Atmosphere, Volume 10, Issue 5 (May 2019) – 65 articles

In this study, we used the positive matrix factorization (PMF) model to evaluate the sources of ambient coarse particulate matter (PM) and their temporal variations in two sampling sites, i.e., a school dormitory and a retirement home, located in central Tehran. 24-h ambient PM samples were collected using low-volume air samplers from May 2012 to June 2013. The collected filters were analyzed for their chemical components, including water-soluble ions, metals, and trace elements, which were used as the input to the PMF model. Our results indicated annual averages of 45.7 ± 3.8 µg/m³ and 36.2. ± 4.0 µg/m³ for coarse PM at the School dormitory and Tohid retirement home, respectively. Moreover, higher ambient coarse PM mass concentrations were observed in the warm season (53.3 ± 5.8 µg/m³ for school dormitory and 43.1 ± 6.1 µg/m³ for Tohid retirement home) as opposed to the cold season (41.4 ± 4.7 µg/m³ for school dormitory and 28.7 ± 4.6 µg/m³ for Tohid retirement home). Our PMF analysis also identified road dust, soil, and industry, and atmospherically processed coarse PM as the three sources of ambient coarse PM in central Tehran. Road dust, soil, and industry were the major sources of ambient coarse PM, contributing respectively to 74 ± 9% and 19 ± 2% of the total coarse PM mass concentration, while atmospherically aged aerosols had a rather minimal contribution of 7 ± 1% to total coarse PM mass concentration. The temporal trends of the resolved factors also revealed higher contributions of road dust to total ambient coarse PM during warm season as opposed to cold season, due to the increased resuspension rate from road surfaces as a result of higher wind speeds, and temperatures, combined with lower relative humidity. Similarly, higher resuspension rate of mechanically originated particulates resulted in higher warm-season time contributions of the soil factor. Results of this study clearly revealed the key role of road dust and non-tail pipe emissions on ambient coarse PM mass concentrations in crowded areas of central Tehran, and have important implications on the potential health impacts that can be caused by these difficult to mitigate sources of coarse PM. Full article

This paper presents results from eight field studies in Asia and Africa on the emissions performance of 16 stove/fuel combinations measured during normal cooking events in homes. Characterizing real-world emissions performance is important for understanding the climate and health implications of technologies being promoted as alternatives to displace baseline cooking stoves and fuels. Almost all of the stove interventions were measured to have substantial reductions in PM_2.5 and CO emissions compared to their respective baseline technologies (reductions of 24–87% and 25–80%, for PM_2.5 and CO emission rates, respectively), though comparison with performance guidance from the World Health Organization (WHO) and the International Organization for Standardization (ISO) suggests that further improvement for biomass stoves would help realize more health benefits. The emissions of LPG stoves were generally below the WHO interim PM_2.5 emissions target (1.75 mg/min) though it was not clear how close they were to the most aspirational ISO (0.2 mg/min) or WHO (0.23 mg/min) targets as our limit of detection was 1.1 mg/min. Elemental and organic carbon emission factors and elemental-to-total carbon ratios (medians ranging from 0.11 to 0.42) were in line with previously reported field-based estimates for similar stove/fuel combinations. Two of the better performing forced draft stoves used with pellets—the Oorja (median ET/TC = 0.12) and Eco-Chula (median ET/TC = 0.42)—were at opposite ends of the range, indicating that important differences in combustion conditions can arise even between similar stove/fuel combinations. Field-based tests of stove performance also provide important feedback for laboratory test protocols. Comparison of these results to previously published water boiling test data from the laboratory reinforce the trend that stove performance is generally better during controlled laboratory conditions, with modified combustion efficiency (MCE) being consistently lower in the field for respective stove/fuel categories. New testing approaches, which operate stoves through a broader range of conditions, indicate potential for better MCE agreement than previous versions of water boiling tests. This improved agreement suggests that stove performance estimates from a new ISO laboratory testing protocol, including testing stoves across low, medium, and high firepower, may provide more representative estimates of real-world performance than previously used tests. More representative results from standardized laboratory testing should help push stove designs toward better real-world performance as well as provide a better indication of how the tested technologies will perform for the user. Full article

