Search Results (480)

This study analyzes winds over the Red Sea (17 N, 39.5 E) and consequences for the northeast African climate in early summer (May–July). As the Indian SW monsoon commences, NNW winds > 6 m/s are channeled over the Red Sea between 2000 m highlands, forming a low-level jet. Although sea surface temperatures of 30C instill evaporation of 8 mm/day and surface humidity of 20 g/kg, the air mass above the marine layer is dry and dusty (6 g/kg, 100 µg/m³). Land–sea temperature gradients drive afternoon sea breezes and orographic rainfall (~4 mm/day) that accumulate soil moisture in support of short-cycle crops such as teff. Statistical analyses of satellite and reanalysis datasets are employed to reveal the mesoscale structure and temporal response of NE African climate to marine winds via air chemistry data alongside the meteorological elements. The annual cycle of dewpoint temperature often declines from 12C to 4C during the Indian SW monsoon onset, followed by dusty NNW winds over the Red Sea. Consequences of a 14 m/s wind surge in June 2015 are documented via analysis of satellite and meteorological products. Moist convection was stunted, according to Cloudsat reflectivity, creating a dry-east/moist-west gradient over NE Africa (13–14.5 N, 38.5–40 E). Diurnal cycles are studied via hourly data and reveal little change for advected dust and moisture but large amplitude for local heat fluxes. Inter-annual fluctuations of early summer rainfall depend on airflows from the Red Sea in response to regional gradients in air pressure and temperature and the SW monsoon over the Arabian Sea. Lag correlation suggests that stronger NNW winds herald the onset of Pacific El Nino. Full article

The topic proposal concerns the axes of climate operation and modification, the consequences and/or benefits of the flow of the economy, as well as the risks to social security, amidst the evolution of human interventions, which the Anthropocene highlights. Atmospheric data demonstrates the interaction of gaseous pollutants and aerosols, with the contribution of different emission and pollution sources to its chemical composition. At the same time, satellite remote sensing of precipitation and the water cycle reveal an imbalance in components and effects, in an environment of rapid rates of commercial production and human mobility in the developed world. How does mobility prevent the full observation and modeling of the elements involved (in atmospheric and hydrological data)? What is the role of multi-sensor technologies for detecting gases and what are their applications in decontamination? With sources from bibliographic reviews, data were collected from the detection of point sources of gases and dynamic analyses of the extent of the water surface, in order to highlight the descriptive characteristics of the meteorological phenomena and their activity. The scientific approach to analyzing the individual data is based on the techno-scientific Actor-Network Theory, in order to test their connection and contribution to the overall problematic result. The aim of this study is to build an interdisciplinary analysis with documentation of vulnerabilities in the expression of weather phenomena, of the present geological time. The ambition of the study is to propose principles of regulation and precaution, related to the sustainable development of geo-resources and ways to reduce vulnerability. Full article

Under the global climate change, variations in climatic elements such as temperature, precipitation, and sunshine duration significantly impact the growth, development, and yield formation of winter wheat. A precise understanding of the impact of climate change on winter wheat growth and the scientific use of meteorological resources are crucial for ensuring food security, optimizing agricultural planting structures and agricultural sustainability. This study uses statistical methods and focuses on the Beijing–Tianjin–Hebei region, utilizing data from 25 meteorological stations from 1961 to 2010 and winter wheat yield data from 1978 to 2010. Twelve refined indicators encompassing temperature, precipitation, and sunshine duration were constructed. Path analysis was employed to determine their weights, establishing a comprehensive climate indicator model. Results indicate: Temperature indicators in the region show an upward trend, with accumulated temperature of the whole growth period increasing at a rate of 61.1 °C·d/10a. Precipitation indicators reveal precipitation of the whole growth period rising at 3.9 mm/10a and pre-winter precipitation increasing at 4.2 mm/10a. Sunshine duration exhibits a declining trend, decreasing at 72.7 h/10a during the whole growth period. Comprehensive climate indicators decrease from south to north, with the southwest region exhibiting the highest tendency rate (18.41), while the central and southern regions show greater variability. This study provides scientific basis for optimizing winter wheat planting patterns and rational utilization of climate resources in the Beijing–Tianjin–Hebei region. It recommends prioritizing cultivation in western southern Hebei and improving water conditions in the central and northern areas through irrigation technology to support sustainable crop production. Full article

