Average Wind Research Articles

Seasonality in synthetic average wind speed

There is a growing demand for computer-generated realistic high-fidelity wind speed data for various applications in the wind industry. Such data should capture the non-stationary dynamics of real-world wind time series, as well as be consistent with the statistical descriptors – the probability density function and power spectral density – of the observed wind speed. However, complying with the statistical descriptors is not a guarantee that the seasonality will be correctly reproduced in synthetic data. The seasonality, characterized by the average diurnal and seasonal variations, is driven by the periodicities embedded in diurnal and annual harmonic series respectively. Those periodicities are determined by the long-term orbital forcing components, which establish the insolation for a given latitude and longitude. We show that average diurnal and seasonal variations can be visualized as the output of comb filters, whose fundamental frequencies match the diurnal and annual fundamental frequency respectively. The aforementioned theoretical findings are readily reproduced in synthetic wind speed, generated by a non-parametric data-driven statistical model, based on the phase-randomized Fourier transform. The model, tested on both 10-min and 1-min resolution real-world datasets, yields average non-stationarities in synthetic wind speed with the accuracy close to the computing precision.

Dynamics of resin yield in Pinus brutia: A quantitative analysis using bark streak tapping

The sustainable harvesting of resin yield from forests plays a crucial role in providing valuable renewable resources. Specifically, Pinus brutia forests in Türkiye are significant for their oleoresin, utilized in various industries. Yet, understanding how dendrometric and meteorological factors influence resin yield is essential for optimizing production while ensuring forest sustainability. This study aimed to estimate oleoresin yield in Pinus brutia plantations using dendrometric parameters (such as diameter at breast height and tree height, basal area, volume and canopy closure) and meteorological parameters (including monthly; minimum, maximum, and average temperature, precipitation, humidity, vapor pressure, and wind speed), to identify the key factors affecting resin production. Resin was collected from 389 Pinus brutia trees of varying diameters across 27 different plots using the bark streak tapping method, with data recorded every 15 days over a year. Weighted Leased Square regression analysis was conducted to explore the relationship between resin yield and the aforementioned dendrometric and meteorological parameters. The analysis revealed that diameter at breast height, monthly average temperature, wind speed, and precipitation significantly influence resin yield. The study underscores the intricate interplay between these factors and resin production, indicating that larger diameters and specific meteorological conditions—especially average temperature, wind speed, and precipitation—are positively correlated with increased resin output. The findings suggest that sustainable resin extraction practices in Pinus brutia forests should account for not only the physical characteristics of the trees but also the local meteorological conditions to maximize yield without compromising forest health. This research contributes to the development of more effective guidelines for oleoresin harvesting, ensuring both economic viability and ecological preservation.

Locational Variance in Nuclear Microreactor Performance Under Net Zero Microgrid Conditions

Microreactors are expected to be deployed in locations or situations where standard macrogrid electricity is not readily or reliably available. Locations such as remote mining communities, military installations, and other similar communities may seek to decarbonize their electricity with a microreactor. Traditional remote communities typically pay much higher energy prices than nonremote communities, so there may be a higher degree of support for microreactors despite higher expected (per unit capacity) capital costs. There is also interest in deploying microreactors on sites that utilize their own microgrids, for example, federal installations or universities, in different locations across the United States. To model the deployment prospects of microreactors on microgrids, HOMER Pro was utilized to generate optimized microgrid configurations under an assumption of net zero, i.e. with no fossil fuels permitted. The economic performance of microreactors on microgrids was analyzed in a variety of locations throughout the United States. It was found that the minimal capital cost required for entry of a microreactor into the system was significantly higher in locations with both low solar resource (less than ~4.5kW∙h/m2∙day−1) and (in particular) low wind (<5 m/s average wind velocity at 80-m hub height), roughly corresponding to locations somewhat inland in both the eastern and the western United States. Under the financial assumptions made in this study, depending on location, the capital cost at which microreactors could enter the system varied from around $24 000/kW(electric) in areas of high wind and/or solar resource to over $90 000/kW(electric) in Alaska, with a range of intermediate results. It was found that the minimum allowed power level of the microreactor did not have a substantial impact on results. A utility presence was found to have a major impact on the financial performance of a microreactor, especially in locations that have strong renewable resources.

