Atmosphere — Open Access Journal

The role of ice hydrometeor-types in bulk schemes available in the Weather Research and Forecasting (WRF) model has been assessed in this study to simulate two heavy rainfall events reported over the southern part of Nigeria. This has been done with a view to provide necessary information on the convective cloud hydrometeor types and compositions in the area to improve heavy rainfall forecasts with the selection of appropriate bulk microphysical schemes. Results from the statistical validation of the simulated rainfall by different schemes showed that for the first event, the WSM5 scheme with less dense snow ice particles performed relatively better than other schemes like WSM6, Morrison with graupel (MORR_G), and Morrison with hail (MORR_H), while the WDM6 scheme performed least effectively when compared to TRMM data. Conversely, the second event showed that a WDM6 scheme with graupel as dense ice particle performed better than other schemes. Further analysis using a spatial distribution plot of simulated rainfall over the area of study shows that for both cases, almost all the schemes fail to capture the intensity and location of the heavy rainfall shown by TRMM data. In addition, the surface accumulated rainfall area average of all schemes for the first (second) event shows an underestimation (overestimation). Vertical profile plots of mass mixing ratios of different ice hydrometeor compositions showed that the WSM5 scheme contains a greater mass of snow than other type ice particles for both cases, while the hydrometeor path calculation of total mass content showed the WSM5 scheme having more snow mass content than other schemes during the period of analysis in both cases. A pressure-time plot of the differences between simulated air temperature and water vapor of the WSM5 scheme showed that WSM5 simulated the higher air temperature that was needed and water vapor at the mid and upper troposphere more than other schemes. In conclusion, results from this study has shown that less dense ice particle (e.g., snow) and high dense ice particle (e.g., graupel and hail) type-bulk schemes can both be suitable for simulating heavy rainfall events that are produced by convective system(s) that are common in the area. Full article

More than half of the world’s population now lives in cities as a result of unprecedented urbanization during the second half of the 20th century. The urban population is projected to increase to 68% by 2050, with most of the increase occurring in Asia and Africa. Population growth and increased energy consumption in urban areas lead to high levels of atmospheric pollutants that harm human health, cause regional haze, damage crops, contribute to climate change, and ultimately threaten the society’s sustainability. This article reviews the air quality and compares the policies implemented in the Mexico City Metropolitan Area (MCMA) and Singapore and offers insights into the complexity of managing air pollution to protect public health and the environment. While the differences in the governance, economics, and culture of the two cities greatly influence the decision-making process, both have made much progress in reducing concentrations of harmful pollutants by implementing comprehensive integrated air quality management programs. The experience and the lessons learned from the MCMA and Singapore can be valuable for other urban centers, especially in the fast-growing Asia-Pacific region confronting similar air pollution problems. Full article

In order to conduct real-time quantitative monitoring of dust storms, Ka-band millimeter wave radar (MMWR) was utilized for the consecutive detection of dust storms over the Taklimakan Desert from April to June 2018. The retrievals of the reflectivity factor, dust spectrum distribution and dust mass concentration were carried out with the power spectrum data detected by MMWR for three dust storm processes. The analysis shows that: The probability density distribution of dust conforms to the lognormal distribution. During the dust storm processes, the effective detection height of the reflectivity factor was within 2000 m and the range of the reflectivity factors was between-25 dBZ and 25 dBZ. During the floating dust period, the effective height of the dust spectrum distribution was lower than 300 m and the values of dust mass concentration were less than 31.62 μg·m^-3,at a height of 200 m. Furthermore, during the blowing sand stage, the effective height of the dust spectrum distribution was normally lower than 600 m and the values of dust mass concentration were mainly less than 316.23 μg·m^-3,at a height of 200 m. During the dust storm period, the effective height of the dust spectrum distributionexceeded1000 m; when the height was 100 m, the values of dust mass concentration were between 1220 μg∙m^-3 and 42,146 μg∙m^-3 and the average mass concentration was 9287 μg·m^-3; whereas, the values of dust mass concentration were between 2 μg∙m^-3 and 820 μg∙m^-3 when the height was 1200m and the average mass concentration was 24 μg∙m^-3. The relationship between the reflectivity factor Z and the dust mass concentration M isdefined as Z=651.6M^0.796. Compared with the observational data from Grimm180 particle detector, the data of the retrieved dust mass concentration are basically accurate and this retrieved method proves to be feasible. Thus, the MMWR cans be used as a new device for quantitative monitoring of dust storms. Full article

