Effects Of Weather Research Articles

Incorporating weather in counts and trends of migrating Common Nighthawks.

Effective conservation planning for species of concern requires long-term monitoring data that can accurately estimate population trends. Supplemental or alternative methods for estimating population trends are necessary for species that are poorly sampled by traditional breeding bird survey methods. Counts of migrating birds are commonly used to assess raptor population trends and could be useful for additional taxa that migrate diurnally and are difficult to monitor during the breeding season. In North America, the Common Nighthawk (Chordeiles minor) is challenging to detect during comprehensive dawn surveys like the North American Breeding Bird Survey and is considered a species of conservation concern because of steep population declines across its range. We conducted standardized evening counts of migrating Common Nighthawks at a fixed survey location along western Lake Superior each autumn from 2008 to 2022. To document peak migration activity, counts spanned ~3 hours each evening from mid-August to early September for a mean of 19.4 ± 2.4 days. These count data were then used to assess the effects of weather on daily counts and high-count days and to calculate population trends over this 15-year period. We used generalized linear mixed effects models to determine the relationship between daily counts and high-count days (i.e., ≥1000 migrating nighthawks) and weather variables. Additionally, using our 15-year dataset, we calculated a geometric mean passage rate that accounted for annual differences in weather to estimate count trends. Annual counts averaged ~18,000 (min = 2514, max = 32,837) individuals and high-count days occurred 56 times throughout the course of the study. Model results indicated lighter, westerly winds and warmer temperatures were associated with higher daily counts and greater probability of a large migratory flight. Results from the trend analyses suggest stable or non-significantly increasing trends for Common Nighthawks during this monitoring period; however, the trend models explained a relatively low percentage of the variation in the counts. Results from a power analysis suggest that continued monitoring efforts and adjustments with weather covariates will be necessary to effectively use visible migration count data to estimate Common Nighthawk trends. Establishing annual monitoring programs that use standardized visual counts to document Common Nighthawk migration at key sites across North America may provide supplemental information useful for population trend estimates of this species. Therefore, we advocate for the use of visible migration counts to monitor Common Nighthawks in North America and emphasize the value of long-term monitoring efforts.

Situation Model of the Transport, Transport Emissions and Meteorological Conditions

Air pollution in cities and the possibilities of reducing this pollution represent one of the most important factors that today’s society has to deal with. This paper focuses on a systemic approach to traffic emissions with their relation to meteorological conditions, analyzing the effect of weather on the quantity and dispersion of traffic emissions in a city. Using fuzzy inference systems (FIS) the model for predicting changes in emissions depending on various conditions is developed. The proposed model is based on traffic, meteorology and emission data measured in Prague, Czech Republic. The main objective of the work is to provide insight into how urban planners and policymakers can plan and manage urban transportation more efficiently with environmental protection in mind.

Wind farm noise prediction and auralization

This work presents the application and validation of a novel auralization approach for the evaluation of wind turbine noise annoyance under diverse conditions. The approach is based on the decomposition of each turbine blade into elementary short-segment sources, whose acoustic radiation in the far field is obtained by coupling Amiet’s emission model with the Harmonoise engineering model for outdoor sound propagation. The transfer functions between the elementary source positions and receivers are obtained. Then, the average and instantaneous sound pressure levels are calculated over one blade rotation. The realism of the audio signals is evaluated through listening tests with audio signals of the real and simulated environments. The predicted noise spectra from five wind turbines capture well the measured trends and the absolute levels. Finally, we present a study of the weather effects on noise emissions and propagation by using the numerical model developed.