About Height of the Surface Air Layer by Sodar Data

Average empirical estimations of the surface air layer height in Moscow have been received by the data of long-term acoustic remote sensing of the atmosphere using MODOS Doppler sodar of METEK (Germany) production. Based on the assumption that the average conditions are close to neutral stratification, this height, as the top of the quasi-linear section of the average long-term wind velocity profile in semi-logarithmic coordinates, is 40–60 m. The wind rotation height, i. e. the height of intersection of day and night wind profiles is on average 95 meters per year. The roughness length in conditions of loose but high urban development in vicinity of Moscow State University in Moscow is 5 m. According to the criterion of the constant wind direction in the surface air layer, its height appears in the average monthly wind direction profiles over the “dead zone” of the sodar (40 m) in approximately one case out of three and usually amounts to 60 m, less often 80 or 100 m. In the rest cases, it is apparently masked by “dead zone”. The average height of the surface layer according to this approach is probably a little less than 50 m, which is close to the estimate obtained from the logarithmic distribution of wind velocity with height in this layer. The daily course of the surface air layer height is noted by the largest values in the afternoon (80–100 m in summer under conditions of prevailing unstable stratification and 60–80 m in winter) and the smallest ones (less than 40 m) in the late evening and at night in summer and from evening to noon in winter.

Turbulent Exchange in Unsteady Air-Sea Interaction at Small and Submesoscales

An adequate description of the interaction between the atmosphere and ocean remains one of the most important problems of modern oceanology and climatology. An extremely wide variety of physical processes occurring in the coupled layers, a large range of scales, a moving boundary, all this factors significantly complicates the creation of models that would allow calculating the physical characteristics in both media with the necessary accuracy. In this paper the temporal variability of dynamic parameters in the driving layer of the atmosphere and in the near-surface layer of the sea on small and sub-mesoscales from one to several tens of hours is considered. The collected experimental data show a very high correlation between the dynamic wind speed and turbulence intensity in the upper sea layer on all scales recorded. An important distinguishing feature of all measured physical quantities in both media is the presence of quasi-periodic oscillations with different periods. For a more accurate description of momentum and energy fluxes from the atmosphere a non-stationary model of turbulent exchange in the near-surface layer of the sea is proposed. The model takes into account quasi-periodicity in the intensity of dynamic interaction between the atmosphere and the sea at these scales. In the model we use the equations of momentum and turbulent energy balance, the system of equations is solved numerically, the calculation results are compared with other models and with experimental data. It is shown that taking into account the non-stationarity of the wind strain improves the correspondence between the calculations and the experimental data. It is noted that in the nonstationary case, the energy and momentum flux from the atmosphere and the turbulence intensity increases compared to the action of a constant average wind of the same duration. Therefore, the strong averaging often used in global models may markedly underestimate the intensity of the dynamic interaction between the atmosphere and ocean.

Estimation and Management of Wind Energy in Ikorodu Lagos Lagoon, Using Weibull Parametric Measurement to Electricity Production in Nigeria

