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Recent studies suggest that hypolimnetic respiration may be responsible for greenhouse gas (GHG) emissions from deep reservoirs. Currently, quantitative evaluation of aerobic vs. anaerobic processes and priming (enhanced processing of organic matter due to the addition of labile carbon) in regulating GHG production and emissions across the reservoir-downstream continuum remains largely unknown. High-resolution, annual time-series observations in a large, subtropical reservoir (Shuikou) experiencing seasonal hypoxia in southeast China indicate that aerobic hypolimnetic CO2 production dominated in most periods of the stratified spring/summer with higher rates at higher temperatures. In addition, anaerobic production of hypolimnetic CO2 occurred in the late stratified spring/summer period, which stimulated hypolimnetic production of CH4 and N2O. Incubation experiments showed that priming in spring enhanced both aerobic and anaerobic production of excess GHGs. A late spring flood event generated the highest daily efflux of CO2 through the flushing of GHG-enriched hypolimnion waters. Turbine degassing contributed 59%, 93%, and 63% of annual CO2, CH4, and N2O effluxes, respectively. Moreover, annual downstream GHG emissions were similar to those in the transition/lacustrine zone of the Shuikou reservoir. Diurnal variation observations revealed net CO2 emissions even during algal bloom seasons. The reservoir-downstream river continuum was a year-round source of GHGs (218.5 ± 18.9 Gg CO2-equivalent yr−1; CO2 contributed 91%). However, the loss of oxygen also leads to increased production and storage of recalcitrant dissolved organic carbon (RDOC). Thus, identifying mechanisms controlling both GHG emissions and RDOC production is crucial to constrain the carbon neutrality issue of hydroelectric reservoirs in the context of climate change mitigation strategies.

https://doi.org/10.1007/s00382-024-07210-5. In this article 17 references, which were wrongly moved to the Supplementary Information, need to be added. The list of added references as given below: The original article has been corrected

Abstract: Subseasonal to seasonal (S2S) prediction of droughts and floods is one of the major challenges of weather and climate prediction. Recent studies suggest that the springtime land surface temperature/subsurface temperature (LST/SUBT) over the Tibetan Plateau (TP) can be a new source of S2S predictability. The project “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction (LS4P)” was initiated to study the impact of springtime LST/SUBT anomalies over high mountain areas on summertime precipitation predictions. The present work explores the simulated global scale response of the atmospheric circulation to the springtime TP land surface cooling by 16 current state-of-the-art Earth System Models (ESMs) participating in the LS4P Phase I (LS4P-I) experiment. The LS4P-I results show, for the first time, that springtime TP surface anomalies can modulate a persistent quasi-barotropic Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train from the TP via the northeast Asia and Bering Strait to the western part of the North America, along with the springtime westerly jet from TP across the whole North Pacific basin. The TRC wave train modulated by the TP thermal anomaly play a critical role on the early summer surface air temperature and precipitation anomalies in the regions along the wave train, especially over the northwest North America and the southern Great Plains. The participant models that fail in capturing the TRC wave train greatly under-predict climate anomalies in reference to observations and the successful models. These results suggest that the TP LST/SUBT anomaly via the TRC wave train is the first order source of the S2S variability in the regions mentioned. Furthermore, the TP surface temperature anomaly can influence the Southern Hemispheric circulation by generating cross-equator wave trains. However, the simulated propagation pathways from the TP into the Southern Hemisphere show large inter-model differences. More dynamical understanding of the TRC wave train as well as its cross-equator propagation into the Southern Hemisphere will be explored in the newly launched LS4P phase II experiment.

