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From concept to action: a united, holistic and One Health approach to respond to the climate change crisis

Infectious Diseases of Poverty 2022年第1期11卷 68-73页

作者： Renhe Zhang Xu Tang Jian Liu Martin Visbeck Huadong Guo Virginia Murray Catherine Mcgillycuddy Bing Ke Gretchen Kalonji Panmao Zhai Xiaoming Shi Jiahai Lu Xiaonong Zhou Haidong Kan Qunli Han Qian Ye Yong Luo Jianmin Chen Wenjia Cai Huiling Ouyang Riyanti Djalante Alexander Baklanov Lu Ren Guy Brasseur George Fu Gao Lei Zhou Integrated Research on Disaster Risk International Centre of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health&Institute of Atmospheric Sciences Fudan UniversityShanghai200438China Science Division United Nations Environment Programme(UNEP)United Nations AvenueGigiriPO Box 30552Nairobi00100Kenya GEOMAR Helmholtz Centre for Ocean Research Kiel and Kiel University KielGermany Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina University of Chinese Academy of Sciences Chinese Academy of SciencesBeijingChina UK Health Security Agency LondonSE18UGUK The Administrative Center for China’s Agenda 21 Ministry of Science and Technology of ChinaBeijing100038China Institute for Disaster Management and Reconstruction Sichuan UniversityChengdu610207China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing100081China China CDC Key Laboratory of Environment and Population Health National Institute of Environmental HealthChinese Center for Disease Control and PreventionBeijing100021China One Health Center of Excellence for Research and Training School of Public HealthSun Yat-Sen UniversityGuangzhouChina National Institute of Parasitic Diseases Chinese Center for Disease Control and Prevention(Chinese Center for Tropical Diseases Research)ShanghaiChina Integrated Research On Disaster Risk-IPO BeijingChina State Key Lab of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing100875China Ministry of Education Key Laboratory for Earth System Modeling and Department of Earth System ScienceTsinghua UniversityBeijingChina ASEAN Secretariat Indonesia Integrated Research on Disaster Risk(IRDR)JakartaIndonesia Science and Innovation Department World Meteorological Organization(WMO)7 bisAvenue de la PaixBP2300CH-1211Geneva 2Switzerland Max Planck Institute for Meteorology HamburgGermany Chinese Center for Dis

It is unequivocal that human influence has warmed the planet,which is seriously affecting the planetary health including human *** climate change should not only be a slogan,but requires a united,holistic action and a paradigm shift from crisis response to an ambitious and integrated approach *** the urgent needs to tackle the risk connection between climate change and One Health,the four key messages and recommendations that with the intent to guide further research and to promote international cooperation to achieve a more climate-resilient world are provided.

关键词： Climate change One Health International coordination and cooperation Risk-oriented recommendations

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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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Spatiotemporal variation of mortality burden attributable to heatwaves in China,1979–2020

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Science Bulletin 2022年第13期67卷 1340-1344,M0004页

作者： Huiqi Chen Liang Zhao Wei Dong Liangliang Cheng Wenjia Cai Jun Yang Junzhe Bao Xin-Zhong Liang Shakoor Hajat Peng Gong Wannian Liang Cunrui Huang School of Public Health Sun Yat-sen UniversityGuangzhou 510080China Shanghai Key Laboratory of Meteorology and Health Shanghai Meteorological ServiceShanghai 200030China The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China 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 Department of Earth System Science Tsinghua UniversityBeijing 100084China Institute for Environmental and Climate Research Jinan UniversityGuangzhou 510632China School of Public Health Zhengzhou UniversityZhengzhou 450001China Earth System Science Interdisciplinary Center&Department of Atmospheric and Oceanic Science University of MarylandCollege Park MD 20742USA Department of Epidemiology and Population Health London School of Hygiene and Tropical MedicineLondon WC1E 7HTUK Department of Earth Sciences the University of Hong KongHong Kong 999077China Vanke School of Public Health Tsinghua UniversityBeijing 100084China Institute of Healthy China Tsinghua UniversityBeijing 100084China

热浪通过增加死亡和发病风险导致巨大的公共卫生负担.而在气候变暖与社会经济发展相交织的风险下,中国人群所面临的热浪导致的健康负担的时间演变规律、空间分布特征及其驱动因素仍然存在大量空白.本研究应用基于事件的归因损失评估方... 详细信息

热浪通过增加死亡和发病风险导致巨大的公共卫生负担.而在气候变暖与社会经济发展相交织的风险下,中国人群所面临的热浪导致的健康负担的时间演变规律、空间分布特征及其驱动因素仍然存在大量空白.本研究应用基于事件的归因损失评估方法定量评估了过去40年格点水平的每日热浪归因死亡人数.研究发现,热浪相关死亡人数具有快速增长、非线性和极端性的特征,40年间增加了4倍,2010年代年均归因死亡人数达15500人.归因死亡负担还呈现强烈的区域异质性,华东和华中地区负担更重.随着时间的推移,中国可归因死亡人数上升的主要影响因素是增加的热浪发生频率,其次是人口增长和老龄化.这项工作为民众提供了更为直观的高温健康危害信息,同时为制定有针对性的气候变化适应措施提供重要信息.

