Search Results (185)

Low-level jets (LLJs) play an important role in the transport of heat, water vapor, and atmospheric pollutants. Based on one year (1 September 2023 to 31 August 2024) of tropospheric wind profiler radar (RWP) observations at the Wenjiang Meteorological Observation Base in Chengdu, this study systematically investigates the wind field structure in the middle and lower troposphere over the Chengdu region and the vertical distribution and evolution characteristics of LLJs. The effective detection height of the RWP reaches at least 7.4 km throughout the year, demonstrating good consistency with concurrent radiosonde data. Horizontal wind speed accelerates markedly above 3 km, with the strongest vertical gradient observed in winter. In the lower layer, the prevailing wind direction is primarily controlled by mountain-valley breezes; with increasing altitude, the westerly belt gradually becomes the dominant wind system. Within the atmospheric boundary layer (below 1 km), the wind field exhibits a distinct diurnal cycle: easterly winds dominate in the afternoon, shifting to northerly winds at night. Surface wind speed peaks in the afternoon, whereas upper-level wind speed peaks at night. The occurrence frequency of LLJs is highest in July (26.3% for LLJ-1), followed by April (17.8%). The prevailing wind directions of LLJs are north-northeasterly and northeasterly, and jet core heights are mainly distributed between 0.7 and 1.9 km. For weaker LLJs (LLJ-1 and LLJ-2), both frequency and intensity are higher at night than during the day, peaking at 22:00. These findings deepen our understanding of boundary layer dynamics over complex basin terrain and provide a high-resolution observational benchmark for model improvements and weather warnings. Full article

Multi-storey pig houses (MSPHs) have been built as a land-efficient solution for intensive swine production in China, but can cause odour nuisances for and complaints from nearby residents. In this study, air quality measurements and dispersion modelling using AERMOD were conducted to quantify the odour impact around a swine barn with two MSPHs equipped with air scrubbers in complex terrain. The field measurements showed strong seasonal fluctuations. The two MSPHs were modelled as eight elevated point sources, incorporating building downwash effects, to determine the setback distances between the barn and residential areas located 1 km away to the north. The results showed a pronounced north–south plume elongation, which was consistent with the prevailing wind direction and the valley topography. Using the odour impact criteria (OIC) with an odour occurrence-free frequency of 99.5%, the maximum setback distance in the north decreased from >4000 m to 951 m with the odour concentration threshold increasing from 1 to 10 OU/m³. The summer-only worst-case scenario yielded larger impact zones (>4000 m for 1–2 OU/m³; 2554 m for 10 OU/m³ at 99.5%), indicating that warm-season exposure should be considered when assessing residential risk. Under the current national OIC of 10 OU/m³ for residential areas, the modelled setback distance (951 m at 99.5%) indicated that the communities were situated outside the odour impact zone, which did not align with the documented complaints, demonstrating that the 10 OU/m³ threshold is lenient for high-density MSPH operations. Full article

A microscale vortex embedded in a cold front over the Pearl River Estuary was observed by weather radars in Hong Kong on the evening of 2 March 2026. This paper presents an observational and simulation study of this vortex. In addition to the reflectivity and Doppler velocity data, the three-dimensional wind field associated with this vortex was analyzed using two radar-based analysis methods. Updrafts were present within the vortex, and the formation of the vortex appears to be related to the horizontal wind shear within the frontal zone and vertical motion triggered by a mid-tropospheric wave. Three commercial aircraft flew across the vortex at low altitude southwest of Lantau Island. Flight data showed marked fluctuations in vertical velocity, including both upward and downward air motions, together with severe turbulence within the vortex. The vortex is therefore of both meteorological interest and operational significance for aviation safety. The event was also simulated using the Weather Research and Forecasting (WRF) model with 200 m resolution. The model reproduced the observed vertical motions and turbulence intensity reasonably well in comparison with aircraft observations. Sensitivity tests with varying sea surface temperature and local terrain over Hong Kong showed no significant impact on the formation of the vortex, confirming that the event was primarily driven by horizontal wind shear in the frontal zone and vertical motion triggered by mid-tropospheric waves. Full article

