Search Results (1,949)

Wet-snow avalanches constitute a major geomorphic hazard in southeastern Tibet, where warm, humid climatic conditions and a steep, high-relief terrain generate failure mechanisms that are distinct from those in cold, dry snow environments. This study investigates the snowpack conditions underlying avalanche initiation in this region by integrating UAV-based multi-sensor surveys with field validation. Ground-penetrating radar (GPR), infrared thermography, and optical imaging were employed to characterize snow depth, stratigraphy, liquid water content (LWC), snow water equivalent (SWE), and surface temperature across an inaccessible avalanche channel. Calibration at representative wet-snow sites established an appropriate LWC inversion model and clarified the dielectric properties of avalanche-prone snow. Results revealed SWE up to 1092.98 mm and LWC exceeding 13.8%, well above the critical thresholds for wet-snow instability, alongside near-isothermal profiles and weak bonding at the snow–ground interface. Stratigraphic and UAV-based observations consistently showed poorly bonded, water-saturated snow layers with ice lenses. These findings provide new insights into the hydro-thermal controls of wet-snow avalanche release under monsoonal influence and demonstrate the value of UAV-based surveys for advancing the monitoring and early warning of snow-related hazards in high-relief mountain systems. Full article

Quantifying the regional source of long-lived ozone precursors (especially GHGs) transported to Hong Kong is hampered by sparse observational data and computational limitations. This study introduces an observation-driven analytical framework that integrates a tracer ratio (ethylbenzene/m,p-xylene), wind–source–distance correlations to constrain transport corridors, and inventory mapping to determine the province- and sector-specific contributions, operationalized by identifying transport periods from observations, classifying sources with diagnostic ratios into five emission categories, deriving seasonal weighting factors via frequency normalization, mapping high-resolution inventory classes to these categories to restructure sectoral inventories, and combining normalized provincial spatial weights with the restructured inventories to quantify cross-boundary CO₂ and CH₄ emissions by sector and region. High-resolution measurements were conducted at the Cape D’Aguilar Supersite (CDSS), which showed dominant wintertime regional transport with mean concentrations of 435.29 ± 7.64 ppm (CO₂) and 2083.45 ± 56.50 ppb (CH₄). Thirteen transport periods were quantitatively analyzed, and province–sector contributions were estimated. The dominant provincial contributors were Guangdong (20.66%), followed by Jiangxi (18.36%) and Zhejiang (11.15%). Motor vehicles (70%), fuel combustion (15%), and solvent use (10%) were the primary contributing sectors. The framework enables province- and sector-specific attribution under stated assumptions and provides a tool for measuring cross-boundary mitigation and developing air quality and climate strategies in monsoon-affected coastal cities. Full article

The pine wood nematode (PWN), one of the globally significant forest diseases, has driven the demand for precise detection methods. Recent advances in satellite remote sensing technology, particularly ultra-high-resolution optical imagery, have opened new avenues for identifying PWN-infected trees. In order to systematically evaluate the ability of ultra-high-resolution optical remote sensing and the influence of spatial and spectral resolution in detecting PWN-infected trees, this study utilized a U-Net network model to identify PWN-infected trees using three remote sensing datasets of the ultra-high-resolution multispectral imagery from Beijing 3 International Cooperative Remote Sensing Satellite (BJ3N), with a panchromatic band spatial resolution of 0.3 m and six multispectral bands at 1.2 m; the high-resolution multispectral imagery from the Beijing 3A satellite (BJ3A), with a panchromatic band resolution of 0.5 m and four multispectral bands at 2 m; and unmanned aerial vehicle (UAV) imagery with five multispectral bands at 0.07 m. Comparison of the identification results demonstrated that (1) UAV multispectral imagery with 0.07 m spatial resolution achieved the highest accuracy, with an F1 score of 89.1%. Next is the fused ultra-high-resolution BJ3N satellite imagery at 0.3 m, with an F1 score of 88.9%. In contrast, BJ3A imagery with a raw spatial resolution of 2 m performed poorly, with an F1 score of only 28%. These results underscore that finer spatial resolution in remote sensing imagery directly enhances the ability to detect subtle canopy changes indicative of PWN infestation. (2) For UAV, BJ3N, and BJ3A imagery, the identification accuracy for PWN-infected trees showed no significant differences across various band combinations at equivalent spatial resolutions. This indicates that spectral resolution plays a secondary role to spatial resolution in detecting PWN-infected trees using ultra-high-resolution optical imagery. (3) The 0.3 m BJ3N satellite imagery exhibits low false-detection and omission rates, with F1 scores comparable to higher-resolution UAV imagery. This indicates that a spatial resolution of 0.3 m is sufficient for identifying PWN-infected trees and is approaching a point of saturation in a subtropical mountain monsoon climate zone. In conclusion, ultra-high-resolution satellite remote sensing, characterized by frequent data revisit cycles, broad spatial coverage, and balanced spatial-spectral performance, provides an optimal remote sensing data source for identifying PWN-infected trees. As such, it is poised to become a cornerstone of future research and practical applications in detecting and managing PWN infestations globally. Full article

