Effects of hydrologic regimes on the loading and spatiotemporal variation of mercury in the microtidal river estuary.

The potential effect of hydrological conditions on distribution and loadings of Hg species was investigated in the microtidal Hyeongsan River Estuary (HRE). Dissolved Hg (DHg) and dissolved methylmercury (DMeHg) from the creek receiving industrial wastes were effectively settled to sediment during the post-typhoon period, while persistent input from the Hg-contaminated creek without settling was observed during the dry periods. The event-based mean approach was applied to explore the hydrological effects on the annual flux of Hg. The largest inputs of DHg and particulate Hg (PHg) were found in the Hg-contaminated creek, and DHg input was higher in the dry than wet periods whereas PHg input was higher in the wet than dry periods. In sediment, Hg and MeHg concentrations decreased after the typhoon, attributed to erosion of surface sediments. Overall, the HRE serves as an effective sink of Hg that reduces the degree of Hg contamination in coastal water.

Long Short-Term Memory Networks' Application on Typhoon Wave Prediction for the Western Coast of Taiwan.

Huge waves caused by typhoons often induce severe disasters along coastal areas, making the effective prediction of typhoon-induced waves a crucial research issue for researchers. In recent years, the development of the Internet of Underwater Things (IoUT) has rapidly increased the prediction of oceanic environmental disasters. Past studies have utilized meteorological data and feedforward neural networks (e.g., BPNN) with static network structures to establish short lead time (e.g., 1 h) typhoon wave prediction models for the coast of Taiwan. However, sufficient lead time for prediction remains essential for preparedness, early warning, and response to minimize the loss of lives and properties during typhoons. The aim of this research is to construct a novel long lead time typhoon-induced wave prediction model using Long Short-Term Memory (LSTM), which incorporates a dynamic network structure. LSTM can capture long-term information through its recurrent structure and selectively retain necessary signals using memory gates. Compared to earlier studies, this method extends the prediction lead time and significantly improves the learning and generalization capability, thereby enhancing prediction accuracy markedly.

Changes in fronts regulate nitrate cycling in Zhanjiang Bay: A comparative study during the normal wet season, rainstorm, and typhoon periods.

Typhoons and rainstorms (>250 mm/day) are extreme weather events changing hydrological characteristics and thus nitrogen (N) cycle in coastal waters. However, responses of N cycle to rainstorms and typhoons and their underlying mechanisms need to be elucidated. In this study, we conducted an analysis of a comparative dataset encompassing concentrations of nitrate (NO3-), ammonium (NH4+), dissolved oxygen (DO), chlorophyll a (Chl a), hydrological parameters, dual isotopic composition of NO3- (δ15N-NO3- and δ18O-NO3-) in Zhanjiang Bay during three distinct periods: the normal wet season, rainstorm, and typhoon periods. After the rainstorm, the salinity front in Zhanjiang Bay was more weakened and steadier than that during the normal wet season, mainly because onshore wind and a large amount of freshwater was inputted into the ocean surface. This weakened and steady salinity front strengthened water stratification and provided a favorable condition for phytoplankton blooms. Correspondingly, evident NO3- deficits coincided with elevated δ15N-NO3- and δ18O-NO3- values indicated that sufficient NO3- sustained phytoplankton blooms, leading to NO3- assimilation during the rainstorm period. By contrast, due to the onshore wind induced by the typhoon, the salinity front in Zhanjiang Bay was more intensified and unsteady after the typhoon than the normal wet season. The salinity front after the typhoon was unsteady enough to enhance vertical mixing in the water column. Relatively high DO concentrations suggested that enhanced vertical mixing after the typhoon support freshly organic matter decomposition and nitrification via oxygen injection from the air into the water column. In addition, NO3- deficits coincided with elevated δ15N-NO3- values and δ18O-NO3- values demonstrated the coexistence of NO3- assimilation during the typhoon period. This study suggests that the changing processes involved in NO3- cycling after typhoons and rainstorms are associated with the stability and intensity of the salinity front altered by these weather events.

Damage to tropical forests caused by cyclones is driven by wind speed but mediated by topographical exposure and tree characteristics.

