[Analysis of the Spatiotemporal Distribution of Algal Blooms and Its Driving Factors in Chaohu Lake Based on Multi-source Datasets].

Eutrophication and harmful algae blooms are one of the common ecological and environmental problems faced by freshwater lakes all over the world. As a typical inland freshwater lake, Chaohu Lake exhibits a high level of eutrophication and algae blooms year-round and shows a spatiotemporal difference in different regions of the lake. In order to understand the basic regularity of the development and outbreak of algal blooms in Chaohu Lake, the data from the comprehensive water observation platform and remote sensing were integrated to obtain the spatiotemporal distribution of algal blooms from 2015 to 2020. Then, an evaluation model based on Boosted Regression Trees (BRT) was constructed to quantitatively assess the importance and interactions of various environmental factors on algal blooms at different stages. The results indicated that:① The occurrence of algal blooms in Chaohu Lake exhibited significant seasonal variations, with the cyanobacteria beginning to recover in spring and bring about a light degree of algal blooms in the western and coastal areas of Chaohu Lake. The density of cyanobacteria reached its maximum in summer and autumn, accompanied by moderate and severe degrees of algal bloom outbreaks. ② During the non-outbreak period, the variation in the cyanobacteria density was greatly affected by physical and chemical factors, which explained 80.3% of the variance in the change in cyanobacteria density. The high concentrations of dissolved oxygen content in the water column and the weak alkalinity (7.2-7.6) and appropriate water temperature (about 3℃) provided a favorable environmental condition for the breeding and growth of cyanobacteria. In addition, the onset of algal blooms was closely related to the air temperature steadily passing through the threshold. According to the statistics, the date of first outbreak of algal blooms in Chaohu Lake was 11 days or so after the air temperature steadily remained above 7℃. ③ During the outbreak period, the occurrence of algal blooms was influenced by the combination of cyanobacterial biomass and meteorological conditions such as temperature, wind speed, and sunshine duration. The cumulative contribution ratio of the four factors was as high as 95%, and each factor had an optimal interval conductive to the outbreak of algal blooms. Furthermore, the results of multi-factor interaction analysis indicated a larger probability of the outbreak of algal blooms in Chaohu Lake under the combined effect of high cyanobacteria density, suitable temperature, and the breeze. This study analyzed and revealed the spatiotemporal characteristics and the dominant influencing factors of algal blooms in Chaohu Lake at different stages, which could provide the scientific basis for the prediction, early warning, and disposal of algal blooms under the context of climate change.

Influence of building spatial patterns on wind environment and air pollution dispersion inside an industrial park based on CFD simulation.

The "spatial pattern-wind environment-air pollution" within building clusters is closely interconnected, where different spatial pattern parameters may have varying degrees of impact on the wind environment and pollutant dispersion. Due to the complex spatial structure within industrial parks, this complexity may lead to the accumulation and retention of air pollutants within the parks. Therefore, to alleviate the air pollution situation in industrial parks in China and achieve the circular transformation and construction of parks, this study takes Hefei Circular Economy Demonstration Park as the research object. The microscale Fluent model in computational fluid dynamics (CFD) is used to finely simulate the wind flow field and the diffusion process of pollutants within the park. The study analyzes the triad relationship and influence mechanism of "spatial pattern-wind environment-air pollution" within the park and studies the influence of different spatial pattern parameters on the migration and diffusion of pollutants. The results show a significant negative correlation between the content of pollutants and wind speed inside the industrial park. The better the wind conditions, the higher the air quality. The spatial morphology parameters of the building complex are the main influences on the condition of its internal wind environment. Building coverage ratio and degree of enclosure have a significant negative correlation with wind conditions. Maintaining them near 0.23 and 0.37, respectively, is favorable to the quality of the surrounding environment. Moreover, the average height of the building is positively correlated with the wind environment condition. The rate of transport and dissipation of pollutants gradually increases as the average building height reaches 16 m. Therefore, a reasonable building planning strategy and arrangement layout can effectively improve the wind environment condition inside the park, thus alleviating the pollutant retention situation. The obtained results serve as a theoretical foundation for optimizing morphological structure design within urban industrial parks.