The Wushan Loess, situated in the Yangtze Three Gorges region of China, represents the southernmost aeolian loess deposit in China and provides critical insights into Late Pleistocene paleoenvironmental conditions and East Asian monsoon dynamics. Despite its significance, the genesis and provenance of this unique loess deposit remain controversial. This study employs an integrated multi-proxy approach combining detrital zircon U-Pb geochronology, optically stimulated luminescence (OSL) dating, and detailed grain size analysis to systematically investigate the provenance and depositional mechanisms of the Wushan Loess. Three representative loess–paleosol profiles (Gaotang-GT, Badong-BD, and Zigui-ZG) were analyzed, yielding 17 OSL ages, 729 grain size measurements, and approximately 420 analyses per profile were conducted, yielding 1189 valid ages (GT 406, BD 391, ZG 402). OSL chronology constrains the deposition period to 18–103 ka (Marine Isotope Stages 2–5), coinciding with enhanced East Asian winter monsoon activity during the Last Glacial period. Grain size analysis reveals a dominant silt fraction (modal size: 20–25 μm) characteristic of aeolian transport, with coarse silt (20–63 μm) averaging 47.1% and fine silt (<20 μm) averaging 44.2% of the sediments. Detrital zircon U-Pb age spectra exhibit consistent major peaks at 200–220 Ma, 450–500 Ma, 720–780 Ma, and 1800–1850 Ma across all profiles. Kernel Density Estimation (KDE) and Multi-Dimensional Scaling (MDS) analyses indicate a mixed provenance model. Non-negative least squares (NNLS) unmixing confirms this quantitative source apportionment., dominated by proximal contributions from the upper Yangtze River basin (including the Three Gorges area and Sichuan Basin, ~65%–70%), supplemented by distal dust input from the Loess Plateau and northern Chinese deserts (~30%–35%). This study establishes for the first time a proximal-dominated provenance model for the Wushan Loess, providing new evidence for understanding southern Chinese loess formation mechanisms and Late Pleistocene East Asian monsoon evolution. Full article

An intense rainfall event affected the United Arab Emirates (UAE) between 15 and 16 April 2024. This study investigated the atmospheric conditions responsible for the formation of large convective storms during this period. Specifically, we analyzed the atmospheric dynamics and large-scale flow that led to the development of a cut-off low-pressure system (COL) over the Arabian Peninsula on 15 April 2024, triggering a two-day period of intense precipitation over the UAE. Our findings indicate that the storms were driven by upper-air instability, a prolonged moisture influx from the monsoon system into the UAE, and the presence of a surface front. Some regions recorded over 200 mm of precipitation within this period, resulting in flash floods, infrastructure disruptions, and significant impacts on the local population. The unusual development of the rainfall event was linked to the displacement of the subtropical jet (STJ), which facilitated the formation and intensification of a COL traversing the region. Full article