Experimental study of the weather effects on LoRa-based vehicular communications

Experimental study of the weather effects on LoRa-based vehicular communications

Dependences of Energetic Neutral Atoms Energy on the Solar Wind Energy and Solar Zenith Angle Observed by the Chang’E-4 Rover

Solar wind can directly interact with the lunar surface and bring a space weathering effect. Some solar wind protons can be scattered as energetic neutral atoms (ENAs), which include rich information of the solar wind–surface interaction. However, people still know little about the ENA truth on the lunar ground due to the lack of in situ measurements. Different from the previous in-orbit measurements, here we present the first ground-based ENA measurements by the Chang’E-4 rover and find a good correlation between the mean ENA energy and the solar wind energy. Moreover, the loss rate of ENA energy can strongly depend on both the solar wind energy and the solar zenith angle (SZA), in which the energy loss rate can be enhanced by 73% when the solar wind energy increases from 400 to 1400 eV and can be reduced by 32% when the SZA increases from 57° to 71°. Combined with numerical simulations by SDTrimSP code, we propose that the solar wind protons can penetrate deeper into the lunar surface with a longer path length when the solar wind energy is higher or the SZA is lower, which results in a larger energy loss rate for the scattered ENAs. Our results provide an important constraint for the solar wind–surface research and have general implications in studying the surficial space weathering of the Moon and other airless bodies.

Exploring the Application of Large-Scale Pre-Trained Models on Adverse Weather Removal.

Image restoration under adverse weather conditions (e.g., rain, snow, and haze) is a fundamental computer vision problem that has important implications for various downstream applications. Distinct from early methods that are specially designed for specific types of weather, recent works tend to simultaneously remove various adverse weather effects based on either spatial feature representation learning or semantic information embedding. Inspired by various successful applications incorporating large-scale pre-trained models (e.g., CLIP), in this paper, we explore their potential benefits for leveraging large-scale pre-trained models in this task based on both spatial feature representation learning and semantic information embedding aspects: 1) spatial feature representation learning, we design a Spatially Adaptive Residual (SAR) encoder to adaptively extract degraded areas. To facilitate training of this model, we propose a Soft Residual Distillation (CLIP-SRD) strategy to transfer spatial knowledge from CLIP between clean and adverse weather images; 2) semantic information embedding, we propose a CLIP Weather Prior (CWP) embedding module to enable the network to adaptively respond to different weather conditions. This module integrates the sample-specific weather priors extracted by the CLIP image encoder with the distribution-specific information (as learned by a set of parameters) and embeds these elements using a cross-attention mechanism. Extensive experiments demonstrate that our proposed method can achieve state-of-the-art performance under various and severe adverse weather conditions. The code will be made available.

Spring haul-out behavior of seals in the Bering and Chukchi Seas: implications for abundance estimation.

Ice-associated seals rely on sea ice for a variety of activities, including pupping, breeding, molting, and resting. In the Arctic, many of these activities occur in spring (April through June) as sea ice begins to melt and retreat northward. Rapid acceleration of climate change in Arctic ecosystems is therefore of concern as the quantity and quality of suitable habitat is forecast to decrease. Robust estimates of seal population abundance are needed to properly monitor the impacts of these changes over time. Aerial surveys of seals on ice are an efficient method for counting seals but must be paired with estimates of the proportion of seals out of the water to derive population abundance. In this paper, we use hourly percent-dry data from satellite-linked bio-loggers deployed between 2005 and 2021 to quantify the proportion of seals hauled out on ice. This information is needed to accurately estimate abundance from aerial survey counts of ice-associated seals (i.e., to correct for the proportion of animals that are in the water, and so are not counted, while surveys are conducted). In addition to providing essential data for survey 'availability' calculations, our analysis also provides insights into the seasonal timing and environmental factors affecting haul-out behavior by ice-associated seals. We specifically focused on bearded (Erignathus barbatus), ribbon (Histriophoca fasciata), and spotted seals (Phoca largha) in the Bering and Chukchi seas. Because ringed seals (Phoca (pusa) hispida) can be out of the water but hidden from view in snow lairs analysis of their 'availability' to surveys requires special consideration; therefore, they were not included in this analysis. Using generalized linear mixed pseudo-models to properly account for temporal autocorrelation, we fit models with covariates of interest (e.g., day-of-year, solar hour, age and sex class, wind speed, barometric pressure, temperature, precipitation) to examine their ability to explain variation in haul-out probability. We found evidence for strong diel and within-season patterns in haul-out behavior, as well as strong weather effects (particularly wind and temperature). In general, seals were more likely to haul out on ice in the middle of the day and when wind speed was low and temperatures were higher. Haul-out probability increased through March and April, peaking in May and early June before declining again. The timing and frequency of haul-out events also varied based on species and age-sex class. For ribbon and spotted seals, models with year effects were highly supported, indicating that the timing and magnitude of haul-out behavior varied among years. However, we did not find broad evidence that haul-out timing was linked to annual sea-ice extent. Our analysis emphasizes the importance of accounting for seasonal and temporal variation in haul-out behavior, as well as associated environmental covariates, when interpreting the number of seals counted in aerial surveys.

