Atmosphere, Volume 15, Issue 3 (March 2024) – 148 articles

In this study, the standard tent used by the China International Medical Team (Sichuan) was used as the research object to study the internal temperature change in medical tents in a low-temperature environment relying on heating equipment. Method: Four temperature sensors were arranged along the horizontal direction at a 1.2 m height in the medical tent, and more sensors were installed at heights of 0.1, 0.2, 0.6, 1.2, 1.8, 2.4, and 2.5 m. A total of 11 temperature sensors were set. Temperature tests were conducted in January and February 2021 in Chengdu, Sichuan Province. During the test, the running time of the heating equipment was controlled in real time according to the temperature change trend. A Kolmogorov–Smirnov(K-S) test was used to verify the reliability of the experimental data. The temperature change trend was used to characterize the influence of the heating and cooling equipment on the temperature change inside the tent. Results: Due to the position angle of the heating equipment and the influence of the external environment, the spatial distribution of the ambient temperature inside the medical tent was obviously uneven. In winter, an electric heater with a heating power of about 2500 W can increase the internal temperature of the tent to 16.7 °C, significantly improving the internal thermal environment of the medical tent. The ambient temperature in the medical tent is positively correlated with the height and the installation position of the heating equipment. Conclusion: Medical tents can maintain the ambient temperature well to meet medical needs with the support of heating equipment with sufficient power. The temperature distribution law of medical tents in this experiment has good guiding significance for the placement angle of heating equipment and the configuration position of medical equipment and provides a reference for the development of thermal insulation materials for medical tents. Full article

Upper air temperature measurements are critical for understanding weather patterns, boundary-layer processes, climate change, and the validation of space-based observations. However, there have been growing concerns over data discrepancies, the lack of homogeneity, biases, and discontinuities associated with historical climate data records obtained using these technologies. Consequently, this article reviews the progress of utilizing radiosondes and space-based instruments for obtaining upper air temperature records. A systematic review process was performed and focused on papers published between 2000 and 2023. A total of 74,899 publications were retrieved from the Google Scholar, Scopus, and Web of Science databases using a title/abstract/keyword search query. After rigorous screening processes using relevant keywords and the elimination of duplicates, only 599 papers were considered. The papers were subjected to thematic and bibliometric analysis to comprehensively outline the progress, gaps, challenges, and opportunities related to the utilization of radiosonde and space-based instruments for monitoring upper air temperature. The results show that in situ radiosonde measurements and satellite sensors have improved significantly over the past few decades. Recent advances in the bias, uncertainty, and homogeneity correction algorithms (e.g., machine learning approaches) for enhancing upper air temperature observations present great potential in improving numerical weather forecasting, atmospheric boundary studies, satellite data validation, and climate change research. Full article

Information about wind variations and future wind conditions is essential for a monsoon domain such as the Northwest Pacific (NWP) region. This study utilizes 10 Generalized Circulation Models (GCM) from CMIP6 to evaluate near-future wind changes in the NWP under various climate warming scenarios. Evaluation against the ERA5 reanalysis dataset for the historical period 1985–2014 reveals a relatively small error with an average of no more than 1 m/s, particularly in the East Asian Marginal Seas (EAMS). Future projections (2026–2050) indicate intensified winds, with a 5–8% increase in the summer season in the EAMS, such as the Yellow Sea, East Sea, and East China Sea, while slight decreases are observed in the winter period. Climate mode influences show that winter El Niño tends to decrease wind speeds in the southern study domain, while intensifying winds are observed in the northern part, particularly under SSP5-8.5. Conversely, summer El Niño induces higher positive anomalous wind speeds in the EAMS, observed in SSP2-4.5. These conditions are likely linked to El Niño-induced SST anomalies. For the application of CMIP6 surface winds, the findings are essential for further investigations focusing on the oceanic consequences of anticipated wind changes such as the ocean wave climate, which can be studied through model simulations. Full article

As a developing country with an agricultural economy as a pillar, Bangladesh is highly vulnerable to adverse effects of climate change, so the generation of high-resolution temperature maps is of great value for Bangladesh to achieve agricultural sustainable development. However, Bangladesh’s weak economy and sparse meteorological stations make it difficult to obtain such maps. In this study, by mining internal features and links inside observed data, we developed an efficient data-driven downscaling technique to generate high spatial-resolution temperature distribution maps of Bangladesh directly from observed temperature data at 34 meteorological stations with irregular distribution. Based on these high-resolution historical temperature maps, we further explored a data-driven forecast technique to generate high-resolution temperature maps of Bangladesh for the period 2025–2035. Since the proposed techniques are very low-cost and fully mine internal links inside irregular-distributed observations, they can support relevant departments of Bangladesh to formulate policies to mitigate and adapt to climate change in a timely manner. Full article