The hydroclimatology of the southeastern U.S. is changing, with increased precipitation, intensified summer-to-fall rainfall, and prolonged dry periods. However, research has yet to determine whether these trends are present in the southern Appalachian Mountains, which contain the most topographic and hydroclimatic variability across the region and serve as a valuable resource for growing population centers. This study examines warm season hydroclimatic variability and changes from 1950 to 2018 using the Global Historical Climatological Network (GHCN) daily data record. Daily rainfall is classified according to different intensities, ranging from light to heavy, and a Mann-Kendall test is used to determine the trend at each station. Additionally, a Spearman’s rank correlation test is performed to test for significant linkages between precipitation class frequencies and large-scale modes of atmospheric variability (Atlantic Multidecadal Oscillation, Caribbean SST Index, Pacific/North American Pattern). The results suggest that dry days became less common and light precipitation became more common across the southern Appalachian region. Similarly, the length of dry spells became shorter at most elevations. Teleconnection patterns are linked to the variability of precipitation class frequencies, particularly with dry days and light precipitation. In conclusion, this research reveals the unique character of hydroclimatic variability and change across the southern Appalachian region in the context of the broader southeastern U.S. Full article

Heat waves pose additional risks to urban spaces because of the additional heat provided by urban heat islands (UHIs) as well as poorer air quality. Our study focuses on the analysis of UHIs, human thermal comfort, and air quality for the city of Madrid, Spain during heat waves. Heat wave periods are defined using the long-term records from the urban station Madrid-Retiro. Two types of UHI were studied: the canopy layer UHI (CLUHI) was evaluated using air temperature time-series from five meteorological stations; the surface UHI (SUHI) was derived from land surface temperature (LST) images from MODIS (Moderate Resolution Imaging Spectroradiometer) products. To assess human thermal comfort, the Physiological Equivalent Temperature (PET) index was applied. Air quality was analyzed from the records of two air quality networks. More frequent and longer heat waves have been observed since 1980; the nocturnal CLUHI and both the diurnal and nocturnal SUHI experience an intensification, which have led to an increasing number of tropical nights. Conversely, thermal stress is extreme by day in the city due to the lack of cooling by winds. Finally, air quality during heat waves deteriorates because of the higher than normal amount of particles arriving from Northern Africa. Full article

To evaluate the feasibility of the Sunset semicontinuous organic and elemental carbon (OC/EC) monitor, the U.S. Environmental Protection Agency (EPA) sponsored the deployment of this monitor at Chemical Speciation Network (CSN) sites with OC and EC measurements via quartz fiber filter collection in Chicago, Illinois; Houston, Texas; Las Vegas, Nevada; St. Louis, Missouri; Rubidoux, California; and Washington, D.C. Houston, St. Louis, and Washington also had collocated Aethalometer black carbon (BC) measurements. Sunset OC generally compared well with the CSN OC (r² = 0.73 across five sites); the Sunset/CSN OC ratio was, on average, 1.06, with a range among sites of 0.96 to 1.12. Sunset thermal EC and CSN EC did not compare as well, with an overall r² of 0.22, in part because 26% of the hourly Sunset EC measurements were below the detection limit. Sunset optical EC had a much better correlation to CSN EC (r² = 0.67 across all sites), with an average Sunset/CSN ratio of 0.90 (range of 0.7 to 1.08). There was also a high correlation of Sunset optical EC with Aethalometer BC (r² = 0.77 across all sites), though with a larger bias (average Sunset/Aethalometer ratio of 0.56). When the Sunset instrument was working well, OC and OptEC data were comparable to CSN OC and EC. Full article

A validated standard k-ε model was used to investigate the effects of ground heating on ventilation and pollutant transport in a three-dimensional (3D) street canyon. Air entered the street canyon from the upper regions of side surfaces and most areas of the top surface and left from the lower regions of side surfaces. Ground heating enhanced the mean flow, ventilation, and turbulence, and facilitated pollutant reduction inside street canyons. The transport patterns in a street canyon that included a pollutant source (PSC) and a target street canyon downstream (TSC) were different. The pollutant did not enter the PSC, and turbulent diffusion dominated pollutant outflow at all boundaries. The pollutant entered the TSC from most regions of the side surfaces and exited from lower regions of the side surfaces and the entire top surface. Air convection dominated pollutant transport at the side surfaces, and its contribution increased significantly with ground temperature; Furthermore, turbulent diffusion dominated pollutant outflow for the top surface, and its contribution increased slightly with ground heating. As revealed by an analysis of both the total pollutant flow rates and air flow rates, although air/pollutant exchange between the TSC and outer space occurred primarily through the side surfaces, the increase in air inflow from the top surface reduced the pollutant concentration inside the street canyon when the ground temperature increased. The top surface played a major role in improving air quality in a 3D environment with ground dispersion. This study supplied valuable suggestions for urban planning strategies. The analyzing method used in this research is helpful for the pollutant transport investigations in urban areas. Full article