Shifting from techno-economic to socio-ecological priorities: Incorporating landscape preferences and ecosystem services into the siting of renewable energy infrastructure.

This study examines the siting scenarios for renewable energy installations (REI) in a mountainous region of Europe (Switzerland), incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed. The energy target for all scenarios is set at 25 TWh/a, stemming from the energy gap anticipated due to the phase-out of Swiss nuclear reactors by 2050. This target is met using renewable energy infrastructure such as wind, roof-mounted photovoltaic, and ground-mounted photovoltaic systems. By integrating social preferences into the optimization, this study showcases a promising implementation that transcends the software's intended applications. It complements techno-economic approaches and offers alternative decision-making avenues. The conventional "roof first" strategy proved ineffective in preventing extensive land use for the development of new renewable energy infrastructure. Strategies incorporating ground-mounted photovoltaic infrastructure were more spatially, ecologically, and socially efficient than those without. The strategy optimized for energy yield exhibited the highest spatial efficiency but incurred significant ecosystem service costs and, surprisingly, had low social costs. In contrast, the strategy prioritizing ecosystem services was the most efficient in terms of ecosystem service costs but had elevated social costs and was spatially less efficient than other strategies. The strategy optimized for social preferences incurred the lowest social costs and excelled in spatial efficiency and ecosystem service costs. Notably, this strategy employed a limited number of planning units linked to both high ecosystem service and social costs. The findings underscore that incorporating social preferences significantly enhances the evaluation of siting options. This inclusion allows for the social acceptance of investments to be factored into costs, facilitating more informed and inclusive decisions.

Improving new energy subsidy efficiency considering learning effect: A case study on wind power.

Subsidy policies are instrumental in driving the development of new energy. However, the effective allocation of new energy subsidies over time is challenging given fiscal constraints. This study addresses this challenge by considering the learning effect associated with the new energy industry. A two-stage dynamic programming model is proposed to capture the investment decision-making process of companies under new energy subsidy policies and government subsidy setups. Theoretical findings suggest that company investment decisions in new energy are influenced by a guiding principle: The subsidy rate should be negatively correlated with the variation rate of production scale increment (VRPSI). We calibrate this investment decision principle using wind power data from 14 countries. According to this principle, excessive subsidy rates may result in a low VRPSI, thereby diminishing future investment profitability in the new energy industry and leading to subsidy inefficiency. Upon investigating the efficiency of annual subsidy allocation, we find that the subsidy rates were potentially set too high in 2014, 2016, and 2017. Furthermore, the government should exercise caution regarding an inefficient subsidy pattern whereby companies invest in new energy only when the subsidy rate exceeds a certain threshold, neglecting traditional power sources. It is crucial to note that although this study uses wind power industry data for calibration and simulation, the theoretical model can be broadly applied to other new energy industries and emerging industries with increasing marginal net profit.

Enhancing the control of doubly fed induction generators using artificial neural networks in the presence of real wind profiles.

This study tackles the complex task of integrating wind energy systems into the electric grid, facing challenges such as power oscillations and unreliable energy generation due to fluctuating wind speeds. Focused on wind energy conversion systems, particularly those utilizing double-fed induction generators (DFIGs), the research introduces a novel approach to enhance Direct Power Control (DPC) effectiveness. Traditional DPC, while simple, encounters issues like torque ripples and reduced power quality due to a hysteresis controller. In response, the study proposes an innovative DPC method for DFIGs using artificial neural networks (ANNs). Experimental verification shows ANNs effectively addressing issues with the hysteresis controller and switching table. Additionally, the study addresses wind speed variability by employing an artificial neural network to directly control reactive and active power of DFIG, aiming to minimize challenges with varying wind speeds. Results highlight the effectiveness and reliability of the developed intelligent strategy, outperforming traditional methods by reducing current harmonics and improving dynamic response. This research contributes valuable insights into enhancing the performance and reliability of renewable energy systems, advancing solutions for wind energy integration complexities.