Agricultural emissions are crucial to regional air quality in the autumn and spring due to the intense agricultural activities in Northeast China. However, information on rural ambient particulate matter (PM) in Northeast China is rare, limiting the accurate estimation of agricultural atmospheric particulate matter emissions. In this study, we monitored hourly ambient PM_2.5 (PM with a diameter of less than 2.5 μm) concentrations and analyzed daily chemical components (i.e., water-soluble ions, trace elements, organic carbon, and element carbon) at a rural site in Northeast China during the autumn and spring and assessed the impact of agricultural activities on atmospheric PM_2.5 concentrations. The results showed that the daily average concentrations of PM_2.5 were 143 ± 109 (range: 39–539) μg m⁻³ from 19 October to 23 November 2017 (i.e., typical harvesting month) and 241 ± 189 (range: 97–976) μg m⁻³ from 1 April to 13 May 2018 (i.e., typical tilling month). In autumn, the ambient PM_2.5 concentrations were high with a Southwest wind, while a Southeast wind caused high PM_2.5 concentrations during spring in the rural site. The concentrations of selected water-soluble ions, trace elements, and carbonaceous fractions accounted for 33%, 4%, and 26% of PM_2.5 mass concentrations, respectively, in autumn and for 10%, 5%, and 3% of PM_2.5 mass concentrations, respectively, in spring. On the basis of the component analysis, straw burning, agricultural machinery, and soil dust driven by wind and tilling were the main contributors to high rural PM_2.5 concentrations. In addition, the increasing coal combustion around the rural site was another important source of PM_2.5. Full article

Runoff in snowy alpine regions is sensitive to climate change in the context of global warming. Exploring the impact of climate change on the runoff in these regions is critical to understand the dynamics of the water cycle and for the improvement of water resources management. In this study, we analyzed the long-term variations in annual runoff in the headwaters region of the Yellow River (HRYR) (a typical snowy mountain region) during the period of 1956–2012. The Soil and Water Assessment Tool (SWAT) with different elevation bands was employed to assess the performance of monthly runoff simulations, and then to evaluate the impacts of climate change on runoff. The results show that the observed runoff for the hydrological stations at lower relative elevations (i.e., Maqu and Tangnaihai stations) had a downward trend, with rates of 1.91 and 1.55 mm/10 years, while a slight upward trend with a rate of 0.26 mm/10 years was observed for the hydrological station at higher elevation (i.e., Huangheyan station). We also found that the inclusion of five elevation bands could lead to more accurate runoff estimates as compared to simulation without elevation bands at monthly time steps. In addition, the dominant cause of the runoff decline across the whole HRYR was precipitation (which explained 64.2% of the decrease), rather than temperature (25.93%). Full article

