Search Results (145)

Using satellite-observed data and reanalysis data, we studied the spatiotemporal variation characteristics and dynamic mechanisms of thermal fronts in the Beibu Gulf (TFIBG). TFIBG occur in December, reach their strongest point in January in the following year, and then gradually weaken until they completely disappear in May. Their formation is related to the bathymetry of the Beibu Gulf. In winter, the seawater in shallow-water areas (deep-water areas) cools down more (less), and Ekman currents concurrently transport warm water from the central basin of the Beibu Gulf to the west coast, which results in the formation of a thermal front at the junction of cold and warm water. The interannual variation in TFIBG intensity is related to the northeast monsoon. The strengthened (weakened) Ekman current caused by the northeast monsoon transports more (less) warm water from the central basin of the Beibu Gulf to the west coast, forming a strong (weak) thermal front at the junction of cold and warm water on an interannual scale. The upward trend of TFIBG intensity may be related to the regional heterogeneity of climate warming. This research systematically studied TFIBG, which will help improve people’s understanding of the thermal front in the South China Sea (SCS). Full article

Different scenarios have been established and simulated based on the Delft3D model to compare and assess the impact of human activities (increased pollutants as oxygen demand, BOD, COD, nutrients, and land reclamation), climate change (rising temperatures, sea level rise), and a combined scenario of human activities and climate change on water quality in the Cat Ba–Ha Long coastal area. The findings quantify the impacts of anthropogenic activities and climate change on the water quality in the study area in 2030 and 2050. During the northeast monsoon and the two transitional seasons, the impact of humans and climate change adversely affects water quality. The impact of climate change is less significant than that of human activities and their combination, which result in a reduction in DO levels of 0.02–0.13 mg/L, 0.07–0.44 mg/L, and 0.09–0.48 mg/L, respectively. Meanwhile, during the southwest monsoon, climate change significantly reduces water quality (0.25–0.31 mg/L), more so than human activities (0.14–0.16 mg/L) and their combined effects (0.13–0.17 mg/L). This may elucidate the fact that the increase in nutrient supply from the river during the southwest monsoon in this region can result in an increase in nutrient levels and biological activity, which, in turn, causes an increase in DO. Additionally, the augmented quantity of DO may partially offset the decrease in DO resulting from climate change. Under the influence of human activities and climate change, the nutrient levels in the area increase, with average values of 0.002–0.033 g/m³ (NO₃⁻), 0.0003–0.034 g/m³ (NH₄⁺), and 0.0005–0.014 g/m³ (PO₄³⁻). Full article

Complex geological, gas geochemical and hydro meteorological studies were conducted to investigate the methane fields present in the bottom sediments and seawater of the Red River and Phu Khanh sedimentary basins. We demonstrate that the system of tectonic faults that formed the sedimentary basins of the Red River and the Phu Khanh (the eastern shelf and slope of Vietnam) created the necessary conditions for the generation and migration of endogenous methane into the bottom sediments and seawater. It is shown that dissolved methane in seawater can be transported by marine currents, which in turn can be influenced by seasonal and irregular synoptic processes. The research shows that part of the dissolved methane contained in the waters above the Ken Bau gas field can be transported to the south by the coastal Vietnamese current, which adapts to the conditions of the winter northeast monsoon. It is concluded that there could be at least two deep sources of hydrocarbon gas emissions in the Phu Khanh basin. The impact of Typhoon Nakri on the transport of dissolved methane in the water column of the Phu Khanh sedimentary basin has been investigated. The typhoon could create favorable hydrodynamic conditions for the movement of dissolved gases from oil and gas deposits near the coasts of the islands of Kalimantan and Palawan to the Phu Khanh basin. A possible route for this transfer has been identified. Full article