This paper is an approach on the estimation and approximation management of wind energy production around the lagoon axis of Ikorodu, Lagos state, Nigeria. The article concentrates on the availability of renewable resource such as wind to generate electrical energy in the greater Ikorodu metropolis of Lagos state Nigeria. Here, probability distribution function is used to generate the wind data. In this paper, three distinct methods are presented; Data time series analysis, Weibull probability function, and theoretical comparison with analytical concept. This research uses two important parameters for analyzing wind data: shape factor “k” and scale factor “c” from Weibull distribution function. The theoretical uses mathematical equations of popular methods such as: (a) Moment method, (b) Empirical Formula, or statistical standard deviation, (c) Peak likelihood, (d) modified peak likelihood, (e) double modified peak likelihood (f) graphical method or smallest mean square, and (g) energy sequence factor. The results obtained are tested to optimize the value from the Weibull parameters by adopting five techniques: (i) root average square error methodology, X2, power of agreement , MAPE, and RRMSE. The results expatiated on the practical and theoretical techniques design to confront the outcome of wind energy harnessed per 1.5 km2. Here, a differential optimization technique is used to determine the precision report. This serve as the basis of error litmus check existing between the wind energy determined by theory of statistical and mathematical Weibull Parametric function and the practical time-series data analysis in LSTM. Again, the wind data (speed and energy/power) were measured and recorded between January 2020 to December 2023 in the Ijede-Ikorodu Lagoon area of Lagos State. The optimized value for the shape factor k and scale factor c parametric measurement and management for maximizing the output electrical energy are obtained by using a well robust Weibull distribution function techniques and by absolutely determining and selecting the best position and location for installing the wind/wave alternators/generator. These generators come with turbines as a single unit. The measurement of the yearly average wind speed and average wind power are 10.09 ms-1 and 10.1 KWm-2, concurrently.

Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii

This study developed three hybrid light gradient boosting machine (LightGBM) models using novel metaheuristic algorithms (golden jackal optimization [GJO], the pelican optimization algorithm [POA], and the zebra optimization algorithm [ZOA]) to predict wildfire susceptibility on Kauaʻi and Molokaʻi islands, Hawaii. Thirteen geo-environmental variables were employed as potentially influential variables to predict wildfire susceptibility, while 1641 and 136 recorded wildfire ignition points on Kauaʻi and Molokaʻi islands, respectively, and 1641 and 136 randomly generated non-wildfire locations on the same islands were used as output data. The impact of the independent variables on wildfire susceptibility was interpreted using the Shapley additive explanations (SHAP) method. It was found that ZOA-LightGBM had the highest accuracy (AUC = 0.9314) for the prediction of wildfire susceptibility on Kaua‘i island, followed by GJO-LightGBM (0.9308), POA-LightGBM (0.9303), and LightGBM (0.9228). On Molokaʻi island, ZOA-LightGBM also achieved the highest AUC (0.858), outperforming POA-LightGBM (0.8488), GJO-LightGBM (0.8426), and LightGBM (0.8395). Analysis of the hybrid models revealed that the use of metaheuristic algorithms resulted in the setting of the optimal hyperparameters for the LightGBM model, enhancing its performance in modeling wildfire susceptibility on both islands. The SHAP results indicated that the distance from roads, elevation, land surface temperature, and average annual wind speed had the strongest impact on wildfire susceptibility on Kauaʻi Island, whereas distance from roads, slope, and average annual rainfall were the most important variables on Molokaʻi island.

A Prediction Method for the Average Winding Temperature of a Transformer Based on the Fully Connected Neural Network

The average winding temperature of a transformer (AWTT), serving as a key indicator for assessing the running state of the transformer, is of utmost importance in determining a transformer’s electrical properties and the insulation longevity of the transformer. An accurate prediction of AWTT is essential for ensuring the safe operation of the transformer. A novel method for predicting AWTT is introduced based on the analysis of field monitoring data. Firstly, the thermal characteristics and operational mechanisms of oil-immersed transformers are examined. Secondly, a factor analysis model is developed to streamline the network structure, accounting for the strong correlations among ambient temperature, load current, and top oil temperature. Thirdly, the independent temperature factor and load factor are extracted as pivotal features, and then input into the fully connected neural network to predict AWTT. Through a case study involving a 110 kV/10 kV oil-immersed transformer, the results show that the proposed method reduces redundant correlation information compared to traditional methods and improves the prediction accuracy of AWTT, establishing a foundation for further transformer state assessments.

