made according to the specific situation of application.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据

    GOES-16 ABI Brightness Temperature Observations Capturing Vortex Rossby Wave Signals during Rapid Intensification of Hurricane Irma(2017)

    Yanyang HUXiaolei ZOU
    768-783页
    查看更多>>摘要：Geostationary Operational Environmental Satellite-16(GOES-16)Advanced Baseline Imager(ABI)observations of brightness temperature(TB)are used to examine the temporal evolutions of convection-affected structures of Hur-ricane Irma(2017)during its rapid intensification(RI)period from 0600 to 1800 UTC 4 September 2017.The ABI observations reveal that both an elliptical eye and a spiral rainband that originated from Irma's eyewall obviously ex-hibit wavenumber-2 TB asymmetries.The elliptical eye underwent a counterclockwise rotation at a mean speed of a wavenumber-2 vortex Rossby edge wave from 0815 to 1005 UTC 4 September.In the following about 2 hours(1025-1255 UTC 4 September),an inner spiral rainband originated from the eyewall and propagated at a phase speed that approximates the vortex Rossby wave(VRW)phase speed calculated from the aircraft reconnaissance data.Dur-ing the RI period of Irma,ABI TB observations show an on-off occurrence of low TB intrusions into the eye,accom-panying a phase lock of eyewall TB asymmetries of wavenumbers 1 and 2 and an outward propagation of VRW-like inner spiral rainbands from the eyewall.The phase lock leads to an energy growth of Irma's eyewall asymmetries.Although the eye remained clear from 1415 to 1725 UTC 4 September,an inner spiral rainband that originated from a large convective area also had a VRW-like outward propagation,which is probably due to a vertical tilt of Irma.This study suggests a potential link between convection sensitive GOES imager observations and hurricane dynamics.
      原文链接:
    • 国家科技期刊平台
    • NETL
    • NSTL
    • 万方数据