Search Results (327)

The dynamical tropopause layer pressure (DTLP) represents a key interface characterizing upper-tropospheric stratification and atmospheric dynamical structure. Its spatial morphology and gradient variations directly influence jet stream distribution as well as the intensity and location of clear-air turbulence (CAT). Over the Tibetan Plateau, complex terrain and pronounced dynamical variability result in a significantly lower tropopause height and enhanced horizontal gradients during winter. Aircraft cruising altitudes frequently approach or intersect the tropopause layer in this region, making accurate and fine-scale characterization of DTLP structures critically important for aviation safety. A deep learning-based DTLP retrieval model (Att-ResUNet_DEM) is developed by integrating terrain constraints and an attention mechanism. Using MERRA-2 reanalysis data as supervisory labels, the model incorporates a squeeze-and-excitation (SE) attention mechanism within a residual encoder–decoder framework, while a digital elevation model (DEM) is introduced as an additional input channel and fused with satellite brightness temperature data to explicitly account for terrain effects. A random forest (RF) model is implemented as a baseline for comparison. Compared with the RF model, the Att-ResUNet_DEM reduces the MAE and RMSE by 13.20% and 9.19%, respectively, while increasing the correlation coefficient to 0.76. Over the primary aviation corridors of the Tibetan Plateau, the Att-ResUNet_DEM model achieves a correlation coefficient(R) of 0.87, with markedly reduced gradient dispersion. A representative CAT case further confirms the model’s ability to capture the overall DTLP morphology and gradient enhancement zones. Overall, by combining a regionalized modeling strategy with terrain constraints, this study systematically improves DTLP retrieval accuracy and gradient consistency over complex terrain, providing a new technical pathway for high-resolution tropopause monitoring and aviation operation support. Full article

Accurate measurement of atmospheric temperature profiles in the mesopause region is crucial for understanding the atmospheric dynamics and climate processes. To address this challenge, a sodium Doppler lidar based on the resonance fluorescence scattering mechanism was recently developed to precisely detect atmospheric temperatures in the mesopause region in Qingdao (36.1°N, 120.1°E), China. For the first time, high-resolution observations of atmospheric temperature in the mesopause region (80–105 km) were achieved by the self-developed Na Doppler lidar in Qingdao under the complex atmospheric conditions of the mid-latitude coastal zone. A systematic cross-validation between the self-developed lidar and SABER satellite observations was conducted, and the temperature bias between the two detection methods in the mesopause region and its altitude-dependent characteristics were quantitatively assessed. The temperature profiles measured by lidar exhibited good agreement when compared with the satellite data yielding estimations of RMSE and mean absolute deviation of 9.2 K and 7.3 K, respectively, from 80 km to 100 km altitudes. A correlation analysis conducted between the lidar temperature data and satellite data showed that the closer the satellite passed over Qingdao, the better the correlation demonstrated by the data. The correlation coefficient of the closer comparison data can reach 0.86, which means that the self-developed lidar system in Qingdao has a good ability to detect temperature profiles in the middle and upper atmosphere. The nocturnal evolution details and short-period fluctuations of the temperature field in the mesopause region over Qingdao were observed, revealing the local temperature structural characteristics under the complex atmospheric conditions at the land–sea interface in the Qingdao area. Full article

We present the performance of a middle atmosphere Rayleigh lidar system that employs three receiver channels. We characterize the biases in the density and temperature profiles retrieved from each of the receiver channels as well as the combined receiver signal. We associate these biases with pulse pile-up, gain switching, and variations in the detector gain due to signal amplitude. We use a top-down temperature convergence methodology to determine the upper altitude up to which the signals should be compensated for the variations in detector gain. We find that the channels have warm biases in their temperatures of 2–8 K at 40 km. These biases decrease to between 1 K and 3 K at 60 km. Uncertainty estimates derived from the photon-counting statistics indicate temperature uncertainties on the order of 2–5 K in the 40–70 km region, which are consistent with the observed level of inter-channel variability after correction. A comparison with MERRA-2 reanalysis indicates an overall agreement in temperatures and differences that are consistent with the comparisons between the Rayleigh lidars and MERRA-02 at other sites. These results demonstrate that the proposed approach proves reliable for processing the multi-channel Rayleigh lidar data, particularly for systems employing more than two detection channels, and improves the fidelity and accuracy of the temperature retrievals. Full article

