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New findings on the influence of El Nino events on tropical cyclone formation

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science China Earth sciences 2024年第3期67卷 892-893页

作者： Liguang WU department of {1. and Oceanic sciences Institute of Atmospheric SciencesFudan UniversityShanghai 200438China

Tropical cyclones typically form over warm tropical and subtropical ocean surfaces, as their formation and intensification rely primarily on the energy provided by the ocean. Pioneering research by Gray (1.68) revealed that the formation of tropical cyclones requires the sea surface temperature (SST) to be no less than 26.5℃. Consequently, SST is commonly recognized as a crucial parameter among the environmental factors influencing tropical cyclone formation(Gray, 1.79;Emanuel and Nolan, 2004).

关键词： tropical cyclone ocean

Reduced Spring Precipitation Bias and Associated Physical Causes over South China in FGOALS-f3 Climate Models:Experiments with the Horizontal Resolutions

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Journal of Meteorological Research 2024年第4期38卷 784-804页

作者： Peng ZI Yimin LIU Jiandong LI Ruowen YANG Bian HE Qing BAO department of {1. science Yunnan UniversityKunming 650504 State Key Laboratory of Numerical Modeling for atmospheric {1.s and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029

Considerable spring precipitation occurs over South China(SC),a region that is adjacent to large-scale Asian topography and *** reasonable simulation is crucial for improving regional climate *** study investigates spring precipitation biases over SC and their possible causes in atmosphere-only and coupled Flexible Global Ocean–Atmosphere–Land System finite-volume version 3(FGOALS-f3) models with different horizontal *** performance of spring precipitation simulation over SC varies across different FGOALS-f3 model versions,with the best reproducibility in the high-resolution coupled model(25 km).In the low-resolution atmosphere-only model(1.0–1.5 km),the precipitation dry bias over SC is closely linked to overestimated surface sensible forcing over the eastern Tibetan Plateau(TP),which weakens the subtropical anticyclone over the western Pacific(SAWP) through regional circulation *** contrast,the high-resolution atmosphere-only model further amplifies surface thermal forcing in the Asian continents,causing intensified land–sea thermal contrast between the Southeast Asian continents and western Pacific,enhanced southerly winds and SAWP,and increased water vapor transport into ***,the reduced middle–high level cold bias over 1.°–30°N in the high-resolution atmosphere-only model intensifies the East Asian westerly jet and ascent over SC,leading to enhanced spring precipitation *** high-resolution coupled model simulation not only reduces sea surface cold bias over the Bay of Bengal,thus intensifying the Indian–Burma trough and strengthening low-level water vapor transport into SC,but also enhances ascent over *** a result,the high-resolution coupled model better reproduces the magnitude and pattern of spring precipitation over SC than its atmosphere-only *** with low-resolution models,the domain-mean spring precipitation dry bias decreases by 1..2% over SC in the high-resolution atmosphere-only mod

关键词： South China spring precipitation high resolution Flexible Global Ocean–Atmosphere–Land System finite-volume version 3(FGOALS-f3)models simulation

Quantitative estimation of global mean precipitation throughout the Phanerozoic era

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science China Earth sciences 2024年第5期67卷 1616-1624页

作者： Xiujuan BAO Yongyun HU Laboratory for Climate and Ocean-atmospheric Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China

Quantitatively estimating the global mean precipitation(GMP)throughout Earth's history is crucial for enhancing our understanding of long-term climate evolution and the hydrological ***,currently there is no established methodology for estimating global mean ***,we present the first study that estimates GMP in the Phanerozoic *** relationship between GMP and global mean surface temperature(GMST)is investigated by analyzing data from 23 models in the Coupled Model Intercomparison Project phase 6(CMIP6).The result reveals consistent and significant impact of temperature on precipitation,with a sensitivity range of 2–3%K^(-1..Additionally,we propose a method for accessing latitudinal variations in precipitation caused by land area distributions and paleo-Koppen climatic *** climatic belts are determined based on geological indicators such as coals,evaporites,and glacial *** GMP is thus quantitatively estimated by combining variations in GMST,land area distributions,and paleo-koppen climatic belts,spanning from 540 Ma to the present *** quantitative GMP curve demonstrates fluctuations in GMP about 500 mm yr^(-1.,with values ranging from 948 to1.42 mm yr-1.ver the Phanerozoic *** curve aligns closely with findings derived from numerical *** presented paleoprecipitation variations facilitate a more comprehensive understanding of the interconnected geological and paleoclimatic developments.

