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Typhoons are extreme weather phenomena that seriously affect the daily lives of residents and regular functioning of society. As one of the most typhoon-prone countries in the world, China is constantly affected by typhoons and their secondary disasters, which can cause significant casualties and economic losses. The extent of damage caused by typhoons is inversely proportional to the effectiveness of the emergency response. Therefore, accurate and comprehensive access to damage information is critical for rescue and recovery. Social media, which is characterized by low collection costs and rich content, is an important means of collecting disaster information. With the development of social media, it has become increasingly important to accurately and comprehensively identify social media texts related to typhoons. In this study, by combining typhoon attribute data and a multi-label classification method with Bidirectional Encoder Representations from Transformers (BERT) and Bidirectional Long Short-Term Memory (BiLSTM) models, a typhoon damage identification method based on Weibo texts and deep learning is proposed to identify the damage caused by severe and super typhoons that made landfall in Guangdong Province from 2010 to 2019. First, texts related to typhoon damage were identified from the massive Weibo texts and further classified into five damage categories: transportation, public, electricity, forestry, and waterlogging. The typhoon damage characteristics were comparatively analyzed using spatial distribution, time curves, and quantity curves. The results showed that the accuracy of typhoon damage classification was high, with an F1 score of 0.907 for identifying typhoon damage-related texts and 0.814 for further classifying them into five damage categories. Typhoon attribute data and multi-label classification methods have improved the accuracy and comprehensiveness of typhoon damage identification. Compared to the use of Weibo texts only and the single-label classification method, typhoon attribute data provide information on the geographic context of the typhoon at the time of the texts' release, and the multi-label classification method allows the texts to belong to more than one damage category. This study shows that there are differences in the proportion of damage caused by different typhoons, which are related to the intensity and track of the typhoon, as well as the development level of the affected areas. In addition, before the typhoon makes landfall, precautions lead to transportation and public-related damage. After the typhoon makes landfall, the typhoon damage shows single and double-peak characteristics, and the different characteristics reflect the changing trends and features of typhoon damage. This study provides a scientific basis for typhoon damage identification and disaster relief in Guangdong Province.

The Tibetan Plateau (TP) has experienced "south drying‐north wetting" extreme precipitation changes over the past half century. The effects of water vapor transport at different timescales on TP extreme precipitation changes remain unexplored. Here, we utilize the reanalysis data sets to quantify the contributions of stationary and transient processes of water vapor transport to the long‐term changes in the extreme precipitation (R95p) during wet season (Jun‐Jul‐Aug‐Sep) over the TP and surrounding regions. We find that the daily scale transient processes dominate the dipole trend of extreme precipitation with a contribution of 55.1% in the northern and 79.5% in the southern TP, respectively, whereas the contribution of monthly scale stationary processes is of 19.0% and 20.5%. The long‐term changes in extreme precipitation are dominated by the transient dynamic component. We identified the synoptic circulation patterns affecting the changes of R95p over the northern and southern TP by using k‐means clustering. The patterns featured with a 500 hPa trough, 200 hPa wind divergence and low transient geopotential height are identified. The frequency of the dominant circulation patterns increases in the northern TP and decreases in the southern TP, which leads to the dipolar changes of extreme precipitation over the TP and surrounding regions. Plain Language Summary: The Tibetan Plateau (TP), known as the "Asian water tower," is facing a crisis of water resources imbalance. Extreme precipitation has attracted much attention because of its large amount and disastrous nature. A "south drying‐north wetting" pattern of extreme precipitation changes over the TP and surrounding regions is seen in recent decades. Understanding the contribution of water vapor transport at different timescales to this dipolar pattern is of vital importance for the water resources changes therein. Based on the state‐of‐the‐art reanalysis data sets, we show that the "south drying‐north wetting" of extreme precipitation over the TP and surrounding regions is dominated by the long‐term changes of transient processes, whereas stationary processes have the same effect but are smaller in magnitude. We also stress the dominant role of changes in the frequency of synoptic circulation patterns on the "south drying‐north wetting" pattern of extreme precipitation changes over the TP and surrounding regions. Our results highlight the strong link between changes in the frequency of synoptic‐scale processes and long‐term changes in extreme precipitation over the TP and surrounding regions. Key Points: The transient processes dominate the extreme precipitation changes over the TP with contributions of 55.1% (north) and 79.5% (south)The frequency changes of the synoptic circulation patterns are responsible for the extreme precipitation changes over the TP [ABSTRACT FROM AUTHOR]