Revisiting the contribution of different factors in determining the changes in potential evapotranspiration over China.

In this paper, a daily gridded observation data across China from 1961 to 2022 were used to calculate daily potential evapotranspiration (PET). The observed variables included daily temperature, sunshine hours, average wind speed, and average relative humidity. PET was determined using the Penman-Monteith method recommended by the Food and Agriculture Organization (FAO). The long-term trend of PET was investigated in six regions of China during different seasons. To further compressed the influence of various meteorological factors on the PET trend, the contribution of each meteorological element to the long-term trend of PET was analyzed. The results indicate the following: (1) PET reaches its peak during summer which values from 145 to 640 mm, while it is lowest during winter from 21 to 244 mm. (2) The spatial patterns of PET trend changes are relatively similar across the four seasons, characterized by a decrease in the eastern regions and an increase in the western regions. The reduction is most significant during the summer and the range of trend is from -2.04 to 1.48 mm/day, while the increase becomes more pronounced in the winter which trend is from -0.34 to 0.53 mm/day. (3) The contribution of factors varies significantly across different regions. In spring and autumn, RH and U have little difference in contribution from other factors. But tsun is varies different from regions, the contribution value is largest in the northwest and smallest in the northeast. However, during summer, tsun become the most significant contributor in the YZ and SE regions, while in winter, Tm emerges as the most significant contributor to the PET trend in all six subregions. In SW, the contribution from U2 is the smallest in all seasons, with RH and Tm being the two crucial factors determining the PET trend in this region.

Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step before promoting a significant undertaking. This paper proposes a framework for identifying risks in deep-sea FOWP projects. First, this paper identifies 16 risk criteria and divides them into 5 groups to establish a criteria system. Second, hesitant fuzzy linguistic term set (HFLTS) and triangular fuzzy number (TFN) are utilized to gather and describe the criterion data to ensure the robustness and completeness of the criterion data. Third, extending the method for removal effects of criteria (MEREC) to the HFLTS environment through the conversion of TFNs, under the influence of subjective preference and objective fairness, a weighting method combining analytic network process (ANP) and MEREC is utilized to calculate criteria weights, and the trust relationship and consistency between experts are used to calculate the expert weights to avoid the subjective weighting given by experts arbitrariness. Fourth, the study's findings indicated that the overall risk level of the deep-sea FOWP projects is "medium." Fifth, sensitivity and comparative analyses were conducted to test the reliability of the assessment outcomes. lastly, this research proposes risk management measures for the deep-sea FOWP project's establishment from economic, policy, technology, environment, and management aspects.

Evaluation and optimization of outdoor wind environment in block based on space syntax and CFD simulation.

The wind environment quality at the height of pedestrians can significantly affect the thermal comfort and physical and mental health of pedestrians, promote the diffusion of air pollutants and inhibit the formation of urban heat island effect, and has been paid more and more attention in the field of urban and rural planning. This paper takes Jianlan Road commercial pedestrian Street as an example to maximize the thermal comfort of pedestrians. Based on CFD numerical simulation technology and space syntax theory, the pedestrian wind environment of the accessible space of the block is selected for quantitative research. Through numerical simulation, the influence of block spatial form on the wind environment at pedestrian height under the initial condition of uniform air flow is analyzed, and some suggestions are put forward for the optimization of block spatial form. Finally, the block optimization scheme is verified and simulated. The visualization results show that the wind environment quality of the optimized high-accessibility space is significantly improved, the proportion of comfort zone is increased from 58.2% to 86%, and the static wind rate is reduced from 41.8% to 14%. The wind environment optimization effect is obvious.

