Atmosphere

19 pages, 20182 KB

Open AccessArticle

Optimal Initial Error and Targeted Observation Sensitive Area for Predicting the Northeast China Cold Vortex Revealed by a Deep Learning Model

by Chen Zhang, Junkai Qian and Qiang Wang

Atmosphere 2026, 17(6), 567; https://doi.org/10.3390/atmos17060567 (registering DOI) - 30 May 2026

Abstract

The Northeast China Cold Vortex (NECV) is a key circulation system affecting weather patterns over North China, frequently triggering thunderstorms, hail, and other severe convective weather. Accurate prediction of NECVs is therefore of great importance. However, substantial forecast errors still remain, largely due [...] Read more.

The Northeast China Cold Vortex (NECV) is a key circulation system affecting weather patterns over North China, frequently triggering thunderstorms, hail, and other severe convective weather. Accurate prediction of NECVs is therefore of great importance. However, substantial forecast errors still remain, largely due to uncertainties in the initial conditions. To improve NECV forecast skills, we investigate the optimal initial errors and targeted observation sensitive areas using a sampling-based approximation of the conditional nonlinear optimal perturbation (CNOP) method together with the Pangu-Weather deep learning model. We first evaluate the model’s performance over Northeast China and find that Pangu-Weather exhibits forecast skill generally comparable to the ECMWF Integrated Forecasting System (IFS) during the May–August 2022 period over Northeast China. Then the CNOP-based approach is used to capture the optimal initial errors with the greatest impact on NECV forecasts. The largest error amplitudes are primarily located upstream of the vortex and near upper-level jet-entrance regions, which are identified as the targeted observation sensitive areas. Perturbation kinetic-energy diagnostics further indicate that baroclinic conversion is the dominant mechanism for error growth. Observing system simulation experiments suggest that, under an idealized assumption of completely eliminating errors in a given region, targeted observations over the sensitive area can produce the largest forecast improvement, with an average error reduction of approximately 13% relative to other areas. This study contributes to a deeper understanding of NECV predictability and may help improve forecasting capability. Full article

(This article belongs to the Special Issue Meteorological Extreme in China)

► Show Figures

Figure 1

20 pages, 5438 KB

Open AccessArticle

Heatwave Conditions and Long-Term Variability of Air Pollutants in a Spanish Urban Environment

by Jude Maduabuchi Anyanwu, María Ángeles García and Isidro A. Pérez

Atmosphere 2026, 17(6), 566; https://doi.org/10.3390/atmos17060566 (registering DOI) - 30 May 2026

Abstract

Heatwave conditions are increasingly being recognized as important drivers of urban air-quality variability in southern European cities, particularly in inland urban environments exposed to persistent summer warming and atmospheric stagnation. This study examines the long-term variability of O₃, NO₂, [...] Read more.

Heatwave conditions are increasingly being recognized as important drivers of urban air-quality variability in southern European cities, particularly in inland urban environments exposed to persistent summer warming and atmospheric stagnation. This study examines the long-term variability of O₃, NO₂, and PM_2.5 concentrations in Valladolid, Spain, between 2006 and 2024, focusing particular attention on the occurrence and persistence of heatwave conditions. Ground-level ozone (O₃), nitrogen dioxide (NO₂), and fine particulate matter (PM_2.5) were analyzed to assess temporal variability, seasonal behavior, long-term trends, and exceedance characteristics. Results indicate an increasing persistence of heatwave episodes during the study period, particularly after 2015, with recent events exhibiting longer duration and broader regional extent. O₃ concentrations showed stronger accumulation during warm-season conditions, which is consistent with enhanced photochemical activity under elevated temperatures, while NO₂ concentrations generally declined over time. PM_2.5 variability reflected both local emissions and episodic regional influences, including Saharan dust intrusions. These findings highlight the growing relevance of heatwave conditions in shaping urban air-quality variability in medium-sized inland cities of the Iberian Peninsula. Full article

(This article belongs to the Section Air Quality and Health)

► Show Figures

Figure 1

18 pages, 2107 KB

Open AccessArticle

Source Apportionment and Ozone Formation Potential Analysis of Atmospheric Unsaturated Hydrocarbon Volatile Organic Compounds in Beihai City During Summer

by Qinqin Wu and Ying Wu

Atmosphere 2026, 17(6), 565; https://doi.org/10.3390/atmos17060565 (registering DOI) - 30 May 2026

Abstract

Unsaturated hydrocarbons, including alkenes, alkynes, and aromatic hydrocarbons, are important components of atmospheric volatile organic compounds (VOCs) and serve as key precursors for ozone, a major photochemical pollutant. This study aimed to characterize the sources and ozone formation potential of 29 unsaturated hydrocarbon [...] Read more.

