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.

Over more than 50 years of continuous research and technological innovation, Fengyun Meteorological Satellite System has achieved significant progress. 21 Fengyun satellites have been launched. Currently, eight of these satellites operate stably in orbit, forming a comprehensive observation system that includes geostationary orbit and sun-synchronous polar orbit satellites. By reviewing the development history and current status of Fengyun meteorological satellites and remote sensing instruments; the effectiveness of ground segments in data reception, processing, and operation; and the construction and service of application systems, the technical capabilities of Fengyun meteorological satellites, their ground segments, and application systems were comprehensively analyzed. Through comparative analysis with major countries around the world in terms of meteorological satellite network observations, remote sensing instrument technology, and ground segment operation capabilities, it was found that the Fengyun Meteorological Satellites not only have a complete orbit layout and remote sensing instrument configuration, but their remote sensing instrument detection capability has reached the advanced international level, although some performance indicators still have spcace for improvement. Ground segments have established efficient data reception, processing, and service processes with advanced data preprocessing technology and sub-pixel-level geolocation accuracy. The radiometric calibration accuracy is 3% in the visible and near infrared channels and 0.2 K in the infrared channels. In addition, the Fengyun Meteorological Satellite System has established a comprehensive and complete quantitative product system for atmospheric, land, marine, and space weather, and has established China Radiometric Calibration Sites for Chinese remote sensing satellites, and carried out validation of the remote sensing products. Fengyun satellite data have been widely used in various fields, such as weather forecasting, climate change research, ecological environment monitoring, and natural disaster warning, and their application level continues to advance. In the future, the Fengyun meteorological satellite observation system will aim to evolve towards establishing a hybrid-architecture space observation system, achieving comprehensive and precise perception of observation elements, enabling intelligent and efficient operation of satellite-ground systems, integrating emerging technologies in data processing, expanding remote sensing application scenarios, and fostering international cooperation and sharing.

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.

As one of the most significant cryospheric landforms that respond to climate warming in permafrost regions, thermokarst lakes profoundly influence ecological changes, regional hydrological cycles, and biogeochemical processes while compromising the stability of permafrost engineering. This study reviews recent advances in the formation and evolution of thermokarst lakes, their hydrological cycles, heat transfer, ecological and environmental effects, and engineering impacts across northern hemisphere permafrost regions. Research indicates that in the discontinuous permafrost zones of the Arctic, lake and pond areas show a predominantly decreasing trend, whereas, in continuous permafrost zones, both expansion and shrinkage are observed. On the Qinghai-Tibet Plateau, climate warming and increased precipitation have led to the rapid formation and expansion of thermokarst lakes. The evolution of these lakes, coupled with hydrological cycling and thermal effects, alters the physicochemical properties of the surrounding soils, influences hydrothermal dynamics in alpine ecosystems, and reduces the stability of adjacent permafrost engineering structures. Furthermore, the development of thermokarst lakes accelerates the decomposition of permafrost carbon stocks, releasing greenhouse gases such as CO₂, CH₄, and N₂O, which further feedback into the climate system. Currently, coupled water-heat-carbon cycling processes and their environmental implications represent a key research focus in permafrost science. Future studies should comprehensively consider the interactive effects of climate change and human activities and, based on coupled water-heat-carbon cycling processes, develop high-precision land surface process models to investigate ecological succession, water resource dynamics, and carbon cycling in permafrost regions under changing environmental conditions, thereby advancing cryospheric science.

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.

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.

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.

As the climate crisis intensifies, Earth system models have become increasingly significant as critical numerical simulation tools for evaluating and addressing future climate change. The Coupled Model Intercomparison Project (CMIP), aimed at promoting model development and deepening the scientific understanding of the Earth's climate system, has become a central platform for international model exchange and application. This paper provides an overview of China’s participation in the Sixth Phase of CMIP (CMIP6), including a statistical analysis of citations, research trends, and key characteristics of the Chinese Earth system models in CMIP6-related studies. In addition, the Seventh Coupled Model Intercomparison Project (CMIP7), which is currently under preparation, is briefly introduced, and the opportunities and challenges faced by China in model development are summarized. Through continuous technological innovation, international cooperation, and exchanges, Chinese scientists are expected to make greater breakthroughs in the field of Earth and Climate System Models and contribute to Chinese wisdom and solutions for global climate change response and governance.