Unveiling the role of forests in landslide occurrence, recurrence and recovery

Abstract Rain‐triggered landslides cause significant socioeconomic loss and long‐term ecological impact, disrupting topsoil and seed banks and creating unfavourable conditions for vegetation establishment. Although hazard management effectively reduces landslide risk, most management plans primarily focus on the societal impacts (loss of property and human lives), while environmental impacts related to landslide occurrence and recurrence are often overlooked. The role of different vegetation types in mitigation strategies remains uncertain due to the time and spatial constraints of traditional field study methods. Therefore, the role of vegetation in landslide restoration should be reconsidered. In this study, we investigated post‐landslide vegetation recovery patterns, analysed the duration of vegetation recovery, identified factors influencing these patterns, examined the role of forests in occurrence and recurrence probability and explored the implications of these findings for each element within an integrated management framework for landslide restoration. We utilised long‐term landslide inventory data (1924–2018) covering the entire city of Hong Kong (~1100 km2) and combined it with structural data derived from airborne LiDAR scanning in 2020 to capture landslide recovery. Our findings revealed significant differences in recovery trajectories between the main bodies and foot areas of scars, with the former taking approximately 46 years to recover and the latter recovering in about 38 years. Scar age, average wind speed, elevation and proximity to the forest were identified as key factors influencing structural recovery on scars, while the proximity to forest also regulated recovery rate of scars. We observed decreased landslide occurrence in forested areas, with recurrent landslides primarily appearing on older, unrecovered scars on barren hillsides. Synthesis and applications: Our research highlights the dynamic patterns, recovery time and drivers of vegetation recovery on landslide scars; and the higher probability of landslide occurrence in non‐forest areas and increased recurrence on bare, low vegetated scars. This information provides valuable insights for informing restoration efforts and managing landslide‐prone areas. Such knowledge is crucial for developing effective mitigation strategies and enhancing the resilience of vulnerable ecosystems facing climate change and increased frequency of extreme weather events.

Impact of Model Resolution and Initial/Boundary Conditions in Forecasting Low-Level Atmospheric Fields over the Incheon International Airport

Abstract This study investigates the impact of initial conditions/boundary conditions (ICs/BCs) and horizontal resolutions on forecast for average weather conditions, focusing on low-level weather variables such as 2-m temperature (T2m), 2-m water vapor mixing ratio (Q2m), and 10-m wind speed (WS10). A Weather Research and Forecasting (WRF) Model is used for regional mesoscale model simulations and large-eddy simulations (LESs). The 6-h-interval forecast fields generated by the Global Forecast System of the National Centers for Environmental Prediction and the Korean Integrated Model of the Korea Meteorological Administration are utilized as ICs/BCs for the regional models. Numerical experiments are performed for 24 h starting at 0000 UTC on each day in April 2021 when the average monthly wind speed was strongest during 10 years (2011–20). A comparison of model simulations with observations obtained around the Yeongjong Island, where Incheon International Airport is situated, shows that the regional models capture the time series of T2m, Q2m, and WS10 more effectively than the global model forecasts. Moreover, the LES experiments with a 100-m horizontal grid spacing simulate higher Q2m and lower WS10 during the daytime compared to the 1-km WRF. This results in a deterioration of their time-series correlation with the observations. Meanwhile, the 100-m LES forecasts time series of T2m over ocean stations and Q2m over land stations, as well as probability density functions of low-level weather variables, more accurately than that of the 1-km WRF. Our study also emphasizes the need for caution when comparing high-resolution model results with observation values at specific stations due to the high spatial variability in low-level meteorological fields.