Fine particulate matter with an aerodynamic diameter less than 2.5 µm ($\mathrm{P}{\mathrm{M}}_{2.5}$) profoundly affects environmental systems, human health and economic structures. Multi-source data and advanced machine or deep-learning methods have provided a new chance for estimating the $\mathrm{P}{\mathrm{M}}_{2.5}$ concentrations at a high spatiotemporal resolution. In this paper, the Random Forest (RF) algorithm was applied to estimate hourly $\mathrm{P}{\mathrm{M}}_{2.5}$ of the North China area (Beijing–Tianjin–Hebei, BTH) based on the next-generation geostationary meteorological satellite Himawari-8/AHI (Advanced Himawari Imager) aerosol optical depth (AOD) products. To improve the estimation of $\mathrm{P}{\mathrm{M}}_{2.5}$ concentration across large areas, we construct a method for co-weighting the environmental similarity and the geographical distances by using an attention mechanism so that it can efficiently characterize the influence of spatial–temporal information hidden in adjacent ground monitoring sites. In experiment results, the hourly $\mathrm{P}{\mathrm{M}}_{2.5}$ estimates are well correlated with ground measurements in BTH, with a coefficient of determination (${\mathrm{R}}^2$) of 0.887, a root-mean-square error (RMSE) of 18.31 $\mathsf{\mu }$g/${\mathrm{m}}^3$, and a mean absolute error (MAE) of 11.17 µg/${\mathrm{m}}^3$, indicating good model performance. In addition, this paper makes a comprehensive analysis of the effectiveness of multi-source data in the estimation process, in this way, to simplify the model structure and improve the estimation efficiency of the model while ensuring its accuracy. Full article

Networks of fixed-point continuous monitoring systems are becoming widely used in the detection and quantification of methane emissions from oil and gas facilities in the United States. Regulatory agencies and operators are developing performance metrics for these systems, such as minimum detection limits. Performance characteristics, such as minimum detection limits, would ideally be expressed in emission rate units; however, performance parameters such as detection limits for a continuous monitoring system (CMS) will depend on meteorological conditions, the characteristics of emissions at the site where the CMS is deployed, the positioning of CMS devices in relation to the emission sources, and the amount of time allowed for the CMS to detect an emission source. This means that certifying the performance of a CMS will require test protocols with well-defined emission rates and durations; initial protocols are now being used in field tests. Field testing results will vary, however, depending on meteorological conditions and the time allowed for detection. This work demonstrates methods for evaluating CMS performance characteristics using dispersion modeling and defines an approach for normalizing test results to standard meteorological conditions using dispersion modeling. Full article

Emerging research indicates that ground-level ozone (O₃) has become a leading contributor to air quality concerns in many Chinese cities, with the Yangtze River Delta (YRD) region facing particular challenges. This study investigated the characterization of air pollutants in Wujiang, which is located within the YRD demonstration zone, during the warm season (April–September) of 2022. The contributions of emission and meteorology to O₃ were identified, the O₃-NO_X-VOC sensitivities were discussed, and the VOC sources and their contributions to O₃ formation were analyzed. A random forest model revealed that the high O₃ concentration was mainly caused by a combination of increased emission intensity due to the resumption of work and production after the COVID-19 pandemic, along with adverse meteorological conditions. The results revealed more than 92% of the pollution days were related to O₃ during the warm season, and the impact of O₃ precursor emissions was slightly greater than that of the meteorological conditions. O₃ formation was in the VOC-limited regime, and emission reduction strategies targeting VOCs, particularly aromatics such as toluene and xylene, have been identified as the most effective approach for mitigating O₃ pollution. Changes in O₃-NO_X-VOC sensitivity were also observed from the VOC-limited regime to the transitional regime, which was primarily driven by variations in the NO_X concentrations. The VOC source analysis results showed that the contributions of gasoline vehicle exhaust and diesel engine exhaust (mobile source emissions) were significantly greater than those of the other sources, accounting for 20.8% and 16.5% of the total VOC emissions, respectively. This study highlights the crucial role of mobile source emission control in mitigating O₃ pollution. Furthermore, prioritizing the control of VOC emission sources with minimal NO_X contributions is highly recommended within the VOC-limited regime. Full article

Cloud dynamics and their response to future climate change continue to present a significant source of uncertainty in climate predictions. Besides the average cloud properties, the diurnal cloud cycle (DCC) exerts a substantial influence on Earth’s energy balance by reflecting solar radiation during the daytime and continuously absorbing and reemitting longwave radiation throughout the whole day. Previous studies have demonstrated that climate models exhibit certain discrepancies in simulating the DCC; however, less research attention has been paid to the patterns of these DCC biases and their impacts on modeling the Earth’s energy balance. Here, we employ satellite data to compare DCC patterns in Coupled Model Intercomparison Project Phase 5 (CMIP5) and their latest versions in CMIP6 at both regional and global scales. We found that some of the latest climate models tend to have larger DCC biases when using satellite observations as the references, and the radiative effects due to DCC changes account for nearly 50% of the changes in total cloud radiative effects (CREs), suggesting that the DCC biases play a significant role in modelingthe global energy budget. We therefore call for improving cloud parameterization schemes with particular attention to their diurnal cycle to reduce their impacts on future climate projections. Full article

