Water security is a strategic issue for the sustainable development of the Chinese nation. Urban stormwater and mine water serve not only as hazards but also as valuable unconventional water resources. Their deep geological storage presents dual benefits of strategic water resource reserves and disaster mitigation. Nevertheless, the large-scale application of this technology is hindered by the absence of standardized criteria for target layer selection, unclear coupling mechanisms of the thermal-stress-seepage-hydrochemical-microbial fields leading to uncontrollable permeability enhancement and capacity expansion, ambiguous evolutionary patterns of groundwater environments in target layers following storage, and a lack of methodologies for assessing geo-environmental effects. This study addresses the core scientific issue of geo-environmental effects of deep geological water storage by constructing a comprehensive scientific framework that encompasses refined hydrogeological evaluation, intelligent target layer optimization, geological environment evolution, fracturing-induced capacity expansion, microbial regulation, and multi-field coupling. Focusing on mine water from inland mining areas and urban stormwater in the Guangdong-Hong Kong-Macao Greater Bay area, the framework quantitatively evaluates the hydrogeological structure and host geological environment of deep target layers such as sandstone and limestone. By integrating machine learning with multi-source geological data, it establishes an environmentally friendly intelligent optimization method for selecting deep storage target layers. Through water-rock-microbe coupling simulations and field deep storage experiments, a coupled numerical model of the thermal-stress-seepage-hydrochemical-microbial fields is developed using AI high-resolution modeling and digital twin technologies. This model reveals the mechanisms of water-rock interactions during deep water storage, elucidates the role of microbial communities in regulating seepage channel opening and closure, and delineates the evolutionary patterns of the host geological environment. Furthermore, an assessment method for geo-environmental effects of deep storage is established, accompanied by differentiated risk identification, early warning, and prevention and control strategies. The expected results will provide a scientific basis for resolving technical bottlenecks in geological water storage and advancing the safe and efficient utilization of unconventional water resources.

The dynamic coupling between the Low-Level Jet (LLJ) and cloud-precipitation systems acts as a vital nexus linking boundary layer processes with mesoscale weather systems, representing a central challenge in understanding extreme precipitation generation and predictability. Previous studies demonstrate that LLJs function as a “moisture conduit and dynamic engine,” critically governing cloud initiation, organization, and precipitation efficiency. This is accomplished by amplifying low-level moisture flux and convergence, modulating vertical wind shear and instability energy, and altering boundary layer turbulent mixing and momentum transport. Conversely, cloud and precipitation processes release latent heat that substantially adjusts thermal and pressure gradients and secondary circulations, while modifying moisture loading and surface flux budgets. These interactions further modulate the jet’s intensity, position, and vertical structure, establishing a multi-scale bidirectional feedback loop in which complex topography exerts a significant modulating influence.This study systematically reviews multi-source coordinated observation systems, elucidating their potential to resolve the dynamic structure, moisture transport, and vertical microphysical processes of LLJs with high fidelity. It also discusses key advancements in convection-resolving regional models and data assimilation techniques regarding the realistic simulation of LLJ diurnal cycles and the quantitative characterization of the thermodynamic environment, including moisture convergence and shear. Despite these advances, multi-source coordination faces persistent challenges related to retrieval uncertainties—particularly the coupling of vertical air motion with particle fall speed in vertically pointing measurements and spectral broadening induced by wind shear, as well as ambiguities in interpreting radar reflectivity within complex microphysical contexts. Meanwhile, numerical simulation necessitates tighter integration with in-situ calibration and artificial intelligence to advance the systematic synthesis of complex non-linear coupling mechanisms. Finally, it is recommended that future research prioritize high-resolution three-dimensional network observations oriented towards “process closure,” deep fusion of cross-platform datasets for optimized parameterizations, cross-scale high-resolution modeling with explicit uncertainty quantification, and interpretable AI-assisted diagnosis. Collectively, these strategies aim to deepen the mechanistic understanding and enhance predictive capabilities regarding the complex interactions between LLJs and cloud-precipitation systems.

Since the 1990s, the Eddy Covariance (EC) system has been widely applied and has become a standard technique for quantifying exchanges of energy and matter between terrestrial ecosystems and the atmosphere. Owing to its ability to provide direct, in situ, and continuous flux measurements, it plays an irreplaceable role in global change research, land surface process modeling, and the validation and calibration of remote sensing products. This paper systematically reviews the fundamental measurement principles and the historical development of the eddy covariance technique, highlighting its theoretical basis in turbulent transport and high-frequency covariance calculations. Particular emphasis is placed on comparing the technical differences and applicable scenarios of open-path and closed-path EC systems. These differences are analyzed in terms of gas sampling methods, frequency response characteristics, environmental adaptability, and data processing procedures. Open-path systems, with their fast response, are advantageous in capturing high-frequency fluctuations, whereas closed-path systems offer better control of environmental conditions and are more suitable for harsh or variable climates. The strengths and limitations of each system are discussed in relation to specific ecosystem types and measurement objectives. In addition, the applications of both systems in measuring surface fluxes of carbon dioxide, water vapor, heat, and other trace gases are summarized, along with a detailed examination of the major sources of uncertainty, including instrumental errors, observational environmental constraints, data processing methods, as well as flux calculation errors. In recent years, the EC technique has been increasingly extended to measurements of multiple trace gas fluxes and integrated into unmanned aerial vehicle platforms, enabling observations over broader spatial scales and more heterogeneous landscapes. This development allows EC measurements to serve as an important “bridge” between ground-based observations and satellite-derived products. Nevertheless, several challenges remain, including the limited spatial representativeness of flux source areas, persistent issues with energy balance non-closure, and reduced measurement accuracy under complex terrain and extreme environmental conditions. Future developments of eddy covariance systems are expected to focus on improving measurement accuracy, enhancing data processing algorithms, expanding application domains, and advancing the development of low-power, miniaturized, and automated systems, thereby better supporting in-depth investigations of ecosystem water, heat, and carbon fluxes in the context of global environmental change.

The high heterogeneity of terrestrial underlying surfaces and the complex coupling characteristics of ecohydrological processes lead to unclear multi-scale coupling evolution mechanisms of terrestrial ecohydrological processes, imperfect coupling simulation systems for multi-factor interactions, including hydrology, soil, vegetation and human activities, as well as insufficient cognition of the resource and environmental effects and derivative risks induced by the multi-scale variations in ecohydrological processes. These issues have become the core bottleneck for clarifying and solving a series of hydrological, ecological, resource, and environmental problems, and also restrict the refined management of regional water resources and the sustainable development of ecological environments.To solve the above issues, this paper breaks through the coupling and effects of typical terrestrial ecological and hydrological systems, coupling from the perspective of the multi-element coupling cycle, energy cycle, and biological process. It proposes the future research on the multi- change process of inland river basin hydrological and ecological and its water resources effects, the multi-scale change mechanism of the coupling process of hydrological and ecological in the Loess plateau, the multi-scale measurement and change mechanism of the hydrological and ecological processes in the lake basin, and the multi-scale change mechanism of the hydrological and ecological processes the Great Bay Area and its social and economic risks and the resource and ecological environment effects of the changes in the terrestrial hydrological and ecological processes. Revealing the typical terrestrial-scale coupling mechanism of inland river basins, the Loess Plateau, lake basins, the Great Bay Area and other typical terrestrial hydrological and ecological processes developing the monitoring methods of key hydrological and ecological parameters such as evapotranspiration, and developing the coupling simulation technology of terrestrial hydrological and ecological processes, elating the resource and environmental effects and its socio-economic risks of the changes in typical terrestrial hydrological and ecological processes under the background of global change, and providing a scientific basis the rational use of regional water resources, ecological environment protection and global change response.