To improve the skills of the regional ensemble forecast system (REFS), a modified ensemble transform Kalman filter (ETKF) initial perturbation strategy was developed. First, sensitivity tests were conducted to investigate the influence of the perturbation scale on the ensemble spread growth and forecast skill. In addition, the scale characteristic of the forecast error was analyzed based on the results of these tests, and a new initial condition perturbation method was developed through scale-selection of the ETKF perturbations, namely, ETKF-SS (scale-selective ETKF). The performances of the ETKF-SS scheme and the original ETKF (hereinafter referred to as ETKF) scheme were tested and compared. The results showed that the large-scale perturbations were much easier to grow than the original ETKF perturbations. In addition, scale analysis of the forecast error showed that the large-scale errors showed significant growth at the upper levels, while the small and meso-scale errors grew fast at the lower levels. The comparison results of the ETKF-SS and the ETKF showed that the ETKF-SS perturbations had more obvious growth than the ETKF perturbations, and the ETKF-SS perturbations in the short-term forecast lead times were more precise than the ETKF perturbations. The ensemble forecast verification results showed that the ETKF-SS ensemble had a larger spread and smaller root mean square error than the ETKF at short forecast lead times, while the probabilistic scores of the ETKF-SS also outperformed those of the ETKF method. In addition, the ETKF-SS ensemble can provide a better precipitation forecast than the ETKF. Full article

Given the increase in the frequency, intensity, and persistence of heat waves since the 1970s, and in view of the impacts that extreme temperatures may cause for society and the economy, this study aims to characterize heat waves in the subtropical region of Brazil and compare findings with the criterion defined by the World Meteorological Organization (WMO). Daily maximum temperature data was used. By using the percentile methodology, the subtropical region was divided into two regions: region 1 and region 2. We identified 54 heat waves in region 1 and 34 in region 2, which occurred more frequently in winter and spring, and less frequently in summer. A close relationship was observed between the Pacific Decadal Oscillation (PDO) and El Niño–Southern Oscillation (ENSO), both of which are able to modulate the heat waves in each of the different regions. Region 1 presented the highest number of heat waves during the warm (cold) phase of the PDO. As for ENSO, heat waves were more frequent in the neutral phase in both regions. Finally, there was shown to be an increase in the frequency and persistence of heat waves since the 1980s, especially in region 2. The methodology used in this study allows the identification and characterization of heat waves in several regions of different climates. Full article

Long-term atmospheric changes are a result of complex interactions on various spatial scales. In this study, we examine the long-term variability of the most important meteorological variables in a convection-permitting regional climate model simulation. A consistent, gridded data set from 1948 to 2014 was computed using the regional climate model COSMO-CLM with a very high convection-permitting resolution at a grid distance of 2.8 km, for a region encompassing the German Bight and Northern Germany. This is one of the very first atmospheric model simulations with such high resolution, and covering several decades. Using a very high-resolution hindcast, this study aims to extend knowledge of the significance of regional details for long-term variability and multi-decadal trends of several meteorological variables such as wind, temperature, cloud cover, precipitation, and convective available potential energy (CAPE). This study demonstrates that most variables show merely large decadal variability and no long-term trends. The analysis shows that the most distinct and significant positive trends occur in temperature and in CAPE for annual mean values as well as for extreme events. No clear and no significant trend is detectable for the annual sum of precipitation and for extreme precipitation. However, spatial structures in the trends remain weak. Full article

Urban heat is a growing environmental concern in cities around the world. The urban heat island effect, combined with warming effects of climate change, is likely to cause an increase in the frequency and intensity of extreme heat events. Alterations to the physical, built environment are a viable option for mitigating urban heat, yet few studies provide systematic guidance to practitioners for adapting diverse land uses. In this study, we examine the use of green infrastructure treatments to evaluate changes in ambient temperatures across diverse land uses in the city of Portland, Oregon. We apply ENVI-met^® microclimate modeling at the city-block scale specifically to determine what built environment characteristics are most associated with high temperatures, and the extent to which different physical designs reduce ambient temperature. The analysis included six green infrastructure interventions modeled across six different land-use types, and indicated the varying degrees to which approaches are effective. Results were inconsistent across landscapes, and showed that one mitigation solution alone would not significantly reduce extreme heat. These results can be used to develop targeted, climate- and landscape-specific cooling interventions for different land uses, which can help to inform and refine current guidance to achieve urban climate adaptation goals. Full article