Facilitating interaction between partial differential equation-based dynamics and unknown dynamics for regional wind speed prediction.

Regional wind speed prediction is an important spatiotemporal prediction problem which is crucial for optimizing wind power utilization. Nevertheless, the complex dynamics of wind speed pose a formidable challenge to prediction tasks. The evolving dynamics of wind could be governed by underlying physical principles that can be described by partial differential equations (PDE). This study proposes a novel approach called PDE-assisted network (PaNet) for regional wind speed prediction. In PaNet, a new architecture is devised, incorporating both PDE-based dynamics (PDE dynamics) and unknown dynamics. Specifically, this architecture establishes interactions between the two dynamics, regulated by an inter-dynamics communication unit that controls interactions through attention gates. Additionally, recognizing the significance of the initial state for PDE dynamics, an adaptive frequency-gated unit is introduced to generate a suitable initial state for the PDE dynamics by selecting essential frequency components. To evaluate the predictive performance of PaNet, this study conducts comprehensive experiments on two real-world wind speed datasets. The experimental results indicated that the proposed method is superior to other baseline methods.

Operationalizing a fisheries social-ecological system through a Bayesian belief network reveals hotspots for its adaptive capacity in the southern North sea.

Fisheries social-ecological systems (SES) in the North Sea region confront multifaceted challenges stemming from environmental changes, offshore wind farm expansion, and marine protected area establishment. In this paper, we demonstrate the utility of a Bayesian Belief Network (BN) approach in comprehensively capturing and assessing the intricate spatial dynamics within the German plaice-related fisheries SES. The BN integrates ecological, economic, and socio-cultural factors to generate high-resolution maps of profitability and adaptive capacity potential (ACP) as prospective management targets. Our analysis of future scenarios, delineating changes in spatial constraints, economics, and socio-cultural aspects, identifies factors that will exert significant influence on this fisheries SES in the near future. These include the loss of fishing grounds due to the installation of offshore wind farms and marine protected areas, as well as reduced plaice landings due to climate change. The identified ACP hotspots hold the potential to guide the development of localized management strategies and sustainable planning efforts by highlighting the consequences of management decisions. Our findings emphasize the need to consider detailed spatial dynamics of fisheries SES within marine spatial planning (MSP) and illustrate how this information may assist decision-makers and practitioners in area prioritization. We, therefore, propose adopting the concept of fisheries SES within broader integrated management approaches to foster sustainable development of inherently dynamic SES in a rapidly evolving marine environment.

[Wind days in Taranto (Southern Italy): a public health intervention between technical and social contradictions. Lessons learned]. / Wind days a Taranto: un intervento di sanità pubblica tra contraddizioni tecniche e sociali. Lezioni imparate.

Public health interventions in the context of environmental crisis are necessary and desirable for the protection of public health. This manuscript highlights the critical aspects and potentials of a public health intervention by reconstructing the most relevant stages of the case study called 'Precautionary measures during wind days in Taranto'. Under particular weather conditions, the 'wind days' intervention includes prescriptions to companies and recommendations to the public. The latter has been found to be scientifically inconsistent, as highlighted by studies published over the years. The case-study analysis showed that any public health measure must include: a timed evaluation of the measure effectiveness and consider the possibility of its revision; involvement of the population at all stages.

Rainfall as a driver for near-surface turbulence and air-water gas exchange in freshwater aquatic systems.

