Recent Enhancement in Co-Variability of the Western North Pacific Summer Monsoon and the Equatorial Zonal Wind

The western North Pacific summer monsoon(WNPSM)is an important subcomponent of the Asian summer monsoon.The equatorial zonal wind(EZW)in the lower troposphere over the western Pacific may play a critical role in the evolution of the El Niño-Southern Oscillation(ENSO).The possible linkage between the EZW over the western Pacific and the offequatorial monsoonal winds associated with the WNPSM and its decadal changes have not yet been fully understood.Here,we find a non-stationary relationship between the WNPSM and the western Pacific EZW,significantly strengthening their correlation around the late 1980s/early 1990s.This observed shift in the WNPSM–EZW relationship could be explained by the changes in the related sea surface temperature(SST)configurations across the tropical oceans.The enhanced influence from the springtime tropical North Atlantic,summertime tropical central Pacific,and maritime continent SST anomalies may be working together in contributing to the recent intensified WNPSM–EZW co-variability.The observed recent strengthening of the WNPSM–EZW relationship may profoundly impact the climate system,including prompting more effective feedback from the WNPSM on subsequent ENSO evolution and bolstering a stronger biennial tendency of the WNPSM–ENSO coupled system.The results obtained herein imply that the WNPSM,EZW,ENSO,and the tropical North Atlantic SST may be closely linked within a unified climate system with a quasi-biennial rhythm occurring during recent decades,accompanied by a reinforcement of the WNPSM–ENSO interplay quite possibly triggered by enhanced tropical Pacific–Atlantic cross-basin interactions.These results highlight the importance of the tropical Atlantic cross-basin influences in shaping the spatial structure of WNPSM-related wind anomalies and the WNPSM–ENSO interaction.

Solar wind ion charge state distributions and compound cross sections for solar wind charge exchange X-ray emission

Solar Wind Charge eXchange X-ray(SWCX) emission in the heliosphere and Ea rth’s exosphere is a hard to avoid signal in soft Xray obse rvations of astrophysical targets.On the other hand,the X-ray imaging possibilities offered by the SWCX process has led to an increasing number of future dedicated space missions for investigating the solar wind-terrestrial inte ractions and magnetospheric interfaces.In both cases,accurate modelling of the SWCX emission is key to correctly interpret its signal,and remove it from obse rvations,when needed.In this paper,we compile solar wind abundance measurements from ACE for different solar wind types,and atomic data from literature,including charge exchange cross-sections and emission probabilities,used fo r calculating the compound cross-section a for the SWCX X-ray emission.We calculate a values for charge-exchange with H and He,relevant to soft X-ray energy bands(0.1-2.0 keV)for various solar wind types and solar cycle conditions.

U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies

El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been developed to simulate and predict it.In some simplified coupled ocean-atmosphere models,the relationship between sea surface temperature(SST)anomalies and wind stress(τ)anomalies can be constructed by statistical methods,such as singular value decomposition(SVD).In recent years,the applications of artificial intelligence(AI)to climate modeling have shown promising prospects,and the integrations of AI-based models with dynamical models are active areas of research.This study constructs U-Net models for representing the relationship between SSTAs andτanomalies in the tropical Pacific;the UNet-derivedτmodel,denoted asτUNet,is then used to replace the original SVD-basedτmodel of an intermediate coupled model(ICM),forming a newly AI-integrated ICM,referred to as ICM-UNet.The simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial Pacific.In the ocean-only case study,theτUNet-derived wind stress anomaly fields are used to force the ocean component of the ICM,the results of which also indicate reasonable simulations of typical ENSO events.These results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling studies.Furthermore,the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies.

