Search Results (972)

Previous studies have suggested that Earth’s annual cycle of modern climate provides information relevant to orbital-scale climate variability, since both are driven by solar insolation changes determined by orbital geometry. However, there has been no systematic assessment of the climate response to annual-scale insolation changes in climate models, leading to large uncertainty in orbital-scale simulation. In this study, we evaluate the Northern Hemisphere land surface air temperature response to the annual insolation cycle in the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. A polynomial transfer framework reveals that CMIP6 models broadly capture the observed 20–30-day lag between insolation and temperature, indicating realistic land thermal inertia. However, CMIP6 models consistently overestimate temperature sensitivities to insolation, with particularly strong biases over mid-latitude and high-latitude regions in summer and winter, respectively. Applying the annual-scale polynomial transfer framework to the middle Holocene (~6000 years ago) shows that models with the highest sensitivity simulate significantly larger seasonal temperature anomalies than the lowest-sensitivity models, underscoring the impact of modern biases on orbital-scale paleoclimate simulations. The results highlight systematic overestimation of temperature–insolation sensitivity in CMIP6 models, emphasizing the importance of constraining seasonal sensitivity for robust orbital-scale climate modeling. Full article

Carpomya vesuviana (Diptera: Tephritidae), a significant invasive forestry pest of Zizyphus crops worldwide, has spread globally across jujube-growing regions, causing substantial yield losses and economic damage. In China, it is classified as both an imported and forestry quarantine pest. Existing risk assessments have primarily focused on the potential geographical distributions (PGDs) of C. vesuviana, but its economic impact on host plants is unknown. Therefore, we used an optimised MaxEnt model based on species distribution records and relevant environmental variables to predict the PGDs of C. vesuviana under current and future climate scenarios. Meanwhile, we used the @RISK stochastic model to assess the economic impact of this pest on the Chinese jujube industry under various scenarios. The results showed that the human influence index (HII), mean temperature of the wettest quarter (Bio8), temperature seasonality (Bio4), and precipitation during the driest month (Bio14) were the significant environmental variables affecting species distribution. Under the current climatic scenario, the total suitable area of C. vesuviana reached 2171.39 × 10⁴ km², which is mainly distributed in southern and western Asia, southern Europe, central North America, western Africa, and eastern South America. Potentially suitable habitats will increase and shift to the middle and high latitudes of the Northern Hemisphere under future climatic scenarios. Under the no-control scenario, C. vesuviana could cause losses of 15,687 million CNY to the jujube industry in China. However, control measures could have saved losses of 5047 million CNY. This study provides a theoretical basis for preventive monitoring and integrated management of C. vesuviana globally and helps reduce its economic impact on the jujube industry in China. Full article

We present three dimensional particle-in-cell simulations of current-voltage characteristics of the hemispherical Langmuir probe (LAP), onboard the China Seismo-Electromagnetic Satellite (CSES). Using realistic plasma parameters and background magnetic fields obtained from the International Reference Ionosphere (IRI) and International Geomagnetic Reference Field (IGRF) models, we simulate probe–plasma interactions at three locations: the equatorial region and two magnetically conjugate mid-latitude sites: Millstone Hill (Northern Hemisphere) and Rothera (Southern Hemisphere). The simulations, performed using the PTetra PIC code, incorporate realistic LAP geometry and spacecraft motion in the ionospheric plasma. Simulated current voltage characteristics or I–V curves are compared against in-situ LAP measurements from CSES Orbit-026610, with Pearson’s correlation coefficients used to assess agreement. Our findings indicate how plasma temperature, density, and magnetization affect sheath structure and probe floating potential. The study highlights the significance of kinetic modeling in enhancing diagnostic accuracy, particularly in variable sheath regimes where classic analytical models such as the Orbital-Motion-Limited (OML) theory may be inadequate. Full article