Currently, the increasingly severe climate change, frequent occurrence of extreme weather events, growing pressure on food security, and the accelerated development of smart agriculture have posed severe challenges to the development of agricultural meteorology. Systems science provides solutions for agricultural meteorology to address these challenges, and developing systematic agricultural meteorology is an urgent need to promote the development of agricultural meteorology. Based on the systematic characteristics of the research object of agricultural meteorology, this article proposes the connotation and theoretical framework of systematic agricultural meteorology and looks forward to the research prospects. The results show that systematic agricultural meteorology is a science that uses system analysis methods to study the interaction mechanisms, dynamic evolution laws, and impacts and optimization paths of various elements within the agricultural meteorological system. It focuses on the interrelationships among various elements in the agricultural meteorological system and emphasizes the application of cybernetics, computer technology, and mathematical theories. Through systematic observation, analysis, description, simulation, and optimization, it builds agricultural meteorological models to achieve state expression, dynamic simulation, and regulatory improvement of the agricultural meteorological system, promoting the coordinated development of the agricultural meteorological system. The key scientific issues of systematic agricultural meteorology include multi-source data scale conversion, multi-factor synergy mechanisms, and multi-process coupling model construction. The research goal is to optimize the structure of the agricultural meteorological system and collaboratively achieve high-yield, high-quality, high-efficiency, and sustainable agricultural production. Systematic agricultural meteorology is a new form and new engine for the development of agricultural meteorology. Through theoretical innovation, technology integration, and service reconfiguration, it promotes the transformation of agricultural production from “relying on nature” to the intelligent paradigm of “knowing nature and working accordingly”, realizing the paradigm shift from empirical judgment to intelligent decision-making, and providing scientific support for addressing the challenges of food security under climate change and developing new quality productive forces in agricultural meteorology.

Under the backdrop of resource competition among world powers and policy adjustments in resource-rich countries, the strategic attributes and significance of copper resources have become increasingly prominent. The competition among major powers over resources has intensified, and the copper resource industry chain and supply chain are facing significant uncertainties and risks. Studying the resilience of the copper resource industry chain and supply chain trade network is of great significance for ensuring the security of copper resources and the stability of the global copper resource industry chain and supply chain. By comprehensively considering all products in the entire copper resource industry chain and supply chain, including upstream mining, midstream smelting, and downstream processing, an analysis framework for the resilience of the international trade network is constructed. Through describing the capabilities and characteristics of network nodes and structures, the evolution characteristics of the resilience of the copper resource industry chain and supply chain network are depicted from both dynamic and static dimensions. The research shows that at the node resilience level, China has a significant advantage in the upstream and midstream, but the downstream is showing a downward trend. Resource-endowed countries such as the Democratic Republic of the Congo and Chile have high resilience in the upstream and midstream due to their resource advantages, but their performance in the downstream is not outstanding. Industrial powers such as Germany and the United States have seen a decline in their upstream resilience, but their overall resilience across the entire chain is relatively prominent, and they still hold important positions in the upstream, midstream, and downstream. At the static structural resilience level, resilience in all links is showing a downward trend, and recovery capabilities are all inadequate, with stronger resistance capabilities in the upstream and downstream. At the dynamic structural resilience level, the polarization effect of the upstream and downstream networks has weakened, and their stability capabilities need to be improved. Midstream trade is increasingly concentrated on important links, leading to a decline in resistance to attacks. In the entire chain, the motivation for re-establishing trade links stems primarily from a country's existing status as a trade hub. Trade hub countries dominate the establishment of potential new links and have stronger reconstruction capabilities.

Microbes are known to show a great spatiotemporal distribution, and exert extensive and intensive geological agents in both modern days and Earth history. These features make the microbes play important roles on great changes of Earth environments, enabling important and wide applications in geoengineering including the pollutant remediation, decrease of atmospheric CO₂, geohazards prevention, as well as toxicity decrease. This necessitates the cross-disciplinary construction from microbial Earth to microbial geoengineering.It is well known that microbes, the engineer of elemental geochemical cycles, have played the key roles in the geoengineering fields including carbon sink, ecological remediation and the agriculture practice. The carbon pump and the microbial carbon pump, the important mechanisms to transport the atmospheric CO₂ into the sediments or seawater, are documented to mainly regulate by the microbial communities either in the sea or on the land. Microbes are widely involved into, and known as the engineer of, the geochemical cycles of greenhouse gases including CH₄, CO₂ and N₂O. These microbial processes could be exploited in the geoengineering to promote the carbon sink or decrease the carbon release. Microbial transformation of a series of metal ions as well as the degradation on organics has been widely used in the ecological remediation of polluted environments. Microbial release of elements including carbon, nitrogen, phosphor etc., from a variety of minerals is applied in agriculture practice. The artificial microbial mixtures on the basis of natural communities could be used as the nature-based fertilizers in the farming practice. Microbial roles, played on the precipitation and erosion of minerals, could also be applied into rocks and soils engineering, deep Earth engineering and mining industry. The microbial application to these geoengineerings will greatly save the costs, remarkably promote efficiency and noticeably protect the natural environments. Microbial transformation of the expansive clay minerals into no-expansive ones could be applied into the oil recovery by water flooding as well as the rocks and soils geotechnical engineering. Carbonate factory is known to be primarily induced by microbial communities via the precipitation of calcium carbonate from the fluids which could be introduced into the building of artificial islands in the sea, the filling and repairing of rock cracks, cementation of coarse grains in a variety of geoengineering. Microbial erosion of minerals could be exploited into the mining industry via the release of metals of economic significance from ores. The presence of the so-called deep biosphere, featured by the dominance of extreme environment microbes, will exert positive and negative effects on the underground storage of dangerous materials including the nuclear wastes, CO₂ and hydrogen gas. The investigations on the microbial roles on these materials as well as the storage containers are of in particular importance.Whilst most microbial geoengineering has been conducted to prevent and control the geohazards that have come into being in natural environments, microbes could further provide the early warning of some geohazards including the biotic or ecological crisis, climatic and environmental disasters, as well as landslides due to their sensitive response to minor environmental changes. To construct the early warning geoengineering via the on-site filed observatory network is of importance so that we could take some measures to prevent the occurrence of the geohazards, or make the positive use of the microbial roles but suppress the negative roles.