Carbon neutrality is a crucial strategy for combating global warming, and negative emissions technologies are key to achieving this goal. As the largest carbon reservoir on Earth, the ocean plays an irreplaceable role in regulating global carbon cycling and holds significant potential for negative emissions. Ocean alkalinity enhancement is a highly efficient and ecologically beneficial negative emissions technology. This technology increases ocean alkalinity by adding alkaline minerals to seawater, thereby enhancing the absorption of atmospheric CO₂ and improving the buffer capacity to resist ocean acidification. This study introduces the mechanisms and advancements in ocean alkalinity enhancement research at multiple scales based on the dissolution theory of carbonates in the ocean. Assessing the potential for negative emissions and associated costs reveals several challenges regarding implementation pathways, environmental impacts, and public acceptance. Considering the specific conditions of China’s coastal regions and the characteristics of ocean alkalinity enhancement technology, this study proposes a pathway integrated with wastewater treatment plants and coastal engineering. Furthermore, it provides an innovative concept on the application of ocean alkalinity enhancement and enriches the scientific understanding of blue carbon sinks.

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.

Human-earth system science, as a foundation of sustainable development research, can help decision-makers design sustainable pathways through multidimensional perspectives, integrated concepts, and systematic thinking. It plays an increasingly important role in the construction of national economies, societies, and ecological civilizations. Human-earth system sustainable development assessment models and scenario analysis techniques have become important tools that are widely used and studied. However, current research lacks a summary of the progress and limitations of these models and scenario analysis techniques. To keep pace with international developments and promote the understanding and advancement of human-earth system modeling and decision analysis of Chinese scholars, it is necessary to review the current international research in this field systematically. By combining literature analysis and quantitative analysis, this study summarizes the difficulty of models in simultaneously supporting multiple sustainable development goals and the challenges in simulating the social dimension. We also analyze the challenges in capturing systematic change, scale conversion, interdisciplinary knowledge integration, uncertainty management, data mining, and the use of new technologies. Additionally, we summarize the methods for setting up scenarios, the general types of scenarios, the content of scenarios, the limitations in addressing internal scenario conflict cross-scale linkages, and connections with decision-making. This study provides an important reference for promoting innovative development among Chinese scholars in this field.

To improve the accuracy of monitoring land gravelization and the efficiency of fieldwork, and further promote the innovation of monitoring methods, a study on the appropriate size and quantity of quadrats was conducted. This study examines the desert region of Inner Mongolia and uses the entropy TOPSIS and Wilcoxon rank sum test methods to determine the optimum sampling scheme for land gravelization monitoring. Based on results using 100 cm×100 cm quadrats as the true values of gravel coverage and surface gravel mass per unit area, new survey areas in the desert regions of Inner Mongolia were selected, and the maximum quadrat was expanded to 200 cm×200 cm to increase the sampling areas and number of quadrats, and optimize the sampling scheme for monitoring land gravelization. The comparative results of the two experiments show that: \mathrm{①} Q25 exhibits good advantages for monitoring suitability, which can improve field work efficiency while ensuring measurement accuracy; \mathrm{②} the appropriate quantity and sizing of quadrats vary significantly with changes in the maximum quadrat size; however, for Q25, the change in appropriate quantity (from 9 to 10) is non-significant, indicating good stability; \mathrm{③} using Q25, the appropriate coverage for monitoring gravelization is consistent with the results from monitoring surface gravel mass per unit area; this not only simplifies the monitoring process, but also ensures the reliability and comparability of monitoring data.

Debris flow disasters, known for their frequent occurrence and high destructiveness, are difficult to monitor effectively due to the limited real-time performance and high false-alarm rates of conventional monitoring methods. This critical limitation underscores the urgent need to develop highly efficient and precise intelligent detection techniques to substantially enhance early warning capabilities. To address the challenges of poor real-time performance and high false alarm rates in traditional debris flow monitoring systems, this study proposes an enhanced YOLOv8m-GCSlide model based on the YOLOv8 framework. The GlobalContext Network (GCNet) is integrated into the backbone network to improve spatial dependency modeling of dynamic fluid boundaries in complex terrains, while a Sliding Loss function (SlideLoss) is designed to dynamically adjust classification thresholds and mitigate sample imbalance. Knowledge distillation is applied to compress the model, resulting in a lightweight variant (YOLOv8n-GCSlide) with reduced computational complexity. A multi-source video dataset was constructed using publicly available resources, with frames extracted at 0.25-second intervals to balance feature retention and training efficiency. Data augmentation techniques, including random cropping, rotation, scaling, Gaussian blur, and color jittering, were used to enhance generalization, supplemented with negative samples (e.g., dry riverbeds and landslides) to reduce false positives. Experimental results show that the optimized model achieves 94.6% (+2.0%) detection accuracy, 88.0% recall, 95.9% mean Average Precision (mAP), and an inference speed of 244.1 FPS, outperforming mainstream lightweight models such as SwinTransformer and MobileNet variants. After compression, the model parameters were reduced by 88.1%, with the distilled version retaining 94.6% (+1.2%) accuracy and 88.0% (+0.7%) recall while maintaining an inference speed of 244.1 FPS. Field validation conducted in Sedongpu Gully, a high-risk debris flow region, confirmed the model’s practical applicability. Under complex environmental interference, the model achieved 82.3% recall, 4.2% false positive rate, and a processing speed of 240.6 FPS. The integration of global attention mechanisms and task-specific loss functions effectively captures dynamic motion features and suppress environmental noise. Additionally, model compression techniques help balance accuracy and computational efficiency, enabling edge deployment for real-time disaster warnings. This approach provides a robust technical foundation for intelligent geological hazard monitoring systems, emphasizing high precision, low latency, and adaptability to resource-constrained scenarios.