Two methods for separating the magnetospheric solar wind charge exchange soft X-ray emission from the diffuse X-ray background

Solar wind charge exchange(SWCX)is the process of solar wind high-valence ions exchanging charges with neutral components and generating soft X-rays.Recently,detecting the SWCX emission from the magnetosphere is proposed as a new technique to study the magnetosphere using panoramic soft X-ray imaging.To better prepare for the data analysis of upcoming magnetospheric soft X-ray imaging missions,this paper compares the magnetospheric SWCX emission obtained by two methods in an XMM-Newton observation,during which the solar wind changed dramatically.The two methods differ in the data used to fit the diffuse X-ray background(DXB)parameters in spectral analysis.The method adding data from the ROSAT All-Sky Survey(RASS)is called the RASS method.The method using the quiet observation data is called the Quiet method,where quiet observations usually refer to observations made by the same satellite with the same target but under weaker solar wind conditions.Results show that the spectral compositions of magnetospheric SWCX emission obtained by the two methods are very similar,and the changes in intensity over time are highly consistent,although the intensity obtained by the RASS method is about 2.68±0.56 keV cm^(-2)s^(-1)sr^(-1)higher than that obtained by the Quiet method.Since the DXB intensity obtained by the RASS method is about 2.84±0.74 keV cm^(-2)s^(-1)sr^(-1)lower than that obtained by the Quiet method,and the linear correlation coefficient between the difference of SWCX and DXB obtained by the two methods in diffe rent energy band is close to-1,the diffe rences in magnetospheric SWCX can be fully attributed to the diffe rences in the fitted DXB.The difference between the two methods is most significant when the energy is less than 0.7 keV,which is also the main energy band of SWCX emission.In addition,the difference between the two methods is not related to the SWCX intensity and,to some extent,to solar wind conditions,because SWCX intensity typically va ries with the solar wind.In summary,both methods are robust and reliable,and should be considered based on the best available options.

A nonlinear wake model of a wind turbine considering the yaw wake steering

Duo to fluctuations in atmospheric turbulence and yaw control strategies,wind turbines are often in a yaw state.To predict the far wake velocity field of wind turbines quickly and accurately,a wake velocity model was derived based on the method of momentum conservation considering the wake steering of the wind turbine under yaw conditions.To consider the shear effect of the vertical incoming wind direction,a two-dimensional Gaussian distribution function was introduced to model the velocity loss at different axial positions in the far wake region based on the assumption of nonlinear wake expansion.This work also developed a“prediction-correction”method to solve the wake velocity field,and the accuracy of the model results was verified in wake experiments on the Garrad Hassan wind turbine.Moreover,a 33-kW two-blade horizontal axis wind turbine was simulated using this method,and the results were compared with the classical wake model under the same parameters and the computational fluid dynamics(CFD)simulation results.The results show that the nonlinear wake model well reflected the influence of incoming flow shear and yaw wake steering in the wake velocity field.Finally,computation of the wake flow for the Horns Rev offshore wind farm with 80 wind turbines showed an error within 8%compared to the experimental values.The established wake model is less computationally intensive than other methods,has a faster calculation speed,and can be used for engineering calculations of the wake velocity in the far wakefield of wind turbines.

Comparison and Verification of Coherent Doppler Wind Lidar and Radiosonde Data in the Beijing Urban Area

As a new type of wind field detection equipment, coherent Doppler wind lidar(CDWL) still needs more relevant observation experiments to compare and verify whether it can achieve the accuracy and precision of traditional observation equipment in urban areas. In this experiment, a self-developed CDWL provided four months of observations in the southern Beijing area. After the data acquisition time and height match, the wind profile data obtained based on a Doppler beam swinging(DBS) five-beam inversion algorithm were compared with radiosonde data released from the same location. The standard deviation(SD) of wind speed is 0.8 m s^(–1), and the coefficient of determination R~2 is 0.95. The SD of the wind direction is 17.7° with an R~2 of 0.96. Below the height of the roughness sublayer(about 400 m), the error in wind speed and wind direction is significantly greater than the error above the height of the boundary layer(about 1500 m). For the case of wind speeds less than 4 m s^(–1), the error of wind direction is more significant and is affected by the distribution of surrounding buildings. Averaging at different height levels using suitable time windows can effectively reduce the effects of turbulence and thus reduce the error caused by the different measurement methods of the two devices.