Aerosols are key factors influencing the energy balance of the Earth-atmosphere system and atmospheric environmental changes. High-precision inversion of their optical parameters has long been a topic of interest in atmospheric environmental remote sensing. Passive remote sensing of aerosol optics primarily utilizes their scattering effects in the visible/near-infrared wavelength bands. However, this approach typically relies on solar scattered radiation as the radiation source, rendering it inapplicable at night and during high-latitude winters (polar nights). Infrared hyperspectral remote sensing technology can resolve the unique spectral absorption and scattering fingerprint characteristics of aerosols, serving as another means to achieve aerosol remote sensing and providing a powerful supplement to traditional visible/near-infrared inversion techniques. This paper systematically elaborates on the fundamental principles of infrared hyperspectral inversion for aerosol microphysical parameters, focusing on key technologies such as physical mechanisms and detection instruments, radiative transfer models, and inversion algorithms. Particular emphasis is placed on discussing the key parameters of existing hyperspectral radiometers, the characteristics of hyperspectral forward radiative transfer models, and the advantages and disadvantages of different inversion methods. Based on this, the paper further outlines future research directions, proposing a focus on developing high-precision, high-efficiency forward radiative transfer models, utilizing the rich information within hyperspectral data to improve inversion algorithms, and actively advancing multi-platform collaborative detection technologies.

The Chinese continental shelf, a region heavily influenced by human activities, has experienced significant ecological and environmental changes. Studying this area is of great scientific and practical importance for advancing oceanographic knowledge and promoting research on marine environmental protection and resource utilization. In recent years, intensified human activities have caused notable changes in the water environment, with Harmful Algal Blooms (HABs) showing new characteristics and shifts in dominant species. This paper provides a systematic review of research on water environmental changes and HABs occurrences in the Chinese continental shelf, offering a comprehensive analysis of major ecological and environmental challenges and outlining prospects for future research. The findings indicate that the marine ecological environment in this region is increasingly influenced by phosphorus limitation and the roles of organic nitrogen and phosphorus, accompanied by a shift in dominant HABs species from diatoms to dinoflagellates, and, in some areas, the simultaneous occurrence of HABs and green tides. These changes are driven by both ongoing alterations in terrestrial inputs and intrinsic self-regulatory mechanisms within the marine ecosystem, reflecting the cumulative effects of long-term environmental changes. Notably, there is a significant time lag between reductions in terrestrial pollution and decreases in HABs frequency, complicating the evaluation of management effectiveness and challenging the scientific determination of ecological risk thresholds or tipping points. Despite considerable progress in understanding the evolution of water environments and risks of HABs in China, significant challenges remain, including insufficient long-term and systematic observational data, the requirement to expand the research scope, and incomplete knowledge of land-sea interaction mechanisms. Future research should focus on elucidating land-sea coupling processes, enhancing marine environmental monitoring networks, improving data processing and technological innovation, and clarifying the thresholds for nitrogen and phosphorus management while developing integrated strategies that encompass monitoring, tracing, calculation, and management. These efforts are crucial for advancing marine environmental research in the Chinese continental shelf.

This paper reviews the 15-year development process of the Integrated Risk Governance Project (IRGP) under IHDP/Future Earth, summarizes its major research achievements, and provides prospects for future research directions in this field. The first five years of IRGP (2010-2014) were carried out under the International Human Dimensions Programme on Global Environmental Change (IHDP), focusing on global integrated risk governance research. Six main research themes were included: social-ecologic system, model and modeling, entry mechanism, early warning system, case comparison, risk governance paradigms. Over the past ten years, IRGP has continued under the framework of the Future Earth (FE), jointly initiated and led by the International Science Council (ISC, formed through the merger of ICSU and ISSC) and United Nations system organizations such as UNESCO, UNEP, and UNU. Its main research directions have included: natural disaster and advanced technology risks, climate change risks in coastal regions, risks from urbanization and agriculture, financial and global systemic risks, as well as green growth and integrated risk management. Major achievements of IRGP include: the paradigm of comprehensive disaster reduction and risk defense—the consilience model, compilation of the Atlas of Natural Disasters in China, compilation of the World Atlas of Natural Disasters, comprehensive rapid assessment studies of global compound chain disasters and mega-disaster risks, construction of the global environmental risk governance paradigm, and systematic analyses of Earth environmental risk prevention and control. Comparing IRGP’s 15-year research progress with the trends of international political, economic, social, environmental, and technological development, future integrated risk governance research should address systemic risks of the Earth and the world, focusing on the trinity of tackling global climate change, reducing disaster risks, and achieving sustainable development. It is advisable to promptly establish an international science programme for integrated disaster risk prevention based on the successful experience and existing work of IRGP, as it is highly essential for ensuring the security and sustainable development of the community with a shared future for mankind.

Oceanic Mesoscale Eddies (ME) carry more than 90% of the kinetic energy in the upper global ocean, playing vital roles in the material and energy transport. They are highly active in the South China Sea (SCS), with complex dynamics for their generation and dissipation, which are received an increasingly attention from physical oceanographers. Through comprehensive analysis of extensively relevant literatures, it is found that the understanding of the three-dimensional structural characteristics of ME in the SCS more clear, the mechanisms of generation mainly include local wind stress, intrusion of the Kuroshio from the Luzon Strait, the westward propagation of Rossby wave in the Pacific Ocean, and a combination of multiple factors. ME’s dissipation is mainly caused by instability during their propagation or interaction with internal waves. It is shown that there is the ability to reconstruct and predict ME for those popular numerical models, data assimilation, and artificial intelligence technologies, but their accuracy still needs to be further improved. It aims to provide a systematic reference for the comprehensive understanding of ME dynamical processes and the improvement of their operational forecasting skills in the SCS. We suggest that combining dynamics theory, advanced ocean numerical models and data assimilation, big data and artificial intelligence to optimize ME simulation, is one of the key points for eddy research and forecasting in the future.

Amidst the accelerating activation of polar cryosphere tipping points due to global warming， significant challenges must be overcome to understand their state and changes， including sparse observations， insufficient physical knowledge， and limitations of traditional model simulations. Artificial Intelligence （AI） provides a powerful tool for efficiently extracting information from vast polar datasets and bridging cognitive gaps. This paper summarizes notable progress by Chinese researchers in AI applications for the polar cryosphere： \mathrm{①} Sea ice forecasting: purely data-driven deep learning models (e.g., SICNet, SIPNet) have been developed, significantly improving weekly, monthly, and seasonal-scale forecasts of Arctic/Antarctic sea ice concentration. Some models incorporate physical constraints and outperform traditional dynamical and statistical models. Various methods (e.g., improved U-Net, EW-Net, SAC-Net, and PMDRnet) have been proposed for sea ice type identification, lead extraction, sea ice thickness relationship modeling, and enhancing the spatial resolution of passive microwave imagery. \mathrm{②} Ice sheet surface hydrology: Applied Random Forest (RF) and BP neural networks were applied to estimate surface melt of the Greenland Ice Sheet and identify supraglacial lakes. An improved U-Net model was used to automatically extract surface water bodies of the Antarctic ice sheet/ice shelf with high accuracy, thereby overcoming the limitations of traditional NDWI methods. \mathrm{③} Subglacial systems: A novel method based on Variational Autoencoders (VAE) and unsupervised clustering was used to automatically detect subglacial lakes from ice-penetrating radar data, thereby improving efficiency and accuracy. \mathrm{④} Crevass identification: Improved U-Net and its variants (e.g., ResUNet) were applied to automatically extract surface crevasse distributions on Antarctic ice shelves from SAR and optical imagery. \mathrm{⑤} Ice stratigraphy and topography: Deep learning (e.g., EisNet and ST-SOLOv2) was employed to automatically extract internal isochronous layers and bedrock interfaces from radargrams, aiming to solve this long-standing manual bottleneck. \mathrm{⑥} Other applications include: Mass balance reconstruction of covered ice sheets (fusing multi-source data with SVM/BPNN), radiation balance dataset construction (RF), near-surface air temperature inversion (RF/DNN), ice shelf basal channel identification (improved U-Net), intelligent classification of glacial seismic events (autoencoders and Gaussian mixture models), GPS data interpolation, tropospheric delay modeling, and identification of geological structures. Although Chinese polar cryosphere AI research began relatively late, it has developed rapidly and yielded fruitful results, demonstrating significant potential in data-driven modeling, automated feature extraction, and multisource information fusion. Current challenges include model interpretability, insufficient integration of physical mechanisms, scarcity of high-quality labeled data, and limited generalization ability in complex regions. Future efforts should focus on developing physically constrained AI models, advancing multimodal learning, enhancing model robustness and interpretability, and strengthening international collaboration and data-sharing to more accurately characterize polar cryosphere changes and support global climate response and risk assessment.