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.

Subsea permafrost, formed by the inundation of terrestrial permafrost due to sea-level variations during the interglacial cycles, is primarily distributed across the Arctic continental shelves. However, a substantial uncertainty remains regarding the extent of its distribution (approximately 1~2.7 million square kilometers). Subsea permafrost is considered a significant carbon reservoir in the Earth’s system, storing vast amounts of Organic Carbon (OC) and methane (CH₄). With global warming and rising Arctic Ocean temperatures, subsea permafrost is undergoing rapid degradation, potentially exacerbating carbon release risks. Consequently, it plays a significant role in the global carbon cycle and climate dynamics. Large-scale CH₄ emissions into the atmosphere have been observed in the East Siberian subsea permafrost region. However, the rates of subsea permafrost degradation, the size of carbon reservoirs, and gas release remain poorly constrained. In particular, rapid Arctic warming, the northward expansion and intensification of the North Atlantic Current (which exacerbates the Atlantification of the Arctic Ocean), and increased human disturbances have intensified climate risks due to accelerated CH₄ emissions from Arctic subsea permafrost. These changes have significant implications for future human sustainability. This study systematically summarizes the spatial distribution, degradation rates, and carbon storage of Arctic subsea permafrost. It also examines CH₄ monitoring in subsea permafrost, including fixed-point observations, aerial surveys, and remote sensing technologies. Furthermore, it discusses the factors influencing CH₄ emissions, emphasizes the importance of understanding Arctic subsea permafrost dynamics within the context of global climate change, identifies key challenges, and suggests future research directions.

Vegetation fire, as a significant disturbance factor in the Earth’s system, can have important impacts on Earth’s surface systems, such as the atmosphere, hydrosphere, cryosphere, biosphere, pedosphere, and anthroposphere. The various gases and aerosol particles released during vegetation fires not only affect the atmospheric environment, but also pose risks to human health. Extreme vegetation fires can cause serious casualties and economic loss. In recent years, under the influence of global warming, various extreme weather events have occurred frequently, and the risk of vegetation fire disasters has also significantly increased. Understanding the stages and mechanisms of modern vegetation fires is of great scientific significance for predicting future changes in vegetation fires, and is of great practical importance for formulating fire management strategies. This study provides an overview of the research progress on vegetation fires in China from the perspective of the evolutionary history of vegetation fires and modern vegetation fire regimes. The following basic understanding is obtained regarding the pattern of modern vegetation fires: First, from historical records, modern vegetation fires are currently at their most frequent period since the Holocene, and from the late 20th century to the present, even to the mid-21st century, vegetation fires in China show an overall upward trend. Second, vegetation fires in China are mainly agricultural fires with forest wildfires as a supplement, concentrated in spring and autumn, and are mainly distributed in northeastern, southwestern, eastern, and southern China, showing regional diversification characteristics under the influence of human activities and climate change. In the future, efforts should be made to strengthen the review of the details of historical changes in vegetation fires in China, elucidate the overall modern vegetation fire regime, and provide more accurate predictions of future changes in vegetation fires.

Wind and solar energy have unparalleled advantages in reducing greenhouse gas emissions and promoting energy transitions. However, the construction of onshore wind/solar farms occupies a tremendous amount of land resources and changes land use considerably. The operation of power generation facilities further changes the local microclimate and ecohydrological processes, profoundly affecting terrestrial carbon cycle processes. Therefore, it is important to clarify the potential impacts of wind/solar farms on the carbon cycle process at the site for sustainable development of the new energy industry. A systematic review of the research undertaken over the past two decades was conducted in this study, with special emphasis on the carbon cycle characteristics, impact mechanisms, and the dynamics and stability of carbon pools in onshore wind/solar farms. The results indicate that these wind/solar farms have the potential to improve local climate conditions, promote the restoration of vegetation, and thus increase the carbon sequestration potential in arid desert environments. However, considerable uncertainties exist regarding the recovery potential of either vegetation or soil carbon pools for wind/solar farms. We argue that there is an urgent need to \mathrm{①} conduct multi-scale and long-term monitoring of the carbon cycling processes in wind/solar farms, \mathrm{②} strengthen research on the synergistic mechanisms of the above- and below-ground carbon processes in onshore wind/solar farms, and \mathrm{③} quantitatively determine the carbon sequestration potential and its spatial and temporal characteristics in wind/solar farms. These efforts are expected to provide scientific references for sustainable design, management, and development of renewable energy sources in the future.