This study aims to create environmentally comfortable building designs in hot and dry steppe climates using more effective approaches. The purpose of this study is to assess the relationship between mean radiant temperature (MRT) and indoor air temperature (Tia), taking into account the orientation of buildings, for better building thermal performance. For this purpose, residential buildings with different orientations were selected in the study region ‘Garmian—northern Iraq’, and their thermal performance was evaluated. The results show how MRT contributes to the buildings’ thermal comfort. The outcomes of this research provide innovative empirical quantification of the correlation of MRT-Tia, as the regression coefficient (β) represents the rate of change in Tia per unit increase in MRT and ranges by orientation in the study area. The findings demonstrate that north-facing buildings buffer radiant heat gain (β~0.52), resulting in a 0.5 °C increase in indoor air temperature for each 1 °C rise in MRT. Moreover, west orientation delivers promising winter passive heating (MRT up to 22 °C and indoor air temperature up to 22.8 °C with a β of ~0.82). However, south-facing buildings perform poorly in the winter, with low MRT and a weak β (~0.44), contrasting with passive solar design strategies that favor south-facing buildings in the northern hemisphere. Furthermore, in the summer, the MRT is always higher than Tia, while it is lower in winter, indicating poor envelope and fenestration thermal insulation properties, which lead to excessive energy usage to maintain thermal comfort. Finally, the study suggests the novel quantified MRT-Tia mathematical correlation responds to the orientations for such climates, offering both diagnostic and predictive tools for thermal comfort performance optimization. This study is the first to empirically quantify orientation-specific MRT–Tia relationships in BSh climates, offering a novel diagnostic tool for sustainable building design. This study involved field observations in 36 residential row houses across four orientations. Key environmental and personal variables measured included mean radiant temperature (MRT), indoor air temperature (Tia), air velocity, relative humidity, metabolic rate, and clothing insulation. Full article

Accurate wind measurements in the mesosphere and lower thermosphere (MLT) region are essential for climate modeling, satellite drag estimation, and space weather prediction. This study presents a comprehensive comparison and correlation analysis of the zonal and meridional wind observations from co-located meteor radar and medium-frequency (MF) radar systems in Kunming (102.1°E, 24.2°N), China, in the year 2022. Both zonal and meridional wind components were analyzed within the overlapping altitude range of 70–100 km. Statistical distributions of the wind speeds from both radars followed a near-Gaussian pattern concentrated within ±100 m/s, indicating good consistency. A joint dataset was constructed for the 78–100 km range, where over 2000 h of concurrent observations were available. The strongest correlation between the wind speed measurements of the two radars was ~0.6, which occurred near 82–84 km. Seasonal analysis further indicated better consistency in the winter and spring months, while the summer months exhibited reduced correlations, especially for zonal wind measurements. Systematic biases between the two instruments were also identified, with minimal intercept offsets observed from April to October. This study is valuable in the development of high-quality, long-term MLT wind field datasets for atmospheric research and numerical model validation. Full article

Dengue, caused by the dengue virus (DENV), is rapidly expanding its geographical footprint, with increasing incidence not only in over 100 endemic countries in the southern hemisphere but also with more autochthonous transmissions now reported in the northern hemisphere, including regions of Europe and the United States. The clinical presentation of DENV infection ranges from mild febrile illness to severe and potentially fatal conditions, such as dengue hemorrhagic fever (DHF), dengue shock syndrome (DSS), and diverse neurological complications. While vaccine development efforts are underway, significant challenges remain, underscoring the urgent need for a deeper understanding of the virus. This urgency is particularly palpable in Brazil, which has faced an unprecedented surge in dengue cases during the 2024–2025 period. The country has recorded an alarmingly high number of infections and related deaths, stretching its public health infrastructure and highlighting the complex interplay of climate change, urbanization, and viral dynamics in disease propagation. This review provides a global perspective on dengue, systematically exploring its history, morphology, viral cycle, pathogenesis, and epidemiology. By integrating these critical aspects, this article aims to identify pivotal knowledge gaps and guide future research directions essential for developing improved public health interventions against this complex and evolving disease. Full article

The warmer air resulting from climate change reduces the lift force on a departing aircraft, potentially reducing its climb angle and causing more engine noise near the airport. Here, we study this phenomenon at a selection of 30 European airports in northern hemisphere summer (June–July–August). We first formulate and verify a low-complexity model of noise propagation around airports, although we emphasise that our high-level results do not explicitly depend on this agreement. The model includes anisotropic noise propagation, atmospheric absorption, and the ability to model the noise emissions from multiple engines. We study the Airbus A320, but the method could be straightforwardly generalised to other aircraft. We refer to the model as an emulator since (using Latin hypercube parameter sampling) it mimics a more comprehensive model against which it is verified. The model is used to calculate the area enclosed by the 50 dB SPL (sound pressure level) contour, $A_{50}$, which agrees well with a similar metric (using the day–evening–night sound level, $L_{\mathrm{den}}$) from the verification target, $\mathcal{A}$. Using temperature and pressure data from IPCC simulations of future climate, and using a straightforward relation between climb angle and air density, we assess how climate change could affect climb angles by mid-century (2035–2064). The value of $A_{50}$ is obtained by efficiently covarying (1) the engine noise at 10 m from the engines and (2) the climb angle under ‘historical’ conditions (1985–2014). The median values (across 10 climate models) of climb angle reduction in the future warmer climate are around 1–3% (depending on the airport and climate model used), but individual days can show values as high as 7.5% for the most extreme warming scenarios. By considering the variation in the absorption coefficient of the air with frequency, we find that the number of people affected by noise pollution could increase by up to 4%—as much as 2500 people for the most highly populated areas—by mid-century and that these changes are maximised for the most damaging and psychologically ‘annoying’ (low) frequencies. Full article