The Greater Athens Area (GAA), situated in the southern part of the European continent (in Greece), has a Mediterranean climate characterized by hot, dry summers and mild, wet winters. As a result of increased sunshine and high temperatures, exceedances in ozone concentrations are often recorded during the hot period. In the present study, the monthly as well as daily variations of O₃ concentrations at thirteen stations in the GAA were investigated for the period 1987–2019. Moreover, the impact of O₃ on the people’s health in Greece was examined by using data from the Global Burden of Disease (GBD) study with the socio-economic conditions of the country. Ozone concentrations were found to be particularly high during the summer months, especially in suburban stations. Values ranged from 65 μg/m³ to 90 μg/m³ during the night, in contrast to urban areas and remain high for several hours. Comparing estimates from GBD, it was found that exposure to ozone can impair respiratory function, leading to death or susceptibility to respiratory diseases that reduce quality of life, especially for people over 55 years of age. Finally, since 2009, when the economic crisis began in Greece, an upward trend was observed for deaths and disability adjusted life years. Full article

This study aims (1) to study the trend and characteristics of average annual air temperature (T_ann), annual precipitation (Pr_ann), and annual evapotranspiration (PET_ann) in Thailand over the present period (1987–2021) and (2) to extract the climate pattern in form of a map using the New Thornthwaite Climate Classification method in Thailand considering the present period. The data were prepared by the Thai Meteorological Department. Data variability, the mean of the data calculation in time series, the homogeneity test of data, and abrupt changes were examined. The trends of each variable were calculated using the Mann–Kendal and Sen’s slope test. The results indicated that the high T_ann found in Bangkok gradually decreased in the next area. T_ann data were heterogeneous with the abrupt change period, and increasing trends were found. Pr_ann values were high in the west side of the southern area and the bottom area of the eastern area; in addition, low rainfall was found in the inner area of the land. Pr_ann data were homogenous with no abrupt change period and slight changes in trends. PET_ann and %CV spatial distribution were determined for the same pattern of T_ann. PET_ann data were heterogeneous with abrupt change periods and rising trends. The torrid thermal index determined based on the New Thornthwaite Climate Classification results indicated an overall torrid-type climate. A semi-arid climate pattern was found in the small area of the middle of Thailand, and then it shifted toward a moist-type pattern in the next area with an in precipitation. The most climate variability was found to be extreme with the power of temperature changes. Full article

This study explores the spatiotemporal variability of the onset, end, and duration of the rainy season in Senegal. These phenological parameters, crucial for agricultural planning in West Africa, exhibit high interannual and spatial variability linked to precipitation. The objective is to detect and spatially classify these indices across Senegal using different approaches. Daily precipitation data and ERA5 reanalyses from 1981 to 2018 were utilized. The employed method enables the detection of key dates. Subsequently, the Kohonen algorithm spatially classifies these indices on topological maps. The results indicate a meridional gradient of the onset, progressively later from the southeast to the northwest, whereas the end follows a north–south gradient. The duration varies from 45 days in the north to 150 days in the south. The use of self-organizing maps allows for classifying the onset, end, and duration of the season into four zones for the onset and end, and three zones for the duration of the season. They highlight the interannual irregularity of transitions, with both early and late years. The dynamic analysis underscores the complex influence of atmospheric circulation fields, notably emphasizing the importance of low-level monsoon flux. These findings have tangible implications for improving seasonal forecasts and agricultural activity planning in Senegal. They provide information on the onset, end, and duration classes for each specific zone, which can be valuable for planning crops adapted to each region. Full article

Cultural tourism helps preserve cultural heritage and provides economic opportunities for local communities. A walkable cultural tourism route has been developed for the old town of Ratchaburi, Thailand. Here, we assessed changes in PM₁ after cars were banned from the walkable tourist route. A near-roadway dispersion model, R-LINE, was evaluated and used to explore the base case (BC) and two scenarios, S1 and S2. In the BC, road traffic activities reflected the current situation; in S1, all vehicles were banned from the walkable route; and in S2, all drivers were encouraged to park their vehicles outside the study area. The road traffic activities in the study area were observed and used to calculate the PM₁ emission rates for the model inputs. The model was capable of simulating PM₁ concentration, especially the average PM₁ concentration over the monitoring period. An increase in PM₁ concentration was seen at the main road in S1 due to the increased traffic volume that had been redirected from the walkable route, with an increase in daily PM₁ of 4.5% compared to BC. S2 showed a decrease in the PM₁ concentration of 8.9%. These findings suggest the need for traffic mitigation measures prior to initiating a walkable route for cultural tourism, to meet environmental sustainability requirements. Full article

