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Numerical prediction of oceanic mesoscale circulation and satellite altimetry data assimilation in the Western Pacific

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Science China Earth Sciences 2025年第3期68卷 909-927页

作者： Zhijin LI Jianfang FEI Renhe ZHANG Xingliang JIANG Wenlong MA Xiaoping CHENG Lei LIU Guihua WANG Changlin CHEN Department of Atmospheric and oceanic Sciences Institute of Atmospheric Sciences Fudan University Shanghai Key laboratory of ocean-land-atmosphere Boundary dynamics and climate Change College of Meteorology and oceanology National University of Defense Technology

oceanic mesoscale circulations, primarily manifesting as eddies, typically span around 100 km horizontally and persist for about a month. These circulations represent the main component of oceanic kinetic energy and are referred to as the“weather” of the ocean. Forecasting efforts, focused on periods from a day to a month, target these mesoscale *** in eddy-resolving models, observing systems such as Argo floats and satellite altimeters, and data assimilation techniques have enabled systems like HYCOM in the United States and Mercator-ocean in Europe to predict these features effectively. To further enhance mesoscale forecasting, the Pacific Regional ocean Forecast System(RPOFS) was developed for the pan-western Pacific(100°E–178°E, 20°S–50°N). Covering the dynamic Kuroshio and Kuroshio Extension regions, RPOFS features a 3 km horizontal grid and 67 vertical levels, with a multi-scale three-dimensional variational data assimilation(MS-3DVAR) scheme implemented. This system assimilates data from various sources, including satellite sea surface height and temperature, as well as subsurface profiles. In particular, an enhanced altimeter data assimilation methodology allows explicitly constraining both barotropic and baroclinic components of sea surface height. RPOFS demonstrates reliable forecasting of mesoscale circulations, with five-day forecasts accurately predicting eddies larger than 150 km and capturing features of the Kuroshio large meander. Forecasting errors are comparable to or smaller than those of HYCOM and Mercator-ocean systems.

关键词： Western Pacific ocean ocean model Mesoscale eddy Numerical prediction Multiscale data assimilation Satellite altimetry

Predictability Study of Weather and climate Events Related to Artificial Intelligence Models

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Advances in Atmospheric Sciences 2025年第1期42卷 1-8页

作者： Mu MU Bo QIN Guokun DAI Department of Atmospheric and oceanic Sciences&Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China Shanghai Key laboratory of ocean-land-atmosphere Boundary dynamics and climate Change Fudan UniversityShanghai 200438China Shanghai Frontiers Science Center of Atmosphere-ocean Interaction Fudan UniversityShanghai 200438China CMA-FDU Joint laboratory of Marine Meteorology Shanghai 200438China Key laboratory of Polar Atmosphere-ocean-ice System for Weather and climate Ministry of EducationShanghai 200438China

Conducting predictability studies is essential for tracing the source of forecast errors,which not only leads to the improvement of observation and forecasting systems,but also enhances the understanding of weather and climate *** the past few decades,dynamical numerical models have been the primary tools for predictability studies,achieving significant ***,with the advances in artificial intelligence(AI)techniques and accumulations of vast meteorological data,modeling weather and climate events using modern data-driven approaches is becoming trendy,where FourCastNet,Pangu-Weather,and GraphCast are successful *** this perspective article,we suggest AI models should not be limited to forecasting but be expanded to predictability studies,leveraging AI's advantages of high efficiency and self-contained optimization *** this end,we first remark that AI models should possess high simulation capability with fine spatiotemporal resolution for two kinds of predictability *** models with high simulation capabilities comparable to numerical models can be considered to provide solutions to partial differential equations in a data-driven ***,we highlight several specific predictability issues with well-determined nonlinear optimization formulizations,which can be well-studied using AI models,holding significant scientific *** addition,we advocate for the incorporation of AI models into the synergistic cycle of the cognition–observation–model *** predictability studies have the potential to transform“big data”to“big and better data”and shift the focus from“AI for forecasts”to“AI for science”,ultimately advancing the development of the atmospheric and oceanic sciences.