Land surfaces are important components of the Earth’s system. The land surface has an important influence on the weather and climate system through processes such as energy, moisture, carbon, and nitrogen cycles, coupling, and interactions with the atmosphere. The study of numerical modelling and forecasting of land surface processes is a hot topic in international research. However, the numerical modelling and forecasting of land surface processes are subject to large uncertainties. Assessing the current level of uncertainty in numerical modelling and forecasting of land surface processes, searching for sources of uncertainty in numerical modelling and forecasting of land surface processes, and exploring ways and means to reduce the uncertainty in numerical modelling and forecasting of land surface processes fall within the scope of research on the predictability of land surface processes. This paper reviews the progress of the author's research in these three areas and discusses key scientific issues and techniques that need to be focused on in future research on the predictability of land-surface processes.

Rain-on-snow floods are extreme hydrological events characterized by sudden onset, low frequency, and high destructiveness, often leading to severe disasters. Due to their complex nature, understanding the disaster-causing mechanisms, evolution processes, and prevention strategies of rain-on-snow floods has become one of the most pressing challenges in contemporary hydrology and a fundamental requirement for national disaster prevention and mitigation. This study reviews the distribution characteristics and hazards of rain-on-snow floods and examines current research progress and development trends. It is found that the definition of rain-on-snow floods remains at a “potential” stage, with varying thresholds and considerable inconsistency. The disaster-causing mechanisms are still unclear, resulting in a limited understanding of flood evolution laws and a lack of robust simulation and forecasting models. These gaps hinder accurate flood warnings and risk management. There is an urgent need to establish a “real” definition of rain-on-snow floods, based on extensive flood event data and related observations. Additionally, revealing the underlying mechanisms, developing reliable simulation and forecasting models, and replicating typical rain-on-snow flood events through application-based demonstrations are essential next steps. This will enable a clearer understanding of the evolutionary processes, future changes, and potential risks of rain-on-snow floods at regional, basin, and global scales, while also supporting the development of effective prevention and mitigation strategies.

Aufeis (icings) are unique cryohydrological features in frozen ground regions, acting as critical solid-water reservoirs by freezing and storing a substantial portion (up to 40%) of the winter baseflow in some basins. Ecologically, they also serve as keystone habitats that provide crucial unfrozen overwintering refugia for cryophilic fish and other aquatic organisms. Concurrently, their formation and evolution pose significant geohazards to engineering infrastructure such as roads, bridges, tunnels, and culverts. In the context of global warming, a synthesis of both long-term in-situ and remote sensing observations confirms that icings are undergoing significant degradation, characterized by shrinking areas, accelerated melt rates, and fragmentation of perennial ice bodies. However, the mechanisms governing their formation and evolution, as well as their broader impacts on eco-hydrological processes and sustainable development in these regions, remain inadequately understood. This study comprehensively reviews the current understanding of icing formation, distribution, and controlling factors (e.g., geology, climate, and permafrost). It traces the evolution of research methodologies, from foundational field surveys and historical mapping to modern approaches combining satellite remote sensing (e.g., NDSI and machine learning) and geophysical techniques (e.g., GPR, ERT, and NMR). This review also highlights the eco-hydrological and hazard-related impacts of changes in ice-riving. We further discuss future research directions, noting a shift in focus, from the broad river systems of the Arctic and subarctic regions to understudied areas such as High Mountain Asia. Future research priorities are identified, calling for a paradigm shift from two-dimensional spatial monitoring towards integrated, three-dimensional quantitative analysis and prediction. Key frontiers include: \mathrm{①} elucidating the fundamental physical mechanisms of icing formation through coupled modeling; \mathrm{②} leveraging artificial intelligence to combine multi-source data (e.g., satellite, UAV, geophysical) for accurate estimation of icing volume; \mathrm{③} quantifying the cascading impacts of icing degradation on geomorphology and ecosystems; and \mathrm{④} developing robust predictive models for water resource management and geohazard mitigation related to icing evolution. Such advancements are crucial for providing the robust scientific basis needed for sustainable development in Earth’s rapidly changing cold regions.

The thermodynamic forcing of the Tibetan Plateau (TP) plays a crucial role in modulating the formation and variability of the Asian summer monsoon. However, due to limitations in both observational data and numerical models, the relative importance of the Plateau’s dynamic versus thermal effects on monsoon development remains a subject of ongoing debate. In recent years, a new framework based on Potential Vorticity (PV) theory has been proposed, introducing the concept of surface PV forcing over the Tibetan Plateau and revealing its relationship with the Asian summer monsoon. This paper reviews and synthesizes related research findings. Key conclusions include the following: the relative significance of TP thermodynamic forcing is closely related to experimental design and model performance; the surface PV index can serve as a quantitative metric to assess this relative significance. Compared to sensible heat flux, surface PV more accurately represents summer surface forcing over the Plateau and can be used to evaluate the strength of TP surface forcing under different model configurations and its impact on monsoonal rainfall. Climatologically, TP surface heating plays a dominant role in the formation of the summer monsoon over land. From an extended-range forecasting perspective, the spatiotemporal scales of thermodynamic disturbances over the TP that modulate synoptic-scale waves are key factors influencing the predictability of downstream precipitation. Notably, the intensity of TP surface forcing in climate system models—and its sensitivity in influencing monsoon precipitation—was quantified across different regions in 2022. Accurate simulation of TP surface PV forcing in June 2022 proved essential for reproducing the persistent rainfall observed over South China. These theoretical and modeling advancements contribute to a deeper understanding of the climatic dynamics associated with TP. However, observational data scarcity—particularly in high-elevation regions of the western TP—due to terrain and environmental constraints, limits the understanding of boundary-layer processes and results in biased physical parameterizations in climate models. Therefore, advancing TP simulation capabilities and deepening understanding of its climatic role require integrating observations, numerical modeling, and theoretical research into a unified framework. This approach will enhance the prediction of weather and climate extremes across TP and adjacent regions.