关键词： Paleoprecipitation Paleoclimate K?ppen climatic belts Global mean precipitation Hydrological cycle

A high-resolution dataset for lower atmospheric process studies over the Tibetan Plateau from 1.81.to 2020

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Big Earth Data 2024年第3期8卷 540-565页

作者： Fei Li Shupo Ma Jinhuan Zhu Han Zou Peng Li Libo Zhou department of Lower {1. Observation Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina State Key Laboratory of atmospheric Boundary Layer Physics and atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina

ABSTRACT A high-resolution meteorological dataset(≤1. km)over the Tibetan Plateau(TP)is the foundation for investigating and predicting the weather and climate over *** TP Subregional Dynamical Downscaling(TPSDD)dataset is a newly developed high-spatial-temporal resolution gridded dataset for land‒air exchange pro-cesses and lower atmospheric structure studies over the whole TP region,taking the climate characteristics of each TP subregion into *** dataset spans from 1.81.to 2020,covering the TP with a temporal resolution of 2 hr and spatial resolution of 1. *** elements of the dataset include near-surface land-air exchange parameters,such as downward/upward long-wave/shortwave radiation flux,sensible heat flux,latent heat flux,*** addition,the vertical distributions of 3-dimensional wind,temperature,humidity,and pressure from the surface to the lower stratosphere are also *** evaluations were con-ducted to verify the performance of the TPSDD dataset by compar-ing TPSDD/reanalysis with surface and vertical observations through the calculation of statistical *** results demonstrate the accuracy and superiority of this dataset against reanalysis data,which provides great potential for future climate change research.

关键词： Tibetan Plateau WRF model dynamical downscaling land‒air interaction the lower atmosphere

A new portable open-path instrument for ambient NH_(3) and on-road emission measurements

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Journal of Environmental sciences 2024年第2期136卷 606-614页

作者： Wenhao Dai Shanshan Wang Sanbao Zhang Jian Zhu Chuanqi Gu Zhibin Sun Ruibin Xue Bin Zhou Shanghai Key Laboratory of atmospheric Particle Pollution and Prevention(LAP3) Department of Environmental Science and EngineeringFudan UniversityShanghai 200438China Institute of Eco-Chongming(IEC) Shanghai 202162China Institute of atmospheric {1.s Fudan UniversityShanghai 200433China

Increased attentions to vehicle emission of NH_(3)have been paid since it is generally regarded as an important source in urban ***,we developed a movable instrument based on Differential Optical Absorption Spectroscopy(DOAS)principle for detecting on-road NH_(3),which can avoid the losses in the sampling process attributed to the non-sampling *** this mobile DOAS,the temporal resolution,detection limit and relative error for NH_(3)were 1.min,2.29 ppbv and 4.57%±2.44%,*** employed to the on-road measurements along the arterial highway in Shanghai,the spatial distributions of NH_(3)and NO were obtained,and their dependence of traffic and road conditions were *** slopes of linear regression between NH_(3)and NO were 0.40,0.02 and 0.07 on the Middle Ring Road,Outer Ring Road and Chongming Island Ring *** indicates that light gasoline vehicles(LGVs)were found to be the main contributor to NH_(3)emissions,while heavy-duty diesel vehicles(HDVs)mainly emitted *** on the measured NH_(3)in the tunnel,the mileagebased NH_(3)emission factor per vehicle was estimated to be 1..9±6.3 mg/*** reported open-path instrument can be broadly used in on-road pollutant monitoring or vehicle emissions,and the measurements can reveal the real situation of emission characteristics,even find the abnormal operations of vehicle catalyst system.

关键词： Ammonia Traffic emissions DOAS Emission factor Mobile measurements

Quantification of CO_(2) Emissions from Three Power Plants in China Using OCO-3 Satellite Measurements

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Advances in atmospheric {1.s 2024年第11期41卷 2276-2288页

作者： Yang YANG Minqiang ZHOU Wei WANG Zijun NING Feng ZHANG Pucai WANG College of Data science Jiaxing UniversityJiaxing 314000China LAGEO Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China CNRC Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of atmospheric Environment and Extreme Meteorology Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Shanghai Ecological Forecasting and Remote Sensing Center Shanghai 200030China department of {1. and Oceanic sciences/Institute of {1. sciences Fudan UniversityShanghai 200082China

Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO_(2) emissions from point sources based on Orbiting Carbon Observatory-2 and-3(OCO-2 and OCO-3) satellite measurements, but the factors affecting CO_(2) flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO_(2) emissions from three power plants in China based on OCO-3 XCO_(2) measurements. Moreover, flux uncertainties resulting from wind information, background values,satellite CO_(2) measurements, and atmospheric stability are discussed. This study highlights the CO_(2) flux uncertainty derived from the satellite measurements. Finally, satellite-based CO_(2) emission estimates are compared to bottom-up *** satellite-based CO_(2) emission estimates at the Tuoketuo and Nongliushi power plants are ~30 and ~1. kt d^(-1. smaller than the Open-Data Inventory for Anthropogenic Carbon dioxide(ODIAC) respectively, but ~1. kt d^(-1. larger than the ODIAC at Baotou.