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.

Qilian Shan, the youngest mountain range formed by the northward expansion of the Tibetan Plateau, plays a crucial role in understanding the expansion processes, uplift mechanisms, and evolution of orogenic belts. Drainage system evolution responds rapidly to mountain uplift, making the study of drainage development and evolution a critical approach for investigating the uplift and expansion of Qilian Shan. Based on chronological and provenance studies of geomorphic records, including erosion surfaces, river terraces, wind gaps and ancient river channels, and Cenozoic sedimentary strata, the current research on drainage system evolution in the Qilian Shan has yielded the following findings and insights: \mathrm{①} The formation and evolution of the upper reaches of the Yellow River in the eastern Qilian Shan involve a process of drainage reorganization driven by tectonic uplift or climate change, characterized by headward erosion and river capture; \mathrm{②} Research on river terraces in the Shiyang River and Heihe River basins of the northern Qilian Shan, as well as in the Lanzhou Basin of the eastern Qilian Shan, indicates climate change, and the tectonic uplift independently govern the timing (transitions between glacial and interglacial periods, and interglacial periods) and extent of river incision. Since the Holocene, terrace formation has been primarily driven by climate change, with river incision occurred during warm and humid periods; \mathrm{③} River terraces reliably record the evolution processes of major tributaries of the Yellow River in the eastern Qilian Shan, including the Huangshui River (flow reversal) and the Datong River (river capture); \mathrm{④} Study of chronology, provenance, and paleohydrology of Cenozoic sedimentary strata in the Yumu Shan of the northern Qilian Shan, as well as the Wulan and Chacha basins of the southern Qilian Shan, has reliably reconstructed the regional drainage evolution history, highlighting the significant potential of sedimentary strata for reconstructing reliable and detailed record of drainage evolution. However, numerous critical issues remain unresolved and require further investigations. Future research should prioritize and emphasize in-depth studies on geomorphic surface and sediment dating, integration of multi-source methods for provenance analysis, continuous exploration of geomorphic features, and advancements in numerical simulations and simulation modeling studies.

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.

Submarine landslides are among the most common and destructive geological hazards on continental margins. Their development can significantly reshape seafloor morphology, generate high-density turbidity currents, and even trigger catastrophic tsunamis, posing serious threats to the safety and operation of sub-sea engineering infrastructures. The formation of submarine landslides typically involves long-term geological processes influenced by multiple interacting factors. Some large-scale submarine landslides exhibit multi-stage sliding events with complex movement histories. However, current understanding of the developmental characteristics and formation mechanisms of multi-phase submarine landslides remains limited, which hinders scientific insight into their evolutionary patterns. Based on high-resolution, two-dimensional (2D) multichannel seismic and borehole data, six phases of Mass Transport Deposits (MTDs) resulting from submarine landslides have been identified in the Kaiping Sag on the northwestern continental margin of the South China Sea. According to the established regional sequence stratigraphic framework, these MTDs are mainly concentrated within the Lower Hanjiang Formation and Yuehai Formation. Seismic interpretation results indicate that the internal structure of MTD 1 and 2 is highly deformed and significantly altered by subsequent geological processes, whereas MTD 3 to MTD 6 exhibit typical landslide features such as prominent headwall scarps and lateral margins. Calculation of sedimentation rates during the occurrence of each phase of MTDs reveals that high sedimentation rates occurring during periods of low sea level provided the necessary sediments for the occurrence of landslides. This rapid sediment accumulation likely prevented the timely expulsion of pore fluids, leading to elevated pore pressure within the sediments and the formation of unstable weak layers. In addition, the widespread development of tectonic normal faults (e.g., Shenkai Fault) and their intersecting relationships with all six MTDs strongly suggest that fault activity also played a significant role in triggering these landslides. This study provides new insights into the formation mechanisms of submarine landslides along the northwestern continental margin of the South China Sea, offering important scientific support for hydrocarbon exploration, geological hazard risk assessment, and disaster prevention and mitigation in the region.