Abstract: The prediction skill for precipitation anomalies in late spring and summer months—a significant component of extreme climate events—has remained stubbornly low for years. This paper presents a new idea that utilizes information on boreal spring land surface temperature/subsurface temperature (LST/SUBT) anomalies over the Tibetan Plateau (TP) to improve prediction of subsequent summer droughts/floods over several regions over the world, East Asia and North America in particular. The work was performed in the framework of the GEWEX/LS4P Phase I (LS4P-I) experiment, which focused on whether the TP LST/SUBT provides an additional source for subseasonal-to-seasonal (S2S) predictability. The summer 2003, when there were severe drought/flood over the southern/northern part of the Yangtze River basin, respectively, has been selected as the focus case. With the newly developed LST/SUBT initialization method, the observed surface temperature anomaly over the TP has been partially produced by the LS4P-I model ensemble mean, and 8 hotspot regions in the world were identified where June precipitation is significantly associated with anomalies of May TP land temperature. Consideration of the TP LST/SUBT effect has produced about 25–50% of observed precipitation anomalies in most hotspot regions. The multiple models have shown more consistency in the hotspot regions along the Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train. The mechanisms for the LST/SUBT effect on the 2003 drought over the southern part of the Yangtze River Basin are discussed. For comparison, the global SST effect has also been tested and 6 regions with significant SST effects were identified in the 2003 case, explaining about 25–50% of precipitation anomalies over most of these regions. This study suggests that the TP LST/SUBT effect is a first-order source of S2S precipitation predictability, and hence it is comparable to that of the SST effect. With the completion of the LS4P-I, the LS4P-II has been launched and the LS4P-II protocol is briefly presented.

With the widespread adoption of the Internet and an increase in the number of Internet users, the security of the network environment has been seriously threatened by Internet public hazards organizations, such as the Internet water army and the internet public hazards community. Given the characteristics of these organizations, which include being distant from domestic supervision and possessing strong concealment and camouflage abilities, a social network characteristic analysis method was proposed for Internet public hazards organizations. Initially, at the user characteristic level, the influence distribution of group members was calculated through centrality measurement to identify the core users with the greatest influence, and an analysis of the anonymity characteristics of these core members was conducted. Subsequently, at the complex network characteristic level, the cluster status and resource distribution within the community were studied through the analysis of small-world effects and scale-free characteristics. Finally, at the temporal characteristic level, after preprocessing the post content of core members, BERTopic was utilized for dynamic topic modeling to ascertain the relationship between community themes and time. A large number of experimental performance analyses have verified the effectiveness of the proposed method. The research results can be utilized to analyze the characteristics of public hazard communities, track criminal activity trajectories, and provide theoretical references for the investigation and crackdown of public hazard organizations, as well as for the design of automated detection systems.

As artificial intelligence-based automatic generation technology advances, the emergence of misinformation in more sophisticated guises has become a significant threat to the economy and social order. Among its forms, out-of-context misinformation stands out as particularly deceptive and readily executable. This type of misinformation involves malicious actors enhancing the credibility of false narratives by misrepresenting contextual details such as individuals, events, and locations within real images. To address the shortcomings of current detection algorithms, which heavily depend on knowledge bases and often overlook the stance relationship between the information under scrutiny and online evidence, a stance analysis-based out-of-context misinformation detection method was developed. This method involved several steps for the detection of an image-caption pair along with the corresponding textual and visual evidence retrieved from the Internet. Initially, a stance gain score for each piece of textual evidence was calculated based on the co-occurrence of named entities. Subsequently, independent stance analysis networks were utilized to perform hierarchical clustering on both the image and visual evidence, as well as on the caption and textual evidence. This process involved the extraction of semantic stance representations, facilitated by multiple attention mechanisms and a stance analysis module. The authenticity of the image-caption pair was subsequently predicted based on the outcomes of semantic comparison and stance analysis. Experimental results indicate that the incorporation of stance analysis significantly enhances the method's detection capabilities. Specifically, the accuracy of this method outperforms the state-of-the-art algorithm that employs Internet evidence for detection by 2.3%.