The representation of vegetation in land surface models (LSM) is crucial for modeling atmospheric processes in regional climate models (RCMs). Vegetation is characterized by the green fractional vegetation cover (FVC) and/or the leaf area index (LAI) that are obtained from nearest difference vegetation index (NDVI) data. Most regional climate models use a constant FVC for each month and grid cell. In this work, three FVC datasets have been constructed using three methods: ZENG, WETZEL and GUTMAN. These datasets have been implemented in a RCM to explore, through sensitivity experiments over the Iberian Peninsula (IP), the effects of the differences among the FVC data-sets on the near surface temperature (T2m). Firstly, we noted that the selection of the NDVI database is of crucial importance, because there are important bias in mean and variability among them. The comparison between the three methods extracted from the same NDVI database, the global inventory modeling and mapping studies (GIMMS), reveals important differences reaching up to 12% in spatial average and and 35% locally. Such differences depend on the FVC magnitude and type of biome. The methods that use the frequency distribution of NDVI (ZENG and GUTMAN) are more similar, and the differences mainly depends on the land type. The comparison of the RCM experiments exhibits a not negligible effect of the FVC uncertainty on the monthly T2m values. Differences of 30% in FVC can produce bias of 1 ${}^{\circ }$ C in monthly T2m, although they depend on the time of the year. Therefore, the selection of a certain FVC dataset will introduce bias in T2m and will affect the annual cycle. On the other hand, fixing a FVC database, the use of synchronized FVC instead of climatological values produces differences up to 1 ${}^{\circ }$ C, that will modify the T2m interannual variability. Full article

Airborne prokaryotes are transported along with dust/aerosols, yet very little attention is given to their temporal variability above the oceans and the factors that govern their abundance. We analyzed the abundance of autotrophic (cyanobacteria) and heterotopic airborne microbes in 34 sampling events between 2015–2018 at a coastal site in the SE Mediterranean Sea. We show that airborne autotrophic (0.2–7.6 cells × 10³ m⁻³) and heterotrophic (0.2–30.6 cells × 10³ m⁻³) abundances were affected by the origin and air mass trajectory, and the concentration of dust/aerosols in the air, while seasonality was not coherent. The averaged ratio between heterotrophic and autotrophic prokaryotes in marine-dominated trajectories was ~1.7 ± 0.6, significantly lower than for terrestrial routes (6.8 ± 6.1). Airborne prokaryotic abundances were linearly and positively correlated to the concentrations of total aerosol, while negatively correlated with the aerosol’s anthropogenic fraction (using Pb/Al or Cu/Al ratios as proxies). While aerosols may play a major role in dispersing terrestrial and marine airborne microbes in the SE Mediterranean Sea, the mechanisms involved in the dispersal and diversity of airborne microorganisms remain to be studied and should include standardization in collection and analysis protocols. Full article

SCALA© (Sampling Campaigns for Aerosols in the Low Atmosphere) is a web-based software system that was developed in a multidisciplinary manner to integrally support the documentation and the management and analysis of atmospheric aerosol data from sampling campaigns. The software development process applied considered the prototyping and the evolutionary approaches. The software product (SCALA©) allows for the comprehensive management of the sampling campaigns’ life cycle (management of the profiles and processes involved in the start-up, development and closure of a campaign) and provides support for both intra- and inter-campaigns data analysis. The pilot deployment of SCALA© considers the Spanish Network on Environmental Differential Mobility Analysers (DMAs) (REDMAAS) and the PROACLIM project. This research project involves, among other objectives, the study of temporal and spatial variations of the atmospheric aerosol through a set of microphysical properties (size distribution, optical properties, hygroscopicity, etc.) measured in several locations in Spain. The main conclusions regarding size distribution are presented in this work. These have been have been extracted through SCALA© from the data collected in the REDMAAS 2015 and 2019 intercomparison campaigns and two years (2015 and 2016) of measurements with two Scanning Mobility Particle Sizers (SMPS) at CIEMAT (Madrid, central Spain) and UDC (A Coruña, NW of Spain) sites. Full article

Particle size distribution in biomass smoke was observed for different burning phases, including flaming and smouldering, during the combustion of nine common Australian vegetation representatives. Smoke particles generated during the smouldering phase of combustions were found to be coarser as compared to flaming aerosols for all hard species. In contrast, for leafy species, this trend was inversed. In addition, the combustion process was investigated over the entire duration of burning by acquiring data with one second time resolution for all nine species. Particles were separately characterised in two categories: fine particles with dominating diffusion properties measurable with diffusion-based instruments (D_p < 200 nm), and coarse particles with dominating inertia (D_p > 200 nm). It was found that fine particles contribute to more than 90 percent of the total fresh smoke particles for all investigated species. Full article

