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Joint Retrieval of PM_(2.5) Concentration and Aerosol Optical Depth over china Using Multi-Task Learning on FY-4A AGRI

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Advances in Atmospheric Sciences 2025年第1期42卷 94-110页

作者： Bo LI Disong FU Ling YANG Xuehua FAN Dazhi YANG Hongrong SHI Xiang’ao XIA Electronic Engineering College Chengdu University of Information TechnologyChengdu 610225China Tianjin meteorological Radar Research Trial Center Tianjin Meteorological BureauTianjin 300074China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Research Centre on meteorological Observation Engineering Technology China Meteorological AdministrationBeijing 100081China Key Laboratory of Atmospheric Environment and Extreme Meteorology Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001China University of Chinese Academy of Sciences Beijing 100049China

Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM_(2.5))play crucial roles in air quality,human health,and climate ***,the complex correlation of AOD–PM_(2.5)and the limitations of existing algorithms pose a significant challenge in realizing the accurate joint retrieval of these two parameters at the same *** this point,a multi-task learning(MTL)model,which enables the joint retrieval of PM_(2.5)concentration and AOD,is proposed and applied on the top-of-the-atmosphere reflectance data gathered by the Fengyun-4A Advanced Geosynchronous Radiation Imager(FY-4A AGRI),and compared to that of two single-task learning models—namely,Random Forest(RF)and Deep Neural Network(DNN).Specifically,MTL achieves a coefficient of determination(R^(2))of 0.88 and a root-mean-square error(RMSE)of 0.10 in AOD *** comparison to RF,the R^(2)increases by 0.04,the RMSE decreases by 0.02,and the percentage of retrieval results falling within the expected error range(Within-EE)rises by 5.55%.The R^(2)and RMSE of PM_(2.5)retrieval by MTL are 0.84 and 13.76μg m~(-3)*** with RF,the R^(2)increases by 0.06,the RMSE decreases by 4.55μg m~(-3),and the Within-EE increases by 7.28%.Additionally,compared to DNN,MTL shows an increase of 0.01 in R^(2)and a decrease of 0.02 in RMSE in AOD retrieval,with a corresponding increase of 2.89%in *** PM_(2.5)retrieval,MTL exhibits an increase of 0.05 in R^(2),a decrease of 1.76μg m~(-3)in RMSE,and an increase of 6.83%in *** evaluation suggests that MTL is able to provide simultaneously improved AOD and PM_(2.5)retrievals,demonstrating a significant advantage in efficiently capturing the spatial distribution of PM_(2.5)concentration and AOD.

关键词： AOD PM_(2.5) FY-4A multi-task learning joint retrieval

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Advantages of the Multimodel Ensemble Approach for Subseasonal Precipitation Prediction in china and the Driving Factor of the MJO

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Advances in Atmospheric Sciences 2025年第3期42卷 551-563页

作者： Li GUO Jie WU Qingquan LI Xiaolong JIA china meteorological administration Key Laboratory for Climate Prediction Studies National Climate CentreBeijing 100081China Collaborative Innovation Centre On Forecast and Evaluation of meteorological Disasters Nanjing University of Information Science and TechnologyNanjing 210066China

Based on the hindcasts from five subseasonal-to-seasonal(S2S)models participating in the S2S Prediction Project,this study evaluates the performance of the multimodel ensemble(MME)approach in predicting the subseasonal precipitation anomalies during summer in china and reveals the contributions of possible driving *** results suggest that while single-model ensembles(SMEs)exhibit constrained predictive skills within a limited forecast lead time of three pentads,the MME illustrates an enhanced predictive skill at a lead time of up to four pentads,and even six pentads,in southern *** on both deterministic and probabilistic verification metrics,the MME consistently outperforms SMEs,with a more evident advantage observed in probabilistic *** superior performance of the MME is primarily attributable to the increase in ensemble size,and the enhanced model diversity is also a contributing *** reliability of probabilistic skill is largely improved due to the increase in ensemble members,while the resolution term does not exhibit consistent ***,the Madden–Julian Oscillation(MJO)is revealed as the primary driving factor for the successful prediction of summer precipitation in china using the *** improvement by the MME is not solely attributable to the enhancement in the inherent predictive capacity of the MJO itself,but derives from its capability in capturing the more realistic relationship between the MJO and subseasonal precipitation anomalies in *** study establishes a scientific foundation for acknowledging the advantageous predictive capability of the MME approach in subseasonal predictions of summer precipitation in china,and sheds light on further improving S2S predictions.