Near-surface wind field characteristics of the desert-oasis transition zone in Dunhuang,China

The desert-oasis transition zone(DOTZ)serves as a buffer area between the desert and oasis.Understanding its wind field characteristics is of great significance for the prevention and control of aeolian disasters in the oasis.In this study,we used meteorological data during 2013–2019 from the portable meteorological stations at five sites(site A on the edge of the oasis,sites B,C,and D in the DOTZ,and site O in the desert)in Dunhuang,China to analyze the near-surface wind field characteristics and their causes,as well as to reveal the key role of the DOTZ in oasis protection.The results showed that the mean wind speed,frequency of sand-driving wind,and directional variability of wind decreased from west to east within the DOTZ,and wind speed was significantly affected by air temperature.The terrain influenced the prevailing winds in the region,mainly from northeast and southwest.Only some areas adjacent to the oasis were controlled by southeasterly wind.This indicated that the near-surface wind field characteristics of the DOTZ were caused by the combined effects of local terrain and surface hydrothermal difference.At site D,the annual drift potential(DP)was 24.95 vector units(VU),indicating a low wind energy environment,and the resultant drift direction(RDD)showed obvious seasonal differences.Additionally,the DOTZ played an important buffering role between the desert and oasis.Compared with the desert,the mean wind speed in the oasis decreased by 64.98%,and the prevailing wind direction was more concentrated.The results of this study will be useful in interpreting the aeolian activity of the DOTZ in Dunhuang.

Effects of wind speed,underlying surface,and seed morphological traits on the secondary seed dispersal in the Tengger Desert,China

The maintenance of sand-fixing vegetation is important for the stability of artificial sand-fixing systems in which seed dispersal plays a key role.Based on field wind tunnel experiments using 11 common plant species on the southeastern edge of the Tengger Desert,China,we studied the secondary seed dispersal in the fixed and semi-fixed sand dunes as well as in the mobile dunes in order to understand the limitations of vegetation regeneration and the maintenance of its stability.Our results indicated that there were significant variations among the selected 11 plant species in the threshold of wind speed(TWS).The TWS of Caragana korshinskii was the highest among the 11 plant species,whereas that of Echinops gmelinii was the lowest.Seed morphological traits and underlying surface could generally explain the TWS.During the secondary seed dispersal processes,the proportions of seeds that did not disperse(no dispersal)and only dispersed over short distance(short-distance dispersal within the wind tunnel test section)were significantly higher than those of seeds that were buried(including lost seeds)and dispersed over long distance(long-distance dispersal beyond the wind tunnel test section).Compared with other habitats,the mobile dunes were the most difficult places for secondary seed dispersal.Buried seeds were the easiest to be found in the semi-fixed sand dunes,whereas fixed sand dunes were the best sites for seeds that dispersed over long distance.The results of linear mixed models showed that after controlling the dispersal distance,smaller and rounder seeds dispersed farther.Shape index and wind speed were the two significant influencing factors on the burial of seeds.The explanatory power of wind speed,underlying surface,and seed morphological traits on the seeds that did not disperse and dispersed over short distance was far greater than that on the seeds that were buried and dispersed over long distance,implying that the processes and mechanisms of burial and long-distance dispersal are more complex.In summary,most seeds in the study area either did not move,were buried,or dispersed over short distance,promoting local vegetation regeneration.

Variational Reconstruction and Simulation Experiments of Sea Surface Wind Field for Ocean Data Buoy

The sea surface wind field is an important physical parameter in oceanography and meteorology.With the continuous refinement of numerical weather prediction,air-sea interface materials,energy exchange,and other studies,three-dimensional(3D)wind field distribution at local locations on the sea surface must be measured accurately.The current in-situ observation of sea surface wind parameters is mainly achieved through the installation of wind sensors on ocean data buoys.However,the results obtained from this single-point measurement method cannot reflect wind field distribution in a vertical direction above the sea surface.Thus,the present paper proposes a theoretical framework for the optimal inversion of the 3D wind field structure variation in the area where the buoy is located.The variation analysis method is first used to reconstruct the wind field distribution at different heights of the buoy,after which theoretical analysis verification and numerical simulation experiments are conducted.The results indicate that the use of variational methods to reconstruct 3D wind fields is significantly effective in eliminating disturbance errors in observations,which also verifies the correctness of the theoretical analysis of this method.The findings of this article can provide a reference for the layout optimization design of wind measuring instruments in buoy observation systems and also provide theoretical guidance for the design of new observation buoys in the future.