Unsaturated hydrocarbons, including alkenes, alkynes, and aromatic hydrocarbons, are important components of atmospheric volatile organic compounds (VOCs) and serve as key precursors for ozone, a major photochemical pollutant. This study aimed to characterize the sources and ozone formation potential of 29 unsaturated hydrocarbon VOCs in Beihai, a coastal city in southern China, on the basis of continuous online monitoring conducted during the summer of 2022. Continuous monitoring of unsaturated hydrocarbon VOCs in the ambient air of Beihai city during summer was conducted using a rapid online monitoring system for atmospheric VOCs. The results revealed that the total daily average concentration of unsaturated hydrocarbon VOCs was 1.21 ppbv, with an average concentration of 0.026 ppbv. The order of abundance was alkenes > aromatic hydrocarbons > alkynes. Source apportionment using the positive matrix factorization (PMF) model revealed that vehicle exhaust emissions were the primary source of unsaturated hydrocarbon VOCs in the city of Beihai, contributing 36.02%. Secondary sources included combustion sources (26.15%), solvent usage (18.55%), fuel evaporation (10.17%), and biogenic sources (9.10%). The contribution of unsaturated hydrocarbon VOCs to ozone formation was estimated using the ozone formation potential (OFP). Aromatic hydrocarbons contributed the most (51.22%), followed by alkenes (41.8%). Analysis of the diurnal variation patterns of unsaturated hydrocarbons revealed that combustion sources occurred during the night (01:00–02:00), suggesting that enhanced supervision and control measures during nighttime hours are warranted. Full article

(This article belongs to the Special Issue Advances in Air Quality Monitoring and Source Apportionment)

► Show Figures

Figure 1

22 pages, 31517 KB

Open AccessArticle

Physics-Guided Machine-Learning Correction of ERA5 Surface Downward Shortwave Radiation over China

by Ming Wang, Pengjie Sun, Yang Cui and Yang Xu

Atmosphere 2026, 17(6), 564; https://doi.org/10.3390/atmos17060564 (registering DOI) - 29 May 2026

Abstract

Accurate surface downward shortwave radiation (SDSR) is essential for solar resource assessment, photovoltaic applications, and land–atmosphere studies. Although ERA5 is widely used in radiation-related research, its SDSR estimates over China still show considerable uncertainties under complex topographic and climatic conditions. Using hourly observations [...] Read more.

Accurate surface downward shortwave radiation (SDSR) is essential for solar resource assessment, photovoltaic applications, and land–atmosphere studies. Although ERA5 is widely used in radiation-related research, its SDSR estimates over China still show considerable uncertainties under complex topographic and climatic conditions. Using hourly observations from the 162-station China Meteorological Administration (CMA) radiation network during April 2024–March 2025, of which 160 stations were retained after quality control, this study systematically evaluated ERA5 SDSR and developed a physics-guided Light Gradient Boosting Machine (LightGBM) correction framework. Raw ERA5 exhibits a strong systematic positive bias (PBIAS = 57.40%, ME = 124.2 W/m²) together with a pronounced nonlinear structural bias, characterized by overestimation under low-radiation conditions and underestimation under high-radiation conditions. The largest errors occur in the Southern Monsoon region in summer and the Northwest Arid region in spring, indicating the combined effects of cloud extinction, aerosol attenuation, and terrain-related representativeness differences. To address these mechanisms, the correction model incorporates physically relevant predictors from ERA5 and Copernicus Atmosphere Monitoring Service (CAMS), including cloud microphysical variables, aerosol optical depth, solar geometry, and elevation. SHapley Additive exPlanations (SHAP) analysis shows that the learned correction behavior is broadly consistent with known radiative-transfer processes. On the independent station hold-out test set, the correction increases the Pearson correlation coefficient from 0.8680 to 0.8967 and reduces RMSE from 173.1 to 100.8 W/m², while substantially suppressing the strong positive bias of raw ERA5. Additional robustness tests, including season-blocked validation, interpolation-sensitivity analysis, ablation experiments, and multi-model comparison, further support the stability of the framework. External benchmarking against FY-4B and Himawari also shows that the corrected ERA5 substantially narrows the gap relative to independent geostationary satellite products. Overall, the proposed framework provides an effective and physically interpretable approach for improving ERA5 SDSR over China. Full article

(This article belongs to the Special Issue Solar Radiation, Aerosol, and Multiple Interactions Between Solar Radiation and Atmospheric Substances)

► Show Figures

Figure 1

21 pages, 4293 KB

Open AccessArticle

Threshold Effects of Vegetation Structure on Outdoor Thermal Comfort: Balancing Radiative Shading and Ventilation in Rural Environments

by Peng Gao, Zhuan Liu and Azmiah Abd Ghafar

Atmosphere 2026, 17(6), 563; https://doi.org/10.3390/atmos17060563 (registering DOI) - 29 May 2026

Abstract

Outdoor open spaces are essential for daily activities in ageing rural environments, yet the thermal effectiveness of vegetation under varying structural configurations remains unclear. Most existing Outdoor Thermal Comfort studies focus on dense urban canyons; the present study addresses this gap by examining [...] Read more.