关键词： multimodel ensemble subseasonal predictions summer precipitation S2S model MJO

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The Enhancing Effect of the East Asian Subtropical Westerly Jet on Summer Extreme High-Temperature Events over Central-Eastern china Since the Late 1990s

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Advances in Atmospheric Sciences 2025年第3期42卷 453-466页

作者： Chujie GAO Yuyu NIU Gen LI Shanlei SUN Bo LU Chaofan LI Bei XU Jinglong HUANG Xiubao SUN College of Oceanography&Key Laboratory of Marine Hazards Forecasting Ministry of Natural ResourcesHohai UniversityNanjing 210098China Key Laboratory of meteorological Disaster Ministry of Education(KLME)&Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China Laboratory for Climate Studies and CMA-NJU Joint Laboratory for Climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China Xiong’an Institute of meteorological Artificial Intellegence Xiong'an 071708China Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary Sciences University of the Chinese Academy of SciencesBeijing 100049China College of Intelligent Science and Control Engineering Jinling Institute of TechnologyNanjing 211169China

The increase in frequency and intensity of Extreme High-temperature Events(EHEs)over Central-Eastern china(CEC)in recent decades has severely impacted social development and *** observation and reanalysis datasets,this study explores the effect of the East Asian subtropical westerly jet stream(EAJ)on the CEC EHEs for the summers spanning 1979–*** its general relative location to the right side of the upper-level jet stream exit region,CEC would theoretically suffer more EHEs with a stronger and northwardly-shifted EAJ in summer due to the likelihood of abnormal subsidence induced by the ***,such an EAJ–EHE connection has been unstable over the past four decades but has displayed an evident interdecadal *** the late 1990s,the interannual variation of the EAJ was manifested mainly by its meridional displacement in the northeastern part of East Asia;thus,the atmospheric responses were essentially located to the east of CEC,exerting less of an influence on the CEC ***,since the late 1990s,the EAJ variation has featured an intensity change in its center over the northwest portion of the CEC,which has resulted in a westward shift in atmospheric responses to cover the CEC ***,the EAJ could potentially affect the summer CEC EHEs during 2000–*** findings offer support for an in-depth understanding of the formation mechanisms of extreme weather/climate events of this nature and thus provide a scientific reference for seasonal climate predictions.

关键词： summer extreme high-temperature events East Asian subtropical jet atmospheric circulation central-eastern china interdecadal change

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Accelerated warming of High Mountain Asia predicted at multiple years ahead

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Science Bulletin 2025年第3期70卷 419-428页

作者： Shuai Hu Tianjun Zhou Bo Wu Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of the Chinese Academy of Sciences Beijing 100049China

High-Mountain Asia(HMA)is an important source of freshwater since it holds the largest reservoir of frozen water outside the polar *** feeds ten great rivers,ultimately supporting more than 2 billion ***,the threat of accelerated glacier melt,which is a consequence of unprecedented global warming since the early 1950s,threatens water resources in the surrounding *** predictions of the near-term temperature change and synergistic mass loss of glaciers are essential but challenging to implement because of the impacts of internal climate ***,based on large ensembles of state-of-the-art decadal climate prediction experiments,we provide evidence that the internally generated surface air temperature variations in HMA can be predicted multiple years in advance,and the model initialization has robust added value to the decadal prediction ***-time decadal forecasts suggest that the HMA will experience accelerated warming in 2025-2032,where the surface warming will increase by 0.98°C(0.67 to 1.33°C;5%to 95%range)relative to the reference period 1991-2020,which is equivalent to 1.75 times the observed warming during *** decadal predictability originates from extratropical Pacific decadal variability modes,which modulate the convective heating in the tropical Pacific and influence HMA via the eastward-propagating atmospheric Kelvin *** warming in the coming decade will likely increase the shrinkage of the glacier volume over the HMA by 1.4%.This change poses unprecedented challenges,including potential water scarcity,ecosystem disruption,and increased risk of natural disasters,to HMA and surrounding regions.

关键词： Decadal prediction High Mountain Asia Surface air temperature Pacific decadal variabilities Glacier

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Targeted sounding observations from geostationary satellite and impacts on high impact weather forecasts

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Science china Earth Sciences 2025年

作者： Wei HAN Ruoying YIN Jun LI Yongzhu LIU Jincheng WANG Yonghui LI Xiaohao QIN Zhiqing ZHANG Xueshun SHEN CMA Earth System Modeling and Prediction Centre (CEMC) State Key Laboratory of Severe Weather (LaSW) National Satellite meteorological Center State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of Sciences University of Chinese Academy of Sciences