Changes in precipitation characteristics directly affect society through their impacts on drought and floods, hydro-dams, and urban drainage systems. Global warming increases the water holding capacity of the atmosphere and thus the risk of heavy precipitation. Here, daily precipitation records from over 700 Chinese stations from 1956 to 2005 are analyzed. The results show a significant shift from light to heavy precipitation over eastern China. An optimal fingerprinting analysis of simulations from 11 climate models driven by different combinations of historical anthropogenic (greenhouse gases, aerosols, land use, and ozone) and natural (volcanic and solar) forcings indicates that anthropogenic forcing on climate, including increases in greenhouse gases (GHGs), has had a detectable contribution to the observed shift toward heavy precipitation. Some evidence is found that anthropogenic aerosols (AAs) partially offset the effect of the GHG forcing, resulting in a weaker shift toward heavy precipitation in simulations that include the AA forcing than in simulations with only the GHG forcing. In addition to the thermodynamic mechanism, strengthened water vapor transport from the adjacent oceans and by midlatitude westerlies, resulting mainly from GHG-induced warming, also favors heavy precipitation over eastern China. Further GHG-induced warming is predicted to lead to an increasing shift toward heavy precipitation, leading to increased urban flooding and posing a significant challenge for mega-cities in China in the coming decades. Future reductions in AA emissions resulting from air pollution controls could exacerbate this tendency toward heavier precipitation.

The Tibetan Plateau (TP) provides vital water resources for downstream regions, with spring precipitation contributing considerably to the annual totals over the southeastern TP. The added value of convection‐permitting modeling in simulating the spring climate over the TP is uncertain. Here, we conducted and compared decade‐long regional convection‐permitting (3.3 km) and convection‐parameterized (13.2 km) Icosahedral Nonhydrostatic Weather and Climate Model (ICON) simulations to reproduce the atmospheric water cycle in spring over the TP. Results indicated that 3.3 km mesh ICON (ICON_3.3 km) exhibited notable added value in simulating the spring atmospheric water cycle over the TP. ICON_3.3 km reduced the wet biases of precipitation in the ERA5 reanalysis and 13.2 km mesh ICON (ICON_13.2 km) simulations, and improved the simulation of surface evaporation over the central and eastern TP. The reduction in the simulated precipitation in ICON_3.3 km was primarily followed by a decrease in surface evaporation from March to May, second by a reduction in water vapor flux convergence in May due to decreased water vapor inflow from the southeastern TP. Furthermore, compared to ICON_13.2 km, ICON_3.3 km alleviated the "drizzling" bias, leading to drier surface soils and decreased evaporation, and lead to 3% decrease in the fraction of evaporation converted into precipitation. Sensitivity experiments conducted at resolution of 13.2 km but turning off the convection parameterization demonstrated that both explicit representation of convection and enhanced horizontal resolution were crucial for accurately representing the spring atmospheric water cycle over the TP. Our results highlighted the need to develop kilometer‐scale models for successfully reproducing the climate characteristics across the TP. Plain Language Summary: Climate modeling is evolving toward kilometer‐scale or convective‐permitting model (CPM). The added value of regional CPM in simulating the spring climate over the Tibetan Plateau (TP), known as "Asian Water Tower," is unknown. Here, we have performed and compared two decade‐long regional climate simulations at two horizontal resolutions: convection permitting (3.3 km) and convection parameterized (13.2 km), to reproduce the atmospheric water cycle in spring over the TP. Results indicated that the CPM reduced the wet biases in the latest reanalysis data and the convection‐parameterized model over the central and eastern TP. The reduction of wet biases was mainly followed by the decreased surface evaporation, which was associated with the alleviation of "drizzling" bias in CPM. We further showed evidences that both explicit representation of convection and enhanced horizontal resolution were crucial for accurately representing the spring climate over the TP. Our findings highlight the importance of developing high‐efficiency kilometer‐scale (<4 km) models for reproducing all the climate characteristics across the TP region. Key Points: Regional convection permitting model exhibited evident added value in simulating the spring atmospheric water cycle over the Tibetan Plateau (TP)Reduced precipitation by convective‐permitting model was mainly followed by decrease in surface evaporation, associated with the alleviation of drizzling biasesBoth explicit convection and enhanced resolution were crucial for well representing the spring atmospheric water cycle over the TP [ABSTRACT FROM AUTHOR]