关键词：社会经济发展气候变化适应区域异质性死亡人数损失评估公共卫生极端性发病风险

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HRPGAN: A GAN-based Model to Generate High-resolution Remote Sensing Images 7

HRPGAN: A GAN-based Model to Generate High-resolution Remote...

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7th Annual International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2019

作者： Sun, Hai Wang, Ping Chang, Yifan Qi, Li Wang, Hailei Xiao, Dan Zhong, Cheng Wu, Xuelian Li, Wenbo Sun, Bingyu Co.Ltd Shanghai China Department of Airborne Remote Sensing National Disaster Reduction Center of China Beijing China Institute of Technology Innovation Hefei Institute of Physical Science Chinese Academy of Sciences Hefei China Third Research Institute of the Ministry of Public Security Shanghai China Guizhou Key Laboratory of Economics System Simulation Guizhou University of Finance and Economics Guiyang China Beijing Aerospace Flight Control Center Beijing China Institute of Intelligent Machines Chinese Academy of Sciences Hefei China

Generative adversarial networks (GAN) has been mainly used in the generation of natural images such as MNIST, CIFAR10 as well as Imagenet datasets and achieves satisfying generation results. However, GAN always fails in generating high quality high-resolution remote sensing images because remote sensing images are large in size and have various ground objects. To address this issue, a novel framework called High-Resolution PatchGAN (HRPGAN) is introduced in this paper. The structure of HRPGAN follows PatchGAN, but the batch normalization layers are removed and the ReLU activation is replaced by the SELU activation. In addition, a new loss function consisting of the adversarial loss, perceptual reconstruction loss and regularization loss is used in HRPGAN. Experiment results show that the proposed HRPGAN model generates the more diverse and lifelike images in HR remote sensing generation than Bicubic method and TGAN model. © Published under licence by IOP Publishing Ltd.

关键词： Chemical activation

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Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

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Advances in Atmospheric Sciences 2020年第7期37卷 663-670页

作者： Fei LIU Chen XING Jinbao LI Bin WANG Jing CHAI Chaochao GAO Gang HUANG Jian LIU Deliang CHEN School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Sun Yat-sen UniversityZhuhai 519082China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China Earth System Modeling and Climate Dynamics Research Center Nanjing University of Information Science and TechnologyNanjing 210044China Department of Geography University of Hong KongPokfulamHong Kong Department of Atmospheric Sciences and International Pacific Research Center University of Hawaii at ManoaHonoluluHI 96822USA Department of Environmental Science Zhejiang UniversityHangzhou 310058China State key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory for Virtual Geographic Environment Ministry of EducationJiangsu Provincial State Key Laboratory Cultivation Base of Geographical Environment EvolutionSchool of Geography ScienceNanjing Normal UniversityNanjing 210023China Department of Earth Sciences University of GothenburgGothenburg 40530Sweden

The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines.A recent eruption occurred on 12 January 2020(Fig.1a),and this volcano is still active with the occurrence of volcanic *** eruption has become a deep concern worldwide,not only for its damage on local society,but also for potential hazardous consequences on the Earth’s climate and environment.

关键词： Volcano Philippines worldwide

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on Tibetan Plateau

SSRN

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SSRN 2024年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin School of Geography South China Normal University Shipai Campus Guangzhou510631 China Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu 210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu 210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Comprehending the spatial variations of evapotranspiration (ET) and its components on Tibetan Plateau (TP) is crucial for grasping the dynamics of the regional water cycle and energy balance. However, the influence of various environmental factors on ET and its components remains unclear. This study addresses this gap by utilizing observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and influencing factors. The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory simulation performance with an average R2 value of 0.75. Our analysis indicates that in alpine meadow, the ratio of transpiration to ET is generally higher (0.55) compared to alpine steppe (0.39). In terms of spatial distribution, both precipitation and leaf area index significantly impact ET and transpiration. Precipitation emerges as the primary driver of interannual spatial variations in ET, while leaf area index plays a pivotal role in regulating proportion of transpiration. Furthermore, our results reveal a transition from water-dominated to energy-dominated in TP grassland ecosystem at an aridity index of 0.73. This finding is significant as it challenges the common application of an aridity index of 0.65 to distinguish arid from humid regions. It suggests that TP grassland, within the 0.65-0.73 range, remain primarily water-driven. These findings enhance our comprehension of the intricate interactions within the water cycle. © 2024, The Authors. All rights reserved.