Each year, an average of 45 tropical cyclones affect coastal areas and potentially impact forests. The proportion of the most intense cyclones has increased over the past four decades and is predicted to continue to do so. Yet, it remains uncertain how topographical exposure and tree characteristics can mediate the damage caused by increasing wind speed. Here, we compiled empirical data on the damage caused by 11 cyclones occurring over the past 40 years, from 74 forest plots representing tropical regions worldwide, encompassing field data for 22,176 trees and 815 species. We reconstructed the wind structure of those tropical cyclones to estimate the maximum sustained wind speed (MSW) and wind direction at the studied plots. Then, we used a causal inference framework combined with Bayesian generalised linear mixed models to understand and quantify the causal effects of MSW, topographical exposure to wind (EXP), tree size (DBH) and species wood density (ρ) on the proportion of damaged trees at the community level, and on the probability of snapping or uprooting at the tree level. The probability of snapping or uprooting at the tree level and, hence, the proportion of damaged trees at the community level, increased with increasing MSW, and with increasing EXP accentuating the damaging effects of cyclones, in particular at higher wind speeds. Higher ρ decreased the probability of snapping and to a lesser extent of uprooting. Larger trees tended to have lower probabilities of snapping but increased probabilities of uprooting. Importantly, the effect of ρ decreasing the probabilities of snapping was more marked for smaller than larger trees and was further accentuated at higher MSW. Our work emphasises how local topography, tree size and species wood density together mediate cyclone damage to tropical forests, facilitating better predictions of the impacts of such disturbances in an increasingly windier world.

Typhoon disaster state information extraction for Chinese texts.

Typhoon disasters undergo a complex evolutionary process influenced by temporal changes, and investigating this process constitutes the central focus of geographical research. As a key node within the typhoon disaster process, the state serves as the foundation for gauging the dynamics of the disaster. The majority of current approaches to disaster information extraction rely on event extraction methods to acquire fundamental elements, including disaster-causing factors, disaster-bearing bodies, disaster-pregnant environment and the extent of damage. Due to the dispersion of various disaster information and the diversity of time and space, it is a challenge for supporting the analysis of the typhoon disaster process. In this paper, a typhoon disaster state information extraction (TDSIE) method for Chinese texts is proposed, which aims to facilitate the systematic integration of fragmented typhoon disaster information. First, the integration of part-of-speech tagging with spatio-temporal information extraction is employed to achieve the tagging of typhoon disaster texts. Second, within the framework of spatio-temporal semantic units, the typhoon disaster semantic vector is constructed to facilitate the identification of information elements of typhoon disaster states. Third, co-referential state information fusion is performed based on spatio-temporal cues. Experimental analysis, conducted using online news as the data source, reveals that the TDSIE achieves precision and recall rates consistently surpassing 85%. The typhoon disaster state information derived from the TDSIE allows for the analysis of spatio-temporal patterns, evolutionary characteristics, and activity modes of typhoon disasters across various scales. Therefore, TDSIE serves as valuable support for investigating the inherent process properties of typhoon disasters.

Impact of climate-induced floods and typhoons on geriatric disabling health among older Chinese and Filipinos: a cross-country systematic review.

BACKGROUND: Apart from both China and the Philippines continuing to be exposed to and affected by different climate-induced hazards, in particular floods and typhoons, they are also reported to be witnessing rapid ageing populations of 60 years and older. As such, this systematic review synthesized the existing evidence about the impacts aggravated by floods and typhoons on the geriatric disabling health of older Chinese and Filipinos, respectively. METHODS: Four (4) electronic databases were systematically searched to identify eligible studies published between 2000 and early 2023. This process had to confirm the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA), as well as the standard protocol registered with PROSPERO (CRD42023420549). RESULTS: Out of 317 and 216 initial records retrieved for China and the Philippines, respectively, 27 (China) and 25 (Philippines) studies were eligible for final review. The disabling conditions they reported to affect the health of older adults were grouped into 4 categories: cognitive and intellectual, physical, chronic and terminal illnesses, and mental and psychological, with the latter identified as the most prevalent condition to affect older Chinese and Filipinos. On a sub-category level, posttraumatic stress disorder (PTSD) was the most common condition reported in 27 flood-related studies in China, while injuries and wounds prevailed in the Philippines, according to 25 typhoon-related studies. CONCLUSION: The increasing occurrence of extreme climate hazards, especially floods and typhoons in China and the Philippines, respectively, impacted the health of their older adults with various disabling effects or conditions. Therefore, this calls for appropriate geriatric-informed interventions in the context of climate change and rapidly ageing settings beyond China and the Philippines to others that are also prone to floods and typhoons.