Equilibrium atmospheric boundary layer model for numerical simulation of urban wind environment

The numerical simulation of urban wind environments faces difficulties in capturing the turbulent characteristics due to the large computational domain. Traditional Reynolds-averaged methods (RANS) can effectively capture the average wind characteristics of urban areas. However, due to the significant dissipation and attenuation of turbulent energy in the downstream direction, this method fails to provide accurate turbulent characteristics after time-averaging processing. Therefore, in order to obtain a higher-precision turbulent wind field distribution within urban areas, this paper proposed a new numerical method named an equilibrium atmospheric boundary layer model (EABL) by modifying the control equation of the shear stress transport k–ω model. During the process, the equilibrium atmospheric boundary layer was achieved successfully, and the attenuation problem of the turbulent kinetic energy and dissipation rate during the computational fluid dynamics numerical simulation was resolved. Simultaneously, a wind tunnel experiment and six turbulence models [standard k–ε, realizable k–ε, renormalization group k–ε, large eddy simulation—narrowband synthesis random flow generator (LES-NSRFG) and LES vortex method and EABL] were employed to simulate the wind field characteristics in an actual residential area. The simulation results demonstrate that, relative to traditional RANS models, the EABL model enhances the simulation accuracy of turbulence characteristics by over two times. Furthermore, compared to LES models, the EABL model can reduce computational time by threefold.

Hair follicle punch grafts in hard-to-heal wounds: A monocenter study and patient survey.

Chronic wounds present a growing challenge in the aging population, resulting in an extended course of treatment and an increased influx of patients with recalcitrant wounds seeking admission to hospitals. Furthermore, the general trend in patient care is toward simple and inexpensive treatment methods, feasible in an outpatient setting with little material costs. This retrospective case study aims to elucidate the operative procedure and outcomes associated with hair follicle unit transplantation utilizing punch grafts from the scalp for the management of hard-to-heal wounds. A cohort of 28 patients, comprising 20 males and eight females, with a mean age of 72.61 years (range: 48-89) and an average wound area of 82.49 cm2, underwent dissection of punch grafts containing hair follicles (2-3 mm in diameter) from the scalp. Subsequently, these grafts were transplanted into the wound bed. The retrospective evaluation of ulcer healing encompassed photo documentation and clinical records, while patient satisfaction was assessed through structured questionnaires. In 78.6% (22) of the cases, a favorable impact on wound healing was observed, characterized by epithelization, and in 57.1% (16) of the patients, complete wound closure was achieved. With the exception of one donor site, all other sites healed without complications. The patient survey indicated that the majority of individuals subjected to the procedure did not perceive it as painful or time-consuming. Notably, 81% (17) of individuals expressed a willingness to undergo the treatment again. Even in challenging wound conditions, such as pyoderma gangrenosum, our method demonstrated a positive effect on wound healing. Within our cohort, the utilization of hair follicle units in the management of hard-to-heal wounds resulted in either complete or partial wound closure for the majority of patients, accompanied by minimal morbidity, reduced operation time, and a low incidence of complications and associated costs.

Gdansk Wound-QoL Questionnaire: Pilot Study on Health-Related Quality of Life of Patients with Chronic Ulcers with Emphasis on Professional Physician-Patient Relations.

Chronic wounds lower health-related quality of life (QoL), as they affect various aspects of life due to pain, odor, tedious treatment, and stigma from society. Implementing proper treatment, where patient is well informed and active is a key for best outcomes. The aim of the study was to evaluate health-related QoL among the patients with chronic ulcers, with the use of new scale Gdansk Wound QoL. We enrolled 108 patients who met the inclusion criteria. Before the education on day 0 patients were asked to fill in Gdansk Wound-QoL questionnaire, that was developed in cooperation between dermatologists, general and plastic surgeons, as well as wound nurses, as well as fill the follow-up Gdansk Would-QoL questionnaire on day 30, which was also the end of the study. Study participants (N = 108) were on average 76.1 ± 10.8 years and all of whom had a venous ulcer on their lower limbs of average wound area of 10.8 cm2. QoL, according to the Gdansk Wound-QoL questionnaire, increased on average by 36.7% after 30 days trial. Moreover, on the follow-up visit 94.4% of the patients stated that their knowledge on the disease has increased and everyone was satisfied with the course of treatment proposed by the current doctor. Furthermore, 44.4% of the study group increased their activity at the end of the study. This pilot descriptive observational study shows that Gdansk Wound-QoL questionnaire can provide professionals in wound care good feedback on health-related QoL of patients with chronic wounds. This information has the potential to enhance patients well-being and overall comfort.