As a mountain–water city in the upper Yangtze River region, Chongqing is characterized by complex river-valley terrain, dense riverside development, extreme summer heat, high humidity, and frequent calm-wind conditions. Existing studies on waterfront thermal comfort mainly focus on plain cities, whereas mountainous riverside parks remain insufficiently understood. This study investigated summer thermal comfort in three riverside parks in Chongqing—Jiulongtan Park, Coral Park, and Jiangtan Park—through field measurements of air temperature, black globe temperature, wind speed, relative humidity, and Thermal Radiation, combined with thermal sensation vote (TSV) and thermal comfort vote (TCV) surveys. Results showed that the maximum air temperature reached 43.7 °C and the maximum black globe temperature reached 61.6 °C. The hydrophilic layer recorded the highest wind speed (1.64 ± 0.39 m/s), while the elastic layer showed high PET values (36.00–46.10 °C). Regression analysis indicated neutral PET values of 32.49–35.74 °C. Correlation analysis showed that PET, mean thermal sensation vote (MTSV), and mean thermal comfort vote (MTCV) were positively correlated with air temperature, black globe temperature, mean radiant temperature (T_mrt), and relative humidity. In contrast, PET was negatively correlated with wind speed. This study reveals the coupled effects of river-valley terrain, elevation stratification, waterfront microclimate, and landscape elements on outdoor thermal comfort, providing a scientific basis for optimizing shading, ventilation, and hydrophilic spaces in hot-humid mountain–water cities. Full article

Near-surface wind field simulation in complex mountainous terrain is essential for predicting wildfire behavior and supporting fire risk management. WindNinja, a widely used diagnostic wind downscaling model, is strongly dependent on its initial input data; however, systematic evaluations of its input sensitivity and simulation accuracy remain limited. In this study, a representative canyon area was selected as the study site. WindNinja was driven by three types of input data: local meteorological station observations, national meteorological station observations, and ERA5-Land reanalysis data. Two indices—the Wind Forcing Intensity (WFI) index and the Thermal Forcing Intensity (TFI) index—were constructed to classify weather-forcing scenarios and evaluate simulation accuracy under different conditions. The results show that differences in the statistical characteristics of the initial wind sources produce pronounced sensitivity in WindNinja simulations. Simulations driven by local meteorological observations generally overestimate wind speed, whereas ERA5-Land-driven simulations systematically underestimate wind speed, with national-station results falling between these two cases. Simulation accuracy varies with terrain position: wind direction errors dominate in valleys, whereas wind speed errors dominate on ridges and hilltops. Weather background conditions significantly influence simulation accuracy. Wind forcing intensity dominates the magnitude and dispersion of simulation errors, while strong thermal forcing leads to an overall decline in simulation accuracy and stability. These findings highlight the sensitivity of WindNinja to initial wind sources and weather background conditions in complex terrain and provide guidance for its application and uncertainty control in wildfire behavior modeling. Full article

This study presents the aerodynamic design of the wing system for a fixed-wing vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV), developed to enhance energy efficiency and operational performance in agricultural applications. The design responds to the limitations of conventional multirotor drones, which are limited by low endurance and high energy consumption, and crop-dusting aircraft, which are unsuitable for irregular terrain such as that found in Chihuahua, Mexico. A comprehensive methodology was adopted, integrating the selection of airfoils optimized for low-Reynolds-number conditions, computational fluid dynamics (CFD) simulations, winglet incorporation, and experimental validation through wind tunnel testing. The SELIG 1223 airfoil was selected for its superior aerodynamic efficiency, demonstrating a potential reduction of up to 55% in power requirements compared to multirotor configurations. Despite some variability in experimental results, the proposed design demonstrated consistent feasibility and reliability. Future work will focus on field validation and geometric adaptation to diverse operational scenarios, reinforcing its applicability across heterogeneous agricultural landscapes. Full article

Global reliance on wind energy continues to grow, leading to an increasing number of wind farms implemented in complex topographies. However, there remains a significant research gap on how the terrain’s features affect the wake recovery, especially when the irregularities scale with the wind turbine’s size. This study uses field data and Reynolds-averaged simulations to quantify the influence of topographical features on a wind farm’s wake recovery and power generation. To characterize the terrain surrounding the turbines, this study introduces two parameters—the Downwind Slope and the surface complexity length $\zeta$—which quantify the local average terrain unevenness. The findings demonstrate that turbines in terrains with streamwise positive slopes exhibit faster wake recovery, averaging 6.35D in length (D = turbine diameter), followed by complex-flat terrain (8.7D on average), then descending terrains with the least beneficial wake recovery (9.2D on average). A terrain with a higher surface complexity also improves wake recovery owing to the turbulent entrainment that enhances momentum transport exchange into the wake. Additionally, simulations of the same turbine distribution, but in a completely flat terrain, showed that the complex terrain may lead to lower performance compared to the idealized flat terrain: 11.5% of power generation decrease in our case. The latter highlights the importance of considering topographic effects when planning wind energy projects. Full article