The object of the study is a single heated carbonaceous particle of relatively small size, 0.003 to 0.01 m. Main hypothesis: The formation of soot particles and black carbon particles is caused by the thermochemical destruction of dry organic matter of forest fuel and the mechanical fragmentation of coke residue. The aim of the study is to conduct numerical simulations of heat and mass transfer in a single heated carbonaceous particle, taking into account the soot formation process and assessing its fragmentation with regard to heat exchange with the external environment in a 2D setting. As part of this study, a new model of heat and mass transfer in a pyrolyzed carbonaceous particle was developed, taking into account its step-by-step fragmentation (fragmentation tree model with four secondary particle formations from the initial particle). The calculations resulted in the distributions of temperature and volume fractions of phases in the carbonaceous particle across various scenarios. Scenarios of surface fires (initial temperatures of 900 K and 1000 K), crown fires (1100 K), and a firestorm (1200 K) for typical vegetation (pine, spruce, birch) are considered. Cubic carbonaceous particles are considered in the approximation of a 2D mathematical model. To describe heat and mass transfer in the structure of the carbonaceous particle, a differential equation of thermal conductivity with corresponding initial and boundary conditions of the third type is used, taking into account the gross reaction in the kinetic scheme of pyrolysis and soot formation. Differential analogues of partial differential equations are solved using the finite difference method of second-order approximation. Options for using the developed mathematical model and probabilistic fragmentation criterion for assessing aerosol emissions are proposed. Recommendations: The suggested mathematical model must be incorporated with mathematical models of forest fire plume and aerosol transport in the upper layers of the atmosphere. Moreover, probabilistic criteria for health assessment must be developed for the practical use of the suggested mathematical model. Full article

Wintertime extratropical cyclones frequently traverse the Kuroshio–Oyashio Extension frontal system. However, their net impacts on synoptic sea-surface temperature (SST) variability and mixed-layer structure remain uncertain in the presence of strong fronts and intrinsic ocean variability. Using reanalysis data, we classify extreme events into cyclone cold-sector and warm-sector types based on synoptic air–sea flux anomalies. With ensembles of single-column model experiments, we decompose the upper-ocean response into surface heat-flux forcing, wind-driven mechanical mixing, Ekman temperature advection, wave-breaking mixing, and freshwater effects. Cold-sector events amplify synoptic SST variability and deepen the mixed layer, whereas warm-sector events suppress SST variability and shoal the mixed layer. Surface heat flux is the primary driver of both responses. Ekman advection provides crucial modulation within the frontal zone. Wave-breaking mixing generally damps temperature perturbations. Freshwater forcing exerts a pronounced regional influence southeast of the subarctic front. The combined effects yield an asymmetric spatial fingerprint on SST variability and mixed-layer depth across the frontal system. Comparison between forced variability and total reanalysis variability indicates that within the frontal zone, atmospheric impacts can be redistributed or partly offset by intrinsic ocean processes, while outside the frontal zone, the behavior is closer to an externally forced response. Full article