The quantitative relationship between Mesoscale Convective Systems (MCSs) and floods over East Asia has not been established. In this study, MCSs are clustered into four types with Self‐Organizing Map approach. Floods in June‐August of 2000–2021 are linked with different types of MCS by automated algorithms we constructed. We find that among the major floods (potential flood peak periods), 91% (87%) are related to MCS, 65% (78%) are dominated by MCS, and 38% (20%) are dominated by multi‐types of MCS. Types 1 and 2 MCS have higher flood‐inducing efficiencies than common MCS (Type‐4). Type‐1 MCS, characterized by the least number (2% of the total number), the largest precipitation volume, longest lifetime, slowest moving, strongest precipitation, can most efficiently produce floods. Type‐2 MCS, characterized by the second largest precipitation volume, more numerous than Type‐1 particularly over land, can induce floods not only relatively efficiently but also more frequently than Type‐1. Plain Language Summary: Mesoscale Convective Systems (MCS) can cause large flood events but how they work in East Asia at climatic scale remains unexplored. In this study, we tracked MCS over the time period of 2000–2021 and grouped them into four types using the Self‐Organizing Map approach. We connected summer floods with the four types of MCS using automated algorithms. We found that most large flood events and potential flood peak periods are dominated by MCS. Type‐1 MCS, which features large land‐rain area, longest lifetime, slowest movement and strongest precipitation, is most efficient in inducing floods. A Longer lifetime not only contributes to greater total precipitation volume but also increases the overlap area, thereby enhancing the precipitation volume per area. The slow movement further increases the overlap area. The high overlap area helps reduce the proportion of precipitation absorbed by the soil. Type‐2 MCS, which features with the second largest precipitation volume, occurs more frequently than Type‐1 especially over land, and can cause floods more frequently than Type‐1. These findings can enhance our understanding of flood formation over East Asia. Key Points: Among the major floods (potential flood peak periods) occurred in 2000–2021 summer, 91% (87%) are related to Mesoscale Convective Systems (MCS), and 66% (78%) are dominated by MCSType‐1 MCS is the most efficient among the four types in causing floods for its strongest precipitation rate, longest lifetime and slowest movementLong lifetime and slow movement increase the overlap area, boosting precipitation per area and reducing the proportion of rainfall absorbed by soil [ABSTRACT FROM AUTHOR]

Cold extremes have large impacts on human society. Understanding the physical processes dominating the changes in cold extremes is crucial for a reliable projection of future climate change. The observed cold extremes have decreased during the last several decades, and this trend will continue under future global warming. Here, we quantitatively identify the contributions of dynamic (changes in large-scale atmospheric circulation) and thermodynamic (rising temperatures resulting from global warming) effects to East Asian cold extremes in the past several decades and in a future warm climate by using two sets of large-ensemble simulations of climate models. We show that the dynamic component accounts for over 80 % of the cold-month (coldest 5 % boreal winter months) surface air temperature (SAT) anomaly over the past 5 decades. However, in a future warm climate, the thermodynamic change is the main contributor to the decreases in the intensity and occurrence probability of East Asian cold extremes, while the dynamic change is also contributive. The intensity of East Asian cold extremes will decrease by around 5 °C at the end of the 21st century, in which the thermodynamic (dynamic) change contributes approximately 75 % (25 %). The present-day (1986–2005) East Asian cold extremes will almost never occur after around 2035, and this will happen 10 years later due solely to thermodynamic change. The upward trend of a positive Arctic Oscillation-like sea level pressure pattern dominates the changes in the dynamic component. The finding provides a useful reference for policymakers in climate change adaptation activities. [ABSTRACT FROM AUTHOR]

Most studies have shown a link between chronotypes and mental health and have identified evening chronotypes (E-types) as a potential risk for depressive symptoms. However, the mechanisms behind this association remain unknown. Abnormal expression of the PER1 gene was not only associated with circadian rhythm disturbance, but also closely related to mental illness. Therefore, this study aimed to examine the association of chronotype with depressive symptoms, and further explore the moderating effects of the PER1 gene DNA methylation on chronotypes and depressive symptoms in Chinese university students. In a stratified cluster sampling design, chronotype and depressive symptoms were assessed in 1 042 university students from 2 universities in a two-year prospective survey from April 2019 to October 2020. The survey was conducted once every 6 months, corresponding to the time points in April 2019 (T0), October 2019 (T1), April 2020 (T2), and October 2020 (T3). At T0, the Morning and Evening Questionnaire 5 (MEQ-5) was adopted to assess chronotype. At T0-T3, the Patient Health Questionnaire 9 (PHQ-9) was adopted to investigate depressive symptoms. Meanwhile, at T0, participants were subjected to a health check-up trip in the hospital, and blood samples were taken from the students to measure the PER1 gene DNA methylation levels. Binary logistic regression was used to analyze the association of chronotypes with depressive symptoms. The depression/total depression group was coded as 1, while the remaining participants was defined as one group, and was coded as 0. The PROCESS plug-in of SPSS software was used to analyze the moderating effects of PER1 gene DNA methylation on the association of chronotype with depressive symptoms. After adjusting for covariates, the results indicated that T0 E-types were positively correlated with T0-T3 depression/total depression in female university students. Furthermore, the PER1 gene DNA methylation has negative moderating effects between T0 chronotype and T3 depressive symptoms and has a sex difference. This study can provide more favorable scientific value for the prevention and control of depression in university students. [ABSTRACT FROM AUTHOR]