The vertical eddy diffusion process plays a crucial role in PM_2.5 prediction, yet accurately predicting it remains challenging. In the three-dimensional atmospheric chemistry transport model (3-D AQM) CMAQ, a parameter, Kz, is utilized, and it is known that PM_2.5 prediction tendencies vary according to the floor value of this parameter (Kz_min). This study aims to examine prediction characteristics according to Kz_min values, targeting days exceeding the Korean air quality standards, and to derive appropriate Kz_min values for predicting PM_2.5 concentrations in the DJFM Seoul Metropolitan Area (SMA). Kz_min values of 0.01, 0.5, 1.0, and 2.0, based on the model version and land cover, were applied as single values. Initially focusing on December 4th to 12th, 2020, the prediction characteristics were examined during periods of local and inflow influence. Results showed that in both periods, as Kz_min increased, surface concentrations over land decreased while those in the upper atmosphere increased, whereas over the sea, concentrations increased in both layers due to the influence of advection and diffusion without emissions. During the inflow period, the increase in vertically diffused pollutants led to increased inflow concentrations and affected contribution assessments. Long-term evaluations from December 2020 to March 2021 indicated that the prediction performance was superior when Kz_min was set to 0.01, but it was not significant for the upwind region (China). To improve trans-boundary effects, optimal values were applied differentially by region (0.01 for Korea, 1.0 for China, and 0.01 for other regions), resulting in significantly improved prediction performance with an R of 0.78, IOA of 0.88, and NMB of 0.7%. These findings highlight the significant influence of Kz_min values on winter season PM_2.5 prediction tendencies in the SMA and underscore the need for considering differential application of optimal values by region when interpreting research and making policy decisions. Full article

Knowledge about regions where lightning occurs is important both for understanding storm development and direction. This can assist in very short-term weather forecasts and in developing lightning warning systems, aiming to minimize exposure of people and equipment in the open sky. A survey on the occurrence of lightning in different types of land use and coverage and different elevation strata in the region of the Itacaiúnas River watershed (IRW), located in the Carajás Mineral Province, in the Eastern Amazon, from 2012 to 2021 was conducted. The results showed significant differences in the occurrence of lightning in mining areas and deforested areas. When comparing the large proportion of deforested areas with the mining area, the results suggested that in IRW mining areas, the lightning incidence is expressively higher. The assessment of electrical activity at different elevations in the region suggested that the slope of the terrain and its thermodynamic effects on the formation of storms have more influence than altitude on lightning activity. The results showed the importance of adopting initiatives aimed at protecting both the local population and mining workers, as well as equipment exposed to the open sky in this region. Full article

In the context of global climate change, lightning disasters have emerged as a serious environmental factor that restricts the sustainable development of megacities. This paper provides a review of the research on the impact of urbanization on thunderstorm processes and lightning activity, exploring various aspects, such as aerosols, urban thermal effects, urban dynamic effects, and building morphology. Despite numerous significant achievements in the study of the impact of air pollutants on lightning activity, there is no consensus on whether aerosols serve to enhance or inhibit lightning activity. The temperature difference between the urban underlying surface and the natural underlying surface could sustain and promote the occurrence and development of convective systems, thus enhancing lightning activity. In terms of urban dynamics, the barrier effect has led to the maximum center of lightning appearing at the edge of a built-up area, which might be associated with factors, such as urban heat island (UHI) intensity, wind speed, synoptic background, and city size. Additionally, the size of a city and the height of the buildings was also an influencing factor on lightning activity. In summary, scholars have made progress in understanding the characteristics and drivers of urban lightning activity in recent years, but there are still some urgent problems that need to be solved: (1) How to analyze, comprehensively, the spatiotemporal patterns of urban lightning activity under different thunderstorm intensity backgrounds? (2) How to conduct analysis to investigate the influence of alterations in the boundary layer structure, water–heat energy balance, and water vapor circulation processes on urban lightning activity in the context of urbanization? (3) How to couple numerical models of different scales to enhance the understanding of the impact of complex underlying surfaces on urban lightning activity? Future studies could investigate the relationship between urbanization and thunderstorm/lightning activity using a combination of observational data, numerical modeling, and laboratory experiments, which holds promise for providing valuable theoretical insights and technical support to enhance the prediction, nowcasting, early warning, and risk assessment of thunderstorms and lightning in urban areas. Full article

This study proposes a deep neural network (DNN)-based downscaling model incorporating kernel principal component analysis (KPCA) to investigate the precipitation uncertainty influenced by typhoons in Taiwan, which has a complex island topography. The best tracking data of tropical cyclones from the Joint Typhoon Warning Center (JTWC) are utilized to calculate typhoon and non-typhoon precipitation. KPCA is applied to extract nonlinear features of the BCC-CSM1-1 (Beijing Climate Center Climate System Model version 1.1) and CanESM2 (second-generation Canadian Earth System Model) GCM models. The length of the data used in the two GCM models span from January 1950 to December 2005 (historical data) and from January 2006 to December 2099 (scenario out data). The rainfall data are collected from the weather stations in Taichung and Hualien (cities of Taiwan) operated by the Central Weather Administration (CWA), Taiwan. The period of rainfall data in Taichung and in Hualien spans from January 1950 to December 2005. The proposed model is constructed with features extracted from the GCMs and historical monthly precipitation from Taichung and Hualien. The model we have built is used to estimate monthly precipitation and uncertainty in both Taichung and Hualien for future scenarios (rcp 4.5 and 8.5) of the GCMs. The results suggest that, in Taichung and Hualien, the summer precipitation is mostly within the normal range. The rainfall in the long term (January 2071 to December 2080) for both Taichung and Hualien typically fall between 100 mm and 200 mm. In the long term, the dry season (January to April, November, and December) precipitation for Taichung and that in the wet season (May to October) for Hualien are less and more affected by typhoons, respectively. The dry season precipitation is more affected by typhoons in Taichung than Hualien. In both Taichung and Hualien, the long-term probability of rainfall exceeding the historical average in the dry season is higher than that in the wet season. Full article