Seamlessly combined historical and projected daily meteorological datasets for impact studies in Central Europe: The FORESEE v4.0 and the FORESEE-HUN v1.0

The FORESEE is an open access, climatological database for Central Europe containing observed and projected meteorological data for the 1951–2100 period. As a climate service, FORESEE disseminates basic meteorological variables at a daily time step with a 0.1° × 0.1° spatial resolution including maximum/minimum temperature, precipitation, incoming shortwave solar radiation and daylight vapour pressure deficit. The future climate in FORESEE v4.0 and FORESEE-HUN v1.0 is projected by 14 regional climate models from the EURO-CORDEX database using the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. Based on RCP4.5 the country-specific results indicate similar projected mean changes in annual mean temperature (1.5–1.7 °C) but considerable differences in precipitation (from −1.6 to 6.9%) in the region for 2071–2100 relative to 1991–2020. We present two case studies to demonstrate the applicability of FORESEE in climate change impact studies using the ensemble approach. Climate change induced negative weather effect (15.4% and 28.9% mean loss for 2071–2100 according to RCP4.5 and RCP8.5, respectively) might dominate the future winter wheat yields in Hungary that is superimposed to the overall trend determined by other factors. The projections provide consistent results about the mean advance in the start of the growing season for forests in Hungary up to 2100 with ensemble mean of 9.1 days (RCP4.5) and 19.8 days (RCP8.5). We also demonstrate that the representative model selection method might lead to misleading results in impact studies that should be considered. The updated FORESEE is a way forward in the dissemination of policy-relevant essential climate data in Central Europe.

Robust and Autonomous Space Weather Charge Mitigation Coatings

National Space Weather Strategy and Action plan calls for the need to enhanceProtection of National Security, Homeland Security, and Commercial Assets and Operations against Effects of Space Weather. Extreme space weather event like solar flares, cosmic rays, and radiation belts cause ionizing radiation that can damage electronics, solar arrays, and optical systems on satellites reducing their functionality and lifetimes, by inducing an ionic charge on the spacecraft’s surface, when a spacecraft fly in and out of the ionosphere. This negative charge buildup can lead to ion sputtering/arcing, and producing irreparable damage in spacecraft components. Therefore, the local application of materials systems that can passively mitigate the negative charge build up by emitting the electron back into space, while improving resistance to erosion during ion sputtering is of interest. Accordingly, Faraday Technology is developing a low-cost, efficient and scalable manufacturing process for the local deposition of lightweight passive highly emissive and erosion resistant coating onto spacecraft viable substrates that can mitigate charging and erosion effects from ionizing radiation. The composite coating showed a ~1500% increase in maximum (Emax) total electron yield over bare aluminum, extending by 4 times the range of electron yields between crossover energies >1, and demonstrated the potential for erosion resilience in modeled International Space Station plasma erosion conditions. The composite coating could be applied to various spacecraft platforms include spacecraft skin, solar arrays, circuit boards, and emitters such that their lifetime, effectiveness and durability within LEO/GEO environments events can be enhanced. Acknowledgements:The financial support of NASA SBIR/STTR program through contract No.80NSSC22PB020 is acknowledged.