Climate prediction is of fundamental importance to various sectors of society and the economy, as it can predict the likelihood of droughts or excessive rainfall in vulnerable regions. Climate models are useful tools in producing reliable climate forecasts, which have become increasingly vital due to the rising impacts of climate change. As global temperatures rise, changes in precipitation patterns are expected, increasing the importance of reliable seasonal forecasts to support planning and adaptation efforts. In this study, we evaluated the performance of NOAA/GFDL models from CMIP6 simulations in representing the climate of South America under three configurations: atmosphere-only, coupled ocean-atmosphere, and Earth system. Our analysis revealed that all three configurations successfully captured key climatic features, such as the South Atlantic Convergence Zone (SACZ), the Bolivian High, and the Intertropical Convergence Zone (ITCZ). However, coupled models exhibited larger errors and lower correlation (below 0.6), particularly over the ocean and the South American Monsoon System, which indicates a poor representation of precipitation compared with atmospheric models. The coupled models also overestimated upward motion linked to the southern Hadley cell during austral summer and underestimated it during winter, whereas the atmosphere-only models more accurately simulated the Walker circulation, showing stronger vertical motion around the Amazon. In contrast, the coupled models simulated stronger upward motion over Northeast Brazil, which is inconsistent with reanalysis data. Moreover, we provided insights into how model biases may evolve under climate change scenarios. Future climate projections for the mid-century period (2030–2060) under the SSP2-4.5 and SSP5-8.5 scenarios indicate significant changes in the global energy balance, with an increase of up to 0.9 W/m². Additionally, the projections reveal significant warming and drying in most of the continent, particularly during the austral spring, accompanied by increases in sensible heat flux and decreases in latent heat flux. These findings highlight the risk of severe and prolonged droughts in some regions and intensified rainfall in others. By identifying and quantifying the biases inherent in climate models, this study provides insights to enhance seasonal forecasts in South America, ultimately supporting strategic planning, impact assessments, and adaptation strategies in vulnerable regions. Full article

The Taipei Basin (TPB) and the Lanyang Plain (LYP) are geographically similar, both situated in northern Taiwan. However, significant differences in heat transfer processes arise between the two regions due to local terrain influences under the Northeast Monsoon. Precipitation patterns in the TPB and LYP, especially during the case study of 26 November 2021, differ markedly due to the distinctive dustpan-shaped terrain of the LYP. Our study, based on the WRF model, reveals that while both the TPB and LYP are characterized by downward cold air transfer, the TPB exhibits stronger atmospheric boundary layer mixing and a higher mixing layer height compared to the LYP. Turbulent kinetic energy (TKE) in the TPB is higher during the morning and evening, while vertical heat flux is more pronounced in the LYP. The average sensible heat flux is greater in the TPB, whereas latent heat flux is higher in the LYP. In addition, the amount of water vapor transported into the LYP by the Northeast Monsoon is greater than in the TPB. In the TPB, the wind field, influenced by the terrain, shifts predominantly from northeast to northeasterly and southeasterly. However, upon entering the LYP, the same environmental wind field is affected by the dustpan-shaped terrain, resulting in a counterclockwise near-surface wind pattern. The wind field transitions from northeasterly in the north to westerly, southwesterly, or northwesterly in the south. This difference in wind field causes precipitation in the TPB to be confined mainly to the windward side of the mountainous areas whereas, in the LYP, precipitation occurs both on the windward side and, more abundantly, in the plains. The effect of different types of terrain under the Northeast Monsoon is quite obvious. Full article

This study employed machine learning, specifically deep neural networks (DNNs) and long short-term memory (LSTM) networks, to build a model for estimating acid rain pH levels. The Yangming monitoring station in the Taipei metropolitan area was selected as the research site. Based on pollutant sources from the air mass back trajectory (AMBT) of the HY-SPLIT model, three possible source regions were identified: mainland China and the Japanese islands under the northeast monsoon system (Region C), the Philippines and Indochina Peninsula under the southwest monsoon system (Region R), and the Pacific Ocean under the western Pacific high-pressure system (Region S). Data for these regions were used to build the ANN_AMBT model. The AMBT model provided air mass origin information at different altitudes, leading to models for 50 m, 500 m, and 1000 m (ANN_AMBT_50m, ANN_AMBT_500m, and ANN_AMBT_1000m, respectively). Additionally, an ANN model based only on ground station attributes, without AMBT information (LSTM_No_AMBT), served as a benchmark. Due to the northeast monsoon, Taiwan is prone to severe acid rain events in winter, often carrying external pollutants. Results from these events showed that the LSTM_AMBT_500m model achieved the highest percentages of model improvement rate (MIR), ranging from 17.96% to 36.53% (average 27.92%), followed by the LSTM_AMBT_50m model (MIR 12.94% to 26.42%, average 21.70%), while the LSTM_AMBT_1000m model had the lowest MIR (2.64% to 12.26%, average 6.79%). These findings indicate that the LSTM_AMBT_50m and LSTM_AMBT_500m models better capture pH variation trends, reduce prediction errors, and improve accuracy in forecasting pH levels during severe acid rain events. Full article