Madden–Julian Oscillation (MJO) modulates the generation of typhoons (TYs) in the western North Pacific (WNP). Using IBTrACS v04 tropical cyclone best path data, ERA5 reanalysis data, and the MJO index from the Climate Prediction Center (CPC), this paper defines an index to describe the persistent anomalies of the MJO and to examine the statistical characteristics of TYs over 44 years (1978–2021), focusing on the analysis of major differences in environmental conditions after the removal of the ENSO signal over the WNP. The results indicate that the persistent anomalous state of the MJO influences the change in large-scale environmental factors, which, in turn, affects the generation of TYs, as follows: (1) For the I high-value years, the center of the MJO stagnates in the Indian Ocean–South China Sea (SCS), the monsoon trough retreats westward, the warm pool becomes warmer, and the Walker circulation is enhanced. There is stronger upper-level divergence and low-level convergence, larger low-level relative vorticity, higher mid-level relative humidity, and smaller vertical wind shear in the SCS and the seas near the Philippines. Consequently, these conditions foster a conducive environment for TY genesis in the SCS and the seas near the Philippines. (2) For the I low-value years, the center of the MJO stagnates in the WNP–North America region, the monsoon trough extends eastward, the warm pool becomes colder, and the Walker circulation is weakened. Consequently, these conditions are more likely to facilitate TY genesis in the central–eastern WNP. The results show that persistent anomalies in MJO active centers can effectively improve the predictive ability of TY frequency. Full article

Urban communities in environmentally sensitive areas face escalating challenges due to climate change and inadequate infrastructural support, particularly in underserved regions like southside Norfolk, Virginia. This area, characterized by its vulnerability to flooding and a predominantly low-income population, lacks equitable inclusion in broader urban flood protection plans. This research focuses on the development of community-centered resilience strategies through active engagement and collaboration with local residents. The methodology centered around building trust and understanding within the community through a series of interactions and events. This approach facilitated a two-way exchange of information, enabling the research team to gather crucial insights on community-valued assets, prevalent flooding issues, and preferred flood mitigation solutions. The engagement revealed a significant increase in community knowledge regarding climate change, sea level rise, and stormwater management. Residents expressed a strong preference for green infrastructure solutions, including rain gardens, permeable pavements, and living shorelines, alongside concerns about pollution and the need for infrastructure redesign. The outcomes of this community engagement have initiated plans to develop tailored, nature-based flooding solutions. These results are set to inform future urban planning and policy, offering insights to the City of Norfolk and the United States Army Corps of Engineers for potential redesigns of flood intervention strategies that are more inclusive and effective. A template for participatory research to inform coastal hazard management includes cross-sector collaboration, a long-term engagement commitment, and education and surveying opportunities to align solutions to lived, local experiences. This template allows for community trust building, which is especially important in environmental justice communities. The study highlights the importance of community involvement in urban resilience planning, demonstrating that local engagement is essential in shaping community-centric solutions and equitable environmental policies. Full article

Meteorological conditions and air quality are important environmental factors in the occurrence and development of cardiovascular diseases (CVDs) such as hypertension. The aim of this study was to take Haikou City, located on the tropical edge, as the research area and to analyze the exposure–response relationship and lag effect between its meteorological conditions, air quality, and the number of hypertensive patients. Using the data from the hypertension outpatient department of Hainan Provincial People’s Hospital from 2016 to 2018, together with meteorological data and air quality data, a distributed lag nonlinear model based on the nested generalized addition model of meteorological element base variables was established. The results showed that the impact of temperature on the risk of hypertension was mainly due to the cold effect, which was associated with high risk, with a lag of 1–10 days. When the temperature dropped to 10 °C, the cumulative effect on the risk of hypertension of relative risk (RR) reached its highest value on the day the low temperature occurred (RR was 2.30 and the 95% confidence interval was 1.723~3.061), passing the test with a significance level of 0.05. This result indicated that efforts should be made to strengthen the prevention of hypertension under low-temperature conditions and the prediction and early warning of disease risks. The impact of the air-quality effect (the environmental Air Quality Index was selected as an indicator) on the risk of hypertension was mainly characterized by a low air-quality effect, with a lag effect of 0–8 days. When the risk reached approximately 124, the RR was highest (RR was 1.63 and the 95% confidence interval was 1.104~2.408), passing the test with a significance level of 0.05. The research results can provide technical support for conducting medical meteorological forecasting, early warning, and services for hypertension. A joint work and research mechanism among multiple departments such as meteorology and medical health should be established to improve the level of medical and health care, optimize the allocation of social resources, and develop targeted prevention and control strategies to reduce the health and economic burden of hypertension. Full article