In the summer of 2022, the Yangtze River Basin experienced unprecedented heat waves, drawing considerable attention from the scientific community. Affected by over a month of record-breaking high temperatures and droughts, this extreme event not only caused escalating losses to human health, the economy, and the environment, but also exacerbated food insecurity and hindered sustainable development. Therefore, a more comprehensive understanding of extreme heat in the Yangtze River Basin during the summer of 2022 is essential to identify the drivers of extreme event variability under global warming, assess the impacts of human activity and natural variability, and evaluate potential climate risks. This study first reviews the main characteristics, formation mechanisms, and causes of the extreme heat in the Yangtze River Basin in the summer of 2022, and further summarizes the research progress on the event over the past three years. The results showed that the 2022 summer high temperature in the Yangtze River Basin was a rare extreme heat event. Its occurrence was primarily driven by atmospheric circulation anomalies related to the western Pacific subtropical high and the South Asian high, the triple La Niña phenomenon, the Atlantic and Indian SST forcing, and land-atmosphere feedback mechanism (e.g., soil moisture and air temperature). In addition to natural variability, human activity is the dominant factor influencing heat extremes. Without anthropogenic forcing, such extremes would have been highly unlikely. Such rare heat waves are projected to become more frequent under ongoing global warming. Finally, the paper highlights key research challenges and knowledge gaps associated with extreme heat events.

Northwest China is one of the world’s typical arid regions, where limited water resources severely constrain social development. However, the current utilization of atmospheric cloud water resources in this region remains significantly underdeveloped. Investigating the spatiotemporal variations of cloud water resources and cloud-precipitation processes is of great practical importance for enhancing technological capacity to exploit atmospheric water resources. To address this challenge, the National Natural Science Foundation of China (NSFC), through its Regional Innovation and Development Joint Fund, has supported the project “Multi-scale Variations of Atmospheric Cloud Water Resources and Cloud-Precipitation Processes in Northwest China”. This study highlights the strategic importance of developing cloud water resources in the region and examines the complexity of water formation and precipitation conversion mechanisms. Key influencing factors include the interaction of multiple atmospheric circulation systems; the macro- and microphysical complexities of cloud processes; the unique activation effects of dust aerosols; the topographic influences of plateaus and major mountain ranges; and the impact of regional climate warming and humidification. The critical role of field observations in supporting these investigations is also emphasized. Based on these insights, the study identifies six key research priorities for the future, including understanding variability patterns, aerosol-cloud interactions, cloud-precipitation conversion mechanisms, and advancing cloud microphysical parameterizations. These efforts aim to establish a robust theoretical and technical foundation for the effective utilization of atmospheric water resources in Northwest China.

Summer heat extremes are among the major meteorological disasters in China, posing severe threats to public health, economic and social development, and natural ecosystems. To address the nation's urgent need for managing heat-related disaster risks, we independently developed a prediction model system for summer heat extremes in China, based on new scientific insights. Since 2018, the model system has demonstrated stable and reliable predictive capabilities, relatively accurately capturing the spatial patterns and anomalies of summer heat extremes. In May 2025, using this system, we predicted that the number of summer hot days in 2024 would be 12.55 days, which is 2.69 days more than the average of normal years (1991-2020). The forecast also indicated more severe heat extremes, elevated disaster risks, and pronounced regional differences. The most significant above-normal heat extremes were expected in the middle and lower reaches of the Yangtze River Basin, South China, the Sichuan Basin, southern Xinjiang, northern Jiangsu, and northern Anhui. These were followed by the Beijing-Tianjin Plain, Shandong, Henan, southern Shaanxi, parts of northeastern China, parts of Gansu, and northern Ningxia. Based on these findings, we also provide response recommendations to prevent and mitigate the impacts of summer heat extremes across China.

The monitoring and early warning of pathogenic microorganisms and infectious diseases serve as a critical foundation for preventing major public health crises and mitigating biosecurity risks. However, research on the monitoring and early warning of pathogenic microorganism transmission in the atmosphere remains limited, with no systematic framework established yet. This study addresses strategic needs in public health security by identifying key scientific challenges in the field, systematically elucidating the environmental response mechanisms of atmospheric pathogens under climate change, monitoring technologies for pathogenic microorganisms in the atmosphere, and advances in infectious disease prediction models. Furthermore, this study identifies critical research frontiers for future breakthroughs, including: elucidating the source characteristics, formation mechanisms, environmental evolution, and transmission mechanisms of atmospheric pathogens; developing high-precision real-time monitoring technologies for atmospheric pathogens and establishing a biosafety surveillance network; constructing a multi-disciplinary, multi-scale and multi-model coupled prediction and early warning platform for atmospheric pathogen and infectious diseases. This research framework will provide scientific decision-making support for preventing public health emergencies, effectively enhance biosecurity governance capacity, and offer a scientific paradigm for building a global community of health for all.

Dust emissions are primary component of the atmospheric dust cycle. A comprehensive and quantitative description of the dust emission process is the basis for accurate simulation and prediction of dust aerosols. Dust emission processes are highly unsteady, non-uniform, and has intermittent features, also known as intermittent dust emissions. Accurately characterizing intermittent dust emissions remains a key scientific challenge in current dust research. This study reviews research from the past two decades, spanning field experiments, wind tunnel tests, and numerical simulations, on intermittent dust emissions. It covers the development of observation techniques using high-frequency measurements, occurrence conditions, and identification methods based on turbulence thresholds and intermittent factors. The influence of boundary-layer turbulence structures and their thermodynamic and dynamic effects on intermittent dust emissions is also summarized. Advancements in parameterization schemes for different dust emission mechanisms are discussed, with a focus on methods incorporating gust variations, intermittent factors, or probability distributions of turbulence parameters to model intermittent dust emissions. Finally, suggestions are provided to address existing challenges in dust emission research and outline future research directions. In the future, more filed experiments of atmospheric boundary layer and dust emission processes need to conduct using high-frequency measurement techniques for dust saltation and emission. In the relevant studies of identification methods and formation mechanisms of intermittent dust emission, both of the dynamic and thermodynamic impact of turbulence should be considered. More attention should be paid on the intermittent dust emission processes caused by direct turbulence aerodynamic entrainment, typically without sand saltation activity. The intermittent dust emission parameterization schemes should be developed and evaluated using field experiment data, in order to improve the simulation and forecasting of dust aerosols and dust events.

Abnormal atmospheric warming on the Tibetan Plateau has caused an imbalance in Asian Water Towers, leading to widespread and frequent cryospheric disasters such as ice avalanches and Glacial Lake Outburst Floods (GLOFs). These events pose a significant threat to life and infrastructure downstream, impacting regional socioeconomic development. Our recent studies, conducted during the Second Tibetan Plateau Scientific Expedition and Research Program, utilized field observations, remote sensing, and modeling to examine glacial lakes and GLOFs on the Tibetan Plateau. As of 2020, we had identified 14 310 glacial lakes on the Tibetan Plateau, covering an area of 1 148.3 km², along with a 20.4% increase in lake number and a 20.2% increase in lake area since 1990. Hazard and risk assessments revealed 1 256 glacial lakes with high or very high hazard levels, including 182 glacial lakes with high or very high-risk levels. These high-risk glacial lakes pose severe GLOF threats to communities and infrastructure downstream. At the regional scale, the eastern Himalayan and southeastern Tibetan regions exhibit the highest number of glacial lakes, the largest area expansion, the most destructive GLOF hazards, and the highest concentration of very high hazard level and very high-risk level glacial lakes on the Tibetan Plateau. In terms of administrative regions, Shigatse City, Nyingchi City, and Shannan City in the Tibet Autonomous Region have the highest distribution of very high-risk level glacial lakes. Future research should focus on precise GLOF assessments, the development of monitoring and early warning systems, and strategies for adapting to GLOF disaster chains and transboundary threats.