Subseasonal-to-seasonal (S2S) precipitation prediction in boreal spring and summer months, which contains a significant number of high-signal events, is scientifically challenging and prediction skill has remained poor for years. Tibetan Plateau (TP) spring observed surface temperatures show a lag correlation with summer precipitation in several remote regions, but current global land-atmosphere coupled models are unable to represent this behavior due to significant errors in producing observed TP surface temperatures. To address these issues, the Global Energy and Water Exchanges (GEWEX) program launched the "Impact of Initialized Land Temperature and Snowpack on Subseasonal-to-Seasonal Prediction"(LS4P) initiative as a community effort to test the impact of land temperature in high-mountain regions on S2S prediction by climate models: more than 40 institutions worldwide are participating in this project. After using an innovative new land state initialization approach based on observed surface 2-m temperature over the TP in the LS4P experiment, results from a multimodel ensemble provide evidence for a causal relationship in the observed association between the Plateau spring land temperature and summer precipitation over several regions across the world through teleconnections. The influence is underscored by an out-of-phase oscillation between the TP and Rocky Mountain surface temperatures. This study reveals for the first time that high-mountain land temperature could be a substantial source of S2S precipitation predictability, and its effect is probably as large as ocean surface temperature over global "hotspot"regions identified here; the ensemble means in some "hotspots"produce more than 40% of the observed anomalies. This LS4P approach should stimulate more follow-on explorations.

Global impoundment of river systems represents a major anthropogenic forcing to carbon cycling in reservoirs with seasonal thermal stratification. Currently, a quantitative and mechanistic understanding of how hypolimnetic deoxygenation in stratified reservoirs alters dissolved organic matter (DOM) cycling and lateral transport along the river continuum remains unresolved. Herein, we used optical and high-resolution mass spectrometric analyses to track seasonal and spatial compositional changes of DOM from a large, subtropical impounded river in southeast China. Aliphatic compounds were contributed by algal blooms to epilimnetic DOM during the spring/summer and by baseflow to the overall DOM pool during low-discharge periods. Deoxygenation-driven hypolimnetic mineralization enhanced in situ production of bio-refractory molecules and humic-like fluorescent DOM (FDOMH) by utilizing bio-labile DOM and settling biogenic particles during periods of stratification. Production efficiency of hypolimnetic FDOMH was 159-444% higher than that of the global dark ocean, and was strongly regulated by temperature and possibly substrate supply. The in situ production rate of hypolimnetic FDOMH was four to five orders-of-magnitude higher than the dark ocean, with much faster turnover rates in dark inland waters versus the dark ocean. Collectively, these findings indicate that the hypolimnion is a hotspot for microbial carbon transformations, and hence an important source and pool of refractory DOM in aquatic systems. The lateral FDOMH flux increased 10.8-32.1% due to hypolimnetic reservoir release during periods of stratification, highlighting the importance of incorporating hypolimnetic carbon transformations into models for carbon cycling of inland waters and the land-sea interface.

Recent observational and modeling studies have demonstrated the substantial influence of the Tibetan Plateau (TP) spring land surface temperature (LST) and subsurface temperature (SUBT) on downstream summer droughts/floods events in East Asia, highlighting the potential application of LST/SUBT on sub-seasonal to seasonal prediction (S2S). In this study, we employ the National Centers for Environment Prediction—Global Forecast System/Simplified Simple Biosphere model version 2 (GFS/SSiB2) to investigate the potential role of the late spring warm LST anomaly over the TP on the extraordinary June 1998 flood in the south of the Yangtze River region. Numerical experiments indicate that the warmer (above normal) May LST over the TP may contribute to the extreme flood of 1998 over the south of the Yangtze River region, with the LST reproducing about 57% and 64% of observed above-normal rainfall anomaly over the south of the Yangtze River region and southeastern China, respectively. Further analyses reveal a possible effect of springtime TP’s LST on summer southern and eastern Asian rainfall and identify some hot spots, suggesting that the TP’s spring LST effect is not only limited to the Yangtze River region, but to a much larger scale. The imposed warm LST/SUBT over the TP triggers a strong wave activities propagating eastward along the upper-level westerly jet, associated with an increase of the atmospheric baroclinic instability as well as a strengthening and southeastward movement of the South Asian high, leading to intensified moisture convergence and convective instability favorable to the excessive rainfall in the downstream region of East Asia. The results of the 1998 case have also been compared with the results from year of 2003, which had a very cold spring LST anomaly over the TP and a severe downstream June 2003 drought (flood) in southern (northern) of the Yangtze River Basin area. Simulation results provide further evidence of the great importance of the TP spring land surface temperature anomaly in regulating summer extreme hydroclimatic events (e.g. droughts and floods) in South and East Asia. The present study suggests that consideration of LST/SUBT anomalies has a strong potential for more skillful S2S prediction of extreme hydroclimatic events such as floods, droughts and heatwaves over both Southern and Eastern Asia.