Comparisons of aerosol composition and sources in different cities or regions are rather limited, yet important for an in-depth understanding of the spatial diversity of aerosol pollution in China. In this study, the data originating from 25 different winter aerosol mass spectrometer (AMS)/aerosol chemical speciation monitor (ACSM) studies were used to provide spatial coverage of the Beijing-Tianjin-Hebei (BTH), Guanzhong (GZ), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions. The spatial distribution and diurnal variations in aerosol composition and organic sources were analyzed to investigate the aerosol characteristics in the four regions. It was found that there were differences in the compositions of non-refractory particulate matter across the regions, e.g., more sulfate in the PRD versus more nitrate in the YRD, as well as in the organic sources, e.g., more coal combustion in BTH versus more biomass burning in GZ. The characteristics of the composition of NR-PM are similar when the campaigns were classified according to the winter of different years or the cities of different regions. The diurnal variation of the PRD-sulfate indicated its regional nature, whereas the organics from burning sources in two regions of northern China exhibited local characteristics. Based on these findings, we suggest that strict control policies for coal combustion and biomass burning emissions should be enforced in the BTH and GZ regions, respectively. Full article

The input of aeolian mineral dust to the oceans is regarded as the major source in supplying bioavailable iron for phytoplankton growth. Severe dust events swept over East Asia during the 26 March to the 4 April 2018, decreasing air quality to hazardous levels, with maximum PM₁₀ mass concentrations above 3000 μg m⁻³ in northern China. Based on a comprehensive approach that combines multiple satellite measurements, ground observations, and model simulation, we revealed that two severe Asian dust events originating from the Taklimakan and Gobi deserts on 26 March and 1 April, were transported through northern China and the East/Japan Sea, to the North Pacific Ocean by westerly wind systems. Transportation pathways dominated by mineral dust aerosols were observed at altitudes of 2–7 km in the source regions, and then ascending to 3–10 km in the North Pacific Ocean, with relatively denser dust plumes within the second dust episode than there were during the first. Our results suggest that mineral dust emitted from the Taklimakan and Gobi deserts could increase ocean primary productivity in the North Pacific Ocean by up to ~50%, compared to average conditions. This emphasizes the potential importance of the deposition of Asian mineral dust over the North Pacific Ocean for enhancing the biological pump. Full article

A field aerosol measurement campaign as part of the Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign was conducted between 16 January 2013 and 15 February 2013 in the coastal city of Wollongong, Australia. The objectives of this research were to study the occurrence frequency, characteristics and factors that influence new particle formation processes. Particle formation and growth events were observed from particle number size distribution data in the range of 14 nm–660 nm measured using a scanning particle mobility sizer (SMPS). Four weak Class I particle formation and growth event days were observed, which is equivalent to 13% of the total observation days. The events occurred during the day, starting after 8:30 Australian Eastern Standard time with an average duration of five hours. The events also appeared to be positively linked to the prevailing easterly to north easterly sea breezes that carry pollutants from sources in and around Sydney. This suggests that photochemical reactions and a combination of oceanic and anthropogenic air masses are among the factors that influenced these events. Full article

This review paper explores the field of mesoscale to microscale modeling over complex terrain as it traverses multiple so-called gray zones. In an attempt to bridge the gap between previous large-scale and small-scale modeling efforts, atmospheric simulations are being run at an unprecedented range of resolutions. The gray zone is the range of grid resolutions where particular features are neither subgrid nor fully resolved, but rather are partially resolved. The definition of a gray zone depends strongly on the feature being represented and its relationship to the model resolution. This paper explores three gray zones relevant to simulations over complex terrain: turbulence, convection, and topography. Taken together, these may be referred to as the gray continuum. The focus is on horizontal grid resolutions from ∼10 km to ∼10 m. In each case, the challenges are presented together with recent progress in the literature. A common theme is to address cross-scale interaction and scale-awareness in parameterization schemes. How numerical models are designed to cross these gray zones is critical to complex terrain applications in numerical weather prediction, wind resource forecasting, and regional climate modeling, among others. Full article