Outdoor open spaces are essential for daily activities in ageing rural environments, yet the thermal effectiveness of vegetation under varying structural configurations remains unclear. Most existing Outdoor Thermal Comfort studies focus on dense urban canyons; the present study addresses this gap by examining a complexity threshold in vegetation cooling under high-SVF rural conditions and the radiation–ventilation trade-off that underlies it. An ENVI-met model was calibrated using field data from a typical village on the North China Plain and 17 vegetation scenarios were simulated. The findings reveal a non-linear relationship between vegetation complexity and cooling efficiency. A threshold of complexity was observed: the cooling performance declined with an increase in stratification from a double-layer (Scenario 12) to a triple-layer (Scenario 14) structure, with the change in mean radiant temperature (∆T_mrt) dropping from 23.16 °C to 21.10 °C. This is due to a radiation–ventilation trade-off, in which denser vegetation increases shading but reduces near-surface ventilation. Dense arrangements exhibit a heat trap effect, with the long-wave radiation flux changing from a cooling (−3.42 K/h) to a heating (+2.11 K/h) state. The results show a threshold effect in vegetation cooling and that thermal comfort is not necessarily enhanced by increased complexity. A shaded-canopy and permeable-understory structure is found to be optimal. The findings inform vegetation design in climate-adaptive rural settings. Full article

(This article belongs to the Special Issue Urban Overheating, UHI Adaptation, and Nexus with Energy Transition in the Context of the Urban Landscape and Environment)

► Show Figures

Graphical abstract

29 pages, 29210 KB

Open AccessArticle

Satellite-Based Assessment of Potential Microclimatic Effects of Photovoltaic (PV) Power Plants in Vulnerable Agroecosystems

by Ioannis Faraslis, Nicolas R. Dalezios, Marios Spiliotopoulos, Nikolaos Alpanakis, Stavros Sakellariou, Vagelis Brisimis and Nicholas Dercas

Atmosphere 2026, 17(6), 562; https://doi.org/10.3390/atmos17060562 (registering DOI) - 29 May 2026

Abstract

There is a strong global increase in the installation of renewable energy power plants, due to increasing energy demand in the electricity generation sector and fast cost reduction. Recent studies indicate that the installation and operation of photovoltaic (PV) power plants have negligible [...] Read more.

There is a strong global increase in the installation of renewable energy power plants, due to increasing energy demand in the electricity generation sector and fast cost reduction. Recent studies indicate that the installation and operation of photovoltaic (PV) power plants have negligible microclimatic effects, although there are minor effects on night temperature in some cases, which, however, do not justify climate or environmental change. The development of solar energy and the installation and operation of PV power plants serve as a key solution for the energy transition to reduce carbon emissions and to address global warming. Despite the benefit of emission reduction, the deployment of solar energy through the installation of solar power plants causes land cover changes and may have minor effects on the surface energy balance by modifying roughness and albedo, biodiversity by disturbing habitats, and water resources by requiring water for cooling and cleaning. These changes may also lead to minor climatic, ecological, and social impacts. The objective of the paper consists of assessing the potential microclimatic effects of photovoltaic power plants based on satellite-based land surface temperature (LST) analyses. Specifically, the potential change in the land surface temperature, both under photovoltaic panels and on the panels, in relation to the temperature of the surrounding area is being examined in this study. The implementation is conducted in Mediterranean ecosystems, which are considered vulnerable agroecosystems due to increased climate variability. The final Landsat-based time series analysis further supports this synthesis, reporting that monthly LST differences between the PV Park and surrounding area are negligible and do not indicate a meaningful microclimate alteration attributable to PV operations. Accordingly, the evidence supports the core conclusion: utility-scale PV deployment does not constitute a driver of climate change, and the documented effects are best understood as localized surface–atmosphere energy-balance perturbations whose sign and magnitude depend on land cover, seasonality, and operation. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

29 pages, 2328 KB

Open AccessArticle

Non-Cumulative, Size-Specific Calibration of Low-Cost Particulate Matter Sensors Under Simulated Construction Drilling Events

by Askarov Komiljon and Jae-ho Choi

Atmosphere 2026, 17(6), 561; https://doi.org/10.3390/atmos17060561 (registering DOI) - 29 May 2026

Abstract

Urban construction activities are recognized as significant contributors to particulate matter (PM) emissions; however, the accurate real-time monitoring of size-resolved PM fractions presents a formidable challenge. Traditional low-cost PM sensors predominantly report cumulative concentrations, which obscures the distinct health and regulatory significance of [...] Read more.