Numerical simulations are performed to investigate the effect of varying CCN (cloud condensation nuclei) concentration on dynamic, microphysics, electrification, and charge structure in weak, moderate, and severe thunderstorms. The results show that the response of electrification to the increase of CCN concentration is a nonlinear relationship in different types of thunderclouds. The increase in CCN concentration leads to a significant enhancement of updraft in the weak thunderclouds, while the high CCN concentration in moderate and severe thunderclouds leads to a slight reduction in maximum updraft speed. The increase of the convection promotes the lift of more small cloud droplets, which leads to a faster and stronger production of ice crystals. The production of graupel is insensitive to the CCN concentration. The content of graupel increases from low CCN concentration to moderate CCN concentration, and slightly decreases at high CCN concentration, which arises from the profound enhancement of small ice crystals production. When the intensity of thundercloud increases, the reduction of graupel production will arise in advance as the CCN concentration increases. Charge production tends to increase as the aerosol concentration rises from low to high in weak and moderate thundercloud cases. However, the magnitude of charging rates in the severe thundercloud cases keeps roughly stable under the high CCN concentration condition, which can be attributed to the profound reduction of graupel content. The charge structure in the weak thundercloud at low CCN concentrations keeps as a dipole, while the weak thunderclouds in the other cases (the CCN concentration above 100 cm⁻³) change from a dipole charge structure to a tripole charge structure, and finally disappear with a dipole. In cases of moderate and severe intensity thunderclouds, the charge structure depicts a relatively complex structure that includes a multilayer charge region. Full article

Health impacts of air pollutants, especially fine particles (PM_2.5) and NO₂, have been documented worldwide by epidemiological studies. Most of the existing studies utilised the concentration measured at the ambient stations to represent the pollutant inhaled by individuals. However, these measurement data are in fact not able to reflect the real concentration a person is exposed to since people spend most of their time indoors and are also affected by indoor sources. The authors developed a probabilistic methodology framework to simulate the lifelong exposure to PM_2.5 and NO₂ simultaneously for population subgroups that are characterised by a number of indicators such as age, gender and socio-economic status. The methodology framework incorporates the methods for simulating the long-term outdoor air quality, the pollutant concentration in different micro-environments, the time-activity pattern of population subgroups and the retrospective life course trajectories. This approach was applied to the population in the EU27 countries plus Norway and Switzerland and validated with the measurement data from European multi-centre study, EXPOLIS. Results show that the annual average exposure to PM_2.5 and NO₂ at European level kept increasing from the 1950s to a peak between the 1980s and the 1990s and showed a decrease until 2015 due to the implementation of a series of directives. It is also revealed that the exposure to both pollutants was affected by geographical location, gender and income level. The average annual exposure over the lifetime of an 80-year-old European to PM_2.5 and NO₂ amounted to 23.86 (95% CI: 2.95–81.86) and 13.49 (95% CI: 1.36–43.84) µg/m³. The application of this methodology provides valuable insights and novel tools for exposure modelling and environmental studies. Full article

A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions—cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R² > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment. Full article

Chlorine is an important atmospheric photochemical oxidant, but few studies have focused on atmospheric chlorine. In this study, PM_2.5 samples were collected from urban and rural sites across China in January 2018, and concentrations of Cl⁻ and other water-soluble ions in PM_2.5 were analyzed. The size-segregated aerosol Cl⁻ data measured across Chinese cities by other studies were compiled for comparison. The observed data demonstrated that the Cl⁻ concentrations of PM_2.5 in northern cities (5.0 ± 3.7 µg/m³) were higher than those in central (1.9 ± 1.2 µg/m³) and southern cities (0.84 ± 0.54 µg/m³), suggesting substantial chlorine emissions in northern cities during winter. The concentrations of Cl⁻ in aerosol were significantly higher in urban regions (0.11–26.7 µg/m³) compared to than in rural regions (0.03–0.61 µg/m³) across China during winter, implying strong anthropogenic chlorine emission in cities. Based on the mole ratios of Cl⁻/Na⁺, Cl⁻/K⁺ and Cl⁻/ ${\mathrm{SO}}_4^{2-}$ and the PMF model, Cl⁻ in northern and central cities was mainly sourced from the coal combustion and biomass burning, but in southern cities, Cl⁻ in PM_2.5 was mainly affected by the equilibrium between gas-phase HCl and particulate Cl⁻. The size-segregated statistical data demonstrated that particulate Cl⁻ had a bimodal pattern, and more Cl⁻ was distributed in the fine model than that in the coarse mode in winter, with the opposite pattern was observed in summer. This may be attributed to both sources of atmospheric Cl⁻ and Cl⁻ involved in chemical processes. This study reports the concentrations of aerosol Cl⁻ on a national scale, and provides important information for modeling the global atmospheric reactive chlorine distribution and the effects of chlorine on atmospheric photochemistry. Full article

