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Accurate prediction of traffic demand and airport capacity plays a crucial role in minimising ground delays and airborne holdings. This paper focuses on the latter aspect. Adverse weather conditions present significant challenges to airport operations and can substantially reduce capacity. Consequently, any predictive model, regardless of its complexity, should account for weather conditions when estimating the airport capacity. At present, the sole shared platform for airport capacity information in Europe is the EUROCONTROL Public Airport Corner, where airports have the option to voluntarily report their capacities. These capacities are presented in tabular form, indicating the maximum number of hourly arrivals and departures for each possible runway configuration. Additionally, major airports often provide a supplementary table showing the impact of adverse weather in a somewhat approximate manner (e.g., if the visibility is lower than 100 m, then arrival capacity decreases by 30%). However, these tables only cover a subset of airports, and their generation is not harmonised, as different airports may use different methodologies. Moreover, these tables may not account for all weather conditions, such as snow, strong winds, or thunderstorms. This paper presents a machine learning approach to learn mapping from weather conditions and runway configurations to the 99th percentile of the delivered throughput from historical data. This percentile serves as a capacity proxy for airports operating at or near capacity. Unlike previous attempts, this paper takes a novel approach, where a single model is trained for several airports, leveraging the generalisation capabilities of cutting-edge machine learning algorithms. The results of an experiment conducted using 2 years of historical traffic and weather data for the top 45 busiest airports in Europe demonstrate better alignment in terms of mean pinball error with the observed departure and arrival throughput when compared to the operational capacities reported in the EUROCONTROL Public Airport Corner. While there is still room for improvement, this system has the potential to assist airports in defining more reasonable capacity values, as well as aiding airlines in assessing the impact of adverse weather on their flights. [ABSTRACT FROM AUTHOR]

High concentration levels of air pollutants may cause damage to plants, animals, and the health of some groups of human beings. Therefore, it is important to investigate different topics related to the high air pollution levels and to find reliable answers to the questions about the possible damages, which might take place when these levels exceed some limits. A few of the numerous questions, the answers of which are highly desirable, are listed below: (a) When are the air pollution levels dangerous? (b) What is the reason for the increased air pollution levels? (c) How can the air pollution levels be decreased? (d) Will the future climate changes result in higher and more dangerous air pollution levels? It is necessary to study carefully many issues connected with the distribution of air pollutants in a given region and with the reasons for the increases of the concentrations to high levels, which might be damaging. In order to do this, it is necessary to develop a Digital Twin of all relevant physical processes in the atmosphere and to use after that this tool in different applications. Such a tool, its name is DIGITAL AIR, has been created. Digital Twins are becoming more and more popular). Many complex problems, arising taking place in very complicated surroundings, can be handled and resolved successfully by applying Digital Twins. The preparation of such a digital tool as well as its practical implementation in the treatment of a special problem, the increase of some potentially dangerous ozone levels, will be discussed and tested in this paper. The Unified Danish Eulerian Model (UNI-DEM) is a very important part of DIGITAL AIR. This mathematical model, UNI-DEM, can be applied in many different studies related to damaging effects caused by high air pollution levels. We shall use it in this paper to get a reliable answer to a very special but extremely important question: will the future climatic changes lead to an increase in the ozone pollution levels in Bulgaria and Europe, which can potentially become dangerous for human health? [ABSTRACT FROM AUTHOR]

Hybrid Electric Vehicles (HEVs) are a prominent solution for reducing CO2 emissions from transport in Europe. They are equipped with at least two propulsion energy converters, an Internal Combustion Engine (ICE) and one or more Electric Machines (EMs), operated in a way to exploit synergies and achieve fuel efficiency. Because of the variety in configurations and strategies, the use of simulation is essential