The impact of a forest canopy on smoke concentration is assessed by applying a numerical weather prediction model coupled with a Lagrangian particle dispersion model to two low-intensity wildland (prescribed) fires in the New Jersey Pine Barrens. A comparison with observations indicates that the coupled numerical model can reproduce some of the observed variations in surface smoke concentrations and plume heights. Model sensitivity analyses highlight the effect of the forest canopy on simulated meteorological conditions, smoke concentrations, and plume heights. The forest canopy decreases near-surface wind speed, increases buoyancy, and increases turbulent mixing. Sensitivities to the time of day, plant area density profiles, and fire heat fluxes are documented. Analyses of temporal variations in smoke concentrations indicate that the effect of the transition from a daytime to a nocturnal planetary boundary layer is weaker when sensible heat fluxes from the fires are stronger. The results illustrate the challenges in simulating meteorological conditions and smoke concentrations at scales where interactions between the fire, fuels, and atmosphere are critically important. The study demonstrates the potential for predictive tools to be developed and implemented that could help fire and air-quality managers assess local air-quality impacts during low-intensity wildland fires in forested environments. Full article

An ensemble of regional climate change scenarios for the North Sea is validated and analyzed. Five Coupled Model Intercomparison Project Phase 5 (CMIP5) General Circulation Models (GCMs) using three different Representative Concentration Pathways (RCPs) have been downscaled with the coupled atmosphere–ice–ocean model RCA4-NEMO. Validation of sea surface temperature (SST) against different datasets suggests that the model results are well within the spread of observational datasets. The ensemble mean SST with a bias of less than 1 ${}^{\circ }$ C is the solution that fits the observations best and underlines the importance of ensemble modeling. The exchange of momentum, heat, and freshwater between atmosphere and ocean in the regional, coupled model compares well with available datasets. The climatological seasonal cycles of these fluxes are within the 95% confidence limits of the datasets. Towards the end of the 21st century the projected North Sea SST increases by 1.5 ${}^{\circ }$ C (RCP 2.6), 2 ${}^{\circ }$ C (RCP 4.5), and 4 ${}^{\circ }$ C (RCP 8.5), respectively. Under this change the North Sea develops a specific pattern of the climate change signal for the air–sea temperature difference and latent heat flux in the RCP 4.5 and 8.5 scenarios. In the RCP 8.5 scenario the amplitude of the spatial heat flux anomaly increases to 5 W/m ${}^2$ at the end of the century. Different hypotheses are discussed that could contribute to the spatially non-uniform change in air–sea interaction. The most likely cause for an increased latent heat loss in the central western North Sea is a drier atmosphere towards the end of the century. Drier air in the lee of the British Isles affects the balance of the surface heat budget of the North Sea. This effect is an example of how regional characteristics modulate global climate change. For climate change projections on regional scales it is important to resolve processes and feedbacks at regional scales. Full article

Extreme precipitation has often occurred in Southeastern China, while the possible mechanism is not clear. In order to bridge the scale gap between large-scale circulation and extreme precipitation, in this paper, the k-means clustering technique—a common method of weather-type (WT) analysis—was applied to regional 850-hPa wind fields. The reasonable determination of k values can make the later WT analyses more reliable. Thus, the Davies–Bouldin (BD) criterion index is used in the clustering process, and the optimal value of the k was determined. Then, we obtain and analyze the frequency, persistence, and progression of WTs. The rule of transitions from one WT to another may help explain some of the physical processes in winter. We found a special evolutionary chain (WT3→WT1→WT2→WT5→WT3) that can be used to explain the cold wave weather process in winter. Different WTs in the evolutionary chain correspond well to different stages of the cold wave weather process (gestation (WT3), outbreak (WT1), eastward withdrawal (WT2), and extinction (WT5)). In addition, we found that there are obvious differences in precipitation between December and February. After reassembling five kinds of WTs, two modes are formed: dry WTs and wet WTs. Our research shows that the intraseasonal variation of precipitation can be attributed to the fluctuation between the wet and dry WTs, and the different phases of teleconnection can correspond well with it. For example, the relative frequencies of wet WTs are higher in February. These WTs correspond to the positive phase of the WP and ENSO, the negative phase of the EA and EU, and the strong MJO state of the second, third, and eighth phase. Our work has well established the relationship between synoptic scale and large-scale circulation, which provides a reference for climate model simulation and future climate prediction. Full article