Oceanic absorption of heat generated by greenhouse gas emissions has resulted in warming of the dark ocean (>200 m) that contains a large refractory DOM (RDOM) pool. However, changes in microbially mediated production and degradation dynamics for RDOM components in response to warming of dark marginal basins remain unclear. Herein, we integrated data from the dark South China, Mediterranean and Japan Seas (temperature range: 0.09–15.1°C) to demonstrate that in situ production efficiency of two ubiquitous humic-like fluorophores increased at higher dark ocean temperature, whereas chromophores at a wavelength of 325 nm (aCDOM(325)) changed from production to degradation at higher temperature. Increased oxygen consumption and a reduction of labile substrates in future warmer dark ocean environments may initiate the final degradation of some semi-refractory components, thereby increasing the recalcitrance of RDOM, but decreasing the DOM inventory in dark basins and creating a positive feedback to rising atmospheric CO2.

Abstract: Land surface processes are vital to the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation by using the weather research and forecasting (WRF) model at 10-km resolution to the land surface schemes over Central Asia. The WRF model was run for 19 summers from 2000 to 2018 configured with four different land surface schemes including CLM4, Noah-MP, Pleim-Xiu and SSiB, hereafter referred as Exp-CLM4, Exp-Noah-MP, Exp-PX and Exp-SSiB respectively. The initial and boundary conditions for the WRF model simulations were provided by the National Centers for Environmental Prediction Final (NCEP-FNL) Operational Global Analysis data. The ERA-Interim reanalysis (ERAI), the GHCN-CAMS and the CRU gridded data were used to comprehensively evaluate the WRF simulations. Compared with the reanalysis and observational data, the WRF model can reasonably reproduce the spatial patterns of summer mean 2-m temperature, precipitation, and large- scale atmospheric circulation. The simulations, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by Multivariable Integrated Evaluation (MVIE) method. To comprehensively understand the dynamic and physical mechanisms for the WRF model’s sensitivity to land surface schemes, the differences in the surface energy balance between Ave-CLM4-SSiB (the ensemble average of Exp-CLM4 and Exp-SSiB) and Ave-NoanMP-PX (the ensemble average of Exp-Noah-MP and Exp-PX) are analyzed in detail. The results demonstrate that the sensible and latent heat fluxes are respectively lower by 30.42 W·m−2 and higher by 14.86 W·m−2 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX. As a result, large differences in geopotential height occur over the simulation domain. The simulated wind fields are subsequently influenced by the geostrophic adjustment process, thus the simulations of 2-m temperature, surface skin temperature and precipitation are respectively lower by about 2.08 ℃, 2.23 ℃ and 18.56 mm·month−1 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX over Central Asia continent.

High-resolution horizontal and vertical distribution of dissolved organic carbon (DOC), chromophoric, and fluorescent dissolved organic matter (CDOM and FDOM) were investigated in the western boundary current system of the tropical Northwest Pacific (

Base-extracted particulate organic matter (BEPOM) collected in low (spring) and high (summer) runoff seasons in the Changjiang Estuary and adjacent nearshore/offshore shelf areas was examined using absorption and fluorescence spectroscopy. Parallel factor analysis (PARAFAC) identified two humic-like (C1p and C2p) biologically-refractory components and two protein-like (C3p and C4p) bioreactive components. Absorption coefficient a350p, C1p and C2p of BEPOM showed strong positive correlations with particulate organic carbon (POC), and were generally higher in spring than in summer. C4p correlated positively with Chl a, and was higher in summer than in spring. In the inner estuary, an anthropogenic POM signal from the highly polluted Huangpu River was effectively identified by the fluorescent component ratio (IT:IC)P. In the nearshore area during spring, resuspension within the well-developed turbidity maximum zone (TMZ) supplied large amounts of refractory POM into the water column. POM fractions from an autochthonous source (i.e., algal bloom) were dominant in the offshore area during the summer. A multivariate regression model inferred that POM export fluxes from the Changjiang River during spring had a higher percentage of labile POM fractions, which were subsequently retained by the TMZ. However, these labile fractions were discharged into the offshore shelf area contributing to hypoxia in the summer. The summer high runoff season also transported large amounts of refractory POM that was subsequently buried in the sediment. This study highlights the utilization of optical analyses to trace pollution sources and reveal POM fate and transport dynamics allowing better assessment of its ecological consequences in estuaries.