Soil improvement plays a critical role in enhancing the soil carbon sink capacity and optimizing karst processes under global climate change. Using bibliometric methods, this study analyzed literature from Chinese and English journals (1990-2024), focusing on the regulatory mechanisms linking soil improvement to soil carbon cycling and karst carbon sinks. The Web of Science (WoS) and China National Knowledge Infrastructure (CNKI) databases indexed 712 and 468 relevant articles, respectively, most of them original research papers. Article numbers showing a fluctuating upward trend over the 34 years. This process can be divided into three phases: germination (before 2005), growth phase (2005-2013), and rapid development (after 2013). English-language journals published more articles than Chinese-language journals. The English-language literature initially focused on biochar carbon sequestration mechanisms and greenhouse gas emissions. Over time, the focus shifted towards the synergistic regulation of soil microbial functional genes and nitrogen-phosphorus nutrient cycling, reflecting a transition from mechanism-based analysis to application-oriented microbial-nutrient coupling. Chinese-language literature has expanded from monitoring basic indicators, such as soil respiration, moisture, and heavy metals, to systematic research on soil aggregate regulation, microbial community optimization, and improvement techniques. In addition, a Carbon-Pool Management Index (CPMI) is established to guide practical applications. In low-productivity karst regions, soil improvement efforts primarily assesses improvement measures on karst processes and the soil carbon balance. This study explored the bidirectional coupling relationship between karst carbon sinks and soil improvement. Specifically, high concentrations of soil CO₂ drive carbonate rock weathering, whereas improvement measures enhance the carbon sink effect by improving soil quality. To advance soil improvement research in karst areas, it is recommended to establish a quantification method for measuring the increase in karst carbon sinks due to soil improvement and develop a database. Furthermore, considering the calcium-rich and alkaline characteristics of karst soils, the synergistic effects of improvement measures on ecological restoration and sustainable agricultural should be evaluated to provide scientific support for global carbon neutrality. By leveraging soil improvement technologies, we can enhance soil and karst carbon sinks, address climate change more effectively, promote the integration of ecological restoration and sustainable agricultural development in karst regions, and contribute to the achievement of China’s Dual Carbon Goals.

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.

Tracking the Earth’s energy imbalance is one of the key methods for studying the contribution of human activities to climate change. Energy imbalance directly reflects the complex responses and feedback of the climate system and is an important indicator of climate change. However, accurately estimating the Earth’s energy budget has long been a challenge. Observations of the top of the atmosphere and surface radiative fluxes have high uncertainties, and it is difficult to validate different observation datasets. In addition, these high uncertainties lead to inaccurate estimates of changes in Earth’s energy budget fluxes. Furthermore, estimating surface radiative fluxes is challenging because of the lack of high-quality, high-resolution observational data. Recently, methods using ocean heat content/sea-level height data for the indirect estimation of the Earth’s energy budget have been widely applied. Considering that most of the energy imbalance flows into the ocean heat content, ocean data observations can yield estimates of the Earth’s energy imbalance with lower uncertainty. Additionally, reasonable estimates of the Earth’s energy budget can be obtained through multi-model ensemble methods using Earth system model outputs, supplemented with appropriate weighting strategies. By improving data integration capabilities and developing related technologies, climate scientists continuously enhance their understanding of the Earth’s energy budget, providing more precise scientific evidence for understanding and addressing increasingly severe global warming.

Passive Microwave Brightness Temperature (PMWBT) is crucial for retrieving various land surface parameters. However, PMWBT images often exhibit many missing observations, particularly in low-latitude areas, owing to the limited coverage of polar-orbit satellites equipped with PMW radiometer imagers. Filling these gaps is essential to enhance the spatiotemporal integrity and application potential of PMW-derived products. To better understand the problem and propose solutions, the PMW radiative transfer theory and the reasons for the observation gaps are comprehensively reviewed. Subsequently, two filling approaches, multi-source data filling and effective data reconstruction, which are commonly used in remote sensing, were introduced and assessed for their suitability in filling PMWBT gaps. Upon reviewing related research and existing issues in filling PMW BT orbital gaps, it was observed that current studies on filling satellite-borne passive microwave brightness temperature orbital gaps are limited, and all use multi-source data with low generalizability because of sensor differences. In conclusion, the current research status and challenges are succinctly summarized. Furthermore, from the perspective of using reanalysis data and time-series modeling, the construction of a high-precision, general reconstruction method under special underlying surface conditions was explored.

