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Revisiting Unstable ENSO Teleconnections From a Global Perspective

Journal of Geophysical research: Atmospheres 2025年第10期130卷

作者： Jiapeng Miao Xian Wu Dabang Jiang Xiangzhou Song Tao Wang Xinping Xu Observation and Research Station of Air-Sea Interface Ministry of Natural Resources Hohai University Nanjing China Key Laboratory of Meteorological Disaster (KLME) Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC–FEMD) Nanjing University of Information Science & Technology Nanjing China Department of Sustainable Earth Systems Sciences The University of Texas at Dallas Richardson Texas USA State Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China School of Atmospheric Sciences Nanjing University Nanjing China

The impacts of El Niño-Southern Oscillation (ENSO) on regional climate may vary from decade to decade. Here, we quantify these unstable ENSO impacts on a global scale by calculating the range of possible correlation coefficients (CCs) between the Niño-3.4 index and climate anomalies in boreal winter at each ∼1° grid point of the globe over any 31-year running time windows during 1880–2014. In observations, the CCs between the Niño-3.4 index and surface air temperature (SAT)/precipitation are significantly unstable at a 95% confidence level over 74.7%/73.6% of the globe, respectively, mainly over tropical Indian and Atlantic Oceans, Africa, Australia, North America, and Eurasia. Further Analyses on Community Earth system Model version 2 pacemaker simulations suggest that after the non-ENSO-related internal variability is largely removed, the simulated CCs are always significant over most of the tropics and North America. This suggests that internal variability is essential for driving unstable ENSO teleconnections over these regions mainly by modulating the Southern Oscillation and Pacific-North American teleconnections. Our findings on the nonstationary impacts of ENSO have important implications for understanding and enhancing global seasonal forecast skill. Approximately 74% of the world experiences unstable El Niño-Southern Oscillation (ENSO) impacts on surface air temperature (SAT) and precipitation in boreal winter on multidecadal timescales Internal variability plays an essential role in the unstable ENSO teleconnections over a broad region in the tropics and North America Internal variability affects linkages between ENSO and remote SAT/precipitation by modulating Southern Oscillation and Pacific-North American teleconnections The El Niño-Southern Oscillation (ENSO) phenomenon is the leading mode of interannual climate variability strongly influencing global climate. Skillful ENSO predictions are crucial for predicting global climate on seasonal timescales. H

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Enhancing global agricultural monitoring system for climate-smart agriculture

Climate Smart Agriculture

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Climate Smart Agriculture 2025年第1期2卷

作者： Le Yu Zhenrong Du Xiyu Li Jinhui Zheng Qiang Zhao Hui Wu Duoji weise Yuanzhen Yang Quan Zhang Xinyue Li Xiaorui Ma Xiaomeng Huang Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing China Ministry of Education Ecological Field Station for East Asian Migratory Birds Beijing China Tsinghua University (Department of Earth System Science)- Xi'an Institute of Surveying and Mapping Joint Research Center for Next-Generation Smart Mapping Beijing China School of Information and Communication Engineering Dalian University of Technology Dalian China Geothermal Geological Brigade Tibet Autonomous Region Geological and Mineral Exploration and Development Bureau Lhasa China Key Laboratory of Environment Change and Resources Use in Beibu Gulf Ministry of Education Nanning Normal University Nanning China Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation Nanning Normal University Nanning China

Global agricultural monitoring systems face unprecedented challenges due to intensifying climate change. This paper reviews the advancements in existing global agricultural monitoring systems, highlighting deficiencies in addressing extreme weather events, data integration, and real-time analysis. To overcome these limitations, we introduce the Earth system Model-Coupled Global Agricultural Monitoring system (ESM-GAMS), an advanced framework that combines satellite and near-surface remote sensing, artificial intelligence-driven modeling, supercomputing, and crop model to enhance the accuracy and timeliness of crop monitoring and yield predictions under diverse climate scenarios. By integrating multi-source remote sensing data, ESM-GAMS mitigates delays caused by satellite revisit cycles and weather interference, enabling near real-time monitoring with results available at hourly or minute-level intervals. Additionally, the system demonstrated high accuracy in yield simulations under extreme weather, with the improved WOFOST model achieving robust R 2 values ranging from 0.55 to 0.77, indicating its reliability in predicting yields across diverse conditions. ESM-GAMS not only enables detailed daily monitoring of crop growth, but also provides early-warning capabilities for extreme weather and its impact on prediction. By optimizing resource allocation, supporting climate resilience, and enabling global data computing, ESM-GAMS represents a further step toward achieving climate-smart agriculture.