Effects of typhoon events on coastal hydrology, nutrients, and algal bloom dynamics: Insights from continuous observation and machine learning in semi-enclosed Zhanjiang Bay, China.

Typhoons can induce variations in hydrodynamic conditions and biogeochemical processes, potentially escalating the risk of algal bloom occurrences impacting coastal ecosystems. However, the impacts of typhoons on instantaneous changes and the mechanisms behind typhoon-induced algal blooms remain poorly understood. This study utilized high-frequency in situ observation and machine learning model to track the dynamic variations in meteorological, hydrological, physicochemical, and Chlorophyll-a (Chl-a) levels through the complete Typhoon Talim landing in Zhanjiang Bay (ZJB) in July 2023. The results showed that a delayed onset of algal bloom occurring 10 days after typhoon's arrival. Subsequently, as temperatures reached a suitable range, with an ample supply of nutrients and water stability, Chl-a peaked at 121.49 µg L-1 in algal bloom period. Additionally, water temperature and air temperature decreased by 1.61 °C and 2.8 °C during the typhoon, respectively. In addition, wind speed and flow speed increased by 1.34 and 0.015 m s-1 h-1 to peak values, respectively. Moreover, the slow decline of 8.2 % in salinity suggested a substantial freshwater input, leading to an increase in nutrients. For instance, the mean DIN and DIP were 2.2 and 8.5 times higher than those of the pre-typhoon period, resulting in a decrease in DIN/DIP (closer to16) and the alleviation of P limitation. Furthermore, pH and dissolved oxygen (DO) were both low during the typhoon period and then peaked at 8.93 and 19.05 mg L-1 during the algal bloom period, respectively, but subsequently decreased, remaining lower than those of the pre-typhoon period. A preliminary learning machine model was established to predict Chl-a and exhibited good accuracy, with R2 of 0.73. This study revealed the mechanisms of eutrophication status formation and algal blooms occurrence in the coastal waters, providing insights into the effects of typhoon events on tropical coastal biogeochemistry and ecology.

Comprehensive risk assessment of typhoon disasters in China's coastal areas based on multi-source geographic big data.

Typhoons can bring substantial casualties and economic ramifications, and effective prevention strategies necessitate a comprehensive risk assessment. Nevertheless, existing studies on its comprehensive risk assessment are characterized by coarse spatial scales, limited incorporation of geographic big data, and rarely considering disaster mitigation capacity. To address these problems, this study combined multi-source geographic big data to develop the Comprehensive Risk Assessment Model (CRAM). The model integrated 17 indicators from 4 categories of factors, including exposure, vulnerability, hazard, and mitigation capacity. A subjective-objective combination weighting method was introduced to generate the indicator weights, and comprehensive risk index of typhoon disasters was calculated for 987 counties along China's coastal regions. Results revealed a pronounced spatial heterogeneity of the comprehensive typhoon risk, which exhibited an overall decreasing trend from the southeast coastal areas toward the northwest inland territories. 61.7 % of the counties exhibited a medium-to-high level of comprehensive risk, and counties with very-high risks are predominantly concentrated in the Shandong Peninsula, Yangtze River Delta, Hokkien Golden Triangle, Greater Bay Area, Leizhou Peninsula, and Hainan Province, mainly due to high exposure and hazard factors. The correlation coefficient between the risk assessment results and typhoon-induced direct economic losses reached 0.702, indicating the effectiveness and reliability of the CRAM. Meanwhile, indicators from intrinsic attributes of typhoons and geographic big data had pronounced importance, and regional mitigation capacity should be improved. Our proposed method can help to scientifically understand spatial patterns of comprehensive risk and mitigate the effects of typhoon disasters in China's coastal regions.