The global climate change, driven by natural processes and increasing human activities, is especially significant for Georgia. The region is experiencing increases in temperature, desertification, redistribution of precipitation, and a rise in the frequency and severity of extreme weather events. Georgia’s complex topography and its proximity to the Black and Caspian seas make it essential to employ high-resolution regional climate models to evaluate future climate change risks. In this study, we examine the results of a high-resolution simulation of mean and extreme precipitation and temperature using the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 4.7.1 for the period 1985–2008, providing an initial evaluation of the model’s performance for the territory of Georgia. The model domain (1524 km; 2388 km) encompasses the entirety of Georgia’s territory and surrounding regions. The simulation, conducted at a 12 km horizontal grid spacing using ERA5 data as boundary conditions, indicates that the least discrepancy between observed and modeled average annual temperatures and precipitation, falling within a −1 to 1 °C and −200 to 200 mm range, respectively, was observed at most stations of eastern Georgia. The largest disparities between the model and observed average annual precipitation totals were noted along the Black Sea coast, in the Kolkheti Lowland, and in some high mountain stations in western Georgia. The most significant differences in average annual temperatures between the model and observations were observed in Ambrolauri, Mt. Sabueti, and Dedoplistskaro. For Georgia territory, such a long run with such a high resolution using ERA5 as boundary conditions was conducted for the first time. Overall, the modeling results are quite satisfactory, providing a solid basis for the successful utilization of the regional climate model RegCM4.7.1 with the selected parameterization for modeling monthly mean and extreme temperatures and precipitation in Georgia. Full article

A gaseous elemental mercury (Hg⁰) sampler was developed for the assessment of mercury (Hg) pollution from the air and utilised aluminium (Al) powder as the accumulation medium. The Hg sampler is presented as an alternative cost-effective sorbent that can be used for the assessment of Hg pollution in atmospheric air in areas where natural bio-indicators such as lichens and moss do not grow, including the urban environments. The chemical treatment of Al materials was necessary to weaken the aluminium oxide (Al₂O₃) layer to increase the adsorption capability of Al material. Treated Al samples were exposed to Hg vapours for one hour to two weeks in a Hg atmosphere chamber. Other Al powder samples were exposed to the ambient air at areas of the Tshwane Metropolitan Municipality for six to ten months. The analysis of samples by an RA-915+ Zeeman mercury analyser showed that the limit of detection (LOD) and limit of quantification (LOQ) for the determination of Hg in Al powder with a mass of 100 mg were found to be 0.31 ng g⁻¹ and 1.0 ng g⁻¹, respectively. The content of Hg that accumulated on Al powder was linear from 0.1 to 25 ng g⁻¹, thus enabling the measurement of Hg accumulation from air at the global average concentration level. Mercury from air that accumulated on Al powder in the Tshwane Metropolitan Municipality ranged between 70 ng g⁻¹ and 155 ng g⁻¹. Full article

Atmospheric turbidity exhibits substantial spatial–temporal variability due to factors such as aerosol emissions, seasonal changes, meteorology, and air mass transport. Investigating atmospheric turbidity is crucial for climatology, meteorology, and atmospheric pollution. This study investigates the variation in atmospheric turbidity over a tropical location in Nigeria, utilizing the Ångström exponent (α), the turbidity coefficient (β), the Linke turbidity factor (T_L), the Ångström turbidity coefficient (β_EST), the Unsworth–Monteith turbidity coefficient (K_AUM), and the Schüepp turbidity coefficient (SCH). These parameters were estimated from a six-month uninterrupted aerosol optical depth dataset (January–June 2016) and a one-year dataset (January–December 2016) of solar radiation and meteorological data. An inverse correlation (R = −0.77) was obtained between α and β, which indicates different turbidity regimes based on particle size. T_L and β_EST exhibit pronounced seasonality, with higher turbidity during the dry season (T_L = 9.62 and β_EST = 0.60) compared to the rainy season (T_L = 0.48 and β_EST = 0.20) from May to October. Backward trajectories and wind patterns reveal that high-turbidity months align with north-easterly air flows from the Sahara Desert, transporting dust aerosols, while low-turbidity months coincide with humid maritime air masses originating from the Gulf of Guinea. Meteorological drivers like relative humidity and water vapor pressure are linked to turbidity levels, with an inverse exponential relationship observed between normalized turbidity coefficients and normalized water vapor pressure. This analysis provides insights into how air mass origin, wind patterns, and local climate factors impact atmospheric haze, particle characteristics, and solar attenuation variability in a tropical location across seasons. The findings can contribute to environmental studies and assist in modelling interactions between climate, weather, and atmospheric optical properties in the region. Full article