In this study, Copernicus Atmosphere Monitoring Service (CAMS) reanalysis data (EAC4 & EGG4) are used. To capture short-term variations and analyze long-term changes in CO₂ and CH₄, this study focuses on two specific regions of interest in each of three European countries: Greece, Italy, and France. Both CO₂ and CH₄ exhibit a positive trend with seasonally averaged increases of over 6% and 2%, respectively, compared to the reference period 2003–2013. Enhanced CH₄ concentrations in Greece are observed during winter, primarily linked to anthropogenic sources such as fossil fuel combustion, heating, industrial activities, and gas distribution. Additionally, positive CH₄ residuals exceeding 0.6% were detected in autumn, likely due to regional agricultural activities in N. Greece and/or wildfires in Athens. Winter, spring, and autumn are the seasons during which CH₄ concentrations are typically highest in the Basilicata and Po Valley regions of Italy, primarily due to agricultural activities, waste management processes, and natural gas extraction, particularly in the Val d’Agri region. Higher CH₄ variability was found during winter in France. Regarding CO₂, all countries show a large diurnal variability (approximately ± 2 ppm), that of a typical mid-northern-hemisphere site, largely associated with the biospheric cycle of photosynthesis and enhanced by anthropogenic emissions and wildfire episodes. Full article

Boreal summer intraseasonal oscillation (BSISO) is highly related to summer monsoon activities, tropical cyclones, flood disasters, and other extreme weather events in the Northern Hemisphere. The propagation of BSISO has considerable complexity. The apparent heat source (Q₁) is the heat generated by radiation, heat conduction, and latent heat release, and their anomalies significantly affect the atmospheric circulation and relevant precipitation. We selected 27 significant events from 30- to 60-day Q₁ anomalies in the northeast Arabian Sea (12–22° N, 66–76° E). K-means cluster analysis was used to further divide significant events into 19 Type-I events and 8 Type-II events. In the equatorial region, the Type-I events have continuous eastward propagation, while the Type-II events have no significant eastward propagation features before −10 days. In East Asia, the northward propagation of the Type-I events is significant and continuous, while there is no northward propagation of the Type-II events. The moisture analyses show that the horizontal advection term plays the most important role in the propagation of convection in most regions. The evaporation term of the Type-I events also plays a significant role in East Asia, and may be related to the difference between the two types of events there. Full article

Amelanchier Medik. (Rosaceae) is a genus of perennial, deciduous shrubs and trees distributed across temperate and boreal regions of the Northern Hemisphere. Traditionally, Native American communities used fruits, leaves, bark, and roots to treat digestive ailments, fevers, colds, inflammation, and to promote general well-being. Scientific investigation began with molecular studies in 1946 and phytochemical research in 1978, with research activity on some Amelanchier species increasing substantially between 2010 and 2025. Fruits are rich in phenolic compounds—particularly flavonoids and anthocyanins—along with triterpenes, carotenoids, vitamins, and minerals. Pharmacological studies of selected species report antioxidant, anti-inflammatory, anticancer, antidiabetic, antibacterial, and antiviral activities. Despite extensive chemical profiling in several members of the genus, the biological and toxicological properties of Amelanchier remain insufficiently explored, and clinical evidence is lacking. This review synthesizes recent findings on the phytochemistry, medicinal applications, and biological effects of Amelanchier species, linking traditional knowledge with modern research and highlighting priorities for future biomedical investigation. Full article

In 2021, the IPCC published new sea level projections. For the first time, the projections gave insight into expected relative sea level rise locally. A prudent designer of coastal infrastructure will want to know how the local projections compare to local observations. That comparison, to date, has not been made. We compared local projections and observations regarding the rate of rise in 2020. We used two datasets with local sea level information all over the globe. In both datasets, we found approximately 15% of the available sets suitable to establish the rate of rise in 2020. Geographic coverage of the suitable locations is poor, with the majority of suitable locations in the Northern Hemisphere. Latin America and Africa are severely under-represented. Statistical tests were run on all selected datasets, taking acceleration of sea level rise as a hypothesis. In both datasets, approximately 95% of the suitable locations show no statistically significant acceleration of the rate of sea level rise. The investigation suggests that local, non-climatic phenomena are a plausible cause of the accelerated sea level rise observed at the remaining 5% of the suitable locations. On average, the rate of rise projected by the IPCC is biased upward with approximately 2 mm per year in comparison with the observed rate. Full article