Impact of typhoon events on microplastic distribution in offshore sediments in Leizhou Peninsula of the South China Sea.

Microplastic is an emerging pollutant and a technical fossil in Anthropocene sediments. Typhoon frequency and intensity have increased due to climate change, which has a major effect on the distribution patterns of microplastics. It is still unknown, though, how the topography of the peninsula affects the reconstruction of the distribution of microplastic in typhoons. Due to frequent typhoons, the Leizhou Peninsula (LZP) in the north part of the South China Sea is an ideal place to study the impact of topographic variations on microplastic distribution during typhoon events. This study investigated microplastics ranging in size from 50 µm to 5 mm in sediment. Microscopic inspection and µ-FTIR tests were used to identify microplastic characteristics from offshore surface sediments before and after typhoons. The average microplastic abundance in offshore sediments decreased from 18 ± 17 items/kg to 15 ± 15 items/kg after typhoons. Results show that typhoons only increase the microplastic abundance in topographically protected areas along the northeast coast of LZP, with no significant difference observed in other regions. The influence of typhoon on the morphological characteristics of microplastics in sediments is more pronounced and widespread, as evidenced by a shift in the predominant shape of microplastics from fibers to fragments and a decrease in size accompanied by an increased abundance within the 100 µm-1 mm fraction. The color of microplastics remained similar before and after typhoons, and the polymer composition of microplastics became more uniform. The alteration of microplastic morphology may be attributed to the enhancement of wave intensity induced by typhoons. This study enhances the comprehension of typhoon-induced impacts on pollutant redistribution, specifically microplastics, thereby providing essential empirical evidence and theoretical foundations for pollution regulation.

Daily impact of the simultaneous passage of binary typhoons on sea surface chlorophyll-a concentration dynamics in the Northwestern Pacific.

Typhoons are recognized as one of the most destructive meteorological phenomena, exerting significant influences on marine ecosystems. Sea surface chlorophyll-a concentration (CHL)an essential indicator of phytoplankton biomass, can be utilized to characterize the disturbances of typhoons on the marine ecosystem. However, it is challenging to investigate this impact at a daily scale due to the missing CHL remote sensing data caused by cloud cover. Given that concurrent passing typhoons may interact with CHL, this study analyzes the effect of the simultaneous passage of binary typhoons Tembin and Bolaven on CHL by using daily CHL reconstruction data, and investigates the role of ocean environmental factors in driving the dynamics of CHL, including sea surface temperature (SST), mixed layer depth (MLD), and sea surface height anomaly (SSHA). The results show that typhoons Tembin and Bolaven increase CHL with the maximum increment of ∼3.2 mg∙m-3 during 4-6 days after typhoons passage. The maximum change areas of CHL are distributed near the intersection of typhoon track of (32°N, 125.2°E), corresponding to the regions of greater variation in SST and MLD. During 15 days before and after typhoons (i.e., from 15 August to 15 September 2012), SST is negatively correlated with CHL (the correlation coefficient of -0.85) and MLD is positively correlated with CHL (the correlation coefficient of -0.80). SST immediately declines after typhoons with a maximum cooling of 7.8 deg. C, showing the decreased SST from ∼28 deg. C to ∼23 deg. C can promote phytoplankton growth. MLD deepens from 10 m to >25 m caused by typhoon-induced strong winds, allowing more nutrients to be transported from the subsurface layer to the euphotic layer for phytoplankton blooms. Furthermore, oceanic eddies captured by SSHA change from cyclonic to anticyclonic eddies accompanied by the beginning of CHL increases, and the largest CHL increases correspond to the distribution of pre-existing cyclonic eddies. It suggests that Tembin and Boravin promote phytoplankton growth to increase CHL by enhancing vertical mixing and upwelling to transport nutrients to the sea surface. These findings inspire us to rethink the daily effects of typhoons on CHL, with critical importance for predicting and managing the ecological consequences of typhoons in the ocean.