The wind environment in furnace cities has attracted considerable research attention. Investigating the impact of suburban residential building arrangements in furnace cities on inter-building wind speed fields is useful and cost-effective for scientifically optimizing layouts. This study simulated 13 wind speed fields across six symmetric and asymmetric building arrangements: linear, inclined, convex, concave, M-shaped, and V-shaped, with varying building offsets and spacing widths. We used the standard k–ε model for simulations through finite element method. Results demonstrated that larger building offsets enhanced inter-building wind speeds, with the concave arrangement most effectively enhanced the wind speed between buildings among the configurations. V-shaped arrangements slightly underperformed concave layouts in wind speed uniformity. Based on the summer wind direction data from Wuhan Tianhe Meteorological Station, we propose two corresponding layouts: concave and V-shaped arrangements, which are conductive to enhancing inter-building wind speed. In practical planning, the orientation of building clusters can be adjusted according to the local wind rose diagram. Full article

Meteorological conditions are a key factor affecting airport site selection and operational efficiency. To overcome the limitations of traditional methods in evaluating the joint impact of multiple meteorological elements, this paper aims to develop an airport site selection decision support method based on case-based reasoning (CBR) and multi-meteorological element clustering. Firstly, we propose a universal framework: utilizing K-means clustering to extract typical weather scenarios from historical meteorological data; subsequently, using Zhengzhou Xinzheng International Airport as a case study, a quantitative mapping relationship was established between these weather scenarios and flight operation efficiency (such as delay rate and cancellation rate) to calibrate and validate the model; finally, by calculating the frequency of occurrence of various weather scenarios at candidate sites, the future operational efficiency can be inferred, providing a ranking basis for site selection decisions. The results indicate that low-cloud-base weather has the greatest impact on flight takeoff performance, while good weather has a relatively small impact on flights. This method can effectively and quickly rank the advantages and disadvantages of all candidate airports, providing a reference for airport construction. Full article

This study presents an integrated assessment of four decades (1985–2023) of environmental and climate alterations in the principal metropolitan conurbation of the eastern Brazilian Amazon, encompassing Belém and its adjacent municipalities. By combining high-resolution land use/land cover (LULC) dynamics with in situ meteorological data, including understudied elements, such as relative humidity (RH) and wind speed, and satellite-derived precipitation estimates (CHIRPS v3), we advance the scientific understanding of regional climate trends. Our results document significant climate shifts, including pronounced dry-season warming (+1.5 °C), atmospheric drying (−4% in RH), attenuated wind patterns (−0.4 m s⁻¹), and altered precipitation regimes, which exhibit strong spatiotemporal coupling with extensive forest loss (−20%) and rapid urban expansion (+84%) between 1985 and 2023. Multivariate analyses reveal that these land–climate interactions are strongest during the dry regime, underscoring the role of surface–atmosphere feedbacks in amplifying regional changes. Comparative analysis of past (1980–1999) and present (2005–2024) decades demonstrates a marked intensification in the frequency and magnitude of extreme seasonal climate events. These findings elucidate a critical feedback mechanism that exacerbates climate risks in tropical urban areas. Consequently, we argue that mitigation public policies must prioritize the strict conservation of peri-urban forest fragments (vital for moisture recycling and local climate regulation) and the strategic implementation of green infrastructure aligned with prevailing wind patterns to enhance thermal comfort and resilience to hydrological extremes. Full article