The air–sea heat fluxes in marginal seas and under extreme weather conditions constitute an essential source for energy transport and mixing dynamics. To reproduce these effects in numerical models, we need a better understanding of these fluxes. In response to this demand, we undertook a study to examine the surface heat fluxes in the Arabian Gulf (2013 to 2014) and Red Sea (2008 to 2010)—the two salty Indian Ocean marginal seas. We use high-quality buoy observations from offshore meteorological stations and data from two reanalysis products, the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2) from the National Aeronautics and Space Administration (NASA) and ERA5, the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses of global climate. Comparison of the reanalyses with the in situ-derived fluxes shows that both products underestimate the net heat fluxes in the Gulf and the Red Sea, with biases up to −45 W/m ${}^2$ in MERRA2. The reanalyses reproduce relatively well the seasonal variability in the two regions and the effects of wind events on air–sea fluxes. The results suggest that when forcing numerical models, ERA5 might provide a preferable dataset of surface heat fluxes for the Arabian Gulf while for the Red Sea the MERRA2 seems preferable. Full article

Representing mesoscale convective systems (MCSs) and their multi-scale interaction with the large-scale atmospheric dynamics is still a major challenge in state-of-the-art global numerical weather prediction (NWP) models. This results in potentially defective forecasts of synoptic-scale dynamics in regions of high MCS activity. Here, we quantify this error by comparing simulations performed with a very large-domain, convection-permitting NWP model to two operational global NWP models relying on parameterized convection. We use one month’s worth of daily forecasts over Western Africa and focus on land regions only. The convection-permitting model matches remarkably well the statistics of westward-propagating MCSs compared to observations, while the convection-parameterizing NWP models misrepresent them. The difference in the representation of MCSs in the different models leads to measurably different synoptic-scale forecast evolution as visible in the wind fields at both 850 and 650 hPa, resulting in forecast differences compared to the operational global NWP models. This is quantified by computing the correlation between the differences and the number of MCSs: the larger the number of MCSs, the larger the difference. This fits the expectation from theory on MCS–mean flow interaction. Here, we show that this effect is strong enough to affect daily limited-area forecasts on very large domains. Full article

We review the state-of-the-art knowledge of Tropical Atlantic Variability (TAV). A well-developed observing system and sustained effort of the climate modeling community have improved our understanding of TAV. It is dominated by the seasonal cycle, for which some mechanisms have been identified. The interannual TAV presents a marked seasonality with three dominant modes: (i) the Atlantic Zonal Mode (AZM), (ii) the Atlantic Meridional Mode (AMM) and (iii) the variability in the Angola–Benguela Front (ABF). At longer time scales, the AMM is active and low-frequency variations in the strength, periodicity, and spatial structure of the AZM are observed. Also, changes in the mean position of the ABF occur. Climate models still show systematic biases in the simulated TAV. Their causes are model-dependent and relate to drawbacks in the physics of the models and to insufficient resolution of their atmospheric and oceanic components. The identified causes for the biases can have local or remote origin, involving the global ocean and atmospheric circulation. Although there is not a clear consensus regarding the role of model resolution in the representation of the TAV, eddy-resolving ocean models combined with atmospheric models with enhanced horizontal and vertical resolutions simulate smaller biases. Full article