This paper investigates the nonlinear dynamics of atmospheric aerosols during the transition from laminar to turbulent flows using the framework of Scale Relativity Theory. It is proposed that the transition from multifractal to non-multifractal scales (in the dynamics of the atmospheric aerosols) can be assimilated to the transition between laminar and turbulent states. These transitions are determined by the multifractal diffusion and deposition processes. The methodology used involves the application of the principle of scale covariance, which states that the laws of atmospheric physics remain invariant with respect to spatial and temporal transformations as well as scale transformations. Based on this principle, several conservation laws are constructed. In such context, the conservation law of the density of states associated with the multifractal-non-multifractal scale transition in a one-dimensional case is then considered. The model describes the non-linear behaviour of atmospheric aerosols undergoing diffusion and deposition processes. The theoretical approach was correlated using experimental data from a ceilometer and radar reflectivity factor data. Full article

Atmospheric sounding using the Tu-134 Optik aircraft-laboratory was conducted in September 2020 over the seas of the Russian sector of the Arctic Ocean, namely the Barents, Kara, Laptev, East Siberian, Chukchi and Bering seas. Unique samples of atmospheric aerosols at altitudes from 200 and up to 10,000 m were taken, including samples for the identification of cultivated microorganisms and their genetic analysis. Data on the concentration and diversity of bacteria and fungi isolated from 24 samples of atmospheric aerosols are presented; the main phenotypic and genomic characteristics were obtained for 152 bacterial cultures; and taxonomic belonging was determined. The concentration of cultured microorganisms detected in aerosols of different locations was similar, averaging 5.5 × 10³ CFU/m³. No dependence of the number of isolated microorganisms on the height and location of aerosol sampling was observed. The presence of pathogenic and condto shitionally pathogenic bacteria, including those referred to in the genera Staphylococcus, Kocuria, Rothia, Comamonas, Brevundimonas, Acinetobacter, and others, as well as fungi represented by the widely spread genera Aureobasidium, Aspergillus, Alternaria, Penicillium, capable of causing infectious and allergic diseases were present in most analyzed samples. Obtained data reveal the necessity of systematic studies of atmospheric microbiota composition to combat emerging population diseases. Full article

In recent decades, glaciers in the southeastern Tibetan Plateau (SETP) have been rapidly melting and showing a large scale of glacier mass loss. Due to the lack of large-scale, high-resolution, and high-precision observations, knowledge on the spatial distribution of the glacier mass balance and the response to climate change is limited in this region. We propose a TanDEM-X bi-static InSAR (Interferometric Synthetic Aperture Radar) algorithm with a non-local mean filter method and difference strategy, to improve the precision of glacier surface elevation change detection. Moreover, we improved the glacier mass balance estimation algorithm with a correction method for multi-source system errors and an uncertainty evaluation method based on error propagation theory to reduce the uncertainty of estimations. We used 13 pairs of TanDEM-X bi-static InSAR images to obtain the glacier mass balance data for the entire SETP. The total area of glaciers monitored was 5821 km² and the total number of glaciers monitored was 2321; the glacier surface elevation change rate was −0.505 ± 0.005 m/yr, and the glacier mass balance estimation was −454.5 ± 13.1 mm w.eq. during 2000–2014. Additionally, we analyzed the spatial distribution of the glacier mass balance within the SETP using the sub-watershed analysis method. The results showed that the mass loss rate had a decreasing trend from the southeast to the northwest. Furthermore, the temperature change and the glacier mass loss rate showed a positive correlation from the southeast to the northwest in this region. This study greatly advances our understanding of the regularities of glacier dynamics in this region, and can provide scientific support for major national goals such as the rational utilization of surrounding water resources and construction of important transportation projects. Full article

The changing climate has a serious bearing on agriculture, particularly livestock production in Botswana. Therefore, studying the relationship between climate and livestock, which at present is largely missing, is necessary for the proper formulation of government policy and interventions. This is critical in promoting the adoption of relevant mitigation strategies by farmers, thereby increasing resilience. The aim of this research is to establish associations between climate variability and livestock production in Botswana at the national level. The paper employs time series data from 1970 to 2020 and the Vector Autoregression with Exogenous Variables (VARX) model for statistical analysis. The trend shows that both cattle and goat populations are decreasing. The VARX model results reveal that cattle and goat populations are negatively associated with increasing maximum temperatures. Cattle respond negatively to increased minimum temperatures as well, while goats tend to respond positively, implying that livestock species react differently to climatic conditions due to their distinct features. The results of the roots of the companion matrix for cattle and goat production meet the stability condition as all the eigenvalues lie inside the unit circle. The study recommends further intervention by the government to deal with increasing temperatures, thereby addressing the dwindling populations of goats and cattle, which have significant contributions to the household economies of smallholders and the national economy, respectively. Full article