The dynamics of cyanobacteria bloom in Lake Taihu, China, are subject to rapid fluctuations under the influence of various factors, with meteorological conditions being particularly influential. In this study, monitoring data on the surface area of cyanobacteria bloom in Lake Taihu and observational data from automatic meteorological stations around Lake Taihu from 2016 to 2022 were utilized. Meteorological sub-indices were constructed based on the probability density distributions of meteorological factors in different areas of cyanobacterial bloom. A stacked ensemble model utilizing various machine learning algorithms was developed. This model was designed to forecast the cyanobacterial bloom area index in Lake Taihu based on meteorological data. This model has been deployed with real-time gridded forecasts from the China Meteorological Administration (CMA) to predict changes in the cyanobacteria bloom area index in Lake Taihu over the next 7 days. The results demonstrate that utilizing meteorological sub-indices, rather than traditional meteorological elements, provides a more effective reflection of changes in cyanobacteria bloom area. Key meteorological sub-indices were identified through recursive feature elimination, with wind speed variance and wind direction variance highlighted as especially important factors. The real-time forecasting system operated over a 2.5-year period (2023 to July 2025). Results demonstrate that for cyanobacteria bloom areas exceeding 100 km², the 1-day lead-time forecast hit rate exceeded 72%, and the 3-day forecast hit rate remained above 65%. These findings significantly enhance forecasting capability for cyanobacterial blooms in Lake Taihu, offering critical support for sustainable water management practices in one of China’s most important freshwater systems. Full article

Achieving net-zero emissions in arid and high-solar-yield regions demands innovative, cost-effective, and scalable energy technologies. This study conducts a comprehensive techno-economic analysis and assessment of a novel hybrid photovoltaic–thermal solar collector (U.S. Patent No. 11,431,289) that integrates a reverse flat plate collector and mini-concentrating solar thermal elements. The system was tested in Qatar and Germany and simulated via a System Advising Model tool with typical meteorological year data. The system demonstrated a combined efficiency exceeding 90%, delivering both electricity and thermal energy at temperatures up to 170 °C and pressures up to 10 bars. Compared to conventional photovoltaic–thermal systems capped below 80 °C, the system achieves a heat-to-power ratio of 6:1, offering an exceptional exergy performance and broader industrial applications. A comparative financial analysis of 120 MW utility-scale configurations shows that the PVT + ORC option yields a Levelized Cost of Energy of $44/MWh, significantly outperforming PV + CSP ($82.8/MWh) and PV + BESS ($132.3/MWh). In addition, the capital expenditure is reduced by over 50%, and the system requires 40–60% less land, offering a transformative solution for off-grid data centers, water desalination (producing up to 300,000 m³/day using MED), district cooling, and industrial process heat. The energy payback time is shortened to less than 4.5 years, with lifecycle CO₂ savings of up to 1.8 tons/MWh. Additionally, the integration with Organic Rankine Cycle (ORC) systems ensures 24/7 dispatchable power without reliance on batteries or molten salt. Positioned as a next-generation solar platform, the Hassabou system presents a climate-resilient, modular, and economical alternative to current hybrid solar technologies. This work advances the deployment readiness of integrated solar-thermal technologies aligned with national decarbonization strategies across MENA and Sub-Saharan Africa, addressing urgent needs for energy security, water access, and industrial decarbonization. Full article

Hainan Island is one of the main tea-producing regions in South China. Climate change has increased agricultural instability, causing fluctuations in tea yield and quality. Based on daily surface meteorological data from 19 national meteorological observation stations on the island from 1990 to 2019, as well as related factors such as topography, a spatial analysis model for climate zoning indicators was established. Zoning indicators were spatialized through GIS spatial analysis, and fuzzy logic was applied to construct membership functions based on climatic elements to assess climatic suitability for tea cultivation. This approach helped refine zoning for tea planting areas and assess potential future climate changes. Results show high climatic suitability for tea production in spring (March-May) and autumn (September–October), but low suitability in summer (June–August) due to high temperatures and strong sunlight. The most suitable zone for tea planting is centered in the northeastern parts of the island; the suitable zone is mainly distributed in the central mountainous areas and the western coastal region; the sub-suitable zone mainly includes central and southern parts of Dongfang; and the unsuitable zone mainly includes eastern and southern parts of Dongfang and southern parts of Changjiang. Under future climatic scenarios, the island’s temperatures will further increase, and suitable temperature areas will shrink from the periphery toward the central mountainous regions. Precipitation will also increase over time, leading to an expansion of suitable precipitation areas on the island. This study helps promote sustainable tea production and the rational utilization of agricultural climate resources on Hainan Island. Full article