Gravity Waves (GWs) significantly influence structure of the entire atmosphere and coupling between atmospheric layers. Research on gravity waves is crucial for deepening our understanding of atmospheric dynamics and for improving the accuracy of atmospheric models. While gravity waves are well-known in the fields of astronomy and physics, they also play a vital role in atmospheric science, particularly in the study of airflow, wave propagation, and climate variability. This review highlights the following key findings: ① Satellites are suitable for observing the middle and upper atmosphere; radar is most effective for detailed observations of vertical wave propagation; and reanalysis data are best suited for analyzing global GW characteristics; ② Compared with non-orographic gravity waves, orographic gravity waves generally have longer vertical wavelengths and can propagate to higher altitudes; ③ Orographic gravity waves are easier to trace due to their relatively fixed sources; and ④ Common parameterization schemes effectively simulate the drag effects of orographic gravity waves, while single-wave and global spectral techniques can predict the east-west momentum flux of non-orographic gravity waves. However, the complete generation and evolution processes of both types of GWs cannot yet be accurately simulated. There is still considerable room for improvement in the observation, identification, feature analysis, and parameterization of gravity waves. In the future, advancements in observational technology are expected to yield higher-quality data, enabling a clearer understanding of GW characteristics. Based on this, progress in parameterization methods and the application of artificial intelligence techniques is anticipated to enhance our understanding of the formation mechanisms of both orographic and non-orographic gravity waves, thereby improving the accuracy of weather and climate simulations.

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.

Marine aerosols are among the most important natural aerosols globally, playing key roles in the Earth’s radiation balance and climate change. They are a critical link between the ocean, atmosphere, and climate. Organic matter constitute a significant fraction of marine aerosols and can contribute up to 50% of submicron aerosol mass. Missing knowledge of the composition and formation of Marine Organic Aerosols (MOA) hinders the accurate evaluation of their climatic effects. This paper reviews research methods, spatial and temporal distribution patterns, chemical composition characteristics, and sources of MOA, providing a comprehensive summary of the domestic and international progress in marine organic aerosols, and proposes key research directions for future studies. Current research on the chemical nature was mainly focused on the fluorescent or water-soluble components, whereas the characterization or quantification of MOA molecular components remains largely unknown. Marine organic aerosols are generally abundant in regions with high phytoplankton activity or those under strong influence from transported continental pollutants. Their sources include sea-spray emissions or secondary formation processes across different sea areas, resulting in distinct MOA compositions and chemical properties. Currently, the limited of observational data limits our deep understanding of MOA formation and further investigation via laboratory experiments or modelling simulations. In the future, integrating observational, experimental, and modeling simulations should be combined to improve our understanding of the sources, sinks, and climate regulations of marine organic aerosols.

Long-term observations and data analysis of the Earth's middle and upper atmosphere, an important region for studying atmospheric processes and even climate change for studying human activities and climate change, are still insufficient. Terahertz limb-sounding technology can obtain atmospheric profiles all day and near all weather with high vertical resolution (approximately 1~5 km) and is particularly sensitive to some of the halogen gases associated with ozone depletion, making it an important method for measuring the Earth's middle and upper atmospheric parameters. The basic principles and advantages of terahertz limb sounding are summarized, the basic framework of the terahertz radiometer is introduced, the development of terahertz limb sounding technology domestically and internationally in the past three decades is discussed, the latest research status is reviewed, the future development direction is discussed, and terahertz limb sounding technology is summarized and outlooked to provide a reference basis for related research.

Studying the relationship between ecosystem patterns and water conservation services is important for promoting ecosystem management and protecting the water supply. Based on the InVEST model, landscape ecology theory, and Pearson correlation coefficient analysis, this study explored the relationship between ecosystem patterns and water conservation services in the Nianchu River Basin during 2010—2020. The study yielded several interesting results: \mathrm{①} Grasslands account for more than 78% of the area, with stable bare land but active bidirectional transitions with grasslands. \mathrm{②} From 2010 to 2020, there was a slight increase in the fragmentation level of the composite ecosystem patterns within the basin. Grassland had a significantly higher Percentage of Landscape (PLAND), Mean Patch Size (MPS), and Aggregation Index (AI) than other ecosystem types. Bare land exhibited the most irregular patch shapes. Forest showed the most significant increase in Patch Density (PD) and a slight decrease in MPS. Urban areas expanded continuously. \mathrm{③} The total water conservation services for 2010, 2015, and 2020 were 272 million m³, 95 million m³, and 247 million m³, respectively, with grasslands contributing nearly 80% of the total. \mathrm{④} There is a significant correlation between the composite ecosystem pattern and water conservation services. Water conservation services are positively correlated with PD, Edge Density (ED), Landscape Shape Index (LSI), Modified Simpson’s Diversity Index (MSIDI), and Modified Simpson’s Evenness Index (MSIEI) but negatively correlated with MPS and AI. However, the correlations between different types of ecosystem patterns and water conservation services show significant variations. For example, PLAND and MPS are negatively correlated with water conservation services for grasslands but positively correlated with glaciers. In summary, grasslands dominate the ecological patterns of the Nianchu River Basin, and their degree of fragmentation is positively correlated with water conservation services. Furthermore, the relationships between different types of ecological patterns and water conservation services exhibit significant differences. This study provides a scientific basis for regional ecosystem management and water resource protection.