关键词： Agricultural monitoring Earth system model Remote sensing Crop model

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A Machine Learning-Based Observation Operator for FY-4B GIIRS Brightness Temperatures Considering the Uncertainty of Label Data

Journal of Geophysical Research: Machine Learning and Comput...

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Journal of Geophysical research: Machine Learning and Computation 2025年第1期2卷

作者： Yonghui Li Wei Han Wansuo Duan Zeting Li Hao Li State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Severe Weather Meteorological Science and Technology (LASW) Beijing China CMA Earth System Modeling and Prediction Centre (CEMC) China Meteorological Administration Beijing China Key Laboratory of Meteorological Disaster Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD) Nanjing University of Information Science & Technology Nanjing China Artificial Intelligence Innovation and Incubation Institute Fudan University Shanghai China Shanghai Academy of Artificial Intelligence for Science (SAIS) Shanghai China

The increasing volume of satellite data, particularly hyperspectral infrared data, combined with the real-time monitoring requirements of numerical weather prediction (NWP) systems, has heightened the demand for computational efficiency and accuracy in radiative transfer models (RTM). Machine learning (ML) offers a promising approach, and numerous studies on ML-based RTM have emerged recently. However, existing ML-based RTMs for hyperspectral infrared were not end-to-end. Moreover, since the label data do not represent truth, models trained with loss functions like mean squared error (MSE) or mean absolute error (MAE) fail to account for its uncertainty. This limitation can lead to suboptimal model parameters, as training may assign higher weights to labels with larger errors. This study construct an end-to-end ML-based RTM focused on clear sky conditions over the ocean for the FengYun-4B satellite (FY-4B) Geostationary Interferometric Infrared Sounder (GIIRS), using maximum likelihood estimation (MLE) and MSE for training, respectively. MLE accounts for the uncertainty of labels. The results indicate both models achieve high accuracy, with mean errors within 0.1 K (K) and standard deviation (STD) of errors within 0.04 K compared to the labels. The model trained with MLE exhibits a mean error closer to 0 and a STD similar to the error STD of labels, suggesting better parameter configurations to reflect the actual error distribution of the labels. Additionally, the temperature and water vapor Jacobian computed by both models are comparable to those obtained from RTTOV, highlighting their potential for application as observational operator in satellite data assimilation for hyperspectral infrared sounder. An end-to-end machine learning-based radiative transfer model for clear sky has been developed for FY-4B GIIRS The model, trained using a likelihood-based loss function that weights each channel differently, captures the uncertainty of labels The Jacobian matrix calc

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Decadal changes of the intraseasonal oscillation during 1979–2016

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Advances in Climate Change research 2021年第6期12卷 772-782页

作者： WU Nan LI Ying LI Juan FENG Li-Cheng LIU Fei Earth System Modeling and Climate Dynamics Research Center Nanjing University of Information Science and TechnologyNanjing210044China Shanghai ZhongChuan NERC-SDT Co. LtdShanghai201114China National Marine Environmental Forecasting Center Ministry of Natural ResourcesBeijing100081China Key Laboratory of Marine Hazards Forecasting National Marine Environmental Forecasting CenterMinistry of Natural ResourcesBeijing100081China School of Atmospheric Sciences Sun Yat-sen University Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studiesand Southern Marine Science and Engineering Guangdong LaboratoryZhuhai519082China

The Intraseasonal Oscillation (ISO) is the cornerstone for 2–8-week subseasonal prediction. Understanding the decadal variation of the ISO is important for improving subseasonal prediction;however, there is still a gap in our knowledge of ISO dynamics. Here, we presented a method, an Empirical Orthogonal Function (EOF) analysis of 11-year-sliding ISO evolution, to objectively detect decadal variation of the ISO originated from the equatorial Indian Ocean (EIO) during 1979–2016. The results show that the properties of ISO have a notable decadal change since 1998 for both boreal summer and boreal winter seasons, mainly in its evolution rather than in its intensity at origin. During the pre-1998 epoch, the boreal summer intraseasonal oscillation (BSISO), was confined to the Indian Ocean;since 1998, however, it propagated northeastward across the Maritime Continent (MC) and the intraseasonal variability over the western North Pacific was significant enhanced. On the other hand, the boreal-winter ISO, usually known as Madden-Julian Oscillation (MJO) shows minor changes in MC ‘barrier effect’ between the two epochs, and continuously propagates eastward across the MC. The MJO only shows suppressed activity over the central equatorial Pacific in the post-1998 epoch. These decadal changes are related to the eastern Pacific cooling during the ‘global warming hiatus’ period rather than to the four-decade global warming. Results here provide a set of potential precursors for foreseeing ISO propagation under different mean states.