In monitoring and predicting high-impact weather(HIW) events, targeted atmospheric temperature and moisture sounding observations in sensitive areas are more valuable than conventional observations. The conditional nonlinear optimal perturbation(CNOP) method and the linear singular vector(SV) method can be employed to identify these weather-sensitive areas for targeted observations. Such observations can be conducted by using hyperspectral infrared sounders onboard geostationary weather satellites. The Geostationary Interferometric Infrared Sounder(GIIRS) onboard china's Fengyun(FY)-4geostationary satellite series can provide atmospheric sounding observations with a temporal resolution of up to 15 min over areas prone to active weather events. GIIRS offers unprecedented opportunities for targeted observations, enabling flexible measurement modes that focus on weather-sensitive areas. High-temporal-resolution measurements not only reveal the threedimensional(3D) thermodynamic structure of the atmosphere, but also track moisture characteristics to capture the 3D dynamic structure. Moreover, high-temporal-resolution measurements of clear radiances can enhance atmospheric sounding retrievals(used for HIW situation awareness) and data assimilation(used to improve numerical weather prediction). The four-dimensional variational(4D-Var) system facilitates the utilization of the high-temporal-resolution GIIRS targeted observations. In this study,we explore the applications of FY-4A and FY-4B GIIRS targeted observations and focus on data assimilation based on the 4DVar system for improving HIW forecasts. Several typhoon cases are selected for impact analysis. Moreover, we compare CNOP and SV methods for identifying sensitive areas, and use the 4D-Var assimilation system of the Global Assimilation Forecasting System of the china meteorological administration(CMA-GFS) for real-time data assimilation. The results indicate hightemporal-resolution observations positively impact ty

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TGNet:Intelligent Identification of Thunderstorm Wind Gusts Using Multimodal Fusion

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Advances in Atmospheric Sciences 2025年第1期42卷 146-164页

作者： Xiaowen ZHANG Yongguang ZHENG Hengde ZHANG Jie SHENG Bingjian LU Shuo FENG National meteorological Centre Beijing 100081China Nanjing University of Information Science and Technology Nanjing 210044China

Thunderstorm wind gusts are small in scale,typically occurring within a range of a few *** is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather ***,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution *** paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust *** shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or ***,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning ***,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind *** products have high accuracy,with a critical success index reaching *** with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,*** new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every *** results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.

关键词： thunderstorm wind gusts shapelet transform multimodal deep feature fusion

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Airborne Investigation of Riming:Cloud and Precipitation Microphysics within a Weak Convective System in North china

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Advances in Atmospheric Sciences 2025年第3期42卷 515-526页

作者： Xiangfeng HU Hao HUANG Shaoyu HOU Kun ZHAO Chuanfeng ZHAO Yinghui LU Jiefang YANG Rong ZHANG Delong ZHAO Weiguo LIU Dan ZHANG Haixia XIAO Key Laboratory of Radar Meteorology and State Key Laboratory of Severe Weather China Meteorology AdministrationBeijing 100044China china meteorological administration Xiong'an Atmospheric Boundary Layer Key Laboratory Xiong'an New AreaHebei 071703China Hebei Provincial Weather Modification Center ShijiazhuangHebei 051430China School of Atmospheric Sciences Key Laboratory of Mesoscale Severe Weather/MOEand Frontiers Science Center for Critical Earth Material CyclingNanjing UniversityJiangsu 210023China Department of Atmospheric and Oceanic Sciences School of PhysicsPeking UniversityBeijing 100871China Laboratory of Cloud-Precipitation Physics and Severe Storms Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Cloud-Precipitation Physics and Weather Modification Key Laboratory China Meteorology AdministrationBeijing 100044China Beijing Weather Modification Center Beijing 100089China Nanjing Joint Institute for Atmospheric Sciences NanjingJiangsu 210000China

The process of riming significantly impacts the microphysical characteristics of *** study uses aircraft and radar observation data in stratiform clouds with convection embedded that occurred in the central and southern regions of North china on 22 May *** microphysical structural characteristics and processes near the embedded convection core and in the stratiform cloud are analyzed *** attention is given to the effect of riming on the microphysical properties near the upper boundary of the melting layer and to the factors influencing riming *** collaborative observations reveal that the particle size distributions observed near the convection core and in the stratiform region are close,while the particle properties like habit and riming degree are quite *** the melting layer,larger plate-like ice particles and supercooled water droplets(D>50μm)are more abundant near the convective core,leading to higher collision efficiencies between ice particles and supercooled water *** fluctuation amplitudes of vertical airflow near the convective core also contribute to the increased riming activity and the formation of more heavily rimed particles,such as ***,in situ measurements from airborne probes also revealed that above the melting layer,the riming process involves two stages:the mass of snow crystals grows as supercooled droplets merge internally without changing size,followed by external freezing that significantly enlarges the crystals.