Abstract. Sub-seasonal to seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging but has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called Impact of initialized Land Surface temperature and Snowpack on Sub-seasonal to Seasonal Prediction (LS4P), as the first international grass-root effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land/atmosphere interactions. LS4P focuses on process understanding and predictability, hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than forty groups worldwide have participated in this effort, including 21 Earth System Models, 9 regional climate models, and 7 data groups. This paper overviews the history and objectives of LS4P, provides the first phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST in the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation and its S2S prediction. LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations which both tend to limit the soil memory; and ii) reanalysis data, that are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems.

With the continuous growth and advancement of the Internet and information technology, continuous growth and advancement of the Internet and information technology.Nevertheless, these applications’ vulnerabilities pose a severe threat to information security and users’ privacy.Fuzzing was widely used as one of the main tools for automatic vulnerability detection due to its ease of vulnerability recurrence and low false positive errors.It generates test cases randomly and executes the application by optimization in terms of coverage or sample generation to detect deeper program paths.However, the mutation operation in fuzzing is blind and tends to make the generated test cases execute the same program path.Consequently, traditional fuzzing tests have problems such as low efficiency, high randomness of inputs generation and limited pertinence of the program structure.To address these problems, a directional fuzzing based on deep reinforcement learning was proposed, which used deep reinforcement learning networks with information obtained by staking program to guide the selection of the inputs.Besides, it enabled fast approximation and inspection of the program paths that may exist vulnerabilities.The experimental results showed that the proposed approach had better performance than the popular fuzzing tools such as AFL and AFLGO in terms of vulnerability detection and recurrence on the LAVA-M dataset and real applications like LibPNG and Binutils.Therefore, the approach can provide support for further vulnerability mining and security research.

Urban creative networks, as distinct forms of production networks, differ from inter-firm-based urban networks. It is featured by flexible production, "temporary cooperation" and being "people-centered." This study attempts to address the concept of the urban creative network in theory, and based on the basic database of Chinese digital music, it integrates the social network, Geographical Information System (GIS) spatial analysis, and econometric model to empirically analyze the structural evolution characteristics and influencing factors of the creative cooperation network of Chinese singers in the past 40 years, which enriches the theoretical and empirical study of urban networks from the perspective of creative individual connections. The results suggest the following: (1) The scale of Chinese urban digital music collaborative networks grows rapidly and shows the characteristics of low density and a "small world", and network density is negatively correlated with network scale, with obvious social network properties. (2) The collaborative network as a whole presents a "core-periphery" structure and the development trend of polycentricity and high-centricity cities are mainly located in the eastern region, with relatively low centrality in the central and western cities, and gradually forms a triad structure of Beijing-Hong Kong-Taipei. (3) The evolution of the digital music cooperation network is characterized by both path dependence and path creation, and the main form of network extension is hierarchical diffusion, with the early high-intensity links between Hong Kong and Taiwanese cities gradually being replaced by mainland cities. (4) The coverage of city ties in the cooperative network expands with an uneven spatial distribution, and high-intensity ties are mainly concentrated in the eastern cities. Over time, the core cities' control over network resources through inter-high-intensity ties weakened. (5) The cooperative network has an obvious community structure, and the communities of this coproduction network appear to be expanding, grouping, and hierarchical, with dual-core and multi-core models as its main spatial organization modes. (6) A negative binomial regression model analysis shows that the scale of the urban economy, industrial structure, and the level of the network economy have significant impacts on the network structure, while the roles of human capital, opening up, urban administrative level, and traffic accessibility are not evident, indicating that the Chinese music cooperation network has obvious endogenous mechanisms and local embeddedness. The findings of this study provide in-depth theoretical and policy insights for understanding intercity interactions and promoting the development of creative industries under the influence of the creative (digital) economy. First, a study on city networks based on the production networks of digital creative industries should focus on the characteristics of creative production networks and the role of creative actors (people). Second, policymakers should fully understand the characteristics of digital creative production sector actors and production modes when formulating policies for the development of digital creative industries and choose development paths that fit the advantages of local resources to realize industrial development. Finally, we propose a future research agenda for urban creative networks.