关键词： Decadal variation Intraseasonal oscillation Madden-Julian oscillation Boreal summer intraseasonal oscillation Global warming hiatus

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A Spatial-Temporal Projection Model for 10-30 Day Rainfall Forecast in South China

A Spatial-Temporal Projection Model for 10-30 Day Rainfall F...

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第八届全国优秀青年气象科技工作者学术研讨会

作者： Pang-Chi Hsu Tim Li Lijun You Jianyun Gao Hong-Li Ren Earth System Modeling Center and Key Laboratory of Meteorological Disaster Nanjing University of In International Pacific Research Center University of Hawaii Honolulu Hawaii Earth System Modeling Fujian Climate Center China Meteorological Administration Fuzhou Fujian China Laboratory for Climate Studies National Climate Center China Meteorological Administration Beijin

Extended-range (10-30 day) forecast, lying between well-developed short-range weather and long-range (monthly and seasonal) climate predictions, is one of the most challenging forecast currently faced by operational meteorological centers around the *** this study, a set of spatial-temporal projection (STP) models was developed to predict low-frequency rainfall events at lead times of 5-30 *** focused on early monsoon rainy season (mid April to mid July) in South *** ensure that the model developed can be used for real-time forecast, a non-filtering method was developed to extract the low-frequency atmospheric signals of 10-60 days without using a band-pass *** empirical models were built based on 12-yr (1996-2007) data, and independent forecast was then conducted for a 5-yr (2008-2012) *** assessment of the 5-year forecast of rainfall over South China indicates that the ensemble prediction of the STP models achieved a useful skill (with a temporal correlation coefficient exceeding 95% confidence level) at a lead time of 20 *** amplitude error was generally less than one standard deviation at all lead times of 5-30 ***, the STP models provided useful probabilistic forecasts with the ranked probability skill score between 0.3-0.5 up to 30-day forecast in *** evaluation demonstrated that the STP models exhibited useful 10-30 day forecast skills for real-time extended-range rainfall prediction in South China.

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What Drives the Decadal Variability of Global Tropical Storm Days from 1965 to 2019?

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Advances in Atmospheric Sciences 2022年第2期39卷 344-353页

作者： Yifei DAI Bin WANG Weiyi SUN Key Laboratory of Meteorological Disaster of Ministry of Education and Earth System Modeling CenterNanjing University of Information Science and TechnologyNanjing 210044China International Pacific Research Center University of Hawaii at ManoaHonoluluHI 96822USA Department of Atmospheric Sciences School of Ocean and Earth Science and TechnologyUniversity of Hawaii at ManoaHonoluluHI 96822USA Key Laboratory for Virtual Geographic Environment.Ministry of Education State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu ProvinceJiangsu Center for Collaborative Innovation in Geographical Information Resource Development and ApplicationSchool of Geography ScienceNanjing Normal UniversityNanjing 210023China

The tropical storm day(TSD)is a combined measure of genesis and *** reflects tropical cyclone(TC)overall activity,yet its variability has rarely been studied,especially *** we show that the global total TSDs exhibit pronounced interannual(3-6 years)and decadal(10 years)variations over the past five-to-six decades without a significant *** leading modes of the interannual and decadal variability of global TSD feature similar patterns in the western Pacific and Atlantic,but different patterns in the Eastern Pacific and the Southern Indian *** interannual and decadal leading modes are primarily linked to El Ni?o-Southern Oscillation(ENSO)and Pacific Decadal Oscillation(PDO),*** TSDs-ENSO relationship has been steady during the entire 55-year period,but the TSDs-PDO relationship has experienced a breakdown in the 1980 *** find that the decadal variation of TSD in the Pacific is associated with the PDO sea surface temperature(SST)anomalies in the tropical eastern Pacific(PDO-E),while that in the Atlantic and the Indian Ocean is associated with the PDO SST anomalies in the western Pacific(PDO-W).However,the PDO-E and PDO-W SST anomalies are poorly coupled in the 1980 s,and this"destructive PDO"pattern results in a breakdown of the TSDs-PDO *** results here have an important implication for seasonal to decadal predictions of global TSD.