Groundwater-dependent vegetation is essential in arid ecosystems, where it maintains ecological balance and supports biodiversity. The health and functionality of this vegetation are closely linked to groundwater characteristics, including groundwater quality, distribution, and fluctuations. This review explores the relationship between vegetation and groundwater, methods for identifying groundwater-dependent vegetation, the impact of groundwater on the plants, adaptation mechanisms of these plants, and the nonlinear dependencies and thresholds of vegetation in groundwater environments. The objectives of the study are to provide a theoretical foundation for protecting and restoring arid ecosystems and to provide support for the sustainable development and utilization of groundwater resources. Future research should focus on plant responses to groundwater changes at the individual, population, and community scales; the effects of climate change and human activities on groundwater-dependent vegetation; innovative methods for studying ecosystem resilience and state-transition mechanisms for groundwater-dependent vegetation; and identifying stable water environment factors and catastrophic thresholds for typical groundwater-dependent vegetation.

Internal Solitary Waves (ISWs), which are characterized by large amplitudes and strong nonlinearity, are pivotal dynamic phenomena in oceanic processes. These waves contribute significantly to vertical mixing, cross-isopycnal transport of nutrients and sediments, and modulation of marine ecosystems, while posing substantial risks to subsea infrastructures, underwater navigation, and offshore operations. Therefore, a comprehensive understanding of their generation mechanisms, spatiotemporal evolution, and environmental impacts is critical for advancing oceanographic knowledge and ensuring maritime safety. The South China Sea (SCS) and its adjacent regions along the Maritime Silk Road, including the Sulu Sea (Sibutu Passage), Celebes Sea, Lombok Strait, and Andaman Sea, serve as global hotspots for ISW activity because of their complex bathymetry, intense tidal currents, and stratified water columns. This paper synthesizes multidisciplinary advances in ISW research across these regions, leveraging integrated methodologies such as multi-sensor satellite remote sensing (e.g., MODIS, VIIRS, and SAR), in situ observational networks, high-resolution numerical modeling (e.g., MITgcm, FVCOM), and emerging seismic oceanography techniques. Furthermore, the review identifies persistent gaps in knowledge, such as the role of mesoscale and submesoscale processes in wave–current interactions and interference effects between ISWs from multiple sources. Technical challenges, including the assimilation of multi-platform data into predictive models and the development of AI-driven forecast systems (e.g., physics-informed neural networks, convolutional neural networks), are critically assessed. The paper concludes by advocating for coordinated international observational campaigns and next-generation, non-hydrostatic models to unravel the multiscale complexity of ISWs, ultimately enhancing predictive capabilities for scientific and operational applications in these strategic waters.

Since 1958, China has conducted numerous artificial fog dissipation field experiments and research. This paper summarizes the classification and characteristics of fog as well as the mechanisms and methods of artificial fog dissipation. Fog areas in China are extensively distributed, with obvious seasonal differences. Land fog is mostly radiation fog, whereas sea fog is distributed in foggy areas along the coast, and its formation and dissipation are restricted by various conditions. The methods and technical approaches for artificial warm and cold fog dissipation were determined. The dissipation methods for warm fog include heating, dynamic mixing, thermodynamic methods, and hygroscopic particle seeding; whereas the dissipation methods for cold fog include seeding silver iodide of ice nucleating agents and spraying refrigerants. Other methods such as ultrasound are currently being researched and tested. The applicability, advantages, disadvantages, and uncertainties of these seeding methods were analyzed. The applicability of the fog dissipation methods varies. When applying these methods, it is necessary to comprehensively consider the technical approaches, implementation challenges, cost-effectiveness, and fog dissipation efficacy in field trials and operational applications. Aircraft-induced downdraft mixing is a simple, expensive, and operationally challenging process for warm fog. Thermal heating is universally applicable to all warm fog types but is cost-prohibitive and reserved for emergencies or critical infrastructure (e.g., major international airports and vital seaports), particularly for high-temperature fog. For cold fog, silver iodide seeding exhibits poor nucleation efficiency at temperatures around -5 ℃ (optimal below -8 ℃), necessitating cooling agents like liquid nitrogen, dry ice, and propane. Despite its high cost, liquid-nitrogen seeding is preferred operationally owing to its reliability and ease of deployment.All the current methods can dissipate local small-range warm or cold fog, but none can dissipate large-scale fog systems. A comprehensive analysis of fog dissipation provided ideas and references for artificial fog dissipation experiments, seeding operations, and future development in China. Future research should integrate numerical modeling, laboratory experiments, and field trials to validate and optimize seeding techniques and enhance the operational efficiency and cost-effectiveness.

With the rapid accumulation of marine big data and the robust development of Artificial Intelligence (AI) technology, intelligent marine forecasting has shown greater precision and efficiency in this new era. Marine data can be categorized into point- and field-observation data based on the observation methods, providing foundational support for marine forecasting. Marine forecasting methods can be divided into three main types based on the characteristics of the dynamic marine processes and phenomena: point-to-point, field-to-point, and field-to-field forecasting. These forecasting approaches not only cover a variety of marine phenomena but also address different forecasting requirements. Through a case analysis, this study specifically introduces intelligent forecasting models and results for point-to-point internal solitary wave forecasting, field-to-point El Niño-Southern Oscillation (ENSO) forecasting, and field-to-field phenomena such as mesoscale eddies and sea ice. Finally, it explores the development directions for intelligent marine forecasting in the context of big data, suggesting that enhancing the integration of data-driven methods with physical mechanisms can improve forecast accuracy and real-time responsiveness, thereby providing technical support for marine environmental monitoring, disaster warning, and the sustainable use of marine resources.

As the largest desert in the world, the Sahara Desert emits dust aerosols, accounting for 50%~60% of the global total dust, exerting significant impacts on regional and even global climate, environment, and ecosystems. Previous domestic and international studies reported two primary transport pathways for Saharan dust: westward across the North Atlantic, reaching North America, or northward to the European continent. In recent years, studies have shown that Saharan dust can be transported across the Middle East and Central Asia, undergoing long-distance (nearly 10 000 km) to East Asia, which is the third transport pathway for Saharan dust. Therefore, this study primarily summarizes the research progress on the long-range transport of Saharan dust to East Asia and its impacts, including the physical and chemical properties of Saharan dust, dust emission mechanisms, transport processes, and climatic and environmental effects. Finally, we highlight the current challenges in the research on the eastward transport of Saharan dust and provide suggestions and ideas for future research.