The summer ozone pollution of Shandong province has become a severe problem in the period 2014–2018. Affected by the monsoon climate, the monthly average ozone concentrations in most areas were unimodal, with peaks in June, whereas in coastal areas the concentrations were bimodal, with the highest peak in May and the second highest peak in September. Using the empirical orthogonal function method, three main spatial distribution patterns were found. The most important pattern proved the influences of solar radiation, temperature, and industrial structure on ozone. Spatial clustering analysis of the ozone concentration showed Shandong divided into five units, including Peninsula Coastal area (PC), Lunan inland area (LN), Western Bohai area (WB), Luxi plain area (LX), and Luzhong mountain area (LZ). Influenced by air temperature and local circulation, coastal cities had lower daytime and higher nighttime ozone concentrations than inland. Correlation analysis suggested that ozone concentrations were significantly positively correlated with solar radiation. The VOCs from industries or other sources (e.g., traffic emission, petroleum processing, and chemical industries) had high positive correlations with ozone concentrations, whereas NO_x emissions had significantly negatively correlation. This study provides a comprehensive understanding of ozone pollution and theoretical reference for regional management of ozone pollution in Shandong province. Full article

In this paper, we investigated the possible impact of snow darkening effect (SDE) by light-absorbing aerosols on the regional changes of the hydrological cycle over Eurasia using the NASA GEOS-5 Model with aerosol tracers and a state-of-the-art snow darkening module, the Goddard SnoW Impurity Module (GOSWIM) for the land surface. Two sets of ten-member ensemble experiments for 10 years were carried out forced by prescribed sea surface temperature (2002–2011) with different atmospheric initial conditions, with and without SDE, respectively. Results show that SDE can exert a significant regional influence in partitioning the contributions of evaporative and advective processes on the hydrological cycle, during spring and summer season. Over western Eurasia, SDE-induced rainfall increase during early spring can be largely explained by the increased evaporation from snowmelt. Rainfall, however, decreases in early summer due to the reduced evaporation as well as moisture divergence and atmospheric subsidence associated with the development of an anomalous mid- to upper-tropospheric anticyclonic circulation. On the other hand, in the East Asian monsoon region, moisture advection from the adjacent ocean is a main contributor to rainfall increase in the melting season. A warmer land-surface caused by earlier snowmelt and subsequent drying further increases moisture transport and convergence significantly enhancing rainfall over the region. Our findings suggest that the SDE may play an important role in leading to hotter and drier summers over western Eurasia, through coupled land-atmosphere interaction, while enhancing East Asian summer monsoonal precipitation via enhanced land-ocean thermal contrast and moisture transport due to the SDE-induced warmer Eurasian continent. Full article

The paper focuses on the development of the method to estimate the mean characteristics of the atmospheric turbulence. Using an approach based on the shape of the energy spectrum of atmospheric turbulence over a wide range of spatial and temporal scales, the vertical profiles of optical turbulence are calculated. The temporal variability of the vertical profiles of turbulence under different low-frequency atmospheric disturbances is considered. Full article

Understanding the characteristics of flash drought events and further predicting the onset of such events on subseasonal timescales is of critical importance for impact assessment, disaster mitigation, and loss prevention. In this study, we employ a rate-of-change approach and define a flash drought event as a drought event with greater than or equal to two categories degradation in a four-week period based on the U.S. Drought Monitor. Unlike conventional drought, which can occur year-round and everywhere in the United States, flash drought has preferred seasons and locations to occur, mostly in the warm season and over the central United States. Widespread flash drought over the United States is largely correlated with La Niña episodes. In contrast with conventional drought, which is mainly driven by precipitation deficits, anomalously high evapotranspiration rates, caused by anomalously high temperatures, winds, and/or incoming radiation, are usually present before the onset of flash drought. Comparing to precipitation and soil moisture, evapotranspiration typically has the largest decline rate during the fast-development phase. Three-month Standardized Precipitation Indexes are mostly dry right before flash drought onset, but large deficits are not required. As a result, monitoring rapid changes in evapotranspiration, along with precipitation and soil moisture conditions, can provide early warnings of flash drought development. Full article