Forecasting short-term heavy precipitation is crucial for the early warning of disasters such as flash floods, landslides, and urban flooding. However, under complex topographic conditions, traditional numerical forecasts still fall short in capturing high-resolution heavy precipitation events, and conventional radar extrapolation methods struggle to accurately characterize the nonlinear evolution of weather systems during advection, deformation, and intensity adjustment processes. To address the challenge of short-term heavy rainfall forecasting in high-altitude, complex terrain, this paper proposes Nowcast with Flow-Net (Nwf-Net), a short-term precipitation forecasting framework that integrates deep learning with multi-source meteorological data. This framework consists of a Morphological Evolution Track Module (MET) and a Rainfall Intensity Correction Module (RIC) connected in series: the former combines upper-air wind fields with traditional optical flow algorithms to jointly characterize the displacement of and morphological changes in radar echoes; the latter utilizes a deep recurrent neural network to correct the intensity of forecast results, thereby enhancing the model’s ability to characterize the evolution of strong convective echoes. Experiments in the Alpine region demonstrate that Nwf-Net achieves CSI, HSS, and F1 scores of 0.392, 0.506, and 0.546, respectively, at 32 dBz. These results outperform those of traditional numerical models and some mainstream models, indicating that Nwf-Net can accurately capture multiscale severe convective information and consistently generate precise forecasts. Full article

A globally applicable and fully automated simulation method based on satellite-derived Earth Observation (EO) data and global circulation models was developed and validated. Inputs to the simulation are DSM/DTM layers, surface roughness layer, forest canopy layer, and single-level point data from the European Centre for Medium-Range Weather Forecasts fifth-generation ECMWF reanalysis (ECMWF ERA5, a global circulation model produced by the Copernicus Climate Change Service (C3S)). High-resolution roughness length maps are produced by deep learning from optical satellite data. Velocity fields are predicted by fluid dynamics simulations in OpenFOAM using the IDDES turbulence model, a 3D resolved tree canopy implemented as isotropic momentum sinks, and a corrector step based on sub-grid-scale dynamic downscaling of ERA5 data. No calibration data from wind measurements close to the target are necessary to achieve results accurate enough for site assessments and wind park planning. The presented method is suitable for the prediction of average wind speeds and average power densities in complex terrain with high ruggedness indices for WEC (wind energy converter) installations closer to the ground and at hub heights of typical large-scale WECs. Full article

Subalpine grasslands represent highly sensitive ecosystems that are increasingly exposed to climate extremes, yet their long-term disturbance dynamics remain poorly documented. This study investigates climate-driven dieback of subalpine grasslands in Central Europe using a harmonized, multi-decadal satellite time series. We analyzed Landsat (TM, ETM+, OLI, OLI-2) and Sentinel-2 imagery spanning 1984–2024 to detect changes in grassland condition, supported by field-based validation, climatic indices, and geomorphological analysis. Several spectral indices related to non-photosynthetic vegetation were evaluated, with the Normalized Burn Ratio (NBR) providing the best discrimination of dead grassland. In spatially grouped cross-validation, NBR achieved very high accuracy for dead versus non-dead grassland, with AUC = 0.9996, precision = 1.00, recall = 0.82, and F1-score = 0.90 for Sentinel-2, and AUC = 0.9982, precision = 1.00, recall = 0.62, and F1-score = 0.76 for Landsat 9. Retrospective mapping revealed four dieback events since 2000: two short-term episodes with rapid within-season recovery (2000, 2003) and two long-term events characterized by persistent degradation and slow regeneration (2012, late 2018–2019). The largest short-term event, in 2003, affected 42.19 ha of total dieback and 96.95 ha including partially damaged or regenerating grassland. Dieback extent was negatively associated with water balance deficit, strongest for SPEI-12 (ρ = −0.548, p = 0.002), while winter frost under shallow-soil conditions likely contributed to long-term damage in 2012. Geomorphological analysis indicated that elevation, terrain curvature, and, to a lesser extent, wind exposure are the primary controls on dieback susceptibility, highlighting the importance of fine-scale environmental controls. Our results demonstrate the value of long-term, multi-sensor satellite observations for detecting and interpreting climate-driven disturbances in subalpine grasslands and provide a transferable framework to support monitoring and conservation of mountain ecosystems under ongoing climate change. Full article