Urban construction activities are recognized as significant contributors to particulate matter (PM) emissions; however, the accurate real-time monitoring of size-resolved PM fractions presents a formidable challenge. Traditional low-cost PM sensors predominantly report cumulative concentrations, which obscures the distinct health and regulatory significance of PM1, PM2.5, and PM10. This study systematically evaluates the performance of two low-cost sensors—PMS5003 and Sniffer4D—utilizing non-cumulative measurements obtained under controlled laboratory conditions designed to simulate construction PM generated from concrete slab drilling. Sensor performance was rigorously analyzed using Pearson correlation coefficients, standard deviation, and mean percentage differences. Six correction models—linear regression, polynomial regression, Random Forest (RF), XGBoost, Artificial Neural Network (ANN), and Kalman filter—were independently developed for each PM size fraction to enhance measurement precision. Findings reveal that RF and ANN consistently provided the most accurate corrections, particularly for PM1 and PM2.5, with RF achieving a coefficient of determination (R²) > 0.89 for PM1 and R² > 0.87 for PM2.5 at the 50 s duration. This investigation introduces a size-resolved correction framework specifically designed for construction environments, thereby advancing the capability of low-cost sensors to enable accurate particle-specific exposure assessments. Full article

(This article belongs to the Special Issue Emerging Technologies for Observation of Air Pollution (2nd Edition))

26 pages, 4583 KB

Open AccessArticle

Assessing the Impact of Energy Retrofits on Indoor Climate Conditions Using Mixed Effects Models: Methodology and R Implementation

by Asit Kumar Mishra

Atmosphere 2026, 17(6), 560; https://doi.org/10.3390/atmos17060560 (registering DOI) - 29 May 2026

Abstract

Energy retrofit interventions have become increasingly critical as building sectors worldwide pursue decarbonization targets and improved energy efficiency. However, establishing robust causal inference about retrofit impacts on indoor climate conditions remains challenging due to confounding variables including outdoor climate fluctuations and occupant behavior. [...] Read more.

Energy retrofit interventions have become increasingly critical as building sectors worldwide pursue decarbonization targets and improved energy efficiency. However, establishing robust causal inference about retrofit impacts on indoor climate conditions remains challenging due to confounding variables including outdoor climate fluctuations and occupant behavior. This paper presents a methodological framework for analyzing pre- and post-retrofit indoor climate data using linear mixed effects (LME) models, which explicitly account for building-level variability while controlling for environmental and behavioral factors. The approach is demonstrated using a case study analyzing partial pressure of water vapor in Irish residential homes before and after energy retrofit interventions. The analysis incorporates standardized coefficients to assess relative importance of predictive factors and employs model parsimony through stepwise removal of non-significant terms. Complete R code is provided to facilitate adaptation by other researchers. Our results demonstrate that LME models provide unbiased estimates of retrofit effects while avoiding aggregation bias that plague simpler analyses. This paper serves as both methodological reference and practical guide for practitioners seeking to rigorously evaluate building retrofit effectiveness across diverse indoor climate parameters. Full article

(This article belongs to the Section Air Quality)

► Show Figures

Figure 1

19 pages, 913 KB

Open AccessArticle

On the Mechanical and Thermodynamic Influences of Ocean Spray in Hurricane Boundary Layers

by Yevgenii Rastigejev, Sergey A. Suslov and Wenbin Dong

Atmosphere 2026, 17(6), 559; https://doi.org/10.3390/atmos17060559 (registering DOI) - 29 May 2026

Abstract

This study investigates the mechanical and thermodynamic effects of evaporating ocean spray on the structure and dynamics of a hurricane marine atmospheric boundary layer using Eulerian multifluid and mixture model approaches coupled with the

E - ϵ

turbulence closure. The multifluid framework treats [...] Read more.

This study investigates the mechanical and thermodynamic effects of evaporating ocean spray on the structure and dynamics of a hurricane marine atmospheric boundary layer using Eulerian multifluid and mixture model approaches coupled with the

E - ϵ

turbulence closure. The multifluid framework treats air and spray as interpenetrating phases, enabling a physically consistent representation of air–droplet interactions governing momentum transfer, enthalpy exchange, and turbulence modulation. The mixture approach is based on a simplified description that captures only part of the underlying physics yet offers an advantage in its ability to yield analytical insight. Mechanically, spray produces competing effects: on one hand, droplet inertia causes wind deceleration, and on the other, spray-induced turbulence attenuation, primarily resulting from the air–droplet friction, leads to strengthening the wind. Analytical and numerical results show that the latter effect prevails for typical spray droplet sizes leading to wind acceleration and drag reduction at hurricane wind speeds. Thermodynamically, evaporating droplets redistribute total heat flux in favor of its latent component, with effects strongly dependent on the droplet size. Small droplets suppress turbulence and reduce the total enthalpy flux, whereas large ones enhance it. Furthermore, spray significantly increases the total enthalpy-to-drag coefficient ratio with wind speed, which agrees with field observations. Full article

(This article belongs to the Section Meteorology)

► Show Figures

Figure 1

22 pages, 11821 KB

Open AccessArticle

Impacts from HONO Chemistry on Atmospheric Oxidation Capacity: A Case Study in Shanghai

by Wei Zhang, Ming Hu, Jialiang Feng, Qingyan Fu and Shunyao Wang

Atmosphere 2026, 17(6), 558; https://doi.org/10.3390/atmos17060558 (registering DOI) - 29 May 2026

Abstract

Nitrous acid (HONO) plays a vital role in atmospheric oxidation capacity (AOC) and ozone (O₃) formation. Based on 2017–2021 observations at urban Pudong (PD) and suburban Qingpu (QP) in Shanghai, HONO concentrations ranged from 0.74 ± 0.45 to 1.38 ± 0.52 [...] Read more.