A call for enhanced data-driven insights into wind energy flow physics

With the increased availability of experimental measurements aiming at probing wind resources and wind turbine operations,machine learning(ML)models are poised to advance our understanding of the physics underpinning the interaction between the atmospheric boundary layer and wind turbine arrays,the generated wakes and their interactions,and wind energy harvesting.However,the majority of the existing ML models for predicting wind turbine wakes merely recreate Computational fluid dynamics(CFD)simulated data with analogous accuracy but reduced computational costs,thus providing surrogate models rather than enhanced data-enabled physics insights.Although ML-based surrogate models are useful to overcome current limitations associated with the high computational costs of CFD models,using ML to unveil processes from experimental data or enhance modeling capabilities is deemed a potential research direction to pursue.In this letter,we discuss recent achievements in the realm of ML modeling of wind turbine wakes and operations,along with new promising research strategies.

Protective benefits of HDPE board sand fences in an environment with variable wind directions on Gobi surfaces:wind tunnel study

The Golmud-Korla Railway in the Gobi area faces operational challenges due to sand hazards,caused by strong and variable winds.This study addresses these challenges by conducting wind tunnel tests to evaluate the protective benefits of High Density Polyethylene(HDPE)board sand fences,focusing on their orientation relative to various wind directions(referred to as'wind angle').This study found that the size of the low-velocity zone on the leeward side of the sand fences(LSF)expanded with an increase in the wind angle(WA).At 1H(the height of the sand fence)and 2H positions on the LSF,the wind speed profiles(WSP)exhibited a segmented logarithmic growth,constrained by Z=H at varying WAs.The efficacy of the sand fence in obstructing airflow escalated as WA increased.The size of the WA has a significant impact on the protective efficiency of HDPE board sand fences.Furthermore,compared to typical sandy surfaces,the rate of sand transport across the Gobi surface diminishes more slowly with height,attributed to the gravel's rebound effect.This phenomenon allows some sand particles to bypass the fences,rendering them less effective at blocking wind and trapping sand than in sandy environments.This paper offers scientific evidence supporting the practical use and enhancement of HDPE board sand fences in varied wind conditions.

Research on Leading Edge Erosion and Aerodynamic Characteristics of Wind Turbine Blade Airfoil

The effects of the erosion present on the leading edge of a wind turbine airfoil(DU 96-W-180)on its aerodynamic performances have been investigated numerically in the framework of a SST k–ωturbulence model based on the Reynolds Averaged Navier-Stokes equations(RANS).The results indicate that when sand-induced holes and small pits are involved as leading edge wear features,they have a minimal influence on the lift and drag coefficients of the airfoil.However,if delamination occurs in the same airfoil region,it significantly impacts the lift and resistance characteristics of the airfoil.Specifically,as the angle of attack grows,there is a significant decrease in the lift coefficient accompanied by a sharp increase in the drag coefficient.As wear intensifies,these effects gradually increase.Moreover,the leading edge wear can exacerbate flow separation near the trailing edge suction surface of the airfoil and cause forward displacement of the separation point.

Modeling Analysis of Factors Influencing Wind-Borne Seed Dispersal: A Case Study on Dandelion

A weed is a plant that thrives in areas of human disturbance, such as gardens, fields, pastures, waysides, and waste places where it is not intentionally cultivated. Dispersal affects community dynamics and vegetation response to global change. The process of seed disposal is influenced by wind, which plays a crucial role in determining the distance and probability of seed dispersal. Existing models of seed dispersal consider wind direction but fail to incorporate wind intensity. In this paper, a novel seed disposal model was proposed in this paper, incorporating wind intensity based on relevant references. According to various climatic conditions, including temperate, arid, and tropical regions, three specific regions were selected to establish a wind dispersal model that accurately reflects the density function distribution of dispersal distance. Additionally, dandelions growth is influenced by a multitude of factors, encompassing temperature, humidity, climate, and various environmental variables that necessitate meticulous consideration. Based on Factor Analysis model, which completely considers temperature, precipitation, solar radiation, wind, and land carrying capacity, a conclusion is presented, indicating that the growth of seeds is primarily influenced by plant attributes and climate conditions, with the former exerting a relatively stronger impact. Subsequently, the remaining two plants were chosen based on seed weight, yielding consistent conclusion.

Assessment of the Physical Capabilities of Heart Failure Patients before and after Cardiovascular Rehabilitation: A Study of 125 Patients from West Africa, Dakar, Senegal

Background: Cardiac rehabilitation represents a critical therapeutic strategy for patients suffering from chronic heart failure. The physical capacity of patients with heart failure, assessed using the exercise test and the 6-minute walk test, is the measure of the patient’s overall functional ability to perform physical activities and tolerate exercise loads. The objective of this study was to assess the impact of cardiac rehabilitation on patients’ physical capabilities and to conduct a thorough comparison of data obtained via exercise testing and the 6-minute walk test before and after the rehabilitation programme. Methods: This was a descriptive and analytical cross-sectional study, conducted from 1 February 2021 to 31 June 2022. Included were heart failure patients who had participated in an outpatient cardiovascular rehabilitation programme. The collected data included anamnestic, clinical, paraclinical data, and the 6-minute walk test. Informed consent was obtained. Data analysis, word processing, and charting were performed using Microsoft Word 2016, Excel 2013, and Sphinx version 5.1.0.2. Data analysis was performed using SPSS (Statistical Package for Social Sciences) version 24.0. Any difference less than 0.05 was considered statistically significant. Results: In a Senegalese study, heart failure patients undergoing rehabilitation in a cardiac unit represented 45.59% of all cases, with a prevalence rate of 3.21%. The average participant was 57.97 years old, with those aged 61 to 70 forming the largest group (35.5%). The study noted a male predominance (sex ratio of 2.1) and identified dyslipidaemia (80.6%) and sedentarism (71%), as prevalent cardiovascular risk factors. All participants initially suffered from NYHA stage 2 or 3 dyspnoea, yet 80.65% showed no symptoms following rehabilitation. Significant improvements were recorded in resting heart rate (from 79 to 67 bpm), and the 6-minute walk test distance (from 328 m to 470 m). Enhanced exercise tolerance and walking test outcomes were particularly notable in patients with LVEF ≥ 50%, women, non-obese individuals, those initially walking less than 300 m, achieving more than 3 METs, and non-smokers. Conclusion: The findings underscore the effectiveness of cardiovascular rehabilitation in improving symptoms, physical capability, and overall quality of life for heart failure patients in Senegal.

Retraction:Optimized Design of Bio-inspired Wind Turbine Blades

The published article titled“Optimized Design of Bio-inspired Wind Turbine Blades”has been retracted from Fluid Dynamics&Materials Processing.

Westerlies Affecting the Seasonal Variation of Water Vapor Transport over the Tibetan Plateau Induced by Tropical Cyclones in the Bay of Bengal

This study investigates the activity of tropical cyclones(TCs)in the Bay of Bengal(BOB)from 1979 to 2018 to discover the mechanism affecting the contribution rate to the meridional moisture budget anomaly(MMBA)over the southern boundary of the Tibetan Plateau(SBTP).May and October–December are the bimodal phases of BOB TC frequency,which decreases month by month from October to December and is relatively low in May.However,the contribution rate to the MMBA is the highest in May.The seasonal variation in the meridional position of the westerlies is the key factor affecting the contribution rate.The relatively southern(northern)position of the westerlies in November and December(May)results in a lower(higher)contribution rate to the MMBA.This mechanism is confirmed by the momentum equation.When water vapor enters the westerlies near the trough line,the resultant meridional acceleration is directed north.It follows that the farther north the trough is,and the farther north the water vapor can be transported.When water vapor enters the westerlies from the area near the ridge line,for Type-T(Type-R)TCs,water vapor enters the westerlies downstream of the trough(ridge).Consequently,the direction of the resultant meridional acceleration is directed south and the resultant zonal acceleration is directed east(west),which is not conducive to the northward transport of water vapor.This is especially the case if the trough or ridge is relatively south,as the water vapor may not cross the SBTP.