关键词： OCO-3 power plant CO_(2)emission Gaussian Plume Model

Path signature-based XAI-enabled network time series classification

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science China(Information sciences) 2024年第7期67卷 91-106页

作者： Le SUN Yueyuan WANG Yongjun REN Feng XIA department of Jiangsu Collaborative Innovation Center of {1. Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and Technology School of Computing Technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

Distribution and Formation Causes of PM_(2.5) and O_(3) Double High Pollution Events in China during 201.–20

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Advances in atmospheric {1.s 2024年第6期41卷 1235-1250,I0004-I0021页

作者： Zhixuan TONG Yingying YAN Shaofei KONG Jintai LIN Nan CHEN Bo ZHU Jing MA Tianliang ZHAO Shihua QI department of {1. science School of Environmental SciencesChina University of GeosciencesWuhan 430074China State Key Laboratory of atmospheric Boundary Layer Physics and atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Research Centre for Complex Air Pollution of Hubei Province Wuhan 430074China Laboratory for Climate and Ocean–Atmosphere Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China Eco-Environmental Monitoring Centre of Hubei Province Wuhan 430074China Key Laboratory of atmospheric Chemistry China Meteorological AdministrationBeijing 100081China School of atmospheric Physics Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430074China

Fine particulate matter(PM_(2.5))and ozone(O_(3))double high pollution(DHP)events have occurred frequently over China in recent years,but their causes are not completely *** this study,the spatiotemporal distribution of DHP events in China during 201.–20 is *** synoptic types affecting DHP events are identified with the Lamb–Jenkinson circulation classification *** meteorological and chemical causes of DHP events controlled by the main synoptic types are further *** show that DHP events(1.55 in total for China during 201.–20)mainly occur over the North China Plain,Yangtze River Delta,Pearl River Delta,Sichuan Basin,and Central *** occurrence frequency increases by 5.1.during 201.–1.,and then decreases by 56.1.during 201.–*** main circulation types of DHP events are“cyclone”and“anticyclone”,accounting for over 40%of all DHP events over five main polluted regions in China,followed by southerly or easterly flat airflow types,like“southeast”,“southwest”,and“east”.Compared with non-DHP events,DHP events are characterized by static or weak wind,high temperature(20.9℃ versus 23.1.)and low humidity(70.0%versus 64.9%).The diurnal cycles of meteorological conditions cause PM_(2.5)(0300–1.00 LST,Local Standard Time=UTC+8 hours)and O_(3)(1.00–21.0 LST)to exceed the national standards at different periods of the DHP *** pollutant conversion indices further indicate the rapid secondary conversions during DHP events,and thus the concentrations of NO_(2),SO_(2) and volatile organic compounds decrease by 1..1.,4.7%and 4.4%,*** results of this study can be informative for future decisions on the management of DHP events.

关键词： double high pollution events PM_(2.5) ozone spatiotemporal distribution meteorological causes chemical composition characteristics

A Physics-informed Deep-learning Intensity Prediction Scheme for Tropical Cyclones over the Western North Pacific

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Advances in atmospheric {1.s 2024年第7期41卷 1391-1402页

作者： Yitian ZHOU Ruifen ZHAN Yuqing WANG Peiyan CHEN Zhemin TAN Zhipeng XIE Xiuwen NIE department of {1. and Oceanic sciences&Institute of {1. sciences Fudan UniversityShanghai 200438China Shanghai Typhoon Institute of China Meteorological Administration Shanghai 200030China department of {1. sciences and International Pacific Research Center University of Hawaii at ManoaHonolulu 96822USA Key Laboratory of Mesoscale Severe Weather/MOE and School of the Atmospheric SciencesNanjing UniversityNanjing 210023China School of Computer science Fudan UniversityShanghai 200438China

Accurate prediction of tropical cyclone(TC)intensity is challenging due to the complex physical processes ***,we introduce a new TC intensity prediction scheme for the western North Pacific(WNP)based on a time-dependent theory of TC intensification,termed the energetically based dynamical system(EBDS)model,together with the use of a long short-term memory(LSTM)neural *** time-dependent theory,TC intensity change is controlled by both the internal dynamics of the TC system and various environmental factors,expressed as environmental dynamical *** LSTM neural network is used to predict the environmental dynamical efficiency in the EBDS model trained using besttrack TC data and global reanalysis data during 1.82–*** transfer learning and ensemble methods are used to retrain the scheme using the environmental factors predicted by the Global Forecast System(GFS)of the National Centers for Environmental Prediction during 201.–*** predicted environmental dynamical efficiency is finally iterated into the EBDS equations to predict TC *** new scheme is evaluated for TC intensity prediction using both reanalysis data and the GFS prediction *** intensity prediction by the new scheme shows better skill than the official prediction from the China Meteorological Administration(CMA)and those by other state-of-art statistical and dynamical forecast systems,except for the 72-h *** at the longer lead times of 96 h and 1.0 h,the new scheme has smaller forecast errors,with a more than 30%improvement over the official forecasts.

关键词： tropical cyclones western North Pacific intensity prediction EBDS LSTM