Nitrous acid (HONO) plays a vital role in atmospheric oxidation capacity (AOC) and ozone (O₃) formation. Based on 2017–2021 observations at urban Pudong (PD) and suburban Qingpu (QP) in Shanghai, HONO concentrations ranged from 0.74 ± 0.45 to 1.38 ± 0.52 ppb in PD and 0.82 ± 0.50 to 1.19 ± 0.62 ppb in QP, with higher levels in summer and a typical morning peak at 8–9 a.m. HONO photolysis produced an average of 1.9 ppb h⁻¹ of OH in summer, significantly elevating AOC. Under HONO constraints, summer O₃ production rates via HO₂ + NO and RO₂ + NO increased by 16% and 20%, respectively. These results highlight the key contribution of HONO chemistry to photochemical pollution and provide implications for air quality control in the Yangtze River Delta. Full article

(This article belongs to the Special Issue Air Pollution: Emission Characteristics and Formation Mechanisms)

► Show Figures

Figure 1

19 pages, 6274 KB

Open AccessArticle

PM_2.5 Concentration Prediction Based on STL-TimesNet-TimeXer Hybrid Framework

by Siqi Xiong, Zuhan Liu, Yan Li and Zonghao Nie

Atmosphere 2026, 17(6), 557; https://doi.org/10.3390/atmos17060557 (registering DOI) - 29 May 2026

Abstract

This study proposes a hybrid forecasting framework that integrates Seasonal-Trend decomposition using LOESS (the following abbreviations are referred to as STL) with two time series models, TimesNet and TimeXer. To capture the complex periodic characteristics of the PM_2.5 series, the original data [...] Read more.

This study proposes a hybrid forecasting framework that integrates Seasonal-Trend decomposition using LOESS (the following abbreviations are referred to as STL) with two time series models, TimesNet and TimeXer. To capture the complex periodic characteristics of the PM_2.5 series, the original data are first decomposed into trend, seasonal and residual components via STL. The trend and seasonal components are then predicted using TimesNet, which maps one-dimensional time series into a two-dimensional representation to better model multi-scale periodicities and temporal dependencies. In parallel, the residual component is forecast using TimeXer, which incorporates exogenous variables to improve the modeling of endogenous dynamics. The final PM_2.5 prediction is obtained by aggregating the forecasts of the three components. Experimental results demonstrate that the proposed STL-TimesNet-TimeXer model achieves high predictive accuracy, with an R² of 0.969, MAE of 2.834, MSE of 19.063, and MAPE of 6.435. Comparative analyses against single-model baselines further confirm that STL-based decomposition significantly enhances forecasting performance, indicating that STL provides an effective and interpretable approach for modeling PM_2.5 time series. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

► Show Figures

Figure 1

16 pages, 19052 KB

Open AccessArticle

Estimating Effect of Sheltering on Horizontal Measurement of Global Solar Radiation Using a Pyranometer

by Yi-Da Chung, Hung-Hsun Chen and Keh-Chin Chang

Atmosphere 2026, 17(6), 556; https://doi.org/10.3390/atmos17060556 (registering DOI) - 28 May 2026

Abstract

Horizontal measurement of global radiation on the rooftop of a weather station is generally hindered by the presence of obstructions surrounding the pyranometer. To investigate the sheltering effect, measured data from two weather stations in Taiwan, namely the Taitung (TWS) and Penghu (PWS) [...] Read more.

Horizontal measurement of global radiation on the rooftop of a weather station is generally hindered by the presence of obstructions surrounding the pyranometer. To investigate the sheltering effect, measured data from two weather stations in Taiwan, namely the Taitung (TWS) and Penghu (PWS) weather stations, were compared with corresponding in situ data measured under zero-shelter environments at nearby locations: the Taitung Center of National Open University (TCNOU) and the Penghu University of Science and Technology (PUST). The shelter view factor around the installed pyranometer was determined using a fisheye-lens image together with a calculation method based on a polar grid representation with sufficiently fine annuli. The shelter view factors for TWS and PWS were 11.8% and 5.0%, respectively. Comparisons of the monthly global radiation data measured at TWS and TCNOU and at PWS and PUST showed that underestimations of global radiation ranged from 1.8 to 9.1% (2016–2017) at TWS and from 1.3 to 4.2% (May 2015–December 2017) at PWS. These underestimations were primarily attributed to the magnitude of the shelter view factor for all obstructions around the pyranometer but were also dependent on the local pattern of global radiation (that is, beam and diffuse radiation), which is a climatological factor. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

► Show Figures

Graphical abstract

25 pages, 10652 KB

Open AccessArticle

Air Temperature and Thermal Regime Evolution in Livingston and Deception Islands, Maritime Antarctica (2000–2022)

by Miguel Ángel de Pablo and Gabriel Goyanes

Atmosphere 2026, 17(6), 555; https://doi.org/10.3390/atmos17060555 (registering DOI) - 28 May 2026

Abstract

Near-surface air temperature is the main atmospheric forcing of frozen-ground systems in maritime Antarctica, yet most studies have emphasized mean annual or seasonal trends rather than thermal-regime evolution. This study analyzes hourly air-temperature records from eight PERMATHERMAL monitoring stations on Livingston and Deception [...] Read more.