Acanthotomicus suncei is a newly discovered bark beetle in China that significantly threatens the American sweetgum Liquidambar styraciflua. In recent years, this pest has spread from its original habitat to many surrounding cities, causing substantial economic and ecological losses. Considering the wide global distribution of its host, Liquidambar styraciflua, this pest is likely to continue to spread and expand. Once the pest colonizes a new climatically suitable area, the consequences could be severe. Therefore, we employed the CLIMEX and Random Forests model to predict the potential suitable distribution of A. suncei globally. The results showed that A. suncei was mainly distributed in Southern China, in South Hokkaido in Japan, Southern USA, the La Plata Plain in South America, southeastern Australia, and the northern Mediterranean; these areas are located in subtropical monsoon, monsoonal humid climates, or Mediterranean climate zones. Seasonal rainfall, especially in winter, is a key environmental factor that affects the suitable distribution of A. suncei. Under future climates, the total suitable area of A. suncei is projected to decrease to a certain extent. However, changes in its original habitat require serious attention. We found that A. suncei exhibited a spreading trend in Southwest, Central, and Northeast China. Suitable areas in some countries in Southeast and South Asia bordering China are also expected to show an increased distribution. The outward spread of this pest via sea transportation cannot be ignored. Hence, quarantine efforts should be concentrated in high-suitability regions determined in this study to protect against the occurrence of hosts that may contain A. suncei, thereby avoiding its long-distance spread. Long-term sentinel surveillance and control measures should be carried out as soon as A. suncei is detected, especially in regions with high suitability. Thus, our findings establish a theoretical foundation for quarantine and control measures targeting A. suncei. Full article

One of the manifests of air-sea interactions is the change in sea level due to meteorological forcing through wind stress and atmospheric pressure. When meteorological conditions conducive to water level increase coincide with high tides during spring tides, the sea level may rise higher than expected and pose a flood risk to coastal low-lying areas. In Hong Kong, specifically when the northeast monsoon coincides with the higher spring tides in late autumn and winter, and sometimes even compounded by the storm surge brought by late-season tropical cyclones (TCs), the result may be coastal flooding or sea inundation. Aiming at forecasting such sea level anomalies on the scale of hours and days with local tide gauges using a flexible and computationally efficient method, this study adapts a data-driven method based on empirical orthogonal functions (EOF) regression of non-uniformly lagged regional wind field from ECMWF Reanalysis v5 (ERA5) to capture the effects from synoptic weather evolution patterns, excluding the effect of TCs. Local atmospheric pressure and winds are also included in the predictors of the regression model. Verification results show good performance in general. Hindcast using ECMWF forecasts as input reveals that the reduction of mean absolute error (MAE) by adding the anomaly forecast to the existing predicted astronomical tide was as high as 30% in February on average over the whole range of water levels, as well as that compared against the Delft3D forecast in a strong northeast monsoon case. The EOF method generally outperformed the persistence method in forecasting water level anomaly for a lead time of more than 6 h. The performance was even better particularly for high water levels, making it suitable to serve as a forecast reference tool for providing high water level alerts to relevant emergency response agencies to tackle the risk of coastal inundation in non-TC situations and an estimate of the anomaly contribution from the northeast monsoon under its combined effect with TC. The model is capable of improving water level forecasts up to a week ahead, despite the general decreasing model performance with increasing lead time due to less accurate input from model forecasts at a longer range. Some cases show that the model successfully predicted both positive and negative anomalies with a magnitude similar to observations up to 5 to 7 days in advance. Full article

The Hong Kong Observatory has been using a parametric storm surge model to forecast the rise of sea level due to the passage of tropical cyclones. This model includes an offset parameter to account for the rise in sea level due to other meteorological factors. By adding the sea level rise forecast to the astronomical tide prediction using the harmonic analysis method, coastal sea level prediction can be produced for the sites with tidal observations, which supports the high water level forecast operation and alert service for risk assessment of sea flooding in Hong Kong. The Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modelling System, which comprises the Weather Research and Forecasting (WRF) Model and Regional Ocean Modelling System (ROMS), which in itself is coupled with wave model WaveWatch III and nearshore wave model SWAN, was tested with tropical cyclone cases where there was significant water level rise in Hong Kong. This case study includes two super typhoons, namely Hato in 2017 and Mangkhut in 2018, three cases of the combined effect of tropical cyclone and northeast monsoon, including Typhoon Kompasu in 2021, Typhoon Nesat and Severe Tropical Storm Nalgae in 2022, as well as two cases of monsoon-induced sea level anomalies in February 2022 and February 2023. This study aims to evaluate the ability of the WRF-ROMS-SWAN model to downscale the meteorological fields and the performance of the coupled models in capturing the maximum sea levels under the influence of significant weather events. The results suggested that both configurations could reproduce the sea level variations with a high coefficient of determination (R²) of around 0.9. However, the WRF-ROMS-SWAN model gave better results with a reduced RMSE in the surface wind and sea level anomaly predictions. Except for some cases where the atmospheric model has introduced errors during the downscaling of the ERA5 dataset, bias in the peak sea levels could be reduced by the WRF-ROMS-SWAN coupled model. The study result serves as one of the bases for the implementation of the three-way coupled atmosphere–ocean–wave modelling system for producing an integrated forecast of storm surge or sea level anomalies due to meteorological factors, as well as meteorological and oceanographic parameters as an upgrade to the two-way coupled Operational Marine Forecasting System in the Hong Kong Observatory. Full article