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.

Projecting future global urbanization pathways and their impacts on climate change is essential for effectively addressing climate change and promoting sustainable regional and global development. To this end, the National Key Research and Development Program’s project, “Global Urbanization Trend and its Impact on Climate Change” simulates the spatial and temporal patterns of global urbanization patterns from 2020 to 2070 under Shared Socioeconomic Pathways (SSPs) framework and quantitatively evaluates the impact of urbanization on regional and global climate change. This provides crucial datasets for revealing the impact of urbanization on regional and global climate change at multiple scales. The findings are of great significance to the realization of the United Nations’ Sustainable Development Goals and the construction of a community with a shared future for mankind. They also provide a scientific foundation for the construction of green and healthy cities, as well as a scientific reference for optimizing urban morphology and mitigating the urban heat island effect.

In the intricate domain of marine geochemistry, barium (Ba) and its isotopes emerge as pivotal elements. Their remarkably high preservation rate in marine sediments allows them to withstand post-depositional alterations, making them ideal proxies for long-term geological records. The stable isotope fractionation behavior of barium serves as a powerful tool for reconstructing paleoproductivity with high precision. In this study, we meticulously compiled high-precision isotope analysis data from various sources, including a comprehensive review of existing literature and in-house experimental results. We then conducted an in-depth investigation into the sources and sinks of marine barium. Our findings demonstrate that terrigenous, hydrothermal, and biological inputs are not isolated contributors, but instead interact synergistically to drive the cycling of barium in the ocean. Regarding Ba isotope fractionation, within the mineral-fluid-melt system, we found that the dynamic interplay between equilibrium and kinetic fractionation mechanisms is of critical importance. Equilibrium fractionation, governed by quantum mechanical differences in bond vibrations, and kinetic fractionation, associated with non-equilibrium processes such as diffusion, jointly shape the isotopic composition of marine barium. Observed regional variations in isotope fractionation further suggest that multiple factors, including temperature, pressure, and the presence of various chemical species, jointly influence marine Ba isotope behavior. This spatial heterogeneity provides a valuable framework for tracing the evolution of the paleo-oceanic environment and reconstructing historical changes in oceanic conditions. Looking ahead, the integration of in-situ micro-area analytical techniques is not merely desirable but essential. These advanced methods will enable detailed investigations at the microscale, enhancing our understanding of the interactions among biological, mineral, and fluid components in marine systems. Ultimately, such insights will improve the accuracy of paleo-oceanic reconstructions and contribute to a more comprehensive understanding of Earth’s past oceanic ecosystems.

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.

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.

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.

The relative abundance of tricyclic terpanes is an important indicator of organic matter origin, depositional environment, and thermal evolution. While traditional coal-measure source rocks typically exhibit low tricyclic terpane contents, anomalously high abundances (relative to hopanes) have been observed in source rocks from the Ordos and Tarim Basins. Therefore, detailed investigations into their distribution patterns, compositional characteristics, and formation mechanisms are of substantial significance. This study employed conventional geochemical analysis methods and gas chromatography-mass spectrometry (GC-MS) to systematically characterize the molecular geochemical features of 30 coal-measure source rock samples from the study area. The results show that tricyclic terpanes in coal-measure source rocks exhibit two distinct abundance patterns: low abundance (∑TT/C₃₀H<2) and high abundance (∑TT/C₃₀H>2). The low-abundance tricyclic terpane samples exhibit a decreasing C_19-21TT distribution, formed in freshwater, oxidizing environments, with hydrocarbon-generating parent material primarily derived from higher plants under low thermal maturity conditions. The high-abundance tricyclic terpane samples showed distribution patterns with C₂₃TT or C₂₁TT as the dominant peak, formed in saline, sulfur-rich depositional environments. The hydrocarbon-generating parent material was mainly derived from bacteria and lower aquatic organisms, reaching mature to highly mature thermal evolution stages. Correlation analysis of maturity, depositional environment, and parent material input parameters with ∑TT/C₃₀H values revealed that depositional environment and source material characteristics had a stronger correlation with tricyclic terpane abundance than thermal maturity. The findings suggest that brackish, high-sulfur coal-forming environments and increased contributions of secondary products from microbial transformation of higher plants are the primary controlling factors for high tricyclic terpane abundance in coal-measure source rock extracts, whereas thermal maturity is a secondary factor. The molecular compositions and formation mechanisms of high-abundance tricyclic terpanes provide crucial geochemical evidence for identifying coal-forming environments, characterizing hydrocarbon-generating organic matter, and evaluating thermal maturity, thereby offering theoretical and practical guidance for coal-measure hydrocarbon exploration.