Gas fluxes from aquatic ecosystems are a significant component of the carbon cycle. Gas exchange across the air-water interface is regulated by near-surface turbulence and can be controlled by different atmospheric forcing conditions, with wind speed and surface buoyancy flux being the most recognized drivers in empirical studies and modeling approaches. The effect of rainfall on near-surface turbulence has rarely been studied and a consistent relationship between rain rate and near-surface turbulence has not yet been established. In this study, we addressed some limitations still present in the quantitative understanding of the effect of rain rate on near-surface turbulence and on the resulting gas transfer velocity in freshwater. We performed controlled laboratory experiments over a wide range of rain rates (7 to 90 mm h-1) and estimated gas transfer velocities from high-resolution measurements of O2 concentration, while rain-induced turbulence was characterized based on particle image velocimetry. We found that the rain-induced dissipation rates of turbulent kinetic energy declined with depth following a consistent power-law relationship. Both energy dissipation rates and gas transfer velocity increased systematically with the rain rate. The results confirm a causal relationship between rainfall, turbulence, and gas exchange. We propose a power-law relationship between near-surface turbulent dissipation rates and rain rate. In combination with surface renewal theory, we derived a direct relationship between gas transfer velocity and rain rate, which can be used to assess the importance of short-term drivers, such as rain events, on gas dynamics and biogeochemical cycling in aquatic ecosystems.

Effect of the modified painless blistering moxibustion with wheat-grain sized moxa cone on cough variant asthma of pathogenic wind attacking the lung: a randomized controlled trial. / æ”¹è‰¯æ— ç—›éº¦ç²’åŒ–è„“ç¸æ²»ç–—é£Žé‚ªçŠ¯è‚ºåž‹å’³å—½å˜å¼‚æ€§å“®å–˜ï¼šéšæœºå¯¹ç §è¯•éªŒ.

OBJECTIVES: To observe the clinical effect of the modified painless blistering moxibustion with wheat-grain sized moxa cone on cough variant asthma (CVA) differentiated as pathogenic wind attacking the lung and explore the influences on eosinophil count (EOS) in the peripheral blood and the content of interleukin-4 (IL-4) and tumor necrosis factor-α (TNF-α) in the serum of patients. METHODS: Ninety-two patients with CVA of pathogenic wind attacking the lung were randomly divided into an observation group and a control group, 46 cases in each group. In the observation group, the modified painless blistering moxibustion with wheat-grain sized moxa cone was applied to the unilateral Feishu (BL 13), Gaohuang (BL 43) and Zusanli (ST 36) in each session of treatment, once every 3 days. In the control group, budesonide and formoterol powder inhaler was delivered, 4.5 µg per inhalation, once every half an hour after breakfast and dinner; one more time of inhalation needed if the symptoms were not well controlled, but less than 6 times of inhalation per day. The duration of treatment was 8 weeks in both groups. Separately, before and after treatment, and during the 1-month follow-up after treatment completion, the score of the symptoms of traditional Chinese medicine (TCM) was observed in the two groups; using the lung function detector, the indexes of pulmonary function (forced expiratory volume in one second [FEV1], FEV1/forced vital capacity [FVC] and peak expiratory flow [PEF]) were determined, and the count of EOS in the peripheral blood and the content of IL-4 and TNF-α in the serum were determined before and after treatment; and the clinical effect was compared between the two groups. RESULTS: After treatment and in follow-up, the TCM symptom scores were decreased compared with those before treatment in the two groups (P<0.05), and the score in the observation group was lower than that of the control group in follow-up (P<0.05). After treatment, FEV1, FEV1/FVC and PEF were increased when compared with those before treatment in the two groups (P<0.05), and the count of EOS in the peripheral blood and the content of IL-4 and TNF-α in the serum were reduced (P<0.05); there was no statistical difference in these indexes between the two groups (P>0.05). After treatment, the total effective rate of the observation group was 95.7% (44/46), which was not different statistically in comparison with the control group (93.5% [43/46], P>0.05). In the follow-up, the total effective rate of the observation group was 95.7% (44/46), which was higher than that of the control group (78.3% [36/46], P<0.05). CONCLUSIONS: The modified painless blistering moxibustion with wheat-grain sized moxa cone may ameliorate the symptoms of CVA of pathogenic wind attacking the lung and improve the pulmonary functions, which is probably related to the regulation of the count of EOS in the peripheral blood and the content of IL-4 and TNF-α in the serum, thereby, reducing the inflammatory response.