关键词： tropical storm days(TSDs) interannual and decadal variations El Ni?o-Southern Oscillation Pacific Decadal Oscillation(PDO)

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Assimilation of All-sky Geostationary Satellite Infrared Radiances for Convection-Permitting Initialization and Prediction of Hurricane Joaquin(2015)

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Advances in Atmospheric Sciences 2022年第11期39卷 1859-1872页

作者： Lei ZHU Zhiyong MENG Yonghui WENG Fuqing ZHANG Key Laboratory of Meteorological Disaster Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environmental Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science and TechnologyNanjing 210044China Laboratory for Climate and Ocean–Atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China I.M.System Group(IMSG) at Environmental Modeling Center(EMC)NCEPNWSNOAACollege ParkMD 20740USA Department of Meteorology and Atmospheric Science and Center for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPennsylvania 16802USA

Intensity forecasting is one of the most challenging aspects of tropical cyclone(TC) forecasting. This work examines the impact of assimilating high-resolution all-sky infrared radiance observations from geostationary satellite GOES-13 on the convection-permitting initialization and prediction of Hurricane Joaquin(2015) with an ensemble Kalman filter(EnKF)based on the Weather research and Forecasting(WRF) model. Given that almost all operational global and regional models struggled to capture Hurricane Joaquin(2015)'s intensity, this study examines the potential in improving Joaquin's prediction when assimilating all-sky infrared radiances from GOES-13's water vapor channel. It is demonstrated that, after a few 3-hour cycles assimilating all-sky radiance, the WRF model was able to forecast reasonably well Joaquin's intensity,including its rapid intensification(RI). The improvement was largely due to a more realistic initial hurricane structure with a stronger, warmer, and more compact inner-core. Ensemble forecasts were used to further explore the important physical mechanisms driving the hurricane's RI. Results showed that the RI forecasts were greatly impacted by the initial inner-core vortex structure.

关键词： all-sky infrared radiance TC intensity EnKF inner-core structure

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Rapid increase in warm-wet compound extreme events with high health risks in southern China:Joint influence of ENSO and the Indian Ocean

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Advances in Climate Change research 2023年第6期14卷 856-865页

作者： Cai-Meng LIANG Liang ZHAO Shun-Wu ZHOU Xin-Yong SHEN Cun-Rui HUANG Yi-Hui DING Yan-Ju LIU Hao-Xin YAO Kai-Xing ZHOU Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Numerical Modeling for Atmosphere Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academyof SciencesBeijing100029China Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province Haikou 570203China Vanke School of Public Health Tsinghua UniversityBejing 100084China Institute of Healthy China Tsinghua UniversityBeijing 100084China National Climate Center China Meteorological AdministrationBejing 100081China Beijing Institute of Electronic System Engineering Bejing 100854China

High temperature and high humidity pose notable threats to the health and survival of humans,and the impact of compound extreme events involving multiple meteorological elements is usually greater than the sum of the impacts of individual extreme ***,there is limited research on the compound extreme meteorological events,defined based on the extreme of health risks rather than just the extreme of meteoro-logical elements,necessitating further investigation into their characteristics and underlying driving *** daily records of emergency ambulance dispatches from selected Chinese cities,together with daily average temperature and relative humidity data,this study identified and quantified warm-wet compound extreme events with high health risks(HRWWs)that occurred in southern China during *** revealed that HRWWs were most prevalent in the coastal region of southern *** annual frequency of HRWWs across China underwent a marked shift in 2014,with the rapid increase in recent years primarily contributed by the increase in summer HRWWs and advance and extension of the period of occurrence of HRWWs in *** analysis indicated that the changes in HRWWs in southern China during summer were primarily regulated by the EIl Nino-Southern Oscillation(ENSO)of the preceding winter and the springtime Indian Ocean basin-wide(IOBW)*** Nino and Indian Ocean warming force a reverse Walker circulation in the tropical Indian Ocean-western Pacific,strengthening the Philippine anticyclone(PAC)in *** weakens convection in the northwestern Pacific and enables the western Pacific subtropical high to extend westward over coastal areas of southern *** resulting abnormal atmospheric circulation causes prevailing subsidence over southern China,which is unfavorable for precipitation but conducive to maintaining high surface *** reduced precipitation,water vapor flux is increased owing to strengthened southwesterlies