Current limitations in typhoon forecasting are primarily attributed to insufficient understanding of mesoscale processes. To address this gap, this review synthesizes the current understanding of mesoscale waves in typhoons, including Vortex Rossby Waves (VRWs) and Typhoon-induced Gravity Waves (TGWs). It investigates their generation mechanisms and characteristics, and systematically examines the linkages between these waves and key typhoon structural features, including the eyewall, spiral rainbands, convective intensity, and (a) symmetric structure. Furthermore, the impact of these structural modifications on typhoon intensity is investigated, along with the statistical correlations between wave characteristics and typhoon intensity changes. The results show that: \mathrm{①} The theoretical frameworks for polygonal eyewall and inner spiral rainband formation have evolved from the TGW approach to that of VRWs. VRWs provide partial explanations for typhoon asymmetric structures and double-eyewall formation while representing one plausible mechanism for outer spiral rainbands. The changes in intensity induced by VRWs manifest through complex processes characterized by differing dynamical responses depending on (i) wave propagation directionality (tangential/radial), (ii) spatial domain (inner-core/outer region) and (iii) levels (mid-lower/upper) at (iv) different periods during the typhoon lifecycle phase (intensification/decay). \mathrm{②} The wave characteristics of TGWs (including amplitude, wavelength, period, and occurrence frequency) exhibit correlation with changes in typhoon intensity. TGWs, primarily excited by convection in the eyewall and spiral rainbands and rapidly propagating vertically, may serve as precursor signals for typhoon (rapid) intensification. \mathrm{③} Both VRWs and TGWs can drive the outward radial transport of momentum and heat within typhoons. Through wave-mean flow interactions, they modify local circulation and enhance typhoon symmetry, ultimately contributing to typhoon intensification (including rapid intensification). Some scientific challenges remain in applying VRWs and TGWs to improve fine-scale wind/precipitation distributions and advance the forecasting of changes in typhoon intensity. Current research underscores the necessity of integrating high-resolution numerical simulations with multi-platform coordinated observations to quantitatively analyze mesoscale wave-typhoon interactions, thereby identifying precursor signals for typhoon intensification, including rapid intensification. Tools such as wave spectrum analysis and wave energy flux diagnostics are instrumental in extracting early-warning indicators from both wave characteristics and energy transport perspectives. Advances in satellite and radar detection technologies will enable the validation of theoretical frameworks through multi-platform observational data, ultimately enhancing monitoring and forecasting capabilities for typhoon structural and intensity changes.

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.

This paper aims to develop solutions for two significant and urgent problems in air transportation. One is the contradiction between the bustle of main airspaces and the huge aviation industry development demand， and the other is the contradiction between the large-scale developments of aviation industry and the traditional aviation management mode. The application of continuous trajectory data and the development of airflow micro-temporal analysis technology have created the conditions for operational efficiency assessment in corridors-in-the-sky to meet the challenges of some key issues such as the detection of full process detection and economic effect measurement. This paper presents a framework for assessing the operational performance of air passenger flow including temporal variation and spatial state， internal composition relationship and external connection relationship. Based on the delayed trajectory data of flights and taking time delay cost as a feedback variable， a series of indicators of delay number， delay duration， delay occurrence area and delay propensity index are concluded， and the operational performance of air passenger flow of major corridors-in-the-sky in Sino-U.S. is compared. There are the following findings： the constraints on operational performance occur mainly in the maintenance phase of the airspace, where delayed trajectory clusters lead to longer Euclidean distances and narrower flight path activity, resulting in increased flight path rigidity or invariability and then reduced opportunities for multi-path selection. In addition, the limited over-flow capacity of the corridors-in-the-sky in China is likely to cause delays in delay-intensive segments and downstream delay contagion, and also leads to the accumulation of terminal delays. On this basis, this paper expected to play a certain role in improving the construction of corridors-in-the-sky, improving the utilization rate of airspace, promoting the reform of airspace configuration and also will bring a comprehensive technical support for optimisation of dynamic airspace and the implementation of the national strategic plan of “Airspace Channel”.