Integrated Pest Management (IPM) is a system that combines ready-made plant protection methods. IPM guidelines apply to all users of plant protection products and require the prioritization of preventative methods. Adherence to IPM principles contributes to the production of healthy and safe food. In Poland, the implementation of IPM into agricultural practice remains a solution to the problem. Furthermore, it is necessary to ensure education and implementation of IPM at the basic or implementation level. The IPM element, particularly emphasized in the 2009/128/EC Directive, is the use of so-called warning systems, tools that address the issue of plant protection application. In this regard, it is necessary to use decision support systems (DSSs). DSSs are digital solutions that integrate meteorological, global, and field data. They include the risk of disease and pest occurrence and the timing of the application. DSSs are not part of the farmer’s experience or presentation but support them in making sound decisions. DSS reduces costs, the side effects of plant protection, and energy consumption. Examples of such solutions in Poland include the eDWIN platform and OPWS, classified, among others, in cereal protection against fungi. The aim of this article is to present the role, capabilities, and limitations of decision support systems in modern agricultural production and their importance in the context of the Green Deal and digital agriculture. Full article

Excessive tailwind, threatening the safety of aircraft takeoff and landing, is one of the prominent research topics in the field of aviation meteorology. This paper analyzes the causes of tailwinds at Beijing Daxing International Airport (BDIA), based on coherent Doppler wind lidar (CDWL) and ERA5 reanalysis data. CDWL with high spatiotemporal resolution is utilized to detect variations in the low-level wind field in the vicinity of airport areas. ERA5 reanalysis data are employed to investigate the distribution characteristics of meteorological elements such as wind fields, pressure, and temperature in the Beijing surrounding regions. The study of two typical tailwind events reveals that frontal activity, through the combined effects of pressure gradient adjustment and topographic constraints from the Taihang Mountains, drives the development of low-level southerly jets. It serves as the key mechanism triggering excessive tailwind. By integrating CDWL and ERA5 data for local and regional analysis, this study contributes to enhancing understanding of tailwind causal mechanisms and provides critical support for aviation meteorological disaster early warning. Full article

With the aggravation of global climate change and the increasing frequency and intensity of extreme weather events, power systems with a high proportion of renewable energy are under threat. In response, in traditional wind–solar–storage–hydrogen multi-energy systems, it is difficult to balance power supply resilience, economy, and environmental protection, and such systems cannot meet actual demand due to the lack of a dynamic meteorological integration mechanism. Therefore, a dynamic collaborative optimization model of a multi-energy system driven by meteorological risk perception is proposed. The dynamic meteorological risk factor integrating various meteorological elements is introduced, and the risk response mechanism is established based on the system’s energy storage state to realize the adaptive adjustment of coupled weight parameters and achieve the goal of collaborative optimization of power supply resilience, economy, and environmental protection. The case analysis results show that, compared with other models, the proposed model can reduce the power supply shortage by 23.1% in extreme weather periods, and the system’s survival probability can reach 97.1% at most. The proposed model minimizes the assembly while ensuring that carbon emissions meet standards, and achieves the collaborative optimization of power supply toughness, economy, and environmental protection. It provides a theoretical tool for solving the collaborative optimization problem that energy systems with a high proportion of renewables face in coping with climate risks. Full article