Near-surface air temperature is the main atmospheric forcing of frozen-ground systems in maritime Antarctica, yet most studies have emphasized mean annual or seasonal trends rather than thermal-regime evolution. This study analyzes hourly air-temperature records from eight PERMATHERMAL monitoring stations on Livingston and Deception Islands (South Shetland Islands, Antarctica) for 2000–2022 to evaluate changes in mean conditions, daily thermal regimes, degree-day forcing, and their implications for frozen ground. Hourly data were aggregated to daily, monthly, annual, and thermal-year scales, and valid days were classified into six thermal regimes (F1, F2, IS, FT, T2, and T1). FDD, TDD, annual degree-day balance (BDD), and freezing and thawing season duration were also calculated. Recent warming is expressed not only as higher mean annual air temperature, but also as a reorganization of the annual thermal regime, with fewer cold days, more thaw-related conditions, and less negative BDD values at most stations. These changes are consistent with previously reported GST evolution and indicate a shift in atmospheric forcing toward weaker freezing dominance and more thaw-favorable conditions. However, their implications for active-layer thickness and permafrost stability should be interpreted as climatic indications rather than as the direct evidence of ground thermal change. Full article

(This article belongs to the Section Meteorology)

► Show Figures

Figure 1

11 pages, 1542 KB

Open AccessArticle

Numerical Simulation of the Impact of Turbulent Bursting on the Entrainment of Sand and Dust Particles

by Zewen Ju, Zhiyuan Wang, Wei Wang, Dan Wang, Ding Tong and Jie Zhang

Atmosphere 2026, 17(6), 554; https://doi.org/10.3390/atmos17060554 (registering DOI) - 28 May 2026

Abstract

Understanding the mechanisms by which sand and dust particles detach from the land surface has always been one of the most fundamental and critical issues in aeolian physics and dust-storm forecasting. In this study, large-eddy simulation (LES) was employed to resolve the near-wall [...] Read more.

Understanding the mechanisms by which sand and dust particles detach from the land surface has always been one of the most fundamental and critical issues in aeolian physics and dust-storm forecasting. In this study, large-eddy simulation (LES) was employed to resolve the near-wall turbulence structures. Turbulent bursting events were identified using the second-quadrant method, and a force-balance equation for dust-particle entrainment was formulated at burst locations to numerically simulate the entrainment process of particles of different sizes under bursting conditions. By integrating the latest observational data on near-wall turbulent coherent structures during dust storms both the accuracy of flow-field simulations and the physical consistency of particle force analyses were enhanced. The results suggest that, within the present idealized force-balance framework, near-wall turbulent bursting can provide aerodynamic forcing that contributes to the entrainment of sand and dust particles over the simulated parameter range. Under the same friction velocity, the mean number of lifted particles first increases and then decreases with particle size, exhibiting a parabolic trend. For particles of the same size, the number of lifted particles increases significantly with friction velocity. Under identical incoming wind speeds, the number flux of lifted particles decreases nonlinearly with increasing particle size, whereas the mass flux continues to rise with both friction velocity and particle size. These findings further confirm the critical contribution of aerodynamic entrainment to aeolian transport and provide numerical support for refining the dual-mechanism theory of sand entrainment. Full article

(This article belongs to the Special Issue Land Surface Dynamic Mechanisms and Anthropogenic Facility Disasters Caused by Sand/Dust Processes)

20 pages, 2129 KB

Open AccessArticle

Seismic Observations of the OSIRIS-REx Sample Return Capsule Reentry: Deployment, Signal Characteristics, and Wavefield Phenomenology

by Logan T. Scamfer, Elizabeth A. Silber, Miro Ronac Gianonne, Daniel C. Bowman, Nora R. Wynn, Michael Fleigle and Justin LaPierre

Atmosphere 2026, 17(6), 553; https://doi.org/10.3390/atmos17060553 - 28 May 2026

Abstract

Controlled spacecraft reentries from interplanetary trajectories provide rare, well-characterized hypersonic sources for advancing seismoacoustic observation techniques. Here we present seismic observations of the OSIRIS-REx sample return capsule (SRC) reentry on 24 September 2023, recorded by 16 three-component nodal seismometers deployed near Eureka, Nevada, [...] Read more.