The threaten of typhoons to the health of residents in inland areas: a study on the vulnerability of residents to death risk during typhoon "Lekima" : In Jinan, China.

BACKGROUND: Studies had suggested increased risk of death of residents was associated with typhoons, particularly coastal regions. However, these findings ignored the impact of inland typhoons on the health of residents, especially the indirect death risk caused by typhoons. This study aimed to investigate the acute death risk of residents during inland typhoon Lekima in Jinan, further identify vulnerable populations and areas. METHODS: We selected the daily death from 11 to 27th August 2019 in Jinan as case period, and conducted a time-stratified case-crossover design to match the contemporaneous data from 2016 to 2018 as control period. We used the generalized linear Poisson models to estimate the related effects of death risk during typhoon Lekima and lag days. RESULTS: During the Lekima typhoon month, there were 3,366 deaths occurred in Jinan. Compared to unexposed periods, the acute death risk of non-accidental diseases (especially circulatory diseases), female and the older adults increased significantly in the second week after the typhoon. The maximum significant effect of circulatory disease deaths, female and older adult deaths were appeared on lag9, lag9, and lag13 respectively. And the typhoon-associated RR were 1.19 (95%CI:1.05,1.34), 1.28 (95%CI:1.08,1.52), and 1.22 (95%CI:1.06,1.42) respectively. The acute death risk of residents living in TQ and CQ increased significantly on Lag2 and Lag6 after the typhoon, respectively, while those living in LX, LC, HY, JY, and SH occurred from Lag 8 to Lag 13 after the typhoon. LC lasted the longest days. CONCLUSIONS: Typhoons would increase the vulnerability of residents living in Jinan which mainly occurred from the seventh day after the typhoon. Residents suffering from non-accidental diseases (circulatory diseases), female and the older adults were more vulnerable. The vulnerability of TQ and CQ occurred on Lag2 and Lag6 after typhoon Lekima, respectively, and the other areas except ZQ and PY occurred from Lag 8 to Lag 13. LC lasted the longest duration. Our findings emphasized the importance of the emergency response, which would help policymakers to identify vulnerable regions and populations accurately during typhoons and formulate the emergency response plan.

[Analysis of O3 Pollution Affected by a Succession of Three Landfall Typhoons in 2020 in Eastern China].

Based on air quality monitoring, surface meteorological data, wind profile radar observation, and the HYSPLIT model, the characteristics and causes of O3 pollution in eastern China during the period of the typhoons BAVI, MAYSAK, and HAISHEN from August 26 to September 8, 2020 were analyzed. The results showed that during the succession of the three landfall typhoons, the O3 pollution sites in Beijing Tianjin Hebei and its surrounding areas (BTHS) and the Yangtze River Delta (YRD) exceeded 50%. During the HAISHEN period, O3 pollution days in the two regions reached 2.22 d and 2.97 d, respectively, with significant persistence characteristics. The location of the typhoon had an obvious influence on O3 concentration. When the typhoons were located within the 24h warning line, the O3 concentrations in BTHS and YRD were relatively low. When the typhoons were located between the 24 h and 48 h warning lines, the O3 concentration in BTHS was the highest. When the typhoons moved north of 34°N, the YRD was most prone to regional O3 pollution. O3 pollution in Shanghai mainly occurred under the control of the northward air flow to the west side of the typhoons, and the regional transport from the upstream area had a significant impact on the increase in O3 and its precursor concentrations. The downdraft below 1 000 m maintained O3 at a high concentration at night. In Jinan, O3 pollution mainly occurred under the control of the subtropical high and typhoon periphery. The downdraft prevailed in the middle and lower levels during the O3 pollution. From August 28 to 30, under the control of the subtropical high, the pollutants were mainly accumulated locally, and some of them were transmitted within the province, showing a "double high" phenomenon of O3 and PM2.5. From September 5 to 8, under the influence of HAISHEN peripheral circulation, the regional transport was obvious, and the O3 concentration increased earlier than that of PM2.5.