Exposure to airborne particulate matter (PM) has been associated with the transcriptional up-regulation of pro-inflammatory mediators. However, the effect of PM on post-transcriptional regulation of pro-inflammatory mediators has not been fully explored. In this study, we examined the acute effect of organic extracts from urban PM, rural PM and diesel exhaust particles (DEP) on the post-transcriptional control of interleukin-6 (IL-6) and interleukin-8 (CXCL8) using a human bronchial epithelial cell line. Both PM and DEP extracts induced the release of IL-6 and CXCL8 after 24 h of exposure. Time-course experiments were conducted to examine changes in mRNA steady-state levels and half-lives. The steady-state levels of CXCL8 mRNA increase at 15 min on cells exposed to both PM and DEP extracts. Meanwhile only the urban extract induced significant increases of IL-6 mRNA levels at 15 min. Indirect measurements of IL-6 mRNA half-life showed a dramatic increase in cells exposed to the organic extracts. CXCL8 mRNA half-life increases in cells exposed to PM extracts and not DEP extract. Nuclear run-ons demonstrated that the urban PM and DEP extracts promoted an up-regulation in the transcription rate of CXCL8 at 15 min but not for IL-6. Urban and rural PM influences the post-transcriptional control of CXCL8. Full article

Hydrologic margins of wetlands are narrow, transient zones between inundated and dry areas. As water levels fluctuate, the dynamic hydrology at margins may impact wetland greenhouse gas (GHG) fluxes that are sensitive to soil saturation. The Prairie Pothole Region of North America consists of millions of seasonally-ponded wetlands that are ideal for studying hydrologic transition states. Using a long-term GHG database with biweekly flux measurements from 88 seasonal wetlands, we categorized each sample event into wet to wet (W→W), dry to wet (D→W), dry to dry (D→D), or wet to dry (W→D) hydrologic states based on the presence or absence of ponded water from the previous and current event. Fluxes of methane were 5-times lower in the D→W compared to W→W states, indicating a lag ‘ramp-up’ period following ponding. Nitrous oxide fluxes were highest in the W→D state and accounted for 20% of total emissions despite accounting for only 5.2% of wetland surface area during the growing season. Fluxes of carbon dioxide were unaffected by transitions, indicating a rapid acclimation to current conditions by respiring organisms. Results of this study highlight how seasonal drying and re-wetting impact GHGs and demonstrate the importance of hydrologic transitions on total wetland GHG balance. Full article

Calculation of actual evapotranspiration (AET) is of vital importance for the study of climate change, ecosystem carbon cycling, flooding, drought, and agricultural water demand. It is one of the more important components in the hydrological cycle and surface energy balance (SEB). How to accurately estimate AET especially for the Tibetan Plateau (TP) with complex terrain remains a challenge for the scientific community. Using multi-sensor remote sensing data, meteorological forcing data, and field observations, AET was derived for the Nagqu river basin of the Northern Tibetan Plateau from a surface energy balance system (SEBS) model. As inputs for SEBS, improved algorithms and datasets for land surface albedo and a cloud-free normalized difference vegetation index (NDVI) were also constructed. The model-estimated AET were compared with results by using the combinatory method (CM). The validation indicated that the model estimates of AET agreed well with the correlation coefficient, the root mean square error, and the mean percentage error of 0.972, 0.052 mm/h, and −10.4%, respectively. The comparison between SEBS estimation and CM results also proved the feasibility of parameterization schemes for land surface parameters and AET. Full article

The authors generalize and analyze the investigation results of joint anomalies of high-frequency geoacoustic emission and atmospheric electric field by the ground–atmosphere boundary which were detected by them in Kamchatka. These anomalies are observed as geoacoustic emission increases in kilohertz frequency range and bay-like decreases of atmospheric electric field with the sign change which occur close in time during calm weather conditions. It is the authors’ opinion that the common nature of these anomalies is short-time stretching of the near-surface sedimentary rocks at an observation site during unstable tectono-seismic process. A scheme of the detected anomalies formation has been suggested. Full article

Even with advances in climate modeling, meteorological impact assessment remains elusive, and decision-makers are forced to operate with potentially malinformed predictions. In this article, we investigate the dependence of the Weather Research and Forecasting (WRF) model simulated precipitation and temperature at 12- and 4-km horizontal resolutions and compare it with 32-km NARR data and 1/16th-degree gridded observations for the Midwest U.S. and Great Lakes region from 1991 to 2000. We used daily climatology, inter-annual variability, percentile, and dry days as metrics for inter-comparison for precipitation. We also calculated the summer and winter daily seasonal minimum, maximum, and average temperature to delineate the temperature trends. Results showed that NARR data is a useful precipitation product for mean warm season and summer climatological studies, but performs extremely poorly for winter and cold seasons for this region. WRF model simulations at 12- and 4-km horizontal resolutions were able to capture the lake-effect precipitation successfully when driven by observed lake surface temperatures. Simulations at 4-km showed negative bias in capturing precipitation without convective parameterization but captured the number of dry days and 99^th percentile precipitation extremes well. Overall, our study cautions against hastily pushing for increasingly higher resolution in climate studies, and highlights the need for the careful selection of large-scale boundary forcing data. Full article