Optimal Scheduling Strategy of Source-Load-Storage Based onWind Power Absorption Benefit

In recent years,the proportion of installed wind power in the three north regions where wind power bases are concentrated is increasing,but the peak regulation capacity of the power grid in the three north regions of China is limited,resulting in insufficient local wind power consumption capacity.Therefore,this paper proposes a two-layer optimal scheduling strategy based on wind power consumption benefits to improve the power grid’s wind power consumption capacity.The objective of the uppermodel is tominimize the peak-valley difference of the systemload,which ismainly to optimize the system load by using the demand response resources,and to reduce the peak-valley difference of the system load to improve the peak load regulation capacity of the grid.The lower scheduling model is aimed at maximizing the system operation benefit,and the scheduling model is selected based on the rolling schedulingmethod.The load-side schedulingmodel needs to reallocate the absorbed wind power according to the response speed,absorption benefit,and curtailment penalty cost of the two DR dispatching resources.Finally,the measured data of a power grid are simulated by MATLAB,and the results show that:the proposed strategy can improve the power grid’s wind power consumption capacity and get a large wind power consumption benefit.

Rare-earth Magnet Free Flux-switching Generator for Wind Turbines in Micro-grids:A Review

In traditional electricity generation plants,large powerful synchronous,induction,and direct current generators were used.With the proliferation of microgrids focused on electricity generation from renewable energy sources in today’s power grids,studies have been conducted on different types of generators.Instead of the traditional generator architecture,generators with brushless structures,particularly those utilizing magnets for excitation,have found broad applications.Fluxswitching generators(FSGs)are innovative types owing to their robust structure,active stator design,and high power density capabilities.However,designs have typically relied on rare-earth element magnets.Rare-earth magnets possess negative characteristics such as price uncertainty,the potential risk of scarcity in the future,and limited geographical production,leading to research on FSGs that do not depend on rare-earth magnets.This study comprehensively examines FSGs that do not use rare-earth element magnets.The study delves into the usage areas,operational mechanisms,structural diversities,and counterparts in the literature of these generators.

A Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning for Offshore Wind Farm Scenarios

This research is the first application of Unmanned Aerial Vehicles(UAVs)equipped with Multi-access Edge Computing(MEC)servers to offshore wind farms,providing a new task offloading solution to address the challenge of scarce edge servers in offshore wind farms.The proposed strategy is to offload the computational tasks in this scenario to other MEC servers and compute them proportionally,which effectively reduces the computational pressure on local MEC servers when wind turbine data are abnormal.Finally,the task offloading problem is modeled as a multi-intelligent deep reinforcement learning problem,and a task offloading model based on MultiAgent Deep Reinforcement Learning(MADRL)is established.The Adaptive Genetic Algorithm(AGA)is used to explore the action space of the Deep Deterministic Policy Gradient(DDPG),which effectively solves the problem of slow convergence of the DDPG algorithm in the high-dimensional action space.The simulation results show that the proposed algorithm,AGA-DDPG,saves approximately 61.8%,55%,21%,and 33%of the overall overhead compared to local MEC,random offloading,TD3,and DDPG,respectively.The proposed strategy is potentially important for improving real-time monitoring,big data analysis,and predictive maintenance of offshore wind farm operation and maintenance systems.

Optimized Design of Bio-Inspired Wind Turbine Blades

To enhance the aerodynamic performance of wind turbine blades,this study proposes the adoption of a bionic airfoil inspired by the aerodynamic shape of an eagle.Based on the blade element theory,a non-uniform extraction method of blade elements is employed for the optimization design of the considered wind turbine blades.Moreover,Computational Fluid Dynamics(CFD)is used to determine the aerodynamic performances of the eagle airfoil and a NACA2412 airfoil,thereby demonstrating the superior aerodynamic performance of the former.Finally,a mathematical model for optimizing the design of wind turbine blades is introduced and a comparative analysis is conducted with respect to the aerodynamic performances of blades designed using a uniform extraction approach.It is found that the blades designed using non-uniform extraction exhibit better aerodynamic performance.