Hail poses a significant meteorological hazard in China, leading to substantial economic and agricultural damage. To enhance the detection of hail and mitigate these impacts, this study presents an ensemble machine learning model (BPNN+Dtree) that combines a backpropagation neural network (BPNN) and a decision tree (Dtree). Using FY-4A satellite and ERA5 reanalysis data, the model is trained on geostationary satellite infrared data and environmental parameters, offering comprehensive, all-day, and large-area hail monitoring over China. The ReliefF method is employed to select 13 key features from 29 physical quantities, emphasizing cloud-top and thermodynamic properties over dynamic ones as input features for the model to enhance its hail differentiation capability. The BPNN+Dtree ensemble model harnesses the strengths of both algorithms, improving the probability of detection (POD) to 0.69 while maintaining a reasonable false alarm ratio (FAR) on the test set. Moreover, the model’s spatial distribution of hail probability more closely matches the observational data, outperforming the individual BPNN and Dtree models. Furthermore, it demonstrates improved regional applicability over overshooting top (OT)-based methods in the China region. The identified high-frequency hail areas correspond to the north-south movement of the monsoon rain belt and are consistent with the northeast-southwest belt distribution observed using microwave-based methods. Full article

A comprehensive analysis was carried out to investigate the driving factors and influencing mechanisms of spatiotemporal variation of sea level at multiple scales in the East China Sea (ECS) via satellite altimetry datasets from 1993 to 2020. Based on the altimetry grid data processed by the local mean decomposition method, the spatiotemporal changes of ECS sea level are analyzed from the multi-scale perspective in terms of multi-year, seasonal, interannual, and multi-modal scales. The results revealed that the ECS regional mean sea level change rate is 3.41 ± 0.58 mm/year over the 28-year period. On the seasonal scale, the regional mean sea level change rates are 3.45 ± 0.66 mm/year, 3.35 ± 0.60 mm/year, 3.39 ± 0.71 mm/year, and 3.57 ± 0.75 mm/year, for the four seasons (i.e., spring, summer, autumn, and winter) respectively. The spatial distribution analysis showed that ECS sea level changes are most pronounced in coastal areas. The northeast sea area of Taiwan and the edge of the East China Sea shelf are important areas of mesoscale eddy activity, which have an important impact on regional sea level change. The ECS seasonal sea level change is mainly affected by monsoons, precipitation, and temperature changes. The spatial distribution analysis indicated that the impact factors, including seawater thermal expansion, monsoons, ENSO, and the Kuroshio Current, dominated the ECS seasonal sea level change. Additionally, the ENSO and Kuroshio Current collectively affect the spatial distribution characteristics. Additionally, the empirical orthogonal function was employed to analyze the three modes of ECS regional sea level change, with the first three modes contributing 26.37%, 12.32%, and 10.47%, respectively. Spatially, the first mode mainly corresponds to ENSO index, whereas the second and third modes are linked to seasonal factors, and exhibit antiphase effects. The analyzed correlations between the ECS sea level change and southern oscillation index (SOI), revealed the consistent spatial characteristics between the regions affected by ENSO and those by the Kuroshio Current. Full article