This study investigated the impact of global warming on Japanese wind energy resources and their short-term variations using the large ensemble d4PDF dataset, which consists of dynamically downscaled historical and +4K future climate projections. The capacity factor under the future and present climate was estimated from an idealized power curve based on hourly near-surface wind speeds. The +4K warming future climate projections showed significant changes in wind energy resources that varied both regionally and seasonally. The wind energy potential was projected to slightly increase (decrease) from winter to spring over northern (southern) Japan and decrease from summer to autumn over most of Japan. The projected annual production decreased by about ~5% over Japan in response to climate change. The frequency of wind ramp events also decreased in the latter seasons. The relationship to synoptic weather was investigated using self-organizing maps, whereby weather patterns (WPs) over the region in the present and future +4K climate were classified for a two-dimensional lattice. Future probabilistic projections of WPs under the global warming scenario showed both increases and decreases in the frequency of different WPs, with corresponding advantages and disadvantages for wind power generation with regard to future changes in capacity factors in Japan. The importance of these frequency changes on the total change was further assessed by separating the dynamical and thermodynamic contributions. Full article

A landscape is part of our daily lives and our perception of its features may significantly impact our quality of life. This article presents the results of research aimed at determining the influence of biometeorological conditions on the way in which we perceive the landscape. An eye tracker was used throughout each season of the year to determine how 52 respondents observed the landscape while taking into consideration whether the landscape had a favorable or unfavorable impact on those same respondents. Additionally, each test was preceded by the completion of a questionnaire intended to assess the mental and physical state of each respondent. The calculated eye movement indexes demonstrated the impact of the biometeorological conditions on their perception of the landscape. Statistically significant differences in their perception of the landscape were ascertained depending on the type of weather and the respondents’ general feeling irrespective of their sex. Full article

Brake-related airborne particulate matter contributes to urban emissions in the transport sector. Recent research demonstrated a clear dependence of the number of ultra-fine particles on the disc brake temperature. Above the so-called transition temperature, the number of ultra-fine particles increases dramatically (several magnitudes). As for exhaust emissions, part of the emissions released during braking can be in the volatile fraction. For this reason, a disc brake test stand specifically designed for aerosol research was equipped with three different aerosol sampling instruments: (i) a standard cascade impactor, (ii) a cascade impactor operating at high temperature with a heated sampling line, and (iii) a standard cascade impactor with a thermodenuder. Tests with a brake assembly representative of European passenger vehicles were executed, and the concentration of released airborne particles was determined. The results showed a decrease by several magnitudes in the concentration (in the size range of below 200 nm) using the cascade impactor operating at 180 °C with the sampling line heated to 200 °C. A further decrease in the concentration of airborne particles with size fractions below 200 nm was measured using a standard cascade impactor with a thermodenuder heated to 300 °C. Full article

Radiation is a key process in the atmosphere. Numerous radiative transfer codes have been developed spanning a large range of wavelengths, complexities, speeds, and accuracies. In the infrared and microwave, line-by-line codes are crucial esp. for modeling and analyzing high-resolution spectroscopic observations. Here we present Py4CAtS—PYthon scripts for Computational ATmospheric Spectroscopy, a Python re-implemen-tation of the Fortran Generic Atmospheric Radiation Line-by-line Code GARLIC, where computationally-intensive code sections use the Numeric/Scientific Python modules for highly optimized array processing. The individual steps of an infrared or microwave radiative transfer computation are implemented in separate scripts (and corresponding functions) to extract lines of relevant molecules in the spectral range of interest, to compute line-by-line cross sections for given pressure(s) and temperature(s), to combine cross sections to absorption coefficients and optical depths, and to integrate along the line-of-sight to transmission and radiance/intensity. Py4CAtS can be used in three ways: in the (Unix/Windows/Mac) console/terminal, inside the (I)Python interpreter, or Jupyter notebook. The basic design of the package, numerical and computational aspects relevant for optimization, and a sketch of the typical workflow are presented. In conclusion, Py4CAtS provides a versatile environment for “interactive” (and batch) line-by-line radiative transfer modeling. Full article