Egypt generally experiences a hot and arid climate, with rainfall primarily confined to the northern coast during winter season. However, on 31 May 2025, Alexandria experienced an unusual late-spring convective storm that was associated with heavy rainfall, strong winds, intense lightning, and localized hail. This rare event caused temporary disruptions to urban life and underscored the growing vulnerability of coastal cities to short-duration, high-intensity precipitation events occurring outside the climatological rainy season. This study investigates the atmospheric mechanisms underlying this event through a comprehensive synoptic and dynamic analysis of pressure systems, wind fields, and temperature structures extending from the surface to the 200 hPa level. Particular emphasis is placed on the role of moisture convergence and upper-level dynamical forcing in triggering the rapid development of deep convection. Furthermore, the influence of anomalous large-scale circulation patterns on storm initiation and intensification is systematically examined. Improved understanding of these processes provides valuable insight into off-season convective activity over the southeastern Mediterranean and enhances forecasting capability, risk assessment, and early warning strategies for similar extreme events in the region. Furthermore, the influence of anomalous large-scale circulation patterns on storm initiation and intensification is quantitatively assessed to clarify their contribution to the event’s development. A deeper understanding of these processes offers critical insight into the mechanisms governing off-season convective activity over the southeastern Mediterranean and strengthens forecasting skill, risk assessment frameworks, and early warning systems for comparable extreme events in the region. Full article

The Late Miocene is known as a period of long-term Cenozoic global cooling and decreasing concentrations of atmospheric CO₂. The conditions provide the opportunity to assess the Earth’s climate sensitivity in altering internal and external drivers in a warmer world with similarity to the modern continental configuration. However, relative warmer Sea Surface Temperature (SST), a deepened thermocline, and reduced upwelling may have occurred in the tropics during the Late Miocene global cooling. Here, we present foraminiferal biostratigraphy data from the Middle Miocene–Pliocene succession in the Halang Formation in the Banyumas Basin in Indonesia. An increase in the planktonic foraminifera Trilobatus trilobus and Orbulina universa during the Late Miocene in the Indian Ocean indicates relative surface temperature warming and reduced productivity inferred from assemblage shifts. Reduced productivity was caused by decreasing upwelling intensity during the Late Miocene based on Globigerinella obesa assemblages. Reduced upwelling in the south of Java is supported by elevated numbers of surface/mixed-layer species (i.e., Trilobatus sacculifer and Trilobatus immaturus). We suppose the distribution of enhanced upper-layer stratification in the eastern Indian Ocean was not only driven by oceanic forcing but was also transferred intensively into the Indian Ocean by atmospheric forcing of strengthening equatorial trade winds. Changes in the Walker circulation controlled a reduction in upwelling over the eastern tropical Indian Ocean and a deeper thermocline during the cooling climate in the Late Miocene. Full article

Recently, an attempt was made to quantify the respective solar and anthropogenic influences on the terrestrial climate, and to cautiously predict the global mean temperature over the next 130 years. In a double regression analysis, both the binary logarithm of carbon dioxide concentration and the geomagnetic aa index were used as predictors of the sea surface temperature (SST) since the mid-19th century. The regression results turned out to be sensitive to end effects, leading to a disconcertingly broad range of the climate sensitivity between 0.6 K and 1.6 K per doubling of CO₂ when varying the final year of the data used. The aim of this paper is to significantly narrow down this range. To this end, the correlations between the two predictors and the dependent variable (SST) are analysed in detail. It is demonstrated that the SST can be predicted until around 2000 almost perfectly using only the aa index, whereas for later periods the role of CO₂ increases significantly. Therefore, the weight of the aa index is fixed to its very robust outcome (around 0.04 K/nT) from the single and double regressions up to 1990. The SST data, reduced by the aa contribution thus specified, are then used in a single regression with CO₂ as the only remaining predictor. This results in a significant reduction in the range of CO₂ sensitivity, narrowing it to 1.1–1.4 K. Given the exceptionally high temperatures in recent years, these values are considered a kind of upper limit that could still be subject to downward corrections when future data are incorporated. Based on this estimate, a prediction of the temperature up to the year 2100 is ventured, assuming various constant emission scenarios combined with a linear sink model for atmospheric CO₂ content. The most risky factor in this prediction is the future of the aa index. For its forecast, the results of a recently developed synchronization model of the solar dynamo are tentatively employed. Full article