Controlled spacecraft reentries from interplanetary trajectories provide rare, well-characterized hypersonic sources for advancing seismoacoustic observation techniques. Here we present seismic observations of the OSIRIS-REx sample return capsule (SRC) reentry on 24 September 2023, recorded by 16 three-component nodal seismometers deployed near Eureka, Nevada, at ground distances of 7–20 km from the capsule trajectory. Air-to-ground coupled signals are detected at all stations, exhibiting impulsive onsets consistent with ballistic shock arrivals from the descending Mach cone. We characterize the seismic wavefield through signal amplitude, period, waveform cross-correlation, and array processing. Signal periods decrease systematically with increasing distance from the trajectory within the airport array, indicating that higher-frequency content becomes more prominent at greater offsets, opposite to expectations from geometric spreading and atmospheric absorption. Seismic array processing identifies frequency-dependent back-azimuth variations whose origin remains unresolved; possible contributing factors include source geometry, scattering by fine-scale layered structure in the stratosphere, and near-surface effects. These observations document a spatially complex seismic wavefield from a well-characterized hypersonic line source and provide constraints for future modeling of atmospheric propagation and air-to-ground coupling. Full article

(This article belongs to the Special Issue Shock Waves in the Atmosphere: Experimental and Computational Approaches for High-Energy Events)

► Show Figures

Figure 1

20 pages, 31107 KB

Open AccessArticle

Evaluation of Sea Ice–Atmosphere Boundary Layer in the North Atlantic–Arctic Ocean Based on High-Resolution Models

by Ruohan Li and Xiaoyu Wang

Atmosphere 2026, 17(6), 552; https://doi.org/10.3390/atmos17060552 - 28 May 2026

Abstract

Rapid Arctic warming has significantly altered sea ice–atmosphere boundary layer processes, which low-resolution models struggle to resolve accurately. This study evaluates the historical performance (1958–2014) of four high-resolution models from CMIP6 HighResMIP—EC-Earth3P-HR, CNRM-CM6-1-HR, HadGEM3-GC3.1-HH, and Fgoals-f3-H—against ORAS5 and CMEMS reanalysis datasets and examines [...] Read more.

Rapid Arctic warming has significantly altered sea ice–atmosphere boundary layer processes, which low-resolution models struggle to resolve accurately. This study evaluates the historical performance (1958–2014) of four high-resolution models from CMIP6 HighResMIP—EC-Earth3P-HR, CNRM-CM6-1-HR, HadGEM3-GC3.1-HH, and Fgoals-f3-H—against ORAS5 and CMEMS reanalysis datasets and examines their physical response to rapid warming under the SSP5-8.5 scenario (2015–2025). Results show substantial intermodel differences in simulating Arctic sea ice thickness, mixed layer depth, sea surface temperature and salinity, and deep convection. HadG-EM3-GC3.1-HH and CNRM-CM6-1-HR perform best overall, reliably reproducing trends in the two major deep convection regions, meridional temperature–salinity gradients, and long-term evolution with lower biases and higher correlations. Under decadal strong warming, models generally simulate shoaling mixed layers in deep convection zones and upper-water destabilization in the Canada Basin, but responses in sea ice, eddy kinetic energy, and transect temperature–salinity vary markedly. HadGEM3-GC3.1-HH and CNRM-CM6-1-HR better represent physical quantities and ocean stratification consistent with observed real-world responses. We conclude that these two models are more suitable for studies of Arctic sea ice–atmosphere boundary layer changes and deep convection, providing a basis for high-resolution model selection and Arctic climate projection. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

► Show Figures

Figure 1

21 pages, 7155 KB

Open AccessArticle

A Decadal Risk Assessment of Tourism Meteorological Disasters in Major Scenic Areas of Dayi County, Sichuan Province, China

by Sijie Gai, Jie Xu, Qiaoqiao Jing, Ruihang Ouyang and Jinjian Li

Atmosphere 2026, 17(6), 551; https://doi.org/10.3390/atmos17060551 - 28 May 2026

Abstract

With the rapid growth of tourism in Dayi County over the past decade, this study develops a meteorological disaster risk assessment framework for major tourist attractions in this region. Drawing upon daily precipitation and temperature records from 25 meteorological stations (2014–2023) alongside multi-source [...] Read more.

With the rapid growth of tourism in Dayi County over the past decade, this study develops a meteorological disaster risk assessment framework for major tourist attractions in this region. Drawing upon daily precipitation and temperature records from 25 meteorological stations (2014–2023) alongside multi-source geospatial data, we evaluate six primary attractions: Xiling Snow Mountain, Huashuiwan, Anren Ancient Town, Xinchang Ancient Town, Tianfu Huaxigu Valley, and Shujiu Cultural Park. The evaluation model integrates four core dimensions: hazard, environmental sensitivity, asset vulnerability, and disaster mitigation capacity. Indicator weights are determined through the Analytic Hierarchy Process, and GIS-based spatial analysis is employed for risk zonation. Additionally, the 45-year ChinaMet dataset provides independent validation for the long-term stability of the hazard assessment. Results reveal a distinct west-low, east-high composite risk gradient. High-altitude mountainous regions in the west exhibit a lower overall risk. Despite frequent extreme weather events, extensive vegetation coverage and low visitor density effectively buffer the negative impacts of physical hazards. Conversely, tourist attractions on the eastern plains fall within high-risk zones. Concentrated visitor populations, dense built environments, and low-lying terrain collectively amplify exposure to severe rainstorms and extreme heatwaves. These findings demonstrate that meteorological disaster risk in tourism destinations fundamentally arises from the deep coupling of natural and human systems. Thus, this study provides a scientific basis for implementing differentiated disaster prevention, mitigation, and localized emergency management strategies. Full article