We evaluated the impact of environmental variability on lobster Panulirus argus and Panulirus laevicauda resources in the waters off Brazil and southern Cuba. This study also covered aspects of larval recruitment associated with the availability of fishing resources in the Southern and Northern Hemispheres. Satellite-generated environmental data were sampled from 18 stations, 6 of which were in the sea off southern Cuba, 6 of which were in the coastal region of Brazil, and 6 of which were offshore near Brazil, covering important lobster fishing grounds and phyllosoma-rich areas of ocean surface circulation along the offshore boundary. The Southern Oscillation Index (SOI) was used to quantify the global ocean–atmosphere variability. Other environmental parameters included in the analysis were the monthly coastal sea levels, surface temperature (SST), salinity, wind/current speed, chlorophyll-a (Chl-a) concentrations, rainfall (RF), and Amazon River discharge (ARD). Variations in the level of puerulus settlement, juveniles, and population harvest in the coastal region of Brazil and Cuba were used to better understand the impact of environmental variability on organisms in their larval stages and their subsequent recruitment to fisheries. The surface temperature, chlorophyll-a concentration, and wind/current patterns were significantly associated with the variability in puerulus settlement. Larger-scale processes (as proxied by the SOI) affected RF, ARD, and sea levels, which reached a maximum during La Niña. As for Brazil, the full-year landings prediction model included Chl-a concentration, SST, RF, and ARD and their association with lobster landings (LLs). The landing predictions for Cuba were based on fluctuations in the Chl-a concentration and SST. Full article

Wave climate variability, including seasonal cycles, long-term trends, and interannual anomalies of wave parameters, was investigated across five latitudinal sectors using ERA5 reanalysis data from 1980 to 2023. Pronounced seasonal cycles were observed in both Northern and Southern Hemisphere sectors, although the variability was more marked in the Northern Hemisphere. In contrast, the tropical region exhibited comparatively stable conditions throughout the year. Long-term trends revealed increases in both significant wave height and peak period across most sectors. The tropical region exhibited a trimodal regime driven by wind waves at low latitudes and remotely generated swells from both hemispheres. Teleconnections associated with the North Atlantic Oscillation (NAO) explained interannual variability in wind-wave direction in the tropics with an r² of 0.74 and wind-wave height variability in the Northern Hemisphere with an r² of 0.81. Additional indices, such as the Arctic Oscillation (AO), the Tropical North Atlantic (TNA) index, and the Northern Annular Mode (NAM), explained 30 to 60 percent of the directional variability. These results underscore the need to account for climate-driven variability in wave modeling frameworks to improve forecast accuracy and representation of directional trends. Full article

The potential distribution of the pulse blue butterfly, Lampides boeticus (Lepidoptera: Lycaenidae), was determined using MaxEnt, random forest, and ensemble models. The results indicate that most tropical, subtropical, and some temperate regions are suitable habitats. Climate change is projected to expand the species’ habitat northward in the Northern Hemisphere. Predicted distributions aligned well with the known occurrence records for the species. The minimum temperature of the coldest month was the climatic variable that most strongly influenced the distribution of L. boeticus. As a tropical and subtropical species, it is assumed that cold temperatures are the main factor limiting its habitat range. Because the potential distribution of this pest covers major pulse cultivation areas under both current and future climate scenarios, these findings highlight the urgent need for developing a sustainable pest management strategy. Full article

The use of remote sensing technologies for mapping forest fires has experienced significant growth in recent decades, driven by advancements in remote sensors, processing platforms, and artificial intelligence algorithms. This study presents a review of 192 scientific articles published between 1990 and 2024, selected using PRISMA criteria from the Scopus database. Trends in the use of active and passive sensors, spectral indices, software, and processing platforms as well as machine learning and deep learning approaches are analyzed. Bibliometric analysis reveals a concentration of publications in Northern Hemisphere countries such as the United States, Spain, and China as well as in Brazil in the Southern Hemisphere, with sustained growth since 2015. Additionally, the publishers, journals, and authors with the highest scientific output are identified. The normalized burn ratio (NBR) and the normalized difference vegetation index (NDVI) were the most frequently used indices in fire mapping, while random forest (RF) and convolutional neural networks (CNN) were prominent among the applied algorithms. Finally, the main technological and methodological limitations as well as emerging opportunities to enhance fire detection, monitoring, and prediction in various regions are discussed. This review provides a foundation for future research in remote sensing applied to fire management. Full article