A new framework for studying climate change projections and disaster risks oriented towards carbon neutrality was developed using a division method of positive emissions, net zero, and net negative periods. Focusing on the main Belt and Road regions, future mean and extreme climate change projections and disaster risks oriented towards carbon neutrality were systematically addressed under the SSP1-1.9 and SSP1-2.6 sustainable development pathways. Moreover, it is projected that over global carbon neutrality or net-zero periods, climate change will exhibit new characteristics and patterns, and disaster risks will undergo new changes over the main Belt and Road regions. The newly developed framework provides a new scheme for climate change projection and disaster risk assessment. The seventh assessment report of the Intergovernmental Panel on Climate Change and other future assessment reports on climate change should include climate change projections and disaster risk assessments oriented towards carbon neutrality, which can provide new scientific knowledge for jointly dealing with climate change and achieving sustainable development. Additionally, the role and application of Artificial Intelligence in future climate change projections and climate disaster risks assessments are discussed.

Short-duration heavy precipitation is one of the most substantial severe convective disasters in China and is prone to causing urban waterlogging and secondary geological disasters, such as mountain torrents, mudslides, and landslides. This paper reviews recent progress in short-duration heavy precipitation research in China and briefly compares relevant findings from the United States and Europe. It covers the spatiotemporal distribution characteristics and diurnal variation patterns of short-duration heavy precipitation, atmospheric circulation patterns and environmental conditions that influence its occurrence and development in major regions of China, radar echo characteristics and raindrop distributions, impact of topography and urbanization on its formation and development, and application of artificial intelligence in potential forecasting, short-term forecasting, and nowcasting of short-duration heavy precipitation in China. With global warming, the frequency and intensity of short-duration heavy precipitation events have increased. In the future, further research will be required to enhance understanding of the formation mechanisms and environmental conditions, improve the spatiotemporal resolution of observations, expand the use of new observation data, and enhance forecasting capabilities in high-resolution, rapid-update cycle assimilation numerical weather prediction models through the fusion and analysis of dense multisource observation data. Additionally, optimizing deep learning models and algorithms—particularly in the development of largescale deep learning models—will be crucial for improving forecasting and early warning capabilities for short-duration heavy precipitation.

Significant advances in the formation mechanism and forecasting methods of severe convective winds and related convective systems were reviewed to improve understanding of the formation mechanism and forecast accuracy of severe convective winds. First, the spatial and temporal distribution characteristics of severe convective winds worldwide are briefly described. Next, the relationship between the organizational types and structural features of the parent convective systems that generate severe convective winds is then summarized, as well as the impact of atmospheric environmental conditions and topography, and forecasting methods. Finally, the current issues and future research directions associated with severe convective winds are discussed.

Humanity’s current water problems range from local-scale issues such as water supply to regional- and global-scale issues including protecting ecosystems, responding to global changes, sustaining the earth system, etc. Water resources exploitation, land utilization and climate changes have intensified pressure on water cycle through water distribution, interconnection, and virtual flows. The impact of anthropogenic pressure on water cycle has extended beyond the catchment-scale, with human activities becoming the primary driving force behind changes in regional, continental and global water cycle. Estimations by planetary boundaries framework indicated that development of global blue water and green water is approaching or beyond water planetary boundaries posing increased rising risks to earth system stabilization. Current water governance, which is focused on catchment scale and water-centric approaches, struggles to address the complexity of these issues. Governance must shift to manage not only increasing water use for economic and societal development, but also the roles and functions of water cycle in sustaining biosphere and Earth systems. Moreover, it should consider the equitable distribution of ecological services provided by water cycle. Concepts of water resilience and the economics of water as a common good enhance the conventional understanding of the water cycle, highlighting its essential role in sustain Earth systems and the cross-scale effects of human activities. Future, water resources governance is likely to evolve in three directions: from blue water management to blue-green water management, from integrated water-centric management to integrated land-water-ecosystem management, and from integrated river basin management to multi-scale management. It is critical for promoting transformation of water governance to strengthen cooperation among scientists of different fields in research of basic theory of water cycle, management policies and governance institutions.

Concerns about aviation emissions and climate change are shared internationally. The aviation industry plays a role in climate warming through its greenhouse gas and high-altitude particulate emissions. Conversely, climate warming alters flight conditions and increases extreme weather, impacts aviation operations and safety. The interaction creates a complex cycle of impacts, and research in this area is not only crucial for coordinating and adapting to climate changes in the aviation industry, but also holds scientific significance. An extensive literature review explores the relationship between aviation and climate warming, examining aviation’s CO₂ and non-CO₂ contributions to global warming and the phenomena and mechanisms by which climate warming in turn affects aviation (including changes in turbulence, flight time, aircraft performance degradation, and increased frequency of extreme events). The review also presents future research prospects. A deeper understanding of this interrelationship will help promote sustainable development of aviation and provide a scientific basis for addressing global climate challenges.

In recent years, flash droughts with rapid onset have occurred frequently worldwide, severely impacting society, economy, and the ecological environment. Major progress in the formation and evolution mechanisms of flash droughts has been reviewed. Concludingly, intense precipitation deficits cause flash droughts, whereas increased evapotranspiration accelerates drought onset, further triggering flash droughts. These abnormal meteorological factors are closely associated with sea surface temperature anomalies (such as the El Ni?o-Southern Oscillation, North Atlantic Tripole, and Indian Ocean Dipole) and their related atmospheric circulation anomalies. In addition, the roles of local and non-local land surface anomalies in the onset and maintenance of flash droughts are important. Moreover, the synergistic effects of climate and land-use change on land-atmosphere-ocean coupling processes make the development of flash droughts more complex and add considerable uncertainty to evolutionary trends. Therefore, future research needs to achieve breakthroughs in several areas, including the large-scale atmospheric circulation background of flash drought onset and maintenance, modulating roles of key land and ocean signals, flash drought-vegetation interactions, and response mechanisms of the variation of flash droughts to climate warming and land cover changes.

The recently published report “Earth System Science in China: The Development Strategy for 2035” identified three major areas for potential research breakthroughs: \mathrm{①} Revisiting the marine carbon pump, \mathrm{②} Hydrological cycle and orbital forcing, and \mathrm{③} Ocean-Continent connection between the Pacific and Asia. The strategy research group was jointly established in 2019 by the National Natural Science Foundation of China and the Chinese Academy of Sciences. Over the course of three years, the group organized 14 thematic workshops, involving over 500 experts from various research fields. This study provides a brief overview of these three major research areas.

With growing concerns about ecosystem functioning and the services provided by soil, the study of soil aggregates has increasingly become a central discipline of modern soil science, with ongoing updates to consensus and methodology. In this review, we provide a holistic overview of the understanding and characterization of the soil aggregate system that has emerged over the last two decades. The evolution of concepts related to soil aggregation, size fractionation, and structural characterization is presented, along with discussions on the separation and examination of the biophysical structure. Additionally, the final core scientific consensus on the soil hierarchy system is synthesized. The key points of understanding soil aggregates are as follows: \mathrm{①} Soil aggregates are considered the fundamental micro-architectural and functional units, composed of mineral particles, organic matter, and microbiomes through their interactions and co-occurrence, thus representing the basic functional particles of soil in nature; \mathrm{②} The micro-spatial distribution of soil aggregates at different hierarchical levels results in the heterogeneity and functional diversity of soil; \mathrm{③} The ultimate nature of soil aggregates can be envisioned as an embedded bio-pore system, created through the dual structure of aggregates and the associated pore system governed by the hierarchical aggregate system; \mathrm{④} A soil aggregate system is generally represented by three major hierarchical size fractions: macroaggregates, microaggregates, and the silt/clay fraction, with macroaggregates formed by binding microaggregates and/or silt-clay particles with coarse organic matter, resembling a pomegranate structure; \mathrm{⑤} Wet sieving of field-moist samples is recommended for the preparation of soil aggregate separates, although dry or moist sieving is often used for samples from drylands; \mathrm{⑥} μCT tomography technology is a powerful tool for quantifying and visualizing the pore system of soil aggregates, with the potential to link soil life processes to ecosystem services. Global cooperation is encouraged to develop a unified protocol for fractionating, quantifying, and visualizing the soil hierarchy system of aggregates across the world’s soils. With these developments, the complex soil system, particularly its biodiversity, can be explored at the aggregate scale. Based on the updated understanding and characterization of the soil aggregate system, nature-based solutions for global soil management policies and technical options will be provided, contributing to Earth’s sustainability.