This study evaluates projected changes to surface wind characteristics for the 2071–2100 period over North America (NA), using four Global Environmental Multiscale regional climate model simulations, driven by two global climate models (GCMs) for two Representative Concentration Pathway scenarios. For the current climate, the model simulates well the climatology of mean sea level pressure (MSLP) and associated wind direction over NA. Future simulations suggest increases in mean wind speed for northern and eastern parts of Canada, associated with decreases in future MSLP, which results in more intense low-pressure systems situated in those regions such as the Aleutian and Icelandic Lows. Projected changes to annual maximum 3-hourly wind speed show more spatial variability compared to seasonal and annual mean wind speed, indicating that extreme wind speeds are influenced by regional level features associated with instantaneous surface temperature and air pressure gradients. The simulations also suggest some increases in the future 50-year return levels of 3-hourly wind speed and hourly wind gusts, mainly due to increases in the inter-annual variability of annual maximum values. The variability of projected changes to both extreme wind speed and gusts indicate the need for a larger set of projections, including those from other regional models driven by many GCMs to better quantify uncertainties in future wind extremes and their characteristics. Full article

In urban areas, fine particulate matter (PM_2.5) associated with local vehicle emissions can cause respiratory and cardiorespiratory disease and increased mortality rates, but less so in rural areas. However, Hong Kong may be a special case, since the whole territory often suffers from regional haze from nearby mainland China, as well as local sources. Therefore, to understand which areas of Hong Kong may be affected by damaging levels of fine particulates, PM_2.5 data were obtained from March 2005 to February 2009 for urban, suburban, and rural air quality monitoring stations; namely Central (city area, commercial area, and urban populated area), Tsuen Wan (city area, commercial area, urban populated, and residential area), Tung Chung (suburban and residential area), Yuen Long (urban and residential area), and Tap Mun (remote rural area). To evaluate the relative contributions of regional and local pollution sources, the study aimed to test the influence of weather conditions on PM_2.5 concentrations. Thus, meteorological parameters including temperature, relative humidity, wind speed, and wind directions were obtained from the Hong Kong Observatory. The results showed that Hong Kong’s air quality is mainly affected by regional aerosol emissions, either transported from the land or ocean, as similar patterns of variations in PM_2.5 concentrations were observed over urban, suburban, and rural areas of Hong Kong. Only slightly higher PM_2.5 concentrations were observed over urban sites, such as Central, compared to suburban and rural sites, which could be attributed to local automobile emissions. Results showed that meteorological parameters have the potential to explain 80% of the variability in daily mean PM_2.5 concentrations—at Yuen Long, 77% at Tung Chung, 72% at Central, 71% at Tsuen Wan, and 67% at Tap Mun, during the spring to summer part of the year. The results provide not only a better understanding of the impact of regional long-distance transport of air pollutants on Hong Kong’s air quality but also a reference for future regional-scale collaboration on air quality management. Full article

This paper describes the use of citizen science-derived data for the creation of a land-use regression (LUR) model for particulate matter (PM_2.5 and PM_coarse) for a vulnerable community in Imperial County, California (CA), near the United States (US)/Mexico border. Data from the Imperial County Community Air Monitoring Network community monitors were calibrated and added to a LUR, along with meteorology and land use. PM_2.5 and PM_coarse were predicted across the county at the monthly timescale. Model types were compared by cross-validated (CV) R² and root-mean-square error (RMSE). The Bayesian additive regression trees model (BART) performed the best for both PM_2.5 (CV R² = 0.47, RMSE = 1.5 µg/m³) and PM_coarse (CV R² = 0.65, RMSE = 8.07 µg/m³). Model predictions were also compared to measurements from the regulatory monitors. RMSE for the monthly models was 3.6 µg/m³ for PM_2.5 and 17.7 µg/m³ for PM_coarse. Variable importance measures pointed to seasonality and length of roads as drivers of PM_2.5, and seasonality, type of farmland, and length of roads as drivers of PM_coarse. Predicted PM_2.5 was elevated near the US/Mexico border and predicted PM_coarse was elevated in the center of Imperial Valley. Both sizes of PM were high near the western edge of the Salton Sea. This analysis provides some of the initial evidence for the utility of citizen science-derived pollution measurements to develop spatial and temporal models which can make estimates of pollution levels throughout vulnerable communities. Full article