The Qinghai–Tibet Plateau is characterized by highly complex terrain, and civil aviation serves as a primary mode of transportation for regional mobility. A comprehensive understanding of wind field characteristics within the terminal areas of plateau mountain airports, as well as the formation mechanisms of wind shear during different flight phases, is of considerable importance for flight risk assessment, improvement of transport efficiency, and refined meteorological support services. However, studies focusing on wind field structures within the terminal areas of plateau mountain airports remain limited. In this study, dry-season observations from Coherent Doppler Wind Lidars at two critical locations in the terminal area of Lhasa Airport are analyzed. A comparative analysis is conducted on the vertical structure, diurnal variation, and the characteristics of turbulence and wind shear under different terrain conditions. The results show that above the valley height, both sites are dominated by stable westerly winds. Below the valley height, the wind field is strongly influenced by terrain complexity. At the Lhasa Airport site (LS), the valley is regular in shape and has a stable orientation. The prevailing wind direction is aligned with the valley, and easterly winds dominate the entire valley, especially in the middle and lower layers. In contrast, the Qushui site (QS) is located at the confluence of two valleys, where the terrain is more open and complex. The prevailing wind shifts clockwise with height, from northeasterly in the lower layers to easterly aloft. The wind direction is less concentrated than at LS. In terms of diurnal variation, a stable easterly layer forms within the valley at LS in the morning. A transition layer of about 200–300 m exists between this layer and the westerlies aloft. Within the transition layer, wind speed is relatively weak and wind direction stability is low. At QS, morning winds are weaker and more variable within the valley. Wind direction stability increases with height. In the afternoon, both sites are influenced by the downward transport of westerly momentum. However, the effect is more pronounced at QS, where low-level wind speed is higher and wind direction is more stable. Turbulence at both sites peaks between 14:00 and 17:00 and is mainly driven by thermally induced updrafts. Turbulence intensity at QS is stronger, with a vertical extent exceeding 1500 m, indicating a stronger response to thermal forcing. Wind shear at both sites mainly occurs between 12:00 and 18:00, with peak frequency from 13:00 to 17:00. This period is consistent with peak turbulence activity. Wind shear at LS occurs more frequently and lasts longer. At QS, momentum transport from above 1500 m enhances wind shear occurrence at 800–1000 m. The causes of wind shear differ under different prevailing wind conditions. Under prevailing westerlies, wind shear is mainly caused by rapid changes in wind direction with height. Under prevailing easterlies, it is primarily associated with an enhanced vertical gradient of wind speed. These results reveal the significant influence of complex terrain on low-level wind structures and causes of wind shear. The findings provide a scientific basis for operational decision-making at plateau mountain airports. Full article