Inter-ocean exchange between the tropical Pacific and the Indian Ocean, which relies on throughflow from the Pacific to the Indian Ocean, serves not only as a crucial conduit for the exchange of mass, momentum, and energy between the Indo-Pacific basins, but also as an oceanic channel for the propagation of climate anomalies between the Pacific and Indian Oceans. In addition, it plays a key role in the closure of the Great Ocean conveyor belt by facilitating the compensation of surface waters in the deep Atlantic. Therefore, interocean exchange is a pivotal component of global ocean and climate systems. It has been recognized as one of the most important academic hotspots for ocean circulation in interocean change regions and their related climates. Since the 1990s, international cooperative actions have been conducted, focusing on the observation of inter-ocean exchange. Starting in 2007, Chinese researchers have conducted observations in the main strait and channels of interocean exchange regions by collaborating with Indonesian researchers. Currently, they have established the largest on-site array for the synchronous observation of interocean exchange. The array covers the key inflow, throughflow, and outflow regions. This paper reviews the major progress and open issues of inter-ocean exchange from four aspects: \mathrm{①} multiscale variations of inter-ocean exchange, \mathrm{②} cross-scale and \mathrm{③} cross-basin interactions, and \mathrm{④} modulation of the primary climate modes of the Pacific and Indian Oceans. The prospects of the key research goals for the next five to ten years are also outlined.

This paper summarizes recent progress in the observation, mechanism, and modeling of land-atmosphere interactions, and demonstrates that existing observational studies have not considered the effects of changes in terrestrial ecophysiology and the atmospheric boundary layer on land-atmosphere fluxes. Consequently, they restrict the parameterization of land surface processes, parameter inversion from satellite remote sensing, and the operational application of the land surface process model. To gain a comprehensive understanding of land-atmosphere interactions and the development of land surface process models, studies on the effects of changes in terrestrial ecophysiology and atmospheric boundary layers on land-atmosphere interactions and the operational application of land-surface process models need to be emphasized in the future. The main tasks to be considered include: \mathrm{①} three-dimensional observation of the land-atmosphere interactions across the boundary layer, \mathrm{②} application of multi-source data in the land-atmosphere interactions across the boundary layer, and \mathrm{③} development and operational application of land surface process models.

The island arc and oceanic plateau models of a mantle plume are two popular models for the origin of the crust. In contrast to the island arc model, the oceanic plateau model can account for most of the features of the Archean crust but meets the fundamental challenge of explaining the water-rich features of the magma source for the Archean crust. The recent water-induced mantle overturn model accounts for not only water-rich features but also several puzzling phenomena in the Archean. The whole-mantle Magma Ocean (MO) separated into outer and basal MO because the crystallized mantle floated in the middle mantle. The water-induced mantle overturn model shows that with crystallization, basal MO became increasingly enriched in water because lower-mantle minerals can only contain a limited amount of water. Water reduced the density of basal MO. The basal MO eventually became less dense than the overlying solid mantle and became gravitationally unstable because of water enrichment. The triggered mantle overturned transport a large amount of water to the shallow part of the Earth and resulted in large pulses of crust and thick subcontinental lithospheric mantle (SCLM) generation. Therefore, the Archean crust was the result of the evolution of the basal MO. Once the mantle overturned from the basal MO, Archean-type crust no longer formed. Thus, the water-induced mantle overturn model can account for global change at the end of the Archean and other puzzling phenomena. For example, why were Tonalite-Trondhjemite-Granodiorite (TTG) and thick SCLM rare in the Hadean, why does the source of Archean basalts remain the primitive mantle from ca 4.0 to 2.5 Ga, and why does only Earth have continental crust?

Sea-Level Rise (SLR) directly changes the hydrology and salinity of estuarine tidal wetlands and is one of the primary drivers of global change that significantly impacts ecosystem processes. Herein, various methodologies and experimental facilities (marsh organs, weirs, and flow-through mesocosms) for manipulating SLR are systematically reviewed. This study provides a comprehensive summary of the effects and mechanisms associated with SLR regarding the fluxes and production rates of CH₄ and CO₂, and the pathways and rates of soil organic carbon mineralization from the perspectives of SLR-saltwater intrusion and inundation increase. Saltwater intrusion due to SLR notably decreases CH₄ production rates and fluxes. It induces a shift in the pathways of soil organic carbon mineralization, transitioning from CH₄ production to microbial SO{}_{\mathrm{4}}^{\mathrm{2}-} reduction in tidal freshwater marshes. The main mechanism reducing saltwater intrusion-induced CH₄ flux is the increased presence of the electron acceptor SO{}_{\mathrm{4}}^{\mathrm{2}-}, which hinders soil CH₄ production. The impact of SLR through saltwater intrusion on CO₂ emissions in tidal freshwater marshes exhibits distinct uncertainty. Owing to the inherent challenges in experimentally manipulating SLR in situ, few reports concerning the effects of SLR-related inundation on CH₄ and CO₂ fluxes and production rates exist. However, some studies have suggested that an increase in inundation height leads to a reduction in CO₂ emissions. Additionally, this study consolidates information surrounding electron acceptors and microbial mechanisms associated with SLR that influence the pathways and rates of soil organic carbon mineralization in coastal tidal wetlands. Finally, this study outlines the specific domains that warrant further exploration in future research on the impact of SLR on the production and emission of carbon greenhouse gases in estuarine tidal marshes.

As computing power continues to improve, the horizontal grid resolution of numerical weather prediction models has reached the kilometer-to-sub-kilometer scale. This grid scale is comparable to the characteristic turbulent scales in the convective boundary layer, allowing the numerical models to resolve the organized convective structures. The assumptions of traditional one-dimensional boundary layer parameterization schemes (suitable for horizontal resolutions of several kilometers or coarser) and large eddy simulation three-dimensional turbulent closure schemes (suitable for horizontal resolutions below several tens of meters) do not hold at this scale, which is referred to as the gray zone. This study discusses the applicability and limitations of traditional parameterization methods and introduces the gray zone of the convective boundary layer from three perspectives: theory, methodological approaches, and impact. It summarizes the characteristics of the simulation methods at the CBL gray zone scale developed over the past two decades and explores the impact of the boundary layer process simulation at this scale on other physical processes (e.g., shallow/deep convection) in numerical models. Further, we anticipate future research directions and approaches.