关键词： predictability artificial intelligence models simulation and forecasting nonlinear optimization cognition–observation–model paradigm

Extracting ship and heading from Sentinel-2 images using convolutional neural networks with point and vector learning

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Journal of oceanology and Limnology 2025年第1期43卷 16-28页

作者： Xiunan LI Peng CHEN Jingsong YANG Wentao AN Dan LUO Gang ZHENG Aiying LU ocean College Zhejiang UniversityZhoushan 316021China State Key laboratory of Satellite ocean Environment dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China National Satellite ocean Application Service Ministry of Natural ResourcesBeijing 100081China

Obtaining accurate ship positions and headings in remote sensing images plays a crucial role in various ***,current deep learning-based methods primarily focus on ship position detection,while the detection of ship wakes relies on traditional non-deep learning approaches,which often underperform in complex marine *** proposed a novel,simple,and efficient method called Point-Vector *** proposed method leverages convolutional neural networks(CNN)for feature extraction and subsequently integrates multi-scale features to generate high-resolution feature *** the final stage,ship positions and headings are represented using a combination of points and *** experiments with results from automatic identification system(AIS)reports demonstrate that our method achieved impressive performance in two-class ship target detection,with an average precision of 96.4%,recall rate of 94.3%,and an F 1 score of 95.2%.Notably,the average heading error was 3.3°.The proposed model achieved a practical inference speed(FPS>30),and the average processing time for inferring a large-scale Sentinel-2 remote sensing image was 11.4 s.

关键词： deep learning ship detection heading remote sensing Sentinel-2

Different mechanisms of Eurasian snow cover on precipitation during the early and late pre-rainy season in South China

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Science China Earth Sciences 2025年第3期68卷 882-897页

作者： Zhixiang XIAO Anmin DUAN Yuhang CHEN Chen WEI Xiaoli LUO School of Geography and Planning Nanning Normal University State Key laboratory of Marine Environmental Science College of Ocean and Earth Sciences Xiamen University Guangxi climate Center

The interannual variability in precipitation during the pre-rainy season(PRS) in South China is significantly correlated with Eurasian snow cover. This study elucidates the distinct mechanisms by which Eurasian snow cover anomalies in March influence precipitation during the early(pre-monsoon) and late(post-monsoon) PRS. In the early PRS, anomalous snow cover in the western region of Eastern Europe(WEE) triggers a southeastward-propagating wave train that impacts Central *** teleconnection pattern induces anomalous cyclonic circulation in Central Asia, which reinforces the midlatitude zonal wind,contributing to the zonal wind wave train pattern towards East Asia. As a result, the East Asian subtropical westerly jet and the western North Pacific subtropical high are enhanced, and the related upper-level divergence, ascending motion, and moisture convergence in South China are intensified, collectively promoting precipitation there. In contrast, during the late PRS, increased snow cover across the eastern sector of Eastern Europe(EEE) and the region east of Lake Baikal(ELB) inhibit South China's precipitation. The wave pattern associated with the EEE(ELB) snow anomaly propagates southeastwards(southwards) to lower latitudes, intensifying the western North Pacific subtropical high. Furthermore, the perturbation stemming from the ELB region induces negative geopotential height anomalies aloft and amplifies the baroclinic anticyclone over the western Pacific. This resulted in prevailing subsidence over South China, which in turn suppresses precipitation during the late PRS. Numerical experiments corroborate the observed circulation adjustments and precipitation responses to snow cover anomalies in the two periods, lending credence to the proposed mechanisms.

关键词： Eurasian snow cover Pre-rainy season South China Wave train

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Isobaric enzymatic assays reveal depth-dependent variation in microbial ectoenzyme activities in the deepest ocean on Earth

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Science China Earth Sciences 2025年第1期68卷 185-194页

作者： Junwei CAO Jiahua WANG Hongge ZHANG Junhao DENG Binbin PAN Jiawang CHEN Li ZHANG Jiasong FANG College of oceanography and Ecological Science Shanghai Ocean UniversityShanghai201306China ocean College Zhejiang UniversityZhoushan316000China laboratory for Marine Biology and Biotechnology Qingdao National Laboratory for Marine Science and TechnologyQingdao266237China

Microbial ectoenzymes play essential roles in the transformation and mineralization of organic matter in the ***,conventional methods for measuring microbial ectoenzyme activities(MEAs)in the deep ocean under atmospheric conditions can misrepresent the metabolic activities of indigenous microbial *** overcome this limitation,we measured the activities of three microbial ectoenzymes(aminopeptidase,α-glucosidase,andβ-glucosidase)under both atmospheric and in situ pressure conditions in seawater collected using pressure-retaining and non-pressure-retaining samplers in the Challenger Deep,Mariana *** the case of aminopeptidase andα-glucosidase,the highest isobaric MEAs were observed in the surface layer(50 m),followed by those at abyssopelagic depths(4,000–6,000 m)for aminopeptidase,hadal realm(10,903 m)forα-glucosidase,whileβ-glucosidase activity exhibited the highest value at 10,903 ***,the isobaric MEAs in hadal waters were commonly found to be higher than the decompressed counterparts,highlighting the importance of pressure-retaining sampling and isobaric enzymatic *** half-saturation constant(K_(m))showed a general decreasing trend with depth,suggesting that the deep ocean microbes might have adapted to the high-pressure and oligotrophic environment by increasing their ectoenzyme's affinity to ***,particle-free MEAs contribute more to the total MEAs in the deep ocean than particle-associated MEAs,suggesting the significance of cell-associated and dissolved ectoenzymes in ocean *** study provides a foundation for future investigations of MEAs in the ocean and has important implications for understanding the dynamics of microbially mediated biogeochemical cycling in marine ecosystems.