Under global warming, the intensification of the hydrological cycle highlights evapotranspiration (ET) as a key process governing land–atmosphere water and energy exchanges. Understanding the spatiotemporal variability of ET and its driving mechanisms is essential for regional hydrological and ecological studies. Based on MOD16 evapotranspiration products, meteorological data, and multi-source remote sensing datasets, this study systematically analyzed the spatiotemporal characteristics of evapotranspiration (ET) and its driving mechanisms in the Yellow River Basin during 2001–2022 using trend analysis, correlation analysis, and geographical detector methods. Results showed that ET exhibited a significant increasing trend across the YRB (5.29 mm·year⁻¹), with extremely significant increases (p < 0.01) observed in 61.93% of the basin. Among climatic factors, precipitation, temperature, and wind speed exhibited significant increasing trends. Human activities were characterized by a significant increase in NDVI and land-use transitions toward forest and built-up land. Geographical detector results identified NDVI and precipitation as the strongest explanatory factors controlling ET spatial heterogeneity, with distinct driving mechanisms across the upper, middle, and lower reaches. Interaction effects among factors were stronger than individual effects, indicating that the spatial differentiation of ET is jointly controlled by climatic conditions and human activities. These findings empirically characterize the spatial heterogeneity, temporal trends, factor hierarchy, and interaction strength of ET variability at the basin scale and provide basin-scale evidence for understanding hydrological cycle responses under the combined influences of climate change and anthropogenic activities. Full article

In the Yingjiang area of western Yunnan, precipitation is high throughout the year, making it one of the regions with the highest annual precipitation in mainland China. Extreme rainfall in this region often triggers severe flooding, yet the key mechanism of water vapor transport underlying abnormally heavy precipitation remains unclear. This study used automatic weather station observations of precipitation, the fifth-generation atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts, and Global Data Assimilation System (GDAS) data to analyze, for the first time, large-scale water vapor transport, precipitation mechanisms, and the primary water vapor sources and their contributions in this region. The results show the following: In the Yingjiang area, the water vapor sources at all height levels in summer are dominated by the southwest monsoon water vapor transport pathways, such as the Bay of Bengal and the Arabian Sea, with their total contributions to specific humidity and water vapor flux exceeding 70%. This indicates that low-latitude sea areas such as the Bay of Bengal and the Arabian Sea serve as key moisture source regions for Yingjiang in the global water vapor cycle. Water vapor transport over the windward slope causes strong low-level convergence and high-level divergence phenomena, and the suction effect leads to strong upward motion near the 850 hPa level. The pseudo-equivalent potential temperature isolines tilt along the mountain slope, maintaining an unstable stratification characterized by warm, humid lower layers and cold, dry upper layers, providing favorable thermal conditions for precipitation. In addition, in the summer of 2020, abnormally high southwest seasonal wind and air transport, combined with strong low-level convergence and high-level divergence of the vertical circulation structure, were key factors causing the abnormally high precipitation. This study provides an important reference for the prediction of extreme precipitation and the early warning of rainstorm disasters in the southwest monsoon region in the context of global climate change. Full article

Understanding the upper-ocean thermal response during and between typhoons is critical for accurate prediction of typhoon intensity and for evaluating air–sea interactions. Previous studies have primarily focused on ocean cooling induced by individual typhoons and sea surface temperature (SST) recovery after that, yet oceanic thermal rejuvenation within the typhoon Inactivity Duration and its influence on the subsequent typhoon remains insufficiently explored. Using 42 years of typhoon best-track data, satellite observations and reanalysis data, we provide the first systematic quantification of the physical link between Inactivity Duration and subsequent typhoon intensification. Here we found that the intensity of the subsequent typhoon increased with typhoon Inactivity Duration. The subsequent typhoon is 6.34 kt and 7.69 hPa stronger than the previous typhoon for every 10 days of increase in typhoon Inactivity Duration. Upper-ocean thermal condition rejuvenated with time and contributed to subsequent typhoon development, and both SST and ocean heat content (OHC) exhibited significant phase changes from negative after the preceding typhoon to positive prior to the subsequent one, accompanied by a notable shoaling of the mixed layer depth (MLD) and sustained high levels of atmospheric instability. These coordinated environmental changes provide enhanced energy reserves and more favorable thermodynamic conditions for typhoon development after the inactivity period. These findings highlight the importance of considering ocean thermal rejuvenation in forecasting typhoon intensity and provide a quantitative framework for assessing sequential typhoon interactions with the upper ocean, offering theoretical support for improved intensity forecasting. Full article

We investigate the multi-layer atmospheric impacts of Typhoon Hagibis (2019), which formed on 6 October, tracked across 12–35° N and 135–155° E, and made landfall on 12 October over the Izu Peninsula, central Honshu, Japan. We present a multi-layer study that involves the troposphere, stratosphere and upper ionosphere to examine the thermodynamic and electromagnetic coupling between these layers due to such extreme weather conditions. Using ERA5 reanalysis, we identify pronounced stratospheric temperature perturbations, elevated atmospheric gravity wave (AGW) potential energy, substantial spatiotemporal variability in the zonal (U) and meridional (V) wind components, relative humidity, and specific rainwater content throughout the cyclone’s evolution. Quantitatively, AGW potential energy increased from background levels of <5 J kg⁻¹ to >40 J kg⁻¹ near the cyclone core, while tropospheric wind anomalies reached $\pm 30$–40 m s⁻¹, accompanied by relative humidity values exceeding 90% and specific rainwater content up to $1.5\times {10}^{-3}$ kg kg⁻¹, indicative of vigorous moist convection and strong vertical energy transport. The ionospheric response, derived from GPS-based Total Electron Content (TEC) at 10 Japanese IGS stations, reveals vertical TEC (VTEC) perturbations whose amplitudes and temporal evolution vary systematically with GPS-station-to-typhoon-eye distance, including clear enhancements and reductions around the closest-approach day. These signatures indicate a measurable ionospheric response to cyclone-driven atmospheric forcing under geomagnetically quiet conditions, confirming that Hagibis produced vertically coupled disturbances linking stratospheric AGW activity with ionospheric electron density variability. Full article

To effectively manage and conserve ecosystems, it is crucial to understand how vegetation changes over time and space and what drives these changes. The Normalized Difference Vegetation Index (NDVI) is a key measure of plant growth that is highly sensitive to climate variations. Despite its importance, there has been limited research on vegetation changes in the upper sections of the Irtysh River. In our study, we combined various datasets, including NDVI, temperature, precipitation, soil moisture, elevation, and land cover. We conducted several analyses, such as Theil–Sen median trend analysis, Mann–Kendall trend and mutation tests, partial correlation analysis, the geographical detector model, and wavelet analysis, to reveal the region’s pronounced warming and moistening trend in recent years, the response relationship between NDVI and the climate, and the primary drivers influencing NDVI variations. We also delved into the spatiotemporal evolution of NDVI and identified key factors driving these changes by analyzing atmospheric circulation patterns. Our main findings are as follows: (1) Between 1901 and 2022, the area’s temperature rose by 0.018 °C/a, with a noticeable increase in the rate of warming around 1990; precipitation increased by 0.292 mm/a. From 1950 to 2022, soil moisture exhibited a steady increase of 0.0002 m³ m⁻³/a. Spatial trend distributions indicated that increasing trends in temperature and precipitation were evident across the entire region, while trends in soil moisture showed significant spatial variation. (2) During 1982 to 2022, the vegetation greening trend was 0.002/10a, indicating a gradual improvement in vegetation growth in the study area. The spatial distribution of monthly average NDVI values revealed that the main growing season of vegetation spanned April to November, with peak NDVI values occurring in June–August. Combined with serial partial correlation and spatial partial correlation analysis, temperatures during April to May effectively promoted the germination and growth of vegetation, while soil moisture accumulation from June to August (or January to August) effectively met the water demand of vegetation during its growth process, with a significant promoting effect. Geographical detector results demonstrate that temperature exhibits the strongest explanatory power for NDVI variation, whereas land cover has the weakest. The synergistic promotional effect of multiple climatic factors is highly pronounced. (3) Wavelet analysis revealed that the periodic characteristics of NDVI and climate variables over a 2–15-year timescale may have been associated with the impacts of atmospheric circulation. Taking NDVI and climatic factors from June to August as an example, before 2000, temperature was the dominant influencing factor, followed by precipitation and soil moisture; after 2000, precipitation and soil moisture became the primary drivers. The North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) were the primary atmospheric circulation patterns influencing vegetation variability in the region. Their effects were reflected in the inverse relationship observed between NAO/AO indices and NDVI, with typical phases of high and low NDVI closely corresponding to shifts in NAO and AO activity. This study helps us to understand how plants have been changing in the upper parts of the Irtysh River. These insights are critical for guiding efforts to develop the area in a way that is sustainable and beneficial for the environment. Full article

During tropical cyclones (TCs), intense exchanges of momentum, heat, and moisture occur across the air–sea interface. The present study was conducted to investigate the role of surface roughness parameterizations under such conditions. To this end, a series of sensitivity experiments was conducted with a focus on Tropical Cyclone Biparjoy, which originated from the Indian Ocean in 2023. The experiments evaluate the impact of different schemes for momentum, thermal, and moisture roughness length on TC track, intensity, significant wave height, and air–sea heat fluxes. The results indicate that the momentum roughness length scheme is critical for accurately forecasting TC track and intensity and for simulating significant wave height; furthermore, Drennan’s parameterization yielded slightly better results in this case, with the smallest track error (72.0 km MAE) among the momentum schemes. Under the premise that Drennan’s parameterization scheme has high accuracy in momentum roughness, sensitivity experiments on thermal and moisture roughness parameterization were conducted. The Drennan–Fairall2014 combination achieved the lowest errors in TC central pressure (4.25 hPa RMSE) and the maximum sustained wind speed (5.31 m/s RMSE). Thermal and moisture roughness mainly affects the efficiency of turbulent heat transfer between the ocean and the atmosphere and thus has a limited impact on the cooling of sea surface temperature, with SST RMSE differences among schemes within 0.3 °C. This effect is mainly confined to the uppermost ocean layer and does not significantly change the thermal structure of the upper layers. Full article

The Mediterranean region has experienced pronounced hydroclimatic variability over recent decades, motivating a closer examination of the physical processes underlying these changes. This study analyzes ERA5 reanalysis data for 1950–2024 to investigate long-term trends and interrelations among temperature, precipitation, evaporation, wind, sensible heat, and column water, distinguishing between land and sea domains and multiple atmospheric layers. Results show a strong warming signal in the lower troposphere, with temperatures increasing by 0.03 °C year⁻¹ over land and 0.015 °C year⁻¹ over sea, and near-stagnancy in the upper troposphere, which indicates a steepening lapse rate. Unlike temperature, evaporation shows no strong long-term increase: over sea, it rises only slightly, and over land, it declines modestly, with both weak tendencies dominated by strong interannual variability and consistent with declining winds. Over land, sensible heat flux increases, while over the sea, it decreases, revealing divergent energy-partition regimes. Precipitation exhibits no significant long-term change, suggesting that the atmosphere has become warmer and slightly moister but less effective in converting vapor into rainfall. Correlation analyses indicate that wind speed exerts a stronger control on evaporation and precipitation than temperature across the whole region. The Hurst–Kolmogorov stochastic framework further reveals persistent long-term variability in Mediterranean hydroclimatic processes, underscoring that the region’s climate behavior is shaped by dynamic and complex interactions rather than by temperature trends alone. Full article