Search Results (331)

Localized ionization enhancements (LIEs) in altitude range corresponding to the D-region ionosphere, disrupting Very-Low-Frequency (VLF) signal propagation. This case study focuses on Lightning-induced Electron Precipitation (LEP), analyzing amplitude and phase variations in VLF signals recorded in Belgrade, Serbia, from worldwide transmitters. Due to the localized, transient nature of Energetic Electron Precipitation (EEP) events and the path-dependence of VLF responses, research relies on event-specific case studies to model reflection height and sharpness via numerical simulations. Findings show LIEs are typically under 1000 × 500 km, with varying internal structure. Accumulated case studies and corresponding data across diverse conditions contribute to a broader understanding of ionospheric dynamics and space weather effects. These findings enhance regional modeling, support aerosol–electricity climate research, and underscore the value of VLF-based ionospheric monitoring and collaboration in Europe. Full article

Accurate detection of the atmospheric boundary layer (ABL) is important for weather forecasting, urban air quality monitoring, and agricultural and ecological protection. In this study, we propose a new method for enhancing ABL height detection accuracy by integrating multi-channel polarized lidar signals at 355 nm and 532 nm wavelengths. Radiosonde observations and ERA5 reanalysis are used to validate the lidar-derived results. By calculating the gradients of signals of different wavelengths and weighted fusion, the position of the top of the boundary layer is identified, and corresponding weights are assigned to signals of different wavelengths according to the signal-to-noise ratio of the signals to obtain a more accurate atmospheric boundary layer height. This method can effectively mitigate the influence of noise and provides more stable and accurate ABL height estimates, particularly under complex aerosol conditions. Three case studies of ABL height detection over the Beijing region demonstrate the effectiveness and reliability of the proposed method. The fused ABLHs were found to be consistent with the sounding data and ERA5. This research offers a robust approach to enhancing ABL height detection and provides valuable data support for meteorological studies, pollution monitoring, and environmental protection. Full article

Aerosol uniformity in the mixing chamber is one of the key factors in evaluating performance of aerosol samplers and accuracy of aerosol monitors which could output the direct reading of particle size or concentration. For obtaining high uniformity and a stable test aerosol sample during evaluation, a portable mixing chamber, where the sample and clean air were dual-vortex turbulent mixed, was designed. By using computational fluid dynamics (CFD), particle motion within the mixing chamber was illustrated or explained. By adjusting critical structure parameters of chamber such as height and diameter, the flow field structure was optimized to improve particle mixing characteristics. Accordingly, a novel portable aerosol mixing chamber with length and inner diameter of 0.7 m and 60 mm was developed. Through a combination of simulations and experiments, the operating conditions, including working flow rate, ratio of carrier/dilution clean air, and mixture duration, were studied. Finally, by using the optimized parameters, a mixing chamber with high spatial uniformity where variation is less than 4% was obtained for aerosol particles ranging from 0.3 μm to 10 μm. Based on this chamber, a standardized testing platform was established to verify the sampling efficiency of aerosol samplers with high flow rate (28.3 L·min⁻¹). The obtained results were consistent with the reference values in the sampler’s manual, confirming the reliability of the evaluation system. The testing platform developed in this study can provide test aerosol particles ranging from sub-micrometers to micrometers and has significant engineering applications, such as atmospheric pollution monitoring and occupational health assessment. Full article