The 2015/2016 super El Niño event resulted in a positive precipitation anomaly during dry seasons in the Jiulong River watershed, southeast China. Four years (2014–2017) of high frequency, in situ humic-like fluorescent DOM (FDOMH) data in the Jiulong Estuary were coupled with extrapolation to a freshwater end-member FDOMH concentration and river discharge data to estimate riverine FDOMH export. The wetter El Niño dry season was followed by lower FDOMH export during the subsequent wet season. Furthermore, in the dry season after El Niño reached its strongest phase, a 90–187% increase in FDOMH export occurred. If widespread, this pattern suggests El Niño events may enhance export of FDOMH from south China rivers in dry seasons resulting in seasonal and annual shunting of the terrestrial DOM export, modulating coastal carbon cycling. This study highlights the need to incorporate climate-driven regulation patterns on DOM transport across the land-ocean interface.

The Land surface scheme is crucial for the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation  with high resolution (10km) WRF model to the land surface schemes over Central Asia. The high resolution WRF simulations for 19 summers from 2000 to 2018 are conducted with four different land surface schemes (hereafter referred to as Exp-CLM, Exp-Noah-MP, Exp-PX and Exp-SSiB, respectively). The initial and boundary conditions for the WRF model simulations are provided from the NCEP-FNL analysis product. The ERA-Interim reanalysis (ERA), the GHCN-CAMS (CAMS) and the CRU gridded data are used to comprehensively evaluate the WRF simulations. Compared with verification data, the WRF model with high resolution can reasonably reproduce the spatial patterns of summer mean large scale atmospheric circulation, 2-m temperature and precipitation. The simulation results, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by the multivariable integrated evaluation method. To comprehensively understand the dynamic and physical mechanisms behind the WRF model sensitivity to land surface schemes, the differences in the surface energy balance between the ensemble means Ens-CLM4-SSiB and Ens-NoanMP-PX are analyzed in detail. The results demonstrate that the intensity of the simulated sensible heat flux over Central Asia is weaker in Ens-CLM4-SSiB than that in Ens-NoahMP-PX. As a result, large differences in geopotential height occur over the model simulation domain. The simulated wind fields are subsequently affected due to the geostrophic adjustment process, thus the simulation of 2-m temperature, precipitation, surface soil moisture and surface skin temperature are all affected.

Abstract: The Third Pole (TP) is experiencing rapid warming and is currently in its warmest period in the past 2,000 years. This paper reviews the latest development in multidisciplinary TP research associated with this warming. The rapid warming facilitates intense and broad glacier melt over most of the TP, although some glaciers in the northwest are advancing. By heating the atmosphere and reducing snow/ice albedo, aerosols also contribute to the glaciers melting. Glacier melt is accompanied by lake expansion and intensification of the water cycle over the TP. Precipitation has increased over the eastern and northwestern TP. Meanwhile, the TP is greening and most regions are experiencing advancing phenological trends, although over the southwest there is a spring phenological delay mainly in response to the recent decline in spring precipitation. Atmospheric and terrestrial thermal and dynamical processes over the TP affect the Asian monsoon at different scales. Recent evidence indicates substantial roles that mesoscale convective systems play in the TP’s precipitation as well as an association between soil moisture anomalies in the TP and the Indian monsoon. Moreover, an increase in geohazard events has been associated with recent environmental changes, some of which have had catastrophic consequences caused by glacial lake outbursts and landslides. Active debris flows are growing in both frequency of occurrences and spatial scale. Meanwhile, new types of disasters, such as the twin ice avalanches in Ali in 2016, are now appearing in the region. Adaptation and mitigation measures should be taken to help societies’ preparation for future environmental challenges. Some key issues for future TP studies are also discussed.