关键词： Evapotranspiration

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on the Tibetan Plateau

SSRN

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SSRN 2024年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin School of Geography South China Normal University Shipai Campus Guangzhou510631 China Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Study region: The Tibetan Plateau in China, the Third Pole of the *** focus: Accurate descriptions of spatial variation in evapotranspiration (ET) and its components on the Tibetan Plateau (TP) are crucial for understanding the dynamics of the regional water cycle and energy balance. However, how various environmental factors affect ET and its components remains unclear. This study addresses this gap using observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and underlying *** hydrological insights for the region: The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory model performance with an average R² of 0.75. The ratio of transpiration to ET was generally higher in alpine meadows (0.55) than alpine steppes (0.39). Across the TP, precipitation and the leaf area index together shaped spatial variation in ET and transpiration. Precipitation emerged as the primary driver of interannual variation in ET, while the leaf area index strongly regulated the proportion of ET accounted for by transpiration. Furthermore, above aridity index values of 0.73, grassland ecosystems transitioned from water to energy. This finding is significant as it challenges the common application of an aridity index value of 0.65 to distinguish arid from humid regions. It suggests that TP grasslands, with an AI of 0.65-0.73, remain primarily water-limited. © 2024, The Authors. All rights reserved.

关键词： Biotic

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Climatic and Biotic Controls of Evapotranspiration Across Grassland Ecosystems on Tibetan Plateau

SSRN

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SSRN 2024年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin School of Geography South China Normal University Shipai Campus Guangzhou510631 China Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation School of Ecology and Environment Hainan University Haikou570228 China Center for Eco-Environment Restoration Engineering of Hainan Province Hainan University Haikou570228 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Understanding the spatial variations of evapotranspiration (ET) and its components on Tibetan Plateau (TP) is pivotal for grasping the regional water cycle and energy balance dynamics. Yet it is unclear how the changes of the intricate synergy among diverse environment factors significantly impacts the patterns of ET and its transformation state. Addressing this gap, this study employed observational data from 14 sites, utilizing the Shuttleworth-Wallace-Hu (SWH) model to investigate the spatial relationships between ET, its components, and influencing factors. Model parameters of SWH were optimized by Monte Carlo method, achieving a commendable simulation performance with a mean R2 value of 0.75. Our analysis reveals that in alpine meadow, the ratio of transpiration (T) to ET (T/ET) is generally higher (0.55) compared to alpine steppe (0.39). The T/ET values for hover around or below 0.5, indicating a balanced contribution of various ET components. Spatially, both PPT and LAI have an impact on ET and T/ET. PPT emerges as the primary driver of interannual spatial variations in ET, while LAI plays a crucial role in regulating T/ET. Our results further demonstrate that a transition from water-dominated to energy-dominated systems in TP grassland ecosystem at an approximately aridity index of 0.73. This is noteworthy considering the general application of an aridity index of 0.65 to delineate arid from humid regions. It implies that TP grasslands, within the 0.65-0.73 range, remain primarily water-driven. This insight holds substantial implications for comprehending water-energy dynamics in similar ecosystems, challenging the conventional binary categorization of arid and humid areas. Such findings are of immense significance in enhancing understanding of the intricate interactions of the water cycle between land and the atmosphere. © 2024, The Authors. All rights reserved.

关键词： Water supply

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Regime shift to extensive valley glaciations over High Mountain Asia during the Early-Middle Pleistocene

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Nature communications 2025年第1期16卷 5185页

作者： Qing Yan Lewis A Owen Ting Wei Philip D Hughes Xiaohan Kong Nanxuan Jiang Jinzhe Zhang Zhongshi Zhang Huijun Wang State Key Laboratory of Earth System Numerical Modeling and Application/Nansen-Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. yanqing@***. Department of Marine Earth and Atmospheric Science North Carolina State University Raleigh NC USA. State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing China. Department of Geography School of Environment Education and Development University of Manchester Manchester UK. State Key Laboratory of Earth System Numerical Modeling and Application/Nansen-Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. Department of Atmospheric and Oceanic Sciences School of Physics Peking University Beijing China. State Key Laboratory of Climate System Prediction and Risk Management Nanjing University of Information Science and Technology Nanjing China. Key Laboratory of Meteorological Disaster/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing China.

In contrast to the well-established onset of Northern Hemisphere high-latitude glaciation at ~2.7 Ma, the timing and drivers of the intensified glaciation over High Mountain Asia (HMA) remain elusive, as glacial geologic evidence within this region is inherently fragmentary. Here, we offer a spatiotemporally complete view of glacier behavior over HMA spanning the last 3 Ma using transient climate-glaciation simulations to address this challenge. We illustrate that intensified glaciations with expanded ice caps and widespread valley glaciation began at ~0.9 Ma over the monsoonal-influenced southern HMA confirmed by the glacial sediments, whereas the intensification started earlier (~1.5 Ma) over the westerly-influenced western HMA, with a further intensification at ~1.0-0.9 Ma, supported by paleoenvironmental proxies. The intensification of glaciation masks obvious shifts in the amplitude and pacing of glacier variability (e.g., the establishment of the 100-ka cycle) and induces larger environmental perturbations, which are in line with geologic evidence and largely linked with the long-term global cooling during the mid-Pleistocene transition.

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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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