In the process of revitalizing historic districts, creating a healthy living environment requires a focus on the microclimate comfort of historic districts. Microclimate comfort refers to the comprehensive physiological perception and psychological satisfaction of climate elements such as heat, wind, and humidity under specific local environmental conditions, typically within a spatial range of horizontal scale < 100 m and vertical scale < 10 m. Among these, wind environment quality, as a key factor influencing pedestrian health experiences and cultural tourism appeal, holds particular research value. This study takes the Dabao Island Courtyard District in Qingdao as its subject, employing computational fluid dynamics (CFD) simulation methods from the artificial intelligence (AI) technology framework for modeling. CFD is a numerical method based on computer simulation, which solves fluid control equations (such as the Navier–Stokes equations) through iterative optimization to achieve high-fidelity simulation of physical environments such as airflow, turbulence, and heat transfer. A three-dimensional geometric model of the Dabao Island courtyard district was established, and boundary conditions were set based on local meteorological data. Numerical simulations were conducted to analyze the wind environment before and after the renovation of different layouts, functional spaces, and spatial scales (individual courtyards, clustered courtyards, and surrounding neighborhoods) of the courtyard district. The results indicate that factors such as building layout, street orientation, and renovation strategies significantly influence the wind environment of the Dabao Island neighborhood courtyards, thereby affecting residents’ perceptions of wind comfort. For example, unreasonable building layouts can lead to excessive local wind speeds or vortex phenomena, reducing wind comfort, whereas reasonable renovation and update strategies can facilitate the introduction of wind corridors into the historical courtyard buildings, improving wind environment quality. This study contributes to better protection and utilization of traditional neighborhoods during urban renewal processes, creating a more comfortable wind environment for residents, providing scientific decision-making support for the renovation of historical neighborhoods under the Healthy China strategy, and offering methodological references for wind environment research in other similar traditional neighborhoods. Full article

The vulnerability of regional agricultural systems continues to intensify under the influence of global climate change. Understanding the spatiotemporal variation in meteorological elements and their agricultural response mechanisms has become a critical scientific challenge for ensuring food security. This study focuses on the 852 Farm in the typical area of the albic soil region on the Sanjiang Plain in China. This research integrates multi-source meteorological observations and crop yield data from 2001 to 2024. Using methods such as wavelet analysis, grey relational analysis, and cross-wavelet analysis, this study systematically investigates the dynamic changes and cyclical evolution patterns of key meteorological factors and their impact on the yields of different staple crops. The results indicate that, in terms of trend evolution, air temperature, relative humidity, and surface temperature show no significant upward trend (Z > 0; p > 0.05), while precipitation significantly increases (Z > 0; p < 0.05). Evaporation and sunlight show a nonsignificant downward trend (Z < 0; p > 0.05). The yields of rice, soybean, and corn generally exhibit fluctuating upward trends (Z > 0; p > 0.05). In terms of periodic coupling characteristics, meteorological factors exhibit multi-time-scale oscillations at 22a, 12a, and 8a. The yields of the three staple crops form significant time–frequency couplings with meteorological factors in the 22a and 8a periods. Regarding the correlation, air temperature demonstrates the highest grey correlation degree (γ ≥ 0.8) and strong coherence with crop yields, followed by precipitation and sunlight. These findings provide a theoretical and quantitative basis for understanding the multi-scale interactive mechanisms of climate adaptation in agricultural systems of the albic soil region, as well as for managing and optimizing climate-resilient farming practices. Full article

It has always been a research topic for some meteorologists to design a new and reasonable calculation scheme of the intensity of the Tibetan Plateau (TP) summer monsoon (TPSM). Existing indices are defined based on dynamic factors. However, the intensity of the TPSM can also be influenced by thermal factors. We therefore propose defining a TPMI in terms of horizontal temperature advection within the main body of the TP. This provides a new index that directly quantifies the extent to which the thermal forcing in the TP region regulates the monsoon system. The new index emphasizes the importance of the atmospheric asymmetry structure in measuring TPSM strength, represents the variability of the TPSM circulation system, effectively reflects the meteorological elements, and accurately represents the climate variation. Tropospheric temperature (TT) and TPSM are linked by the new index. These significant centers of correlation are characterized by alternating positive and negative phases along the Eastern European Plain, across the Turan Plain, and into southwestern and northeastern China. The correlation coefficients are found to be significantly out of phase between high and low altitudes in the vertical direction. This research broadens our minds and helps us to develop a new approach to measuring TPSM strength. It can also predict extreme weather events in advance based on TPMI changes, providing a scientific basis for disaster warnings and the management of agriculture and water resources. Full article