关键词： Pressure-retaining sampling Microbial ectoenzyme activity Deep-sea microbes High pressure Mariana Trench

Rapid reduction of air pollution and short-term exposure risks in China

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Journal of Environmental Sciences 2025年第3期149卷 126-138页

作者： Hao Fan Chuanfeng Zhao Yikun Yang Xingchuan Yang State Key Joint laboratory of Environmental Simulation and Pollution Control School of EnvironmentBeijing Normal UniversityBeijing 100875China laboratory for climate and ocean-Atmospheric Studies Department of Atmospheric and Oceanic SciencesSchool of PhysicsPeking UniversityBeijing 100871China College of Resource Environment and Tourism Capital Normal UniversityBeijing 100048China

With the continuous control of anthropogenic emissions,China’s air quality has improved significantly in recent *** this background,research on how the short-term exposure risks caused by air pollution in China have changed is *** study utilized hourly concentration data from ground observation stations and the official air quality guidelines of the Ministry of Ecology and Environment of China and the World Health Organization as standards to systematically investigate the spatiotemporal characteristics and short-term exposure risks of air pollution in China from 2015 to *** results indicate that various atmospheric pollutants except for ozone showed a decreasing trend ***,both single pollutant air pollution days(SAPDs)and multiple pollutant air pollution days(MAPDs)showed varying degrees of reduction within 15 and 25 days,*** was dominated mainly by excessive PM_(2.5)and PM_(10)pollutants,while MAPD was dominated mainly by excessive pollutant combinations,including PM_(2.5)+PM_(10),CO+PM_(2.5)+PM_(10),and SO_(2)+PM_(2.5)+PM_(10).As the concentration of atmospheric pollutants decreased,the total excess risk(ER)decreased yearly from 2015 to 2022,but there were significant regional ***,the ER is less than 0.25%in southern China,in the range of 0.25%-0.5%in the North China Plain and some cities in the northeast,and higher than 1%in the *** matter is currently the primary pollutant posing short-term exposure risk in China,especially due to the impact of sandstorm *** study indicates that China’s atmospheric cleaning action is significantly beneficial for reducing health risks.

关键词： Air pollution Emission-reduction Total excess risk Particulate matter China

Rising frequency of ozone-favorable synoptic weather patterns contributes to 2015-2022 ozone increase in Guangzhou

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Journal of Environmental Sciences 2025年第2期148卷 502-514页

作者： Nanxi Liu Guowen He Haolin Wang Cheng He Haofan Wang Chenxi Liu Yiming Wang Haichao Wang Lei Li Xiao Lu Shaojia Fan School of Atmospheric Sciences Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Guangdong Provincial Observation and Research Station for climate Environment and Air Quality Change in the Pearl River Estuary Key Laboratory of Tropical Atmosphere-Ocean System(Sun Yat-sen University)Ministry of EducationZhuhai 519082China

Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns(SWPs),however,the consistency of different classification methods is rarely *** this study,we apply two widely-used objective methods,the self-organizing map(SOM)and K-means clustering analysis,to derive ozone-favorable SWPs at four Chinese megacities in *** find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese *** the case of classifying six SWPs,the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods,and the difference in themean frequency of each SWP is less than 7%.The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature,lower cloud cover,relative humidity,and wind speed,and stronger subsidence compared to climatology *** find that during 2015-2022,the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 days/year,faster than the increases in the ozone exceedance days(3.0 days/year).The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of *** particular,the significant increase in ozone-favorable SWPs in 2022,especially the Subtropical High type which typically occurs in September,is consistent with a long-lasting ozone pollution episode in Guangzhou during September *** results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.