The Effect of Warm Water Compress on the Vagina on the Healing of Perinium Wounds in Post Partum Mothers

Background: Based on data from the World Health Organization (WHO) in 2017, around 830 women died every day due to complications during pregnancy or childbirth. In Indonesia, 75% of women who give birth vaginally experience perineal wounds and some of these wounds have the potential to become infected. In the Tanjung Emas Community Health Center working area, out of 23 post partum mothers, 4 people (27%) experienced slow wound healing. One cause of infection is poor perineal care. The cause of the high infection rate is due to a decrease in the body's resistance in mothers who are susceptible to infection. To reduce the risk of maternal death globally from 216.1 million live births in 2015 to 70 per 100,000 live births in 2030.Purpose:The purpose of this research is to determine the effect of warm water compresses on the vagina on healing perineal wounds in post-partum mothers. Methods: The design of this research is a two-group post test only control group design. The population in this study was all postpartum mothers (0-40 days) from December-March 2024 who gave birth in the Tanjung Emas Community Health Center Working Area, namely 23 people. The sampling technique used is a non-probability sample using the sampling technique method in this research using purposive sampling, namely 8 intervention groups and 8 control groups.Results: The results of this study were that the average wound healing was 5.5 and in the Control Group 6.5 days with a mean difference of 1 day and SD = 0.926. The results of calculations using the Paired T-Test showed p value = 0.039 (p 0.05), which means Ho is rejected and Ha is accepted, meaning there is a significant influence between the effect of warm water compresses on the vagina on healing perineal wounds.Conclusion: Further research may be carried out to develop research on other effective methods for healing perineal wounds in pregnant women.

An Evaluation of the Dust Emission Characteristics of Typical Underlying Surfaces in an Aeolian Region in the Middle Reaches of the Yarlung Zangbo River on the Qinghai–Tibet Plateau

Some of the most severe aeolian damage occurs along the middle reaches of the Yarlung Zangbo River in Tibet. Dust emission amounts (DEAs) are often used to assess aeolian damage; however, the research on DEAs in this area is currently almost blank. This article uses field-measured wind speed data from 2021 to 2022 in the Shannan wide valley area, combined with the Gillette dust emission estimation model to quantitatively determine the contributions of three surface types (riverbank quicksand area, foothill sand dunes, and the river floodplain vegetation area) to DEAs in the research area. The influence of surface characteristics on DEAs is analyzed and discussed. The results show the following: (1) The threshold friction velocity (u*t) in the riverbank quicksand area, foothill sand dunes, and the river floodplain vegetation area is 30.6 cm/s, 71.2 cm/s, and 85.6 cm/s, respectively, the threshold velocity (ut) is 6.1 m/s, 7.0 m/s, and 7.5 m/s, respectively, and the vegetation area is 2.8 times and 1.3 times that of the quicksand area, respectively. (2) The DEAs were in the following order: the riverbank quicksand area (652.9 t/km2) &gt; foothill sand dunes (326.5 t/km2) &gt; the river floodplain vegetation area (107.8 t/km2), the riverbank quicksand area is about 6.1 times that of the river floodplain vegetation area, and DEAs are a significant seasonal distribution: winter (44.7%) &gt; spring (28.3%) &gt; autumn (15.7%) &gt; summer (11.3%). (3) The DEAs from the dusty weather were in the following order: blowing sand (60.2%) &gt; sandstorms (28.6%) &gt; gusty winds (11.2%). (4) The DEAs increase with the increase in the average wind speed greater than 6.1 m/s, but the increase rate is obviously different, which showed that Changguo and Azha are greater than Sangyesi, Duopazhang, Sangri, and Senburi. At approximately the same average wind speed greater than 6.1 m/s, the DEAs in the quicksand area are much greater than in the vegetation area.