Building loss assessment using deep learning algorithm from typhoon Rusa.

Climate crises such as extreme weather events, natural disasters and climate change caused by climate transformations are causing much damage worldwide enough to be called a climate catastrophe. The private sector and the government across industries are making every effort to prevent and limit the increasing damage, but the results have yet to meet market demand. Therefore, this study proposes a method that uses a deep learning algorithm to predict the damage caused by typhoons. Model development is based on a Deep Neural Network (DNN) algorithm, and learning data is obtained by fine-tuning the network structure and hyperparameters; the amount of damage caused by Typhoon Rusa was known as training data. The constructed DNN model underwent evaluation and validation by computation of mean absolute error (MAE) and root mean square error (RMSE). Furthermore, a comparative analysis was conducted to confirm the applicability of the proposed framework against a traditional multi-regression model to ensure the model's accuracy and resilience. Finally, this study offers a novel approach to predicting typhoon damage using advanced deep-learning techniques. Subsequently, government disaster management officials, facility managers, and insurance companies can utilize this method to accurately predict the extent of damage caused by typhoons. Preventive actions such as improved risk assessment, expanded insurance companies, and enhanced disaster responses plans can be implemented using these outcomes. Ultimately, the proposed model will help to reduce typhoon damage and strengthen general resilience to climate crises.

Tropical cyclone winds and precipitation stimulate cone production in the masting species longleaf pine (Pinus palustris).

Many trees exhibit masting - where reproduction is temporally variable and synchronous over large areas. Several dominant masting species occur in tropical cyclone (TC)-prone regions, but it is unknown whether TCs correlate with mast seeding. We analyzed long-term data (1958-2022) to test the hypothesis that TCs influence cone production in longleaf pine (Pinus palustris). We integrate field observations, weather data, satellite imagery, and hurricane models to test whether TCs influence cone production via: increased precipitation; canopy density reduction; and/or mechanical stress from wind. Cone production was 31% higher 1 yr after hurricanes and 71% higher after 2 yr, before returning to baseline levels. Cyclone-associated precipitation was correlated with increased cone production in wet years and cone production increased after low-intensity winds (≤ 25 m s-1 ) but not with high-intensity winds (> 25 m s-1 ). Tropical cyclones may stimulate cone production via precipitation addition, but high-intensity winds may offset any gains. Our study is the first to support the direct influence of TCs on reproduction, suggesting a previously unknown environmental correlate of masting, which may occur in hurricane-prone forests world-wide.

Multi-order analytical solving computation of rainstorm causal decomposition during typhoons using a designed key-lock quasi-Newton optimizing derivation.

To precisely identify multi-dimensional spatiotemporal rain-making parameters, generate an approximate Hessian matrix, and solve the nonlinear ill-posed problem, this study uses composite logical tangent hyperbolic functions to construct the rain-generating simulation model as nonlinear algebraic equations with designed key-lock quasi-Newton optimization for deriving multi-order objective functional derivatives for rainstorm causal decomposition into advanced functional, analytical solution (lock) and Newton's conditional constraints. Specifically, the rank-two approximate structure of the Levenberg-Marquardt and Broyden-Fletcher-Goldfarb-Shanno quasi-Newton algorithms are modified as the symmetric rank-four structure to efficiently calculate a positive definite stable Hessian and solve the constrained nonlinear rain-making threshold. The model projects various rain-making factors into multi-rank loading scores, characterizing rain-generating mechanisms and causal components as associated DNAs. To accelerate/modify directional convergence, avoid local minimum, and detect global optimum, the devised vectorized limited switchable step sizes are optimized using advanced double-bracketing approaches combined with candidate parameters' correction vectors (key) and referenced step-size distributions solved by Newton's constrained analytical solution to reduce heterogeneous differences and eliminate the conventional overestimated Hessian. The identified rain-making DNAs reveal that typhoons with similar DNAs move in similar directions. Specifically, rain-making DNAs in Taipei Category 1 were correlated with wind force/direction and cloud height along PCs 1, 3, 4, and 7, and those in Category 2 were correlated with cloud-cover distribution along PCs 1, 2, and 5. The identified rain-making thresholds of typhoons with constant direction/structure showed a weaker steady state, whereas the unsteady rest produced multi-peak rainfall hydrographs. Rain evolution analysis reveals that cloudy rainbands, carried by the wind field, move along the Tamsui River valley when traveling between northeast and south-southeast of Taipei; converge with gradient and geostrophic winds when traveling between east-northeast and southwest; merge with southwest monsoon when traveling between west-southwest and northeast of Kaohsiung.

Hurricane wind regimes for forests of North America.

Despite the ubiquity of tropical cyclones and their impacts on forests, little is known about how tropical cyclone regimes shape the ecology and evolution of tree species. We used a simple meteorological model (HURRECON) to estimate wind fields from hurricanes in the Western North Atlantic and Eastern North Pacific tropical cyclone basins from storms occurring between 1851 and 2022. We characterize how the intensity and frequency of hurricanes differ among geographically distinct hurricane regimes and define four hurricane regimes for North America (Continental, Inland, Coastal, and Fringe). Along this coastal-to-inland gradient, we found major differences in the frequency and intensity of hurricane wind regimes. The Fringe regime experiences category 1 winds relatively frequently [return period (RP) 25 y], whereas the Inland regime experiences category 1 winds very infrequently (RP ~3,000 y). We discuss how species traits related to tree windfirmness, such as mechanical properties and crown traits, may vary along hurricane regime gradients. Quantitative characterization of forest hurricane regimes provides a critical step for understanding the evolutionary and ecological role of hurricane regimes in wind-prone forests.

Impacts of extreme weather events on microplastic distribution in coastal environments.

Microplastic pollution is a pressing environmental threat to the ecosystem, which can be influenced by varying weather factors. With arising weather extremes in recent years, it is crucial to assess the weather effects on coastal microplastic pollution. In this study, we conducted a year-long baseline survey on beach sediment and surface seawater in Hong Kong, and additional surveys after rainstorm and typhoon events. Our data reveals that microplastic abundance was 5 times higher in wet season over dry season. Yet, the seasonal variation was insignificant when considering only the baseline condition, suggesting the role of extreme weather as the main driver of the seasonal variation in microplastic distribution. Typhoons and rainstorms induced 5.1 to 36.4 times and 1.9 to 11.7 times more microplastics in beach sediment, respectively, and 3.5 to 6.0 times and 2.5 to 4.3 times more microplastics in surface seawater, respectively. The larger microplastic mass in beach sediment and the increased proportion of hard fragments under extreme weather conditions indicate the larger mobility of heavier plastic debris from a wider source. We identified positive correlations between plastic levels and multiple weather factors (including rainfall, wind and tide), suggesting the potential terrestrial inputs of microplastics via surface runoff and wind transport, and the potential redistribution of microplastics from deep to surface sediment via wave agitation. We also identified a strongly positive correlation between macro- and microplastic abundance in beach sediment, suggesting the potential plastic fragmentation under strong wave abrasion, which may intensify the coastal microplastic pollution. This study sheds light on the need for reinforced security of waste management systems to avoid terrestrial plastic inputs under extreme weather forces, as well as the timing of coastal cleanup work in terms of limiting plastic fragmentation and achieving better cleanup efficiency.

A comparative study on source of water masses and nutrient supply in Zhanjiang Bay during the normal summer, rainstorm, and typhoon periods: Insights from dual water isotopes.

Typhoons and rainstorms (rainfall >250 mm day-1) are extreme weather events that seriously impact coastal oceanography and biogeochemical cycles. However, changes in the mixing of water masses and nutrient supply induced by typhoons and rainstorms can hardly be identified and quantified by traditional methods owing to the complex hydrological conditions in coastal waters. In this study, we analysed a comparative data set of dual water isotopes (δD and δ18O), hydrological parameters, nutrients, and chlorophyll-a from three periods (normal summer, rainstorm, and typhoon periods) in Zhanjiang Bay, a typical semi-enclosed mariculture bay in South China, to address this issue. The results revealed a significant increase in contributions from freshwater during rainstorms and typhoons. Correspondingly, nutrient supplies from freshwater during these periods remarkably increased compared to the normal summer, indicating that heavy rainfall can transport substantial amounts of terrestrial nutrients into the bay. Furthermore, disparities in hydrodynamic processes between typhoon and rainstorm periods were notable due to inconsistencies in freshwater diffusion paths. During rainstorms, freshwater primarily diffuses towards the outer bay in the upper layer due to strong stratification and cannot form an ocean front. However, under intense external forces caused by the typhoon, high-salinity water intruded into the bay, and enhancement of vertical mixing disrupted stratification. The massive influx of freshwater column during the typhoon mixed with higher salinity seawater column in the bay led to the formation of an ocean front, which could retain contaminants. This study suggests that although both rainstorms and typhoons can discharge large quantities of terrestrial nutrients into Zhanjiang Bay, the front formed during the typhoon period impedes the contaminant transportation to open sea thereby deteriorating water quality and affecting mariculture activities within the bay.

Influential factors of long-term and seasonal 137Cs change in agricultural and forested rivers: Temperature, water quality and an intense Typhoon Event.

In this study, the effect of temperature, water quality, and the impact of an intense typhoon event on change in 137Cs concentration in the water of agricultural and forested rivers near the Fukushima Daiichi nuclear power plant (Japan) was evaluated using monthly stationary observations obtained under baseflow conditions 2.8-10.6 years after the nuclear accident in 2011. The dissolved 137Cs concentration fluctuated seasonally with water temperature in all rivers, and the increase in dissolved 137Cs concentration for unit increase in temperature was higher in forested rivers than in agricultural rivers. The relationship between water temperature and the apparent distribution coefficient of 137Cs well followed the van 't Hoff equation in the two agricultural rivers, where the enthalpy of reaction was estimated as -15.6 and -19.6 kJ mol-1. The van 't Hoff equation was not well followed for a forested river, where the suspended solids mainly comprised organic matter, suggesting that the dominant process determining dissolved 137Cs concentrations in forested rivers is not only water temperature effect on ion exchange, but rather the input of 137Cs and K+ (competing with 137Cs for exchange sites on mineral particles) into the water phase via litter leaching. Suspended solids concentrations in agricultural rivers correlated negatively with 137Cs concentrations in suspended solids, suggesting an increased proportion of coarse particles or the input of soils with low 137Cs concentration from decontaminated agricultural land. At some sites, 137Cs concentrations in dissolved form and in suspended solids were reduced sharply in association with the passage of Typhoon Hagibis in October 2019, suggesting that Typhoon Hagibis caused large-scale surface erosion that removed the source of 137Cs.

Field Measurements of Wind-Induced Responses of the Shanghai World Financial Center during Super Typhoon Lekima.

In this paper, the wind-induced responses of the Shanghai World Financial Center (SWFC) under Super Typhoon Lekima are measured using the health monitoring system. Based on the measurements, the characteristics of vibration, including probability density distribution of accelerations, power spectra, and mode shapes are studied. The curve method and the standard deviation method are used to analyze the relationship of the first- and second-order natural frequencies and damping ratios with amplitudes and the mean wind speed. The results show the following: (1) The structural wind-induced responses in the X and Y directions have high consistencies, and the vibration signals exhibit a peak state; moreover, response amplitudes and acceleration signals disperse when the floor height increases. (2) The first- and second-order natural frequencies in the X and Y directions decrease with the increasing amplitudes and are negatively correlated with mean wind speed; the maximum decrease in natural frequency is 5.794%. The first- and second-order damping ratios in the X and Y directions increase with the increasing amplitudes and are positively correlated with the mean wind speed; the maximum increase in damping ratio is 95.7%. (3) The curve method and the standard deviation method are similar in identifying dynamic characteristic parameters, but the discreteness of the natural frequencies obtained by the curve method is lesser. (4) Under excitations of various typhoons, the mode shapes of SWFC are basically the same, and the mode shapes in the X and Y directions increase with the height and have nonlinearity.