EXTREME WEATHER AND HEALTH AMONG OLDER POPULATIONS: INDIVIDUAL AND CONTEXTUAL-LEVEL VULNERABILITY AND RESILIENCE

Abstract Intense, frequent extreme weather events pose a significant public health threat, particularly for middle-aged and older adults who may be at elevated health risk. Yet, the social and environmental factors that determine their vulnerability and resilience remain largely unexplored. This study investigates individual and contextual determinants associated with exposure to and the health effects of extreme weather. Data were from the 2021 California Health Interview Survey of adults aged 50+ (N=14,726). Respondents were asked whether they had experienced any hazardous weather events such as heat waves, floods, and wildfires in the past two years and whether mental or physical health was harmed by these events. About 53% were exposed to extreme weather events. Among the exposed group, 18% and 17% reported harm to mental and physical health, respectively. Logistic regression analysis revealed increased exposure risk among middle-aged adults (age 50-64), those with chronic conditions, people living alone, and residents of rural and unsafe neighborhoods. Similarly, mental and physical health harms were more prevalent among these groups, along with females and those with unstable housing conditions. Conversely, living in cohesive neighborhoods was identified as a resilient factor, associated with reduced mental (OR=0.78, p< 0.05) and physical health risks (OR=0.70, p< 0.01). This study reveals pronounced vulnerabilities to climate change risks among populations identified as socioeconomically disadvantaged. Moreover, the findings emphasize the role of contextual conditions in shaping vulnerability and resilience. Our study contributes valuable insights to develop targeted climate change mitigation strategies, fostering resilience among older populations and supportive communities.

Weather influences survival probability in two coexisting mammals directly and indirectly via competitive asymmetry.

Ecologists have studied the role of interspecific competition in structuring ecological communities for decades. Differential weather effects on animal competitors may be a particularly important factor contributing to the outcome of competitive interactions, though few studies have tested this hypothesis in free-ranging animals. Specifically, weather might influence competitive dynamics by altering competitor densities and/or per-capita competitive effects on demographic vital rates. We used a 9-year data set of marked individuals to test for direct and interactive effects of weather and competitor density on survival probability in two coexisting mammalian congeners: Columbian ground squirrels (Urocitellus columbianus) and northern Idaho ground squirrels (Urocitellus brunneus). Ambient temperature and precipitation influenced survival probability in both species, but the effects of weather differed between the two species. Moreover, density of the larger Columbian ground squirrel negatively impacted survival probability in the smaller northern Idaho ground squirrel (but not vice versa), and the strength of the negative effect was exacerbated by precipitation. That is, cooler, wetter conditions benefited the larger competitor to the detriment of the smaller species. Our results suggest weather-driven environmental variation influences the competitive equilibrium between ecologically similar mammals of differential body size. Whether future climate change leads to the competitive exclusion of either species will likely depend on the mechanism(s) explaining the coexistence of these competing species. Divergent body size and, hence, differences in thermal tolerance and giving up densities offer potential explanations for the weather-dependent competitive asymmetry we documented, especially if the larger species competitively excludes the smaller species from habitat patches of shared preference via interference.

Reliability evaluation of radial distribution system considering common mode failures and different weather effects

Reliability evaluation of distribution systems plays a crucial role in ensuring the uninterrupted supply of electricity to consumers. This paper presents a comprehensive analysis of distribution system reliability using the Failure Mode and Effects Analysis (FMEA) technique. The study focuses on evaluating the reliability of the distribution system considering various failure modes, including busbar failure, section failure, distributor failure, transformer failure, maintenance-related issues, transient failures, and the impact of weather conditions. The findings of this research can assist utilities and system operators in identifying critical failure modes and implementing appropriate measures to enhance the reliability of distribution systems, ensuring continuous and reliable electricity supply to consumers.

Climate Change Impact on Corrosion of Reinforced Concrete Bridges and Their Seismic Performance

As a consequence of climate change impact, a significant variation in terms of temperature, atmospheric humidity, and carbon dioxide concentration levels is happening. This condition leads to several negative effects on the safety and the life cycle of existing concrete structures, such as the increase in the rate of material degradation, due to corrosion phenomena. In fact, the presence of carbonation and corrosion phenomena significantly influence the load-bearing capacity of existing reinforced concrete (RC) structures, under both static and dynamic loads. Among the wide range of existing RC constructions, bridges stand out for their importance. Furthermore, as structures directly exposed to the weather effects, they are more susceptible to these phenomena. In this paper, the influence of corrosion on existing RC motorway viaducts’ seismic behavior, considering the impact of climate change, is investigated, by means of an efficient procedure based on the implementation of 3D simplified finite element models and the use of analytical relations to obtain the amount of reduction in the steel reinforcement area as a function of the age of the bridge and of the different corrosion scenarios analyzed. Several scenarios for the expected variations in CO2 concentrations, temperature, and relative humidity are evaluated, considering that most of the viaducts present in the Italian motorway network were built between the 1960s and the 1970s. The results obtained using the projection of climate change impacts are compared with those calculated considering the corrosion scenarios resulting from the DuraCrete research project, to understand if the evolution of climate change leads to worse scenarios than those previously assessed.