关键词： Health risk Warm-wet compound events ENSO IOBW

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research on HRI Evaluation system and Diver Safety Equipment

Research on HRI Evaluation System and Diver Safety Equipment

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OCEANS 2024 - Halifax, OCEANS 2024

作者： Lee, Ye Jun Kim, Min-Gyu Shin, Myung-Jun Park, Tae Sung Kim, Jinhyung Kim, Sunghun Lee, Kichoon Lee, Jihun Min, Jeongtack Research Center Pohang Korea Republic of Pusan National University Hospital Pusan National University School of Medicine Department of Rehabilitation Medicine Busan Korea Republic of Institute of Technology Pusan National University Hospital Department of Convergence Medical Busan Korea Republic of Technical Research Center RNWare Co. Ltd Daegu Korea Republic of Gleam-Systems System Development Division Daejeon Korea Republic of Gleam-Systems Modeling and Simulation Division Daejeon Korea Republic of Marine Leisure Equipment R&d Center Pohang Korea Republic of

ISBN: (纸本)9798331540081

Scuba diving is a common aquatic leisure sport that many individuals enjoy in the sea. With the increasing number of people participating, there is a corresponding rise in related incidents and accidents. Typically, such events are caused by inadequate user proficiency with equipment, sudden onset of physical symptoms, failure to respond to external obstacles, and equipment malfunctions. As interest in scuba diving grows, the development of diver safety equipment that enhances convenience and usability through the interaction between divers and equipment is crucial, not only to assist underwater activities but also to preemptively prevent accidents. This paper explores the analysis of divers' physiological conditions and diver equipment evaluation criteria. Building upon this, it proposes a HRI(Human-Robot Interaction) evaluation system to facilitate the research and development of safety equipment for secure scuba diving operations. © 2024 IEEE.

关键词： Human robot interaction

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Effect of potential HONO sources on peroxyacetyl nitrate(PAN)formation in eastern China in winter

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Journal of Environmental Sciences 2020年第8期32卷 81-87页

作者： Jingwei Zhang Yitian Guo Yu Qu Yong Chen Ruipeng Yu Chaoyang Xue Rui Yang Qiang Zhang Xingang Liu Yujing Mu Jing Wang Can Ye Haihan Zhao Qiangqiang Sun Ziwen Wang Junling An State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry(LAPC) Institute of Atmospheric Physics(IAP)Chinese Academy of SciencesBeijing 100029China College of Earth Science University of Chinese Academy of SciencesBeijing 100049China College of Resources and Environmental Sciences China Agricultural UniversityBeijing 100193China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China Guangzhou Meteorological Observatory Guangzhou 511430China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijingChina Collaborative Innovation Center for Regional Environmental Quality BeijingChina State Key Laboratory of Water Environment Simulation School of EnvironmentBeijing Normal UniversityBeijing 100875China Center for Excellence in Urban Atmospheric Environment Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China College of Land Science and Technology China Agricultural UniversityBeijing 100193China Qinghai Climate Center Qinghai Meteorological BureauXiningQinghai 810001China

As an important secondary photochemical pollutant,peroxyacetyl nitrate(PAN)has been studied over decades,yet its simulations usually underestimate the corresponding observations,especially in polluted *** observations in north China found unusually high concentrations of PAN during wintertime heavy haze events,but the current model still cannot reproduce the observations,and researchers speculated that nitrous acid(HONO)played a key role in PAN *** the first time we systematically assessed the impact of potential HONO sources on PAN formation mechanisms in eastern China using the Weather research and Forecasting/Chemistry(WRF-Chem)model in February of *** results showed that the potential HONO sources significantly improved the PAN simulations,remarkably accelerated the RO x(sum of hydroxyl,hydroperoxyl,and organic peroxy radicals)cycles,and resulted in 80%–150%enhancements of PAN near the ground in the coastal areas of eastern China and 10%–50%enhancements in the areas around 35–40°N within 3 km during a heavy haze *** direct precursors of PAN were aldehyde and methylglyoxal,and the primary precursors of PAN were alkenes with C>3,xylenes,propene and *** above results suggest that the potential HONO sources should be considered in regional and global chemical transport models when conducting PAN studies.

关键词： Nitrous acid(HONO) Peroxyacetyl nitrate(PAN) WRF-Chem model Winter haze RO x cycles

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