Recent satellite measurements of glacier mass balances show mountain glaciers all over the world had generally negative mass balances in the first decades of the 21st century. Mean summer temperatures all over the world rose from the 1961–1990 period to the 1991–2020 period, implying increasingly negative mass balances. We studied archived annual balances for 38 northern hemisphere glaciers to assess changes within the 1961–2020 period. We used a modified double-mass curve to visualize mass balance changes occurring around 1990. Mean balances in 1961–1990 were already small negative for many of the studied glaciers and became even more negative in 1991–2020 for glaciers in the Alps, at high latitudes and in western North America. The largest mass balance changes were for some glaciers in the Alps. We are unable to explain the lack of change in mean balance for one glacier in High Mountain Asia. We found complex changes for eight glaciers in Scandinavia, even including one glacier with a positive balance. We explain these changes by visualizing the deviations in winter and summer balances from their respective 1961–1990 mean values. High winter balances in the 1990s for Scandinavia partly obscured the emerging trend of increasingly negative summer balances, which we expect to continue in the future. Full article

This study aims to estimate the surface runoff and examine the impact of climate change on water resources in the Upper Kabul River Basin (UKRB). A hydrological model was developed using the Soil and Water Assessment Tool (SWAT) from 2009 to 2019. The monthly calibration was conducted on streamflow in six stations for the period from 2010 to 2016, and the results were validated from 2017 to 2018 based on available observed data. The hydrological sensitivity parameters were further prioritized using SWAT-CUP. The uncertainty of the model was analyzed by the 95% Prediction Uncertainty (95PPU). Future projections were analyzed for the 2040s (2030–2049) and 2090s (2080–2099) compared to the baseline period (1986–2005) under two representation concentration pathways (RCP4.5, RCP8.5). Four Regional Climate Models (RCMs) were bias-corrected using the linear scaling bias correction method. The modeling results exhibited a very reasonable fit between the estimated and observed runoff in different stations, with NS values ranging from 0.54 to 0.91 in the calibration period. The future mean annual surface runoff exhibited an increase in the 2040s and 2090s compared to the baseline under both RCPs of 4.5 and 8.5 due to an increase in annual precipitation. The annual precipitation is projected to increase by 5% in the 2040s, 1% in the 2090s under RCP4.5, and by 9% in the 2040s and 2% in the 2090s under RCP8.5. The future temperature is also projected to increase and consequently lead to earlier snowmelt, resulting in a shift in the seasonal runoff peak to earlier months in the UKRB. However, the shifts in the timing of runoff could lead to significant impacts on water availability and exacerbate the water stress in this region, decreasing in summer runoff and increasing in the winter and spring runoffs. The future annual evapotranspiration is projected to increase under both scenarios; however, decreases in annual snowfall, snowmelt, sublimation, and groundwater recharge are predicted in the UKRB. Full article

For the first time, data on the emission of climate-active gases from soils of different types of use of the south taiga sub-zone were obtained. Soils of the boreal belt are key elements of the global carbon cycle. They determine the sink and emission of climate-active gases. Soils near large cities are a major carbon sink, in the face of climate change, soils from sinks can become a source of carbon and contribute significantly to climate change on the planet. Studies of F_CO2 and F_CH4 fluxes were carried out on the territory of the monitoring site “Ladoga” located in the southern taiga subzone in soils of land not used in agriculture, former agriculture lands, and wetlands. During the chamber measurements, a portable gas analyzer GLA131-GGA (ABB, Canada) was used. The chamber was placed on the soil, after which the concentration of CO₂, CH₄ and H₂O in the mobile chamber was recorded. As a result of the study it was found that the lowest emission of carbon dioxide is characteristic of soils developing on the soils of wetland and is 0.64 gCO₂/(m²*year). Which is associated with a high degree of hydrophobicity of the territory and changes in the redox regime. The highest emission of carbon dioxide is registered in soils on the land not used in agriculture and is 4.16 gCO₂/(m²*year). This is due to the formation of predominantly labile forms of carbon in the soil, which can be relatively rapidly involved in the carbon cycle and affect the active emission of carbon from the soil. According to the data obtained on F_CH4 emission from soils, it was found that soils of land not used in agriculture and former agriculture lands were net sinks, while soils of wetlands were characterized by CH₄ source, the emission was from 0.05 to 0.83 gCH₄/(m²*year). The results obtained indicate spatial heterogeneity and changes in the carbon cycle within the monitoring site “Ladoga”, which are due to the change of plant communities and habitat type. Monitoring the release of important greenhouse gases in close proximity to major urban areas is an important task in the face of predicted climate change and increasing rates of urbanization. Full article

In the context of global climate change and rising sea levels, the adverse impacts of storm surges on the environment, economy, and society of affected areas are becoming increasingly significant. However, due to differences in geography, climate, and other conditions among the affected areas, a single method for assessing the risk of storm surge disasters cannot be fully applicable to all regions. To address this issue, an increasing number of new methods and models are being applied in the field of storm surge disaster risk assessment. This paper introduces representative traditional statistical methods, numerical simulation methods, and artificial intelligence-based techniques in this field. It compares these assessment methods in terms of accuracy, interpretability, and implementation difficulty. The paper emphasizes the importance of selecting appropriate assessment methods based on specific conditions and scientifically combining various methods in practice to improve the accuracy and reliability of storm surge disaster risk assessments. Full article