Mountain orchards in southern China are characterized by fragmented and complex terrain with a wide slope variation range (5~30°), which easily leads to uneven pesticide distribution and pesticide accumulation on gentle slopes. These issues give rise to core technical bottlenecks such as low pesticide utilization rate, poor operational efficiency, and unclear atomization mechanism, hindering the optimization of pesticide application parameters, causing pesticide waste and environmental pollution, and restricting the sustainable development of the mountain fruit industry. To address this problem, this study designed a slope-classified pipeline layout and developed a high-efficiency fixed pipeline system for phytosanitary application in mountain orchards, featuring stable operation, low labor intensity, and easy intelligent transformation. Following the technical route of “theoretical design-atomization mechanism analysis-parameter optimization-laboratory verification-field application”, ruby nozzles with high wear resistance, uniform droplet distribution, and long service life were selected and optimized to meet the demand for long-term fixed pesticide application in mountain orchards. High-speed imaging technology was used to real-time capture the dynamic atomization process of nozzles, providing support for clarifying the atomization mechanism. Advanced methods such as fluorescence tracing were adopted to quantitatively evaluate key indicators including droplet deposition in canopies, and the system performance was verified through laboratory and field tests, laying a scientific foundation for its popularization and application. Field test results showed that the optimal spray pressure should not be less than 8 MPa. The XR9002 nozzle can generate fine droplets to achieve pesticide reduction while forming a stable hollow cone atomization flow. Fluorescence tracing analysis indicated that the droplet deposition on the adaxial leaf surface decreases with increasing altitude (presumably affected by wind speed), while the initial deposition on the abaxial leaf surface is low and shows no significant variation with altitude. Deposition on the adaxial leaf surface decreased with canopy height, while abaxial deposition was much lower (8.9–14.9%). This technology enables high-precision quantitative analysis of droplet deposition. The core innovations of this study are: clarifying the atomization mechanism of ruby high-pressure nozzles under pesticide application conditions in mountain orchards, constructing a slope-classified terrain-adaptive pipeline layout model, and establishing a closed-loop technical system of “atomization mechanism-pipeline layout-parameter optimization-deposition detection”. This study provides theoretical and technical support for green and precision pesticide application in mountain orchards, and has important academic value and broad application prospects for promoting the intelligent upgrading of the fruit industry in southern China. Full article

Accurate wind field simulation in forest areas is crucial for wind energy development but remains challenging for traditional WRF models due to complex terrain and vegetation heterogeneity. This study proposes a multi-source optimization framework integrating seasonal PBL scheme selection, localized leaf area index (LAI) adjustment, and 3DVAR data assimilation to improve WRF performance in forested terrain. The framework was validated using observations at 20 m, 50 m, and 100 m heights in Maoershan forest area. Results show that: (1) PBL schemes exhibit significant seasonal dependence—YSU performs best in spring (unstable conditions), while MYJ shows slight advantages near the surface in winter (stable conditions). (2) Localized LAI correction reduces near-surface wind speed bias by 35% and improves wind direction accuracy by 28%, with stronger effects in summer. (3) 3DVAR assimilation further enhances accuracy, achieving correlation coefficients of 0.869 for wind speed and 0.813 for wind direction, with greater improvements in summer and near the surface. (4) Winter wind power density at 100 m reaches 475 W/m², 38% higher than summer, indicating stable exploitable resources. The proposed framework provides a replicable methodology for wind field simulation in forest regions worldwide. Full article

This study investigates the wind field characteristics of long-span suspension bridges in mountain valleys terrain, with a particular focus on the disturbance effects caused by bridge structure on wind measurements. Field data are collected using the Wind3D 6000 LiDAR installed near the bridge. By comparing wind field characteristics before and after bridge completion, this study evaluates the influence of the bridge structure on both mean and turbulent wind characteristics. The findings show that the presence of the bridge tower and deck reduces the measured mean wind speed and modifies its probability distribution. The bridge tower increases the effective ground roughness coefficient, thereby attenuating the vertical wind speed gradient. In addition, the bridge tower raises the measured turbulence intensity, alters its probability distribution, and decreases the agreement between the turbulent wind power spectrum and the von Kármán spectrum. It is necessary to correct the data affected by these disturbances to improve the accuracy of wind load assessments for long-span bridges, thus enhancing the reliability of bridge structural operation. Full article

Coastal cities exposed to extreme wind events are facing increasing challenges in emergency management under climate change. Accurate and high-resolution wind environment information over complex urban terrain is essential for disaster risk assessment and evidence-based emergency planning; however, such information is often unavailable in conventional management practices. This study proposes an integrated UAV–CFD framework to support urban wind risk assessment by combining multi-source geospatial data and high-resolution numerical simulation. A refined urban terrain model with a spatial resolution of 0.5 m was constructed through the fusion of Google Earth data and UAV oblique photogrammetry, and subsequently coupled with a computational fluid dynamics (CFD) model to analyze the urban wind environment. Field measurements obtained from a 50 m wind observation tower were used to validate the simulation results. The results reveal significant wind speed amplification caused by complex terrain and building configurations, with a maximum amplification factor of 1.95 due to the canyon effect. The relative errors between simulated and measured wind speeds and turbulence intensity were generally within 15%, demonstrating the reliability of the proposed framework. By providing high-resolution and spatially explicit wind risk information, this study offers practical decision-support for emergency management, urban planning, and resilience-oriented disaster mitigation in coastal cities. Full article