[Shelterbelt construction in the scenario of coordinated development of mountain, river, forest, farmland, lake, grassland, and sandy land ecosystems in semi-arid wind-sand areas: Principles and methods]. / 半干旱风沙区"山水林田湖草沙"建设中防护林营建的原理与方法.

We established the systematic concept framework of shelterbelt construction, with "shelterbelts" as the core concern in the construction of integrated ecosystems including mountain, river, forest, farmland, lake, grassland and sandy-land in semi-arid wind-sand areas. In the construction of shelterbelts, it is necessary to adhere to the principles of scientific coordination and systematic management, considering the carrying capacity of water resources, the demand for dust control, the greening and beautification effects, as well as the principle of improving economic benefits. In practice, the construction methods should base on the types and temporal-spatial distribution of shelterbelts, following the shelterbelts construction theory and technology to form different structure and service functions, achieving the functional goals of shelterbelts. By focusing on the key elements including people, forests, grass, fields, water, and sand, we put forward the timeliness, practicality, and scientificity of shelterbelt construction, proposing construction methods for farmland shelterbelts, pastureland shelterbelts, windbreak and sand-fixing forests and protective forest around village (city), which might provide production technical support for the high-quality construction of green ecological barrier in northern China.

[Spatial and temporal distribution characteristics of extreme wind and its effect on wind erosion in Northeast China]. / ä¸œåŒ—åœ°åŒºæžç«¯å¤§é£Žæ—¶ç©ºåˆ†å¸ƒç‰¹å¾åŠå ¶å¯¹é£Žèš€é‡çš„å½±å“.

Under the background of climate change, extreme wind events occur frequently in Northeast China, and the soil erosion caused by these extreme wind events has attracted progressively more attention from scholars. We used the methods of linear analysis, Sen+Mann-Kendal trend analysis, and Kriging interpolation to analyze the spatial and temporal characteristics of extreme wind in Northeast China from 2005 to 2020, and used the RWEQ wind erosion estimation model to calculate the annual soil wind erosion of typical wind erosion sites and wind erosion under extreme wind conditions. The results showed that the extreme wind frequency in Northeast China presented a significant upward trend from 2005 to 2020, with an increase of 2.9 times·a-1. The annual average extreme wind frequency in Northeast China ranged from 1 to 49 times·a-1, and the high frequency areas were distributed in the northwest of Xilin Gol, the west of the Hulunbuir Plateau, and the northeast of Changbai Mountain. The average contribution rate of extreme wind to soil wind erosion in four typical sites (Xilinhot, New Barhu Right Banner, Nenjiang, and Tongyu) was 31%.

Research on distributionally robust energy storage capacity allocation for output fluctuations in high permeability wind and solar distribution networks.

This paper presents a novel approach to addressing the challenges associated with energy storage capacity allocation in high-permeability wind and solar distribution networks. The proposed method is a two-phase distributed robust energy storage capacity allocation method, which aims to regulate the stochasticity and volatility of net energy output. Firstly, an energy storage capacity allocation model is established, which considers energy storage's investment and operation costs to minimize the total cost. Then, a two-stage distributed robust energy storage capacity allocation model is established with the confidence set of uncertainty probability distribution constrained by 1-norm and ∞-norm. Finally, a Column and Constraint Generation (C&CG) algorithm is used to solve the problem. The validity of the proposed energy storage capacity allocation model is confirmed by examining different wind and solar penetration levels. Furthermore, the model's superiority is demonstrated by comparing it with deterministic and robust models.

Land Resources for Wind Energy Development Requires Regionalized Characterizations.