Urban ventilation corridors are designed to enhance air quality, alleviate urban thermal conditions, reduce pollution and energy consumption, as well as improve human comfort within cities. They play a pivotal role in mitigating environmental impacts, particularly in densely populated urban areas. Based on satellite remote sensing data, meteorological observations, basic geographic information of Zhengzhou City and its surroundings, and urban planning data, we analyzed the urban wind environment, urban heat island, ecological cold sources, and ventilation potential. The findings reveal several key insights: (1) Dominant winds in Zhengzhou City predominantly originate from the northwest, northeast, and south, influenced by topography and the monsoon climate, with seasonal variations. These wind patterns are crucial considerations for designing primary ventilation corridors. (2) The urban heat island exhibits a polycentric spatial distribution, with intensity decreasing from the city center towards the periphery. Ecological cold sources, primarily situated in the city outskirts, act as reservoirs of fresh air that mitigate the urban heat island effect through designated corridors. (3) A preliminary corridor system, termed “eight primary and thirteen secondary corridors”, is proposed for Zhengzhou City based on an integrated assessment of ventilation potential, urban surface roughness, and sky view factor. This research contributes to advancing the understanding of urban ventilation systems and provides practical insights for policymakers, urban planners, and researchers seeking sustainable solutions to mitigate climate impacts in rapidly urbanizing environments in the region. Full article

Through the integration of high-resolution hydrodynamic modeling and comprehensive field measurements, this study elucidates the intricate three-dimensional hydrographic characteristics of the eastern Gulf of Thailand (eGOT). In addition to the prevalent tidal currents dictating alternating flow along the northwestern and southeastern axes, our investigation reveals pronounced seasonal variations in mean currents, water temperature, and salinity within the eGOT, closely linked to the dynamics of the Asian–Australian monsoon system. During the southwest monsoon, mean currents exhibit a southeasterly trend, contrasting with a northwesterly pattern during the northeast monsoon. Lowest water temperatures occur during the latter, while the highest levels are observed during the 1st monsoon transition (April–March). Notably, salinity levels reach their lowest levels during the southwest monsoon and the 2nd monsoon transition (October), coinciding with the seasonal stratification of the water column and the emergence of a distinct stable along-the-shore northwesterly current with the average speed of 15 cm/s, defined here as the “Chanthaburi Coastal Current (CCC)”. Model experiments attribute the formation of the CCC to decreased salinity induced by direct rainfall, highlighting the significance of rainfall as a key factor influencing coastal water dynamics in tropical regions or areas experiencing high precipitation. Full article

The middle and lower reaches of the Yangtze River (MLYR) frequently experience extreme precipitation events (EPEs) during June and July, the so-called Meiyu season. This study investigated EPEs in the MLYR during Meiyu seasons over 1961–2022, using rain gauge observations and ERA5 reanalysis data. EPEs associated with the Northeast China cold vortex featured more undulating westerlies with a distinct wave train pattern from Europe to Northeast Asia. Due to robust Rossby wave energy, the trough deepened from Northeast China towards the MLYR and was confronted with a westward extension of the western Pacific subtropical high. Such a configuration enhanced the warm and moist monsoon conveyor belt and convergence of water vapor flux from southwestern China to the MLYR. The warm and moist air favored upward motion. The increased rainfall prevailed from southwestern China to the MLYR. In contrast, ordinary EPEs were characterized by zonal westerlies and weaker Rossby wave propagation. The Meiyu trough was comparatively shallow and confined to the MLYR with less westward expansion of the subtropical high. In response, the warm and moist monsoon conveyor belt was more localized, resulting in weaker EPEs in the MLYR. Full article

We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed for the equation (i.e., minimum and maximum daily temperature, specific humidity, wind speed, incoming shortwave radiation, and pressure) were obtained from the North American–CORDEX initiative. We used dynamically downscaled projections of three CMIP5 GCMs for RCP8.5 emission scenarios (i.e., HadGEM2-ES, MPI-ESM-LR, and GFDL-ESM2M), and each was dynamically downscaled to ~25 km by two RCMs (i.e., WRF and regCM4). All terrestrial annual PET projections showed a statistically significant increase when comparing the historical period (1986–2005) to future projections (2020–2039 and 2040–2059). The regional spatial average of the six GCM-RCM combinations projected an increase in the annual PET of about +4% and +8% for 2020–2039 and 2040–2059, respectively. The projected average 20-year annual changes over the study area range for the two projection periods were +1.4%–+8.7% and +3%–+14.2%, respectively. The projected annual PET increase trends are consistent across the entire region and for the six GCM-RCM combinations. Higher annual changes are projected in the northeast part of the region, while smaller changes are projected along the pacific coast. The main drivers for the increase are the projected warming and increase in the vapor pressure deficit. The projected changes in PET, which represent the changes in the atmospheric evaporative demand, are substantial and likely to impact vegetation and the hydrometeorological regime in the area. Quantitative assessments of the projected PET changes provided by this study should be considered in upcoming studies to develop resilience plans and adaptation strategies for mitigating the projected future changes. Full article