This study utilized Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite level-2 data with high-confidence cloud–aerosol discrimination (|CAD| > 70) to investigate the optical properties, vertical distributions, seasonal variations, and aerosol interactions of near-surface cloud layers (cloud base height < 2.5 km) over Australia from 2006 to 2021. This definition encompasses both traditional low clouds and part of mid-level clouds that extend into the lower troposphere, enabling a comprehensive view of cloud systems that interact most directly with boundary-layer aerosols. The results showed that the optical depth of low clouds (CODL) exhibited significant spatial heterogeneity, with higher values in central and eastern regions (often exceeding 6.0) and lower values in western plateau regions (typically 4.0–5.0). CODL values demonstrated clear seasonal patterns with spring peaks across all regions, contrasting with traditional summer-maximum expectations. Pronounced diurnal variations were observed, with nighttime CODL showing systematic enhancement effects (up to 19.29 maximum values compared to daytime 11.43), primarily attributed to surface radiative cooling processes. Cloud base heights (CBL) exhibited counterintuitive nighttime increases (41% on average), reflecting fundamental differences in cloud formation mechanisms between day and night. The geometric thickness of low clouds (CTL) showed significant diurnal contrasts, decreasing by nearly 50% at night due to enhanced atmospheric stability. Cloud layer number (CN) displayed systematic nighttime reductions (18% decrease), indicating dominance of single stratiform cloud systems during nighttime. Regional analysis revealed that the central plains consistently exhibited higher CODL values, while eastern mountains showed elevated cloud heights due to orographic effects. Correlation analysis between cloud and aerosol layer properties revealed moderate but statistically significant relationships (|R| = 0.4–0.6), with the strongest correlations appearing between cloud layer heights and aerosol layer heights. However, these correlations represent only partial influences among multiple factors controlling cloud development, suggesting measurable but modest aerosol effects on cloud properties. This study provides comprehensive observational evidence for cloud optical property variations and aerosol–cloud interactions over Australia, contributing to an improved understanding of Southern Hemisphere cloud systems and their climatic implications. Full article

Blowing snow is a common phenomenon over the Antarctic ice sheet and sea ice regions, playing a crucial role in the Antarctic climate system. Previous research developed an optimized machine learning (ML) model to diagnose blowing snow occurrence using meteorological fields from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). This paper extends that work by optimizing an ML model to estimate blowing snow height and optical depth for operational data production. Observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) serve as ground truth for training. The optimization process involves selecting relevant input features and identifying the most effective ML regressor. As a result, 21 MERRA-2 fields were identified as key input features, and Extreme Gradient Boosting emerged as the most effective regressor. Feature importance analysis highlights wind components and surface pressure as the most significant predictors for blowing snow height and optical depth. Individual models were developed for each month. Using 10 years of CALIPSO data (2007–2016) for training, these optimized models can be applied across the full MERRA-2 dataset, spanning from 1980 to the present. This enables the generation of hourly blowing snow height and optical depth data on the MERRA-2 grid for the entire MERRA-2 time span. Full article

The impact of stratospheric aerosols on Earth’s climate, particularly through atmospheric heating and ozone depletion, remains a critical area of atmospheric research. While satellite data provide valuable insights, independent validation methods are necessary for ensuring accuracy. Twilight near-infrared (NIR) radiometry offers a promising approach for investigating aerosol properties, such as optical depth and layer height, at high altitudes. This study aims to evaluate the effectiveness of twilight radiometry in corroborating satellite data and assessing aerosol characteristics. Two methods based on twilight radiometry—the color ratio and the derivative method—are employed to derive the aerosol layer height and optical depth. Radiances at 450, 550, 762, 775, and 1050 nm wavelengths are analyzed at varying solar zenith angles, using zenith viewing geometry for consistency. Comparisons of aerosol optical depths (AODs) between Research Pandora (ResPan) and AErosol RObotic NETwork (AERONET) data (R = 0.99) and between ResPan and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data (R = 0.86) demonstrate a strong correlation. Twilight ResPan data are also used to estimate the aerosol layer height, with results in good agreement with SAGE and lidar measurements, particularly following the Hunga Tonga eruption in Lauder, New Zealand. The simulation database, created using the libRadtran DISORT and Monte Carlo packages for daylight and twilight calculations, is capable of detecting AODs as low as 10⁻³ using the derivative method. This work highlights the potential of twilight radiometry as a simple, cost-effective tool for atmospheric research and satellite data validation, offering valuable insights into aerosol dynamics at stratospheric altitudes. Full article

Marine atmospheric boundary-layer height (MABLH) is crucial for ocean heat, momentum, and substance transfer, affecting ocean circulation, climate, and ecosystems. Due to the unique geographical location of the South China Sea (SCS), coupled with its complex atmospheric environment and sparse ground-based observation stations, accurately determining the MABLH remains challenging. Coherent Doppler wind lidar (CDWL), as a laser-based active remote sensing technology, provides high-resolution wind profiling by transmitting pulsed laser beams and analyzing backscattered signals from atmospheric aerosols. In this study, we developed a stacking optimal ensemble model (SOEM) to estimate MABLH in the vicinity of the site by integrating CDWL measurements from a representative SCS site with ERA5 (fifth-generation reanalysis dataset from the European Centre for Medium-Range Weather Forecasts) data from December 2019 to May 2021. Based on the categorization of the total cloud cover data into weather conditions such as clear/slightly cloudy, cloudy/transitional, and overcast/rainy, the SOEM demonstrates enhanced performance with an average mean absolute percentage error of 3.7%, significantly lower than the planetary boundary-layer-height products of ERA5. The SOEM outperformed random forest, extreme gradient boosting, and histogram-based gradient boosting models, achieving a robustness coefficient ($R^2$) of 0.95 and the lowest mean absolute error of 32 m under the clear/slightly cloudy condition. The validation conducted in the coastal city of Qingdao further confirmed the superiority of the SOEM in resolving meteorological heterogeneity. The predictions of the SOEM aligned well with CDWL observations during Typhoon Sinlaku (2020), capturing dynamic disturbances in MABLH. Overall, the SOEM provides a precise approach for estimating convective boundary-layer height, supporting marine meteorology, onshore wind power, and coastal protection applications. Full article

This study presents a systematic analysis of the optical-physical properties of low clouds and their vertical interaction mechanisms with aerosols over three African sub-regions (A: North African Desert; B: Congo Basin; C: Southeastern Plateau and Coastal Zone) using CALIPSO satellite vertical observations taken between 2006 and 2021. The results revealed distinct spatiotemporal variations: For example, the low-cloud aerosol optical depth (AOD) in Region A peaked during December–February, while Regions B and C exhibited higher values from June to November, with elevated dry-season and daytime levels. A positive correlation emerged between low-cloud AOD and its fractional contribution. Regional contrasts in low-cloud vertical structure were evident, with Region C showing the highest seasonal mean cloud base/top heights and Region A the lowest. The depolarisation ratio of low clouds was higher in desert areas (Region A) but lower in rainforest regions (Region B), while the SRlc (Low-cloud spectral reflectance ratio) was maximised in the Congo Basin (Region B), with wet-season and daytime enhancements. The near-surface aerosol AOD in Regions A and B was positively correlated with low-cloud AOD proportion (PAOD_lc). Across all regions, the near-surface aerosol layer top height showed positive correlations with the low-cloud base height and vertical extent, while the height of the bottom of the near-surface aerosol layer was positively aligned with the low-cloud base height. For Region C, there were negative correlations between near-surface aerosol layer heights and PAOD_lc, whereas the springtime aerosol parameters in Region A exhibited positive PAOD_lc correlations. These findings advance the current understanding of aerosol sources and ecosystem impacts, and provide critical insights for refining aerosol and low-cloud parameterisations in climate models. Full article

This study investigated the dust storm observation data from the Taklimakan Desert in 2018, focusing on analyzing horizontal dust flux (Q), vertical dust flux (F), their relationships with aerosol optical depth (AOD), and the relationship between HYSPLIT backward trajectories and dust storm dispersion direction. Key findings include: (1) at the Xiaotang (XT) station, Q values at low heights (1–10 m) exceeded those at higher altitudes, highlighting the role of flat terrain in dust accumulation, while Q values at the Tazhong (TZ) station remained relatively stable, suggesting dust redistribution influenced by undulating topography; (2) vertical dust flux (F) decreased with height, with significant seasonal variations in spring linked to frequent dust events; (3) at station XT, the contribution of F at 5 m height is relatively strong to AOD and its peak precedes AOD by 24–72 h, although the direct correlation is weak; and (4) dust dispersion directions aligned with HYSPLIT trajectories and high Q values corresponded with remotely derived dust dispersion patterns. Full article

Open burning of biomass has occurred around the world, and emissions from biomass burning are impacting local, regional, and global air quality issues and climate change. This study focuses on severe biomass burning aerosols (BBAs) in Sumatra in September 2019. The chemical transport simulation model employed in this study is based on a meteorological field simulated by SCALE (Scalable Computing for Advanced Library and the Environmental Regional Model) for offline calculations. Simulation results are validated by using ground-based measurements and biomass burning aerosol distribution observed by JAXA/GCOM-C (Global Change Observation Mission-Climate)/SGLI (second-generation global imager). The results of this study show that the injection process in the model simulations has a significant impact on the aerosol distribution. Aerosols generated by fires can rise to higher altitudes due to the heat of the fire, but aerosols originating from surface and soil fires were found to reproduce well at less elevated injection height. Full article

Lidar has emerged as a pivotal technique within the booming field of plant phenotyping, which has seen significant advancements in recent years. Beyond the conventional LiDAR systems that determine distance based on time-of-flight principles, Scheimpflug LiDAR, an emerging technique proposed within the past decade, has also expanded its field to plant phenotyping. However, early applications of Scheimpflug LiDAR were predominantly focused on aerosol detection, where stringent requirements for range resolution were not paramount. In this paper, a detailed description of a Scheimpflug LiDAR designed for plant phenotyping is proposed. Furthermore, to ensure high-precision scanning of plant targets, a distance-adaptive Gaussian fitting methodology is proposed to improve the spatial precision from 0.1781 m to 0.044 m at 10 m, compared with the traditional maximum method. The results indicate that the point cloud data acquired through our method yield more precise phenotyping outcomes, such as diameter at breast height (DBH) and plant height. This paves the way for further application of the Scheimpflug LiDAR on growth stages monitoring and precision agriculture. Full article

Methane (CH₄) emissions in coal-energy-rich regions are characterized by hidden emission point sources and highly variable emission rates. While the Matched Filter (MF) method for detecting the CH₄ point source using hyperspectral satellite sensors has been validated for high-emission concentrations, the accurate inversion of low-concentration emissions in complex environments remains challenging. In this study, an ‘end-to-end’ experiment—from emission simulations to satellite spectra and inversion results—has been designed to quantify the impact of internal payload parameters and environmental parameters for CH₄ emission inversions, and perform real-scenario calculations. The study reveals several key findings: (1) Under ideal conditions, 15% of satellite spectral noise contributes to a 13% bias in CH4 detection inversion, and a spectral resolution of 10–14 nm allows the detection of CH₄ emissions with concentrations as low as 350 ppb, above the background level of 1900 ppb. (2) For near-surface aerosols at 2100 nm, an aerosol optical depth (AOD) of 0.1 leads to a low bias of −51.6% with water-soluble aerosols and a strong bias of −69.2% with black carbon aerosols, while dust aerosols induce a medium bias of up to −60.7%. (3) The height of the aerosol layer affects the accuracy of methane inversion, which is up to 7.3% higher under aerosol conditions at 3 km than under aerosol conditions near the ground. (4) When the CH₄ emission source and its diffuse plume are located above a high-reflectance (bright) surface, while the background CH₄ concentration is associated with a low-reflectance (dark) surface, the significant reflectance contrast between the two surfaces leads to a rapid degradation in inversion accuracy. This contrast makes it impossible to effectively extract CH₄ signals when the reflectance difference reaches 0.2. (5) Under harsh conditions, where multiple parameters are present (AOD = 0.2, albedo = 0.2, aerosol layer height (ALH) = 2), the MF method is still able to detect CH₄ emissions, but with a significant error of 74.65%. (6) External environmental variables, particularly atmospheric pressure and water vapor content, significantly influence the inversion accuracy of methane (CH₄) concentrations. Variations in atmospheric pressure induce deviations in the CH₄ concentration distribution, resulting in an average inversion error of −12.06%. Similarly, elevated water vapor levels can lead to a maximum error of −16.2%. These findings highlight the substantial challenges in accurately detecting low-concentration CH₄ emissions. The results offer critical insights for refining CH₄ detection algorithms and enhancing the precision of satellite-based inversions for low-concentration CH₄ point-source emissions. Full article

Near-surface ozone is a secondary pollutant, and its high concentrations pose significant risks to human and plant health. Based on an Extra Tree (ET) model, this study estimated near-surface ozone concentrations with the high spatiotemporal resolution based on Himawari-8 aerosol optical depth (AOD) data and meteorological variables from 1 January 2016 to 31 December 2020. The SHapley Additive exPlanation (SHAP) method was employed to evaluate the contribution of AOD and meteorological factors on ozone concentration. The results indicate that (1) the ET model achieves a sample-based cross-validation R² of 0.75–0.87 and an RMSE (μg/m³) of 17.96–20.30. The coefficient of determination (R²) values of the model in spring, summer, autumn, and winter are 0.81, 0.80, 0.87, and 0.75, respectively. (2) Higher temperature and boundary layer heights were found to positively contribute to ozone concentration, whereas higher relative humidity exerted a negative influence. (3) From 11:00 to 15:00 (Beijing time, UTC+08:00), ozone concentration increases gradually, with the highest occurring in the summer, followed by spring. This study has obtained high spatial and temporal resolution ozone concentration data, offering valuable insights for the development of fine-scale ozone pollution prevention and control strategies. Full article