Impact of Climate Change in Physical Activity and Competitive Sports: Adaptive Measures and Evaluating Future Impacts in Arunachal Pradesh, India

The aim of this paper is to make a detailed study on climate change's impacts on physical activity and organized competitive sports with further attention paid to their adaptation efforts and evaluating the future impacts with special reference to Arunachal Pradesh, India. Linkages between climate and human activity cannot be ignored and it is a universal phenomenon and is certainly possible due to adaptations. These adaptations have direct linkage with physical, mental, emotional, social and overall wellbeing of human beings. Ignoring the degree of adaptation could impact the health upto severe consequences due to climate change. The relationship between sport and environment has to be examined to understand how environment and climatic parameters impacts sport in terms of training, performance and sports injuries. Arunachal Pradesh is a hub of youth potentials especially in sports. Looking at the present climatic crisis, the study aims to assess the impacts of climate change, and measures to be taken by organized competitive sport entities to adapt to the impacts. The study adopts a descriptive analysis including both qualitative and quantitative assessment by exploring secondary information. The findings of the study states that most of the outdoor sport activities especially endurance sports are strongly influenced by meteorological parameters. The effects of weather on sports are varied, performances can get reduced or improved, becomes very severe during extreme weather conditions leading to threat for life. If climate change progresses in scope and severity as predicted, no doubt physical activity and outdoor organized competitive sports is under threat. The valence of this paper lies in its conceptualization of the climate vulnerability on sport activities and its potential to inspire future research and interest in this domain. However, it is important for government, agencies, sports organizations, coaches, athletes, environmentalists, and health experts to have the tools to identify the risks and understand their vulnerabilities.

Examining the Heat Health Burden in Australia: A Rapid Review

Extreme heat has been linked to increased mortality and morbidity across the globe. Increasing temperatures due to climatic change will place immense stress on healthcare systems. This review synthesises Australian literature that has examined the effect of hot weather and heatwaves on various health outcomes. Databases including Web of Science, PubMed and CINAHL were systematically searched for articles that quantitatively examined heat health effects for the Australian population. Relevant, peer-reviewed articles published between 2010 and 2023 were included. Two authors screened the abstracts. One researcher conducted the full article review and data extraction, while another researcher randomly reviewed 10% of the articles to validate decisions. Our rapid review found abundant literature indicating increased mortality and morbidity risks due to extreme temperature exposures. The effect of heat on mortality was found to be mostly immediate, with peaks in the risk of death observed on the day of exposure or the next day. Most studies in this review were concentrated on cities and mainly included health outcome data from temperate and subtropical climate zones. There was a dearth of studies that focused on tropical or arid climates and at-risk populations, including children, pregnant women, Indigenous people and rural and remote residents. The review highlights the need for more context-specific studies targeting vulnerable population groups, particularly residents of rural and remote Australia, as these regions substantially vary climatically and socio-demographically from urban Australia, and the heat health impacts are likely to be even more substantial.

Calamitous weather, yield risk and mitigation effect of harvest mechanisation: Evidence from China's winter wheat

AbstractStable agricultural production has been substantially challenged by increasingly frequent calamitous weather conditions. For winter wheat, continuous precipitation during the harvest season is particularly detrimental. This study utilises a county‐level panel dataset of agricultural production in China for the period of 1998–2016 to evaluate the impact of continuous precipitation on the downside risk of winter wheat yield. Results show that continuous precipitation during the harvest season remarkably increases the downside risk of winter wheat yield. At the same time, the progressive adoption of harvest machinery in recent decades has effectively mitigated the downside risk of winter wheat yield driven by continuous precipitation. The mitigation effects of harvest mechanisation are more pronounced for plain areas with better‐developed transportation infrastructure.