Dynamical downscaling is an essential approach for bridging the gap between coarse-resolution global climate models and regional details required for climate impact assessment and sustainable development planning. Thailand, a climate-sensitive country in Southeast Asia, requires robust climate information to support its adaptation and resilience strategies. This study evaluated the Weather Research and Forecasting (WRF) model in dynamically downscaling selected Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations over Thailand during the baseline period of 1976–2005. A two-way nested WRF configuration was employed, with domains covering Southeast Asia (36 km) and Thailand (12 km) in the model. Model outputs were compared with gridded observations from the Climatic Research Unit (CRU TS), and spatial variations were analyzed across six administrative regions in Thailand. The WRF successfully reproduces broad climatological patterns, including the precipitation contrast between mountainous and lowland areas and the north–south gradient of temperature. Seasonal cycles of rainfall and temperature are generally well represented, although systematic biases remain, specifically the overestimation of orographic rainfall and a cold bias in high-elevation regions. The 12 km WRF simulations demonstrated improved special and temporal agreement with the CRU TS dataset, showing a national-scale wet bias (MBE = +17.14 mm/month), especially during the summer monsoon (+65.22 mm/month). Temperature simulations exhibited seasonal derivations, with a warm bias in the pre-monsoon season and a cold bias during the cool season, resulting in annual cold biases in both maximum (−1.25 C) and minimum (−0.80 C) temperatures. Despite systematic biases, WRF-CMIP5 downscaled framework provides enhanced regional climate information and valuable insights to support national-to-local climate change adaptation, resilience planning, and sustainable development strategies in Thailand and the broader Southeast Asian region. Full article

Tidal dynamics substantially govern nearshore circulation patterns. The discharge of sewage at different tidal stages may have a significant impact on the dilution of pollutants. However, discussions on tidal phase sewage discharge strategy are still rare. This study focuses on the narrow tidal passage in the Ningbo-Zhoushan sea area, which receives a large amount of coastal wastewater, but the role of the unique hydrodynamic processes in the dilution of pollutants in this region remains unclear. By using a combination of on-site measurements and the FVCOM-dye simulation method, the scenario of high-concentration sewage retention in the tidal passage was demonstrated. The coastal residual circulation formed by strong tidal currents confined over 78% of the tracers within a 3 km range near the shore, and a subsurface dye accumulation zone emerged along the 25–50 m isobaths. Monsoon transitions regulated pollution plumes, inducing 5–8% seasonal variability in pollution footprints controlled by wind-tide-stratification interplay. The tidal phase discharge strategy was revealed to be highly effective in this study; both submerged discharge in deep-water zones and intermittent discharge strategies implemented in shallow-water zones significantly reduce the spatial coverage of high-concentration sewage plumes. Our findings highlight the importance of formulating discharge strategies based on tidal phases in typical narrow and deep tidal passages. Full article

Heavy-textured soils in monsoon-affected regions face challenges related to waterlogging and structural degradation, yet the long-term efficacy of biochar as a physical soil amendment under such conditions remains inadequately understood. This two-year field study (2018–2019) therefore evaluated the transient impacts of birch-derived biochar (360–380 °C pyrolysis; 0, 1, 3 kg/m²), subsurface drainage systems, and fertilizer regimes on key physical properties of Endoargic Anthrosols (clay loam) in coastal Primorsky Krai, Russia. Granulometric composition remained stable (silt loam: sand 42–48%, silt 38–44%, clay 12–16%), though drainage significantly increased the silt fraction by >7.5% (p < 0.05). Biochar induced short-term reductions in bulk density (ρ_b; max −12% at 3 kg/m², 2018) and aggregate density (ρ_a; max −9.3%, 2018), but these effects dissipated by 2019 due to tillage redistribution and monsoonal fragmentation, as verified by SEM. Total porosity fluctuated seasonally (0.50–0.65 cm³/cm³), peaking post-tillage but declining under monsoon saturation, with no significant sustained biochar contribution. Crucially, intra-aggregate pore architecture (2–50 nm) resisted amendment-induced changes; N₂ adsorption showed treatment-invariant mesopore dominance (65–75% volume; mean pore diameter 17–21 nm), attributable to biochar’s physical exclusion (>1 µm particles from sub-0.5 µm pores) and inert fragmentation. Drainage dominated structural dynamics, modulating pore volume seasonally (−15% in 2018; +18% in 2019), while organic fertilizer enhanced porosity through polysaccharide-stabilized microaggregation (+22%, 2019). We conclude that biochar’s physical benefits in clay loams under monsoon climates are transient and dose-dependent, operating primarily through inter-aggregate macroporosity rather than intra-aggregate modification, necessitating reapplication for sustained improvements. Full article