Aerosol vertical stratification significantly influences the Earth’s radiative balance and particulate-matter-related air quality. Continuous vertically resolved observations remain scarce compared to surface-level and column-integrated measurements. This work presents and makes available a novel, long-term (2016–2022) aerosol dataset derived from continuous (24/7) vertical profile observations from three selected stations (Aosta, Rome, Messina) of the Italian Automated Lidar-Ceilometer (ALC) Network (ALICENET). Using original retrieval methodologies, we derive over 600,000 quality-assured profiles of aerosol properties at the 15 min temporal and 15 metre vertical resolutions. These properties include the particulate matter mass concentration (PM), aerosol extinction and optical depth (AOD), i.e., air quality legislated quantities or essential climate variables. Through original ALICENET algorithms, we also derive long-term aerosol vertical layering data, including the mixed aerosol layer (MAL) and elevated aerosol layers (EALs) heights. Based on this new dataset, we obtain an unprecedented, fine spatiotemporal characterisation of the aerosol vertical distributions in Italy across different geographical settings (Alpine, urban, and coastal) and temporal scales (from sub-hourly to seasonal). Our analysis reveals distinct aerosol daily and annual cycles within the mixed layer and above, reflecting the interplay between site-specific environmental conditions and atmospheric circulations in the Mediterranean region. In the lower troposphere, mixing processes efficiently dilute particles in the major urban area of Rome, while mesoscale circulations act either as removal mechanisms (reducing the PM by up to 35% in Rome) or transport pathways (increasing the loads by up to 50% in Aosta). The MAL exhibits pronounced diurnal variability, reaching maximum (summer) heights of >2 km in Rome, while remaining below 1.4 km and 1 km in the Alpine and coastal sites, respectively. The vertical build-up of the AOD shows marked latitudinal and seasonal variability, with 80% (30%) of the total AOD residing in the first 500 m in Aosta-winter (Messina-summer). The seasonal frequency of the EALs reached 40% of the time (Messina-summer), mainly in the 1.5–4.0 km altitude range. An average (wet) PM > 40 μg m⁻³ is associated with the EALs over Rome and Messina. Notably, 10–40% of the EAL-affected days were also associated with increased PM within the MAL, suggesting the entrainment of the EALs in the mixing layer and thus their impact on the surface air quality. We also integrated ALC observations with relevant, state-of-the-art model reanalysis datasets (ERA5 and CAMS) to support our understanding of the aerosol patterns, related sources, and transport dynamics. This further allowed measurement vs. model intercomparisons and relevant examination of discrepancies. A good agreement (within 10–35%) was found between the ALICENET MAL and the ERA5 boundary layer height. The CAMS PM₁₀ values at the surface level well matched relevant in situ observations, while a statistically significant negative bias of 5–15 μg m⁻³ in the first 2–3 km altitude was found with respect to the ALC PM profiles across all the sites and seasons. Full article

An ultralight aircraft was equipped with atmospheric monitoring instruments and flown above Copenhagen on the 17 June 2022 to measure a range of aerosol parameters and meteorology. Three flights were carried out from sunrise to early afternoon with the aim to capture the boundary layer structure and evolution due to surface warming, emissions from the city, and atmospheric mixing. The data show clear evidence of the boundary layer which expanded from 400–600 m in height at around 07:30 to 1200–1400 m by around 14:30. Additionally, a residual boundary layer was observed in the early morning, and an entrainment of pollution at the top of the boundary layer in the early afternoon. The observed atmospheric features were consistent between monitoring instruments and meteorological sensors, supporting the reliability of the data and aircraft setup. These results demonstrate the merits and limitations of the use of small aircraft for scientific research and monitoring of aerosols in the vertical dimension, especially in densely populated areas and high-traffic airspaces. Full article