Impact of the East Asian subtropical jet on summer precipitation in China and its response to Atlantic sea surface temperature

AbstractERA5 reanalysis data, precipitation data from China, and National Oceanic and Atmospheric Administration (NOAA) monthly sea surface temperature (SST) data are used to analyse the impact of the meridional position of the East Asian subtropical jet (EASJ) on summer precipitation in China and its correlation with Atlantic SST. The results indicate that when the EASJ significantly shifts northward, the western North Pacific subtropical high (WNPSH) weakens with an eastward displacement. Upper‐level convergence and moisture divergence, corresponding to descending motion, lead to decreased precipitation in the Yangtze River Valley (YRV). Meanwhile, upper‐level divergence occurs over South China (SC), the Hexi Corridor (HC), and Northeast China (NEC), where moisture converges and ascends, favouring an increase in precipitation. Conversely, when the EASJ undergoes a significant southward shift, the WNPSH strengthens and expands westward. Opposing atmospheric circulation patterns in these four regions result in reversed precipitation anomalies compared with those observed when the jet shifts northward. The meridional position of the EASJ is closely related to the summer subtropical Atlantic SST. The positive (negative) SST anomaly (SSTA) over the subtropical Atlantic induces negative (positive) geopotential height anomaly in the upper troposphere over the North Atlantic by modulating the atmospheric meridional circulation. Geopotential height anomalies trigger eastward‐propagating Rossby waves, generating anomalous cyclones and anticyclones over East Asia. These anomalous cyclones and anticyclones lead to zonal wind anomalies, which alter the strength of the westerlies on both sides of the climatological jet axis, thereby changing the jet's meridional position. Additionally, the difference in the propagation direction of wave activity flux between positive and negative SSTA alters the distribution of wave energy convergence and divergence in the EASJ region, further affecting the intensity of the average westerly winds on both sides of the climatological jet axis, ultimately producing the changes in the meridional position of the EASJ.

Changes in Snow Cover and Its Surface Temperature across the Tibetan Plateau Region from 2000 to 2020

Currently, the global climate system is complex and ever-changing, with multiple factors influencing climate change. The Qinghai–Tibet Plateau, known as the “Third Pole” of the Earth, is particularly sensitive to global climate change. Without timely and scientific research on the ecological environment of the Qinghai–Tibet Plateau and without summarizing relevant adaptive strategies, global climate change will impact the sustainable development of the plateau. This study utilized Landsat remote sensing images from 2000 to 2020 to extract the snow cover area and snow temperature of the Qinghai–Tibet Plateau using the snow frequency threshold method. The study analyzed the spatiotemporal characteristics of snow cover and temperature over the 20-year period and investigated some of the climate and topographical driving factors influencing their changes. The results showed that from 2000 to 2020, the permanent snow cover area in the Qinghai–Tibet Plateau region showed a fluctuating decreasing trend, reducing from approximately 12.34 thousand km2 to around 9.01 thousand km2; the permanent snow temperature showed an initial increase followed by a decrease during the same period. The highest annual average snow temperature was approximately −3.478 °C, while the lowest annual average temperature was around −8.150 °C. Over the 20-year period, the snow cover area in the plateau was negatively correlated with temperature and precipitation, while snow temperature was positively correlated with temperature and precipitation. The snow cover in the weak wind areas of the plateau showed a significant reduction. Areas with higher average wind speeds, such as shaded slopes and semi-shaded slopes, had larger snow cover areas. These research findings provide important insights into the protection and management of the ecological environment of the Qinghai–Tibet Plateau.