关键词： Ozone(O3) Objective weather classification methods Synoptic weather patterns Trends Guangzhou

Compositions and Distributions of Secondary Organic Aerosols and Their Tracers over the Pearl River Estuary Region Influenced by Continental and Marine Air Masses

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Advances in Atmospheric Sciences 2025年第4期42卷 682-696页

作者： Zhenhao LING Junlin HUANG Liqing WU Yee Jun THAM Guizhen FANG Bing WU Lili MING Xuemei WANG Xiang DING School of Atmospheric Sciences Sun Yat-sen UniversityKey Laboratory of Tropical Atmosphere-Ocean SystemMinistry of Educationand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)ZhuhaiChina College of ocean and Meteorology Guangdong Ocean UniversityZhanjiangChina School of Marine Sciences Sun Yat-sen UniversityZhuhaiChina Technical Center of Gongbei Customs District of China ZhuhaiChina College of Environment and climate Guangdong-Hongkong-Macao Joint Laboratory of Collaborative Innovation for Environmental QualityJinan UniversityGuangzhouChina Guangzhou Institute of Geochemistry Chinese Academy of SciencesGuangzhouChina

The compositions and distributions of monoterpenes,isoprene,aromatics and sesquiterpene SOA tracers(SOAM,SOAI,SOAA and SOAS,respectively)at an island site(Da Wan Shan Island,DWS)were investigated in the context of the influence of continental and marine air masses over the Pearl River Estuary(PRE)region in winter *** sum concentration of SOA tracers was 6.2–132.8 ng m^(−3),with SOAM and SOAI as the main components in both continental(scenarios A1 and A2)and marine air masses(scenario A3),as well as their combination(scenario A4).The highest and lowest levels of SOAM were observed in A1 and A3,respectively,which were mainly related to the variations in meteorological conditions,precursor concentrations,and the degree of photochemical *** MBTCA/HGA(3-methyl-1,2,3-butanetricarboxylic acid/3-hydroxyglutaric acid)ratios suggested a less significant contribution fromα-pinene to *** variations of SOAI in the different scenarios were associated with differences in relative humidity,particle acidity,and isoprene/NOx *** respective highest and lowest concentrations of aromatics SOA tracers in A1 and A3 revealed the influence of anthropogenic precursors from upwind continental areas,which was confirmed by the correlation among biogenic and anthropogenic *** results of the tracer-based-method suggested dominant contributions of SOAs from aromatics and monoterpenes,with the highest concentrations in A1.A WRF-Chem simulation revealed that the SOAs from the above precursors only contributed 12%–25%to the total SOA at DWS,while the spatial distributions of SOAs further highlighted that the abundance of SOAs over the PRE region in winter is highly associated with air masses transported from upwind continental areas.

关键词： secondary organic aerosols tracers continental and marine air masses Pearl River Estuary region

Subsurface Temperature and Salinity Structures Inversion Using a Stacking-Based Fusion Model from Satellite Observations in the South China Sea

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Advances in Atmospheric Sciences 2025年第1期42卷 204-220页

作者： Can LUO Mengya HUANG Shoude GUAN Wei ZHAO Fengbin TIAN Yuan YANG Frontier Science Center for Deep ocean Multispheres and Earth System(FDOMES)and Physical oceanography laboratory/Key laboratory of ocean Observation and Information of Hainan Province Sanya Oceanographic InstitutionOcean University of ChinaQingdao 266100/Sanya 572000China Laoshan laboratory Qingdao 266237China

Three-dimensional ocean subsurface temperature and salinity structures(OST/OSS)in the South China Sea(SCS)play crucial roles in oceanic climate research and disaster ***,real-time OST and OSS are mainly obtained through in-situ ocean observations and simulation by ocean circulation models,which are usually challenging and ***,dynamical,statistical,or machine learning models have been proposed to invert the OST/OSS from sea surface information;however,these models mainly focused on the inversion of monthly OST and *** address this issue,we apply clustering algorithms and employ a stacking strategy to ensemble three models(XGBoost,Random Forest,and LightGBM)to invert the real-time OST/OSS based on satellite-derived data and the Argo ***,a fusion of temperature and salinity is employed to reconstruct OST and *** the validation dataset,the depth-averaged Correlation(Corr)of the estimated OST(OSS)is 0.919(0.83),and the average Root-Mean-Square Error(RMSE)is0.639°C(0.087 psu),with a depth-averaged coefficient of determination(R~2)of 0.84(0.68).Notably,at the thermocline where the base models exhibit their maximum error,the stacking-based fusion model exhibited significant performance enhancement,with a maximum enhancement in OST and OSS inversion exceeding 10%.We further found that the estimated OST and OSS exhibit good agreement with the HYbrid Coordinate ocean Model(HYCOM)data and BOA_Argo dataset during the passage of a mesoscale *** study shows that the proposed model can effectively invert the real-time OST and OSS,potentially enhancing the understanding of multi-scale oceanic processes in the SCS.

关键词： subsurface temperature and salinity structures clustering algorithms stacking strategy temperature and salinity fusion the South China Sea