This study aims (1) to study the trend and characteristics of monthly air temperature, monthly rainfall, and potential evapotranspiration (PET) in Thailand over the mid-21st century (2022–2060) period, and (2) to create a climate pattern map using the New Thornthwaite Climate Classification in Thailand over the same period under RCP4.5 and RCP8.5 scenarios using CSIRO-Mk3 in the CMIP5 dataset with Empirical Quantile Mapping (EQM) statistical downscaling. Spatial analyses of temperature and PET reveal significant warming trends, with temperatures rising by approximately 0.033 °C/year and PET rising by about 10 mm/year, especially in the Bangkok Metropolitan Region due to the urban heat island effect, with temperature values under RCP8.5 remaining consistently higher than those under RCP4.5. Rainfall projections show relatively stable spatial patterns across both scenarios, with higher concentrations along the Andaman coast, the eastern peninsula, and northeastern Thailand; these are areas influenced by the southwest monsoon and tropical cyclones. Central Thailand, however, exhibits persistently low rainfall, likely due to rain-shadow effects. PET patterns mirror early 21st-century observations, with the highest values projected in central Thailand and increasing trends under both scenarios, suggesting heightened drought risks. By 2060, The New Thornthwaite Climate Classification indicates that Moist climate zones are projected to disappear nationwide, with Semi-arid and Dry climates dominating under both RCP4.5 and RCP8.5 scenarios. Annual mean temperature will rise by 0.033 °C/year and PET by ~10 mm/year, while rainfall trends remain nearly stable. The classification’s reliance on minimal parameters—temperature, precipitation, and PET—provides a practical tool for climate monitoring and policy development. Full article

Ion-adsorption type rare earth element (IREE) deposits are critical strategic resources formed under strong lithological, geomorphological, and weathering controls. In Houaphanh Province, Laos, widespread granitic intrusions and tropical monsoon weathering provide favorable conditions for IREE mineralization; however, exploration is limited by rugged terrain, dense vegetation cover, and sparse geological data. This study integrates Landsat 9, ASTER multispectral, and digital elevation data to enhance IREE exploration. Band ratio and principal component analysis (PCA) were applied to extract lithological and alteration features, while six topographic parameters describing elevation, slope, relief amplitude, incision depth, surface roughness, and elevation variability were derived from ASTER GDEM data. These datasets were combined using a weighted overlay to delineate favorable geomorphic zones. Six prospectives zones were identified, and field verification at Nongkhang confirmed 19 IREE ore bodies. The results demonstrate that integrating spectral and topographic indicators significantly improves the accuracy for IREE prediction in tropical, densely vegetated regions, offering a transferable framework for similar geological settings worldwide. Full article

The roles of man-made weirs in flood control during the summer monsoon are well-known, but the function of habitats for wintering water birds has not been explored. This study examined the effects of man-made weirs on the wintering distribution of water birds in Tancheon Stream, Korea, with a focus on the impact of the freeze–thaw process. Data collected from January to February 2003 included thawed water surface ratios, water depths, sandbar areas, and bird distribution under different weather conditions. The analysis revealed a strong positive correlation between thawed surface areas in front of the weir’s drop structures and the abundance of dabbling and diving water birds during severe cold conditions with temperatures below −9 °C. However, it was also observed that the stagnant water impounded by the weirs tended to freeze easily in winter, making it difficult for water birds to inhabit those areas. These results suggest an adaptation of wintering water birds to man-made weirs in urban streams, providing significant insights for enhancing habitat functions in urban stream management. Full article

Long-term relative humidity (RH) variations on the Tibetan Plateau remain poorly understood due to the limited length of instrumental records. Here we developed a 160-year tree-ring width chronology from Populus cathayana on the eastern Tibetan Plateau. Based on climate-tree growth relationships between the tree growth of P. cathayana and current May relative humidity, we reconstructed May relative humidity for the past 146 years. The reconstruction reveals three drought periods (1874–1901, 1921–1932 and 2001–2011) and two wet periods (1902–1920 and 1955–2000). The RH reconstruction is highly consistent with other nearby tree-ring-based temperature and moisture records, suggesting our reconstruction represents large-scale relative humidity variability on the eastern Tibetan Plateau. Spectral analysis detected 2–5 years cycles, likely related to EI Nino–Southern Oscillation (ENSO) variability. Moreover, the reconstruction correlates significantly with the East Asian Summer Monsoon (EASM) index, indicating EASM’s influence on regional moisture transport. These findings highlight the role of ocean–atmosphere coupling in driving humidity variability on the eastern Tibetan Plateau. This study advances understanding of regional climate dynamics and provides a valuable proxy record for future climate change assessments. Full article