DESCRIPTION OF A COLLECTION OF SALVIA SCLAREA L. IN TERMS OF ITS BIOCHEMICAL PROPERTIES

The study object is the accumulation of essential oil in the inflorescences of clarysage, the content of its main components and the sclareol yield. The study purpose is to analyze a collection of clarysage (112 specimens) in terms of the basic biochemical properties (the essential oil content in raw material, its chemical composition and the sclareol yield) and to identify the specimens showing good prospects for inclusion in the breeding process. The study was carried out in 2018–2020 at the experimental plot of the Research Institute of Agriculture of Crimea located in the piedmont region of Crimea (KrymskayaRoza village, Belogorsk district). The climate is moderate continental. The average year-round temperature is +10 °С. The average year-round air humidity is 70%, the hydrothermic factor is 0.91. The accounting and analyses were performed in accordance with the techniques developed. The study revealed higher degree of genetic determination of the essential oil buildup in plants as compared to the weather effect. As noted, increased precipitation and extremely high temperatures during the plant flowering and seed formation time affect negatively the sclareol buildup. The variability of the properties analyzed (Cv=7.8–23.4%) bears evidence to a feasibility of selecting promising parent material for breeding. Based on the outcomes of the collection analysis there have been isolated 12 specimens leaving behind the varieties cultivated in terms of the basic biochemical properties including five specimens with a high mass fraction of essential oil – 0.90–1.06% on the dry basis (as compared to 0.6–0.88% in the varieties cultivated) and seven specimens with a high sclareol content in raw material – 2.00–2.35% (as compared to 1.58–1.71% in the varieties cultivated).

Modeling and detection of low-altitude flight conflict network based on SVM

With the continuous increase in low altitude flight density, the issue of low altitude navigation safety has attracted widespread attention. Due to the complex low altitude environment, low altitude flight is more susceptible to ground obstacles and weather effects than commercial aviation. In order to ensure the flight safety of helicopters in low altitude airspace, this paper proposes an improved support vector machine based flight conflict detection model. By modeling the conflict network in low altitude flight areas and utilizing Support Vector Machine (SVM) classification features, the safety discrimination of low altitude flight was achieved, ultimately achieving the safety of aircraft in low altitude flight. This article adopts a protected area model that considers the shape of the aircraft as a conflict zone. In order to reduce the complexity of the conflict detection model, an improved ID3 decision tree algorithm and random forest are used to reduce the complexity of the classifier. The study solved the saturation problem of S-type functions in conflict detection models by using more sensitive functions for probability mapping. And use intelligent optimization algorithms to pre train key parameters, achieving efficient conflict detection suitable for low altitude flight.

Economic impacts of climate change on EU agriculture: will the farmers benefit from global climate change?

This paper analyses how climate change might impact EU agricultural markets by mid-century, considering a large ensemble of climate change projections from different models, market adjustments and trade feedbacks. Applying consistent climate change driven productivity shocks to a global multi-commodity agricultural market model we show that the negative direct effects from climate change on crop production in the EU could be offset by market and trade adjustments. The simulations reveal that climate change has heterogeneous impacts across regions. EU farming sector, in particular, might actually benefit from climate change as the impacts on agricultural productivity are expected to be more severe in important non-EU production regions such as US, Russia and Ukraine, depending on the crop. Higher producer prices for important crops such as wheat, barley, grain maize, rice and soybeans, lead to an increase in EU production and exports. For instance EU wheat production could increase by 13% and exports by 28%, with 19% higher farm incomes on average than in a business-as-usual situation. Our study has several limitations. In particular, we do not consider CO2 fertilization effects and direct effect from climate change on livestock sector, climate variability and extreme weather effects. Notwithstanding, our findings highlight the heterogeneity of climate change impacts across regions, specifically Northern versus Southern Europe, and the importance of market and trade adjustments as economic adaptation mechanisms to climate change.

Duskywings (Erynnis: Hesperiidae) of Roxborough State Park, Colorado USA: Possible Weather and Biotic Effects on Abundance 2018–2022

Duskywings (Erynnis: Hesperiidae) of Roxborough State Park, Colorado USA: Possible Weather and Biotic Effects on Abundance 2018–2022