Estimates of the land area occupied by wind energy differ by orders of magnitude due to data scarcity and inconsistent methodology. We developed a method that combines machine learning-based imagery analysis and geographic information systems and examined the land area of 318 wind farms (15,871 turbines) in the U.S. portion of the Western Interconnection. We found that prior land use and human modification in the project area are critical for land-use efficiency and land transformation of wind projects. Projects developed in areas with little human modification have a land-use efficiency of 63.8 ± 8.9 W/m2 (mean ±95% confidence interval) and a land transformation of 0.24 ± 0.07 m2/MWh, while values for projects in areas with high human modification are 447 ± 49.4 W/m2 and 0.05 ± 0.01 m2/MWh, respectively. We show that land resources for wind can be quantified consistently with our replicable method, a method that obviates >99% of the workload using machine learning. To quantify the peripheral impact of a turbine, buffered geometry can be used as a proxy for measuring land resources and metrics when a large enough impact radius is assumed (e.g., >4 times the rotor diameter). Our analysis provides a necessary first step toward regionalized impact assessment and improved comparisons of energy alternatives.

What is China's efficient power generation portfolio under carbon neutrality target? An empirical analysis considering flexibility and system cost.

Variable renewable energy (VRE) is the most promising form of primary generation under a carbon neutrality target due to its environmental benefits, incentive policy, and technological progress. However, the increasing proportion of VRE generation, such as solar and wind power, has sharply increased integration cost and reduced power grid stability. This study uses portfolio theory to investigate China's optimal power generation portfolio by 2050 considering flexibility constraint and system cost, including technical and integration costs. The results demonstrate that non-fossil-fuel power generation technologies have cost and emission reduction advantages over fossil-fuel-based technologies. VRE generation technologies must be developed in synergy with other forms of power generation when considering flexibility requirement and integration cost. A complete phase-out of fossil-fuel power generation technologies in China appears unlikely in the study period. Gas-fired and coal-fired power generation are the pillar forms of power generation to meet future flexibility needs.

Six-dimensional force/torque sensor for aerodynamic characteristic study of high-speed train with different wind angles under stationary tornado.

Researchers conducted an investigation by tornado simulator to study the impact of wind angle on the aerodynamic characteristics of a reduced (1:150) high-speed train model using six-dimensional force/torque sensor. The reduced scale model size can match the relative size relationship between high-speed train and tornado vortex core in real condition. Results show that the wind angle affects the mean value and standard deviation of the force and moment coefficient of the high-speed train at the same radial position. The variations of the mean value and standard deviation of the pitching moment coefficient of the high-speed train carriage model at 60°and 90°are different from that at other wind angles. The variations of the mean value of the pitching moment coefficient of the high-speed train head model at 0°, 15°and 30°are different from that at other wind angles. The variations of the standard deviation of the pitching moment coefficient of the high-speed train head model at 60°,75°and 90°are different from that at other wind angles. This research will help the further study of the operation safety of high-speed train in the event of a tornado impacting a high-speed train network.

Hurricane season hindsight 2020: Applying the IDEA model toward local tropical cyclone forecasts.

Hurricane Laura began as a disorganized tropical depression in August 2020. Early forecast guidance showed that the tropical cyclone could either completely dissipate or strengthen to a major hurricane as it approached the United States Gulf Coast. While this uncertainty was known by meteorologists, it was not necessarily communicated to the public in a direct manner. As it turned out, the worst-case scenario was the correct one. The tropical depression rapidly intensified and made landfall near Cameron, Louisiana, with sustained winds of 150 mph, making Laura a Category 4 hurricane on the Saffir-Simpson scale. Laura's rapid intensification caught some people off guard. Ideally, weather forecasts would have begun warning Louisiana residents to prepare for the possibility of a devastating hurricane in the early stages of tropical cyclone development. No one is suggesting that meteorologists did anything wrong. However, with the benefit of hindsight and decades of scholarly research in risk communication, we can speculate how an ideal forecast would have been written. This paper demonstrates that there are some simple considerations that could be made that might better alert the public to future hurricane worst-case scenarios, even in uncertain situations.