Floods are among the most frequent and damaging natural hazards in the Mekong River Basin, where the interplay of monsoon-driven climate variability, complex topography, and rapid socio-economic change creates high exposure and vulnerability. This study presents a comprehensive assessment of flood disaster patterns, loss distribution, and regional disparities across five countries in the Lower Mekong Basin—Cambodia, Laos, Myanmar, Thailand, and Vietnam. Using multivariate spatiotemporal analysis based on EM-DAT, MRC, and national government datasets, the study quantifies flood frequency, casualties, and affected population to reveal cross-country differences in disaster impact and timing. Results show that while Vietnam and Thailand experience high flood frequency and storm-induced events, Laos and Cambodia face riverine flooding under constrained economic and infrastructural conditions. The findings highlight a basin-wide increase in flood frequency over recent decades, driven by climate change, land use transitions, and uneven development. The analysis identifies critical gaps in adaptive governance, particularly the need for dynamic policy frameworks that can adjust to spatial disparities in flood typologies (e.g., Vietnam’s storm floods vs. Cambodia’s riverine floods) and improve transboundary coordination of reservoir operations. Despite the region’s extensive reservoir capacity, most infrastructure prioritizes hydropower over flood mitigation. The study evaluates the role of regional cooperation frameworks such as the Lancang–Mekong Cooperation (LMC), demonstrating how strengthened institutional flexibility and knowledge-sharing mechanisms could enhance progress toward Sustainable Development Goals (SDGs) related to water governance (SDG 6), resilient infrastructure (SDG 9), and disaster risk reduction (SDG 11). By constructing the first integrated national-level flood disaster database for the basin and conducting comparative analysis across countries, this research provides empirical evidence to support differentiated yet coordinated flood risk governance strategies at both national and transboundary levels. Full article

Climate projections suggest ecosystems could face drastic changes due to global climate change, including more severe and frequent droughts than those recorded in the last century. Paleoclimatic series provide more extensive information than that available with instrumental records, allowing for the analysis of trends and recurrence of extreme events over a longer time periods. The objective of this research was to reconstruct the precipitation variability for southwestern Chihuahua, based on the tree-ring records of Pinus arizonica Engelm. and to assess the influence of ocean atmospheric circulations like El Niño Southern Oscillation (ENSO) and the North American Monsoon (NAM) on both low- and high-frequency climate variability. We developed three dendrochronological series covering 214 years (1802–2015), 265 years (1750–2014) and 369 years (1647–2015), for the Talayotes (TAL), Predio Particular Las Chinas (PPC) and El Cuervo (CUE) sites, respectively. The 369-year regional chronology was significantly related to cumulative precipitation variability between January and September. Recurring droughts were observed at approximately 50-year intervals. This regional climate variability was significantly related (p < 0.05) to Niño 3 SST and PDSI (JJA) indices. Maximum and minimum extreme events reconstructed in the last 369 years were synchronized with ENSO events, both in the El Niño warm phase and the La Niña cold phase. These results suggest that P. arizonica tree rings record shared a common response to the regional climate that was significantly modulated by ENSO and the NAM. This is the first dendroclimatic study to reconstruct summer precipitation patterns in northern Mexico, which is valuable given the importance of this seasonal precipitation on the regional economy. Full article

Climate change is reshaping weather patterns and atmospheric circulation globally, particularly in monsoon-dominated tropical environments. To examine how these changes are unfolding in Bangladesh, we extend the Spatial Synoptic Classification (SSC) using ERA5 reanalysis (1960–2024) at three representative stations (Chittagong, Khulna, and Sylhet) to assess long-term changes in the SSC weather types and their internal meteorological properties. The SSC calendars were constructed and analyzed for seasonal distribution, interannual trends, and decadal anomalies of temperature and dew point. Results reveal that Bangladesh’s climatology is dominated by Moist Tropical (MT), Moist Moderate (MM), and Dry Moderate (DM) weather types with a coherent seasonal cycle. Interannually, MT increased strongly across all stations, while MM and DM declined significantly. Decadal anomalies show consistent warming and moistening since the 2000s, which are most pronounced for Dry Tropical (DT) and MT. These findings indicate that climate change in Bangladesh is expressed not only through shifting frequencies but also through evolving thermodynamic characteristics of daily weather types, underscoring the SSC framework’s value in tropical monsoon regions for generating actionable climate information to support heat-stress planning and climate-health services. Full article