Climate state of the Three Gorges Region in the Yangtze River basin in 2022–2023

Based on daily observation data of the Three Gorges Region (TGR) of the Yangtze River basin and global reanalysis data, the climate characteristics, climate events, and meteorological disasters of the TGR in 2022 and 2023 were analyzed. For the TGR, the average annual temperature for 2022 and 2023 was 0.8 °C and 0.4 °C higher than normal, respectively, making them the two warmest years in the past decade. In 2022, the TGR experienced its warmest summer on record. The average air temperature was 2.4 °C higher than the average, and there were 24.8 days of above-average high temperature days during summer. Rainfall in the TGR varied significantly between 2022 and 2023. Annual rainfall was 18.4 % below normal and drier than normal in most parts of the region. In contrast, the precipitation in 2023 was considerably higher than the long-term average, and above normal for almost the entire year. The average wind speed exhibited minimal variation between the two years. However, the number of foggy days and relative humidity increased in 2023 compared to 2022. In 2022–2023, the TGR mainly experienced meteorological disasters such as extreme high temperatures, regional heavy rain and flooding, overcast rain, and inverted spring chill. Analysis indicates that the abnormal western Pacific subtropical high and the abnormal persistence of the eastward-shifted South Asian high were the two important drivers of the durative enhancement of record-breaking high temperature in the summer of 2022.摘要基于长江三峡地区观测资料和全球再分析资料, 分析了该地区 2022–2023年气候特征, 酸雨状况以及主要天气气候事件. 2022 年和2023年三峡地区平均气温分别较常年偏高0.8 °C和0.4 °C, 是近十年来最暖的两年, 特别是2022年夏季出现破记录极端高温; 2022年三峡地区降水量较常年偏少18.4 %, 2023年降水量转为偏多15.3 %. 在这两年中该地区主要出现了极端高温, 区域性暴雨洪涝, 连阴雨和倒春寒等气候事件. 分析表明, 西太平洋副热带高压和南亚高压协同异常是2022年夏季极端高温维持的两个重要因素.

Phytochemical profile, antioxidant, and wound healing activities of Echium amoenum (Boraginaceae)

Natural products’ inflammatory and antioxidant properties have crucial roles in tissue repair and regeneration. This study aimed to investigate HPLC analysis, antioxidant activity, and wound-healing effect of Echium amoenum (EA) on rats. The EA was analysed for the determination of shikonin a derivative of naphthoquinone. In the wound healing assessment, forty Wistar rats were divided into five groups that were receiving the cream base, normal saline (NS), 1% silver sulfadiazine (SSD), and 5 and 10% EA cream (EAC). Shikonin was found in the EA extract. The average wound area on the 10th day was 0.71 ± 0.01, 0.86 ± 0.13, 0.58 ± 0.08, 0.53 ± 0.03 and 0.43 ± 0.04 cm2 for the cream base, NS, SSD, and 5 and 10% EAC, respectively. The collagen fibres were well formed and horizontally oriented in 5 and 10% EAC groups compared to other groups. EA cream was an effective treatment for wound healing in comparison with SSD.

Study of dust events based on multi-source data in the North Slope of the Tianshan Mountains

To reveal the spatial-temporal characteristics of atmospheric pollution during dust events on the North Slope of the Tianshan Mountains (NSTM), this study conducted a joint detection experiment from April to June from 2019 to 2021 at Shihezi, using satellite remote sensing, a microwave radiometer, meteorological sensors, and environmental monitors. Using long-term detection data from the aforementioned equipment, this study analyzed the characteristics of meteorological elements, Aerosol Optical Depth (AOD), PM, and gaseous pollutants. The main findings are as follows: The dust particles from the two severe pollution dust events on April 9, 2020, and May 1, 2021, on the NSTM originated from the Gurbantünggüt Desert and were transported along the northwest direction, leading to a significant increase in AOD (averaging 1.36 g/m2) and dust column mass concentration (averaging 1.58 g/m2). During the two dust storms, the PM10 concentration peaks reached 2536.5 μg/m³ and 1804.5 μg/m³, respectively. The average relative humidity (RH) was less than 30%, the average wind speed was more than 6 m/s, and the average visibility (V) was less than 1000 m. Moreover, during the dust events from April to June, the temperature and relative humidity were higher in June, but the wind speed was lower. The vertical thermodynamic interactions of the dust storms were stronger than those of the blowing and floating dust storms. Finally, the relationship between PM10 and V was fitted using the following equation: V=11326.8166e−0.0015PM10.This study provides scientific support for the prediction of dust storms on the NSTM.