关键词： riming collision efficiency airflow fluctuation particle habit aircraft measurement

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A Second Tutorial Review of the Solar Power Curve:Applications in Energy Meteorology

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Advances in Atmospheric Sciences 2025年第2期42卷 269-296页

作者： Dazhi YANG Bai LIU Hao ZHANG Xiang’ao XIA Yanbo SHEN Martin János MAYER School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbinHeilongjiang 150001China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China Public meteorological Service Centre China Meteorological AdministrationBeijing 100089China Department of Energy Engineering Faculty of Mechanical EngineeringBudapest University of Technology and EconomicsMüegyetem rkp.3H-1111 BudapestHungary

The fundamental scientific and engineering knowledge concerning the solar power curve,which maps solar irradiance and other auxiliary meteorological variables to photovoltaic output power,has been gathered and put forward in the preceding tutorial *** the many pages of that review,it was incomplete in the sense that it did not elaborate on the applications of this very important tool of solar energy ***,solar power curves are ubiquitously needed in a broad spectrum of solar forecasting and solar resource assessment ***,this tutorial review should continue from where it left off and present examples concerning the usage of solar power *** a nutshell,this tutorial review,together with the preceding one,should elucidate how surface shortwave radiation data,be they ground-based,satelliteretrieved,or model-output,are bridged to various power system operations via solar power curves.

关键词： review solar power curve model chain solar forecasting resource assessment

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Convolutional Graph Neural Network with Novel Loss Strategies for Daily Temperature and Precipitation Statistical Downscaling over South china

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Advances in Atmospheric Sciences 2025年第1期42卷 232-247页

作者： Wenjie YAN Shengjun LIU Yulin ZOU Xinru LIU Diyao WEN Yamin HU Dangfu YANG Jiehong XIE Liang ZHAO Central South University Changsha 410083China Hunan Expressway Information Technology Co. Ltd.Changsha 410053China Guangdong Climate Center Guangzhou 510610China Hong Kong Polytechnic University Shenzhen Research Institute Guangdong 518057China Jieyang meteorological Bureau Jieyang 522031China State Key Laboratory of Numerical Modeling for Atmosphere Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Traditional meteorological downscaling methods face limitations due to the complex distribution of meteorological variables,which can lead to unstable forecasting results,especially in extreme *** overcome this issue,we propose a convolutional graph neural network(CGNN)model,which we enhance with multilayer feature fusion and a squeeze-and-excitation ***,we introduce a spatially balanced mean squared error(SBMSE)loss function to address the imbalanced distribution and spatial variability of meteorological *** CGNN is capable of extracting essential spatial features and aggregating them from a global perspective,thereby improving the accuracy of prediction and enhancing the model's generalization *** on the experimental results,CGNN has certain advantages in terms of bias distribution,exhibiting a smaller *** it comes to precipitation,both UNet and AE also demonstrate relatively small *** for temperature,AE and CNNdense perform outstandingly during the *** time correlation coefficients show an improvement of at least 10%at daily and monthly scales for both temperature and ***,the SBMSE loss function displays an advantage over existing loss functions in predicting the98th percentile and identifying areas where extreme events ***,the SBMSE tends to overestimate the distribution of extreme precipitation,which may be due to the theoretical assumptions about the posterior distribution of data that partially limit the effectiveness of the loss *** future work,we will further optimize the SBMSE to improve prediction accuracy.

关键词： statistical downscaling convolutional graph neural network feature processing SBMSE loss function

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A Second Tutorial Review of the Solar Power Curve:Applications in Energy Meteorology

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Advances in Atmospheric Sciences 2025年第02期 269-296页

作者： Dazhi YANG Bai LIU Hao ZHANG Xiang'ao XIA Yanbo SHEN Martin János MAYER School of Electrical Engineering and Automation Harbin Institute of Technology Institute of Atmospheric Physics Chinese Academy of Sciences Public meteorological Service Centre China Meteorological Administration Department of Energy Engineering Faculty of Mechanical Engineering Budapest University of Technology and Economics

The fundamental scientific and engineering knowledge concerning the solar power curve, which maps solar irradiance and other auxiliary meteorological variables to photovoltaic output power, has been gathered and put forward in the preceding tutorial review. Despite the many pages of that review, it was incomplete in the sense that it did not elaborate on the applications of this very important tool of solar energy meteorology. Indeed, solar power curves are ubiquitously needed in a broad spectrum of solar forecasting and solar resource assessment tasks. Hence, this tutorial review should continue from where it left off and present examples concerning the usage of solar power curves. In a nutshell, this tutorial review,together with the preceding one, should elucidate how surface shortwave radiation data, be they ground-based, satelliteretrieved, or model-output, are bridged to various power system operations via solar power curves.

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