(This article belongs to the Special Issue Holocene Climate and Environmental Change in Arid Central Asia)

► Show Figures

Graphical abstract

18 pages, 13473 KB

Open AccessArticle

Evaluation of PBL Schemes in Weather Research and Forecasting Model Simulations of Downslope Windstorm over Modest Terrain in Southern Brazil

by Mateus Rebelo, Michel Stefanello, Daniel C. Santos, Richard Lobato, Tamires Zimmer, Murilo Lopes, Cinara E. da Rosa, Alecsander Mergen, Ernani de Lima Nascimento, Gervasio Degrazia, Debora Roberti and Rafael Maroneze

Atmosphere 2026, 17(6), 550; https://doi.org/10.3390/atmos17060550 (registering DOI) - 28 May 2026

Abstract

Vento Norte (VNOR; Portuguese for North Wind) is a downslope windstorm that develops over modest terrain in the central region of Rio Grande do Sul (RS), southern Brazil. The regional topography is characterized by an abrupt terrain transition with elevation differences of approximately [...] Read more.

Vento Norte (VNOR; Portuguese for North Wind) is a downslope windstorm that develops over modest terrain in the central region of Rio Grande do Sul (RS), southern Brazil. The regional topography is characterized by an abrupt terrain transition with elevation differences of approximately 400–500 m. This atmospheric flow typically occurs during the cold season and is characterized by strong wind gusts, rapid warming, and drying of the planetary boundary layer (PBL). In this study, the performance of different PBL parameterization schemes in the Weather Research and Forecasting (WRF) model is assessed for simulating a VNOR event that occurred between 19 and 20 August 2021 in Santa Maria (SMA), RS. Five high-resolution numerical simulations were conducted using the Yonsei University (YSU), Asymmetric Convective Model version 2 (ACM2), Mellor–Yamada–Nakanishi–Niino level 2.5 (MYNN2.5), Quasi-Normal Scale Elimination (QNSE), and Three-Dimensional Turbulent Kinetic Energy (3DTKE) PBL schemes. Model results were evaluated against observations from a flux tower providing turbulence measurements, twice-daily radiosoundings, and hourly surface meteorological observations. Statistical metrics indicate that the MYNN2.5 scheme provided the most accurate representation of the nighttime stable boundary layer preceding the VNOR, as well as its onset and subsequent evolution. Although this study analyzes a single VNOR event and the results may be case-dependent, the overall performance of the MYNN2.5 scheme suggests that it is a promising option for the operational forecasting of VNOR events. These findings provide new insights into the ability of different PBL schemes to reproduce the mean boundary-layer structure and turbulence characteristics associated with downslope windstorms over modest terrain, contributing to the understanding of these events. Full article

(This article belongs to the Special Issue Observations, Modeling, and Theory of the Atmospheric Boundary Layer)

► Show Figures

Figure 1

21 pages, 8762 KB

Open AccessArticle

Improving 10 m Wind Speed Forecasts over the Northwest Pacific Using a Deep Learning Network

by Jie Xiao, Xiaomei Chen, Bao Wang and Xishan Pan

Atmosphere 2026, 17(6), 549; https://doi.org/10.3390/atmos17060549 - 28 May 2026

Abstract

Accurate sea surface wind forecasts are essential for marine disaster prevention, maritime economic activities, and renewable energy development. However, traditional numerical weather prediction (NWP) models often encounter limitations such as nonlinear error accumulation and systematic biases during long-lead-time integration. Consequently, this study develops [...] Read more.

Accurate sea surface wind forecasts are essential for marine disaster prevention, maritime economic activities, and renewable energy development. However, traditional numerical weather prediction (NWP) models often encounter limitations such as nonlinear error accumulation and systematic biases during long-lead-time integration. Consequently, this study develops a spatiotemporal deep learning post-processing framework based on state space mechanisms, utilizing ERA5 reanalysis data to correct errors in 0–72 h NWP 10 m wind speed forecasts over the Northwest Pacific and adjacent regions (0–90° N, 100–150° E). Evaluations against mainstream spatiotemporal deep learning models indicate that the proposed framework improves the forecast accuracy and spatial consistency of the NWP. Regarding overall error control, the post-processing model reduces the root mean square error (RMSE) of the raw NWP from 1.47 m/s to 1.10 m/s for 24 h forecasts. Meanwhile, during the 72 h long-lead-time integration, the pattern correlation coefficient (PCC) of the forecasted wind field is maintained at 0.86, and the overall systematic bias converges from −0.27 m/s to −0.02 m/s. Additionally, the framework effectively mitigates the over-prediction of gale-force winds, reducing the false alarm ratio (FAR) by 30–50% compared to the raw NWP. These results indicate that the proposed deep learning post-processing strategy effectively corrects underlying systematic biases in numerical models, thereby enhancing the accuracy and reliability of long-term wind field forecasts. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

► Show Figures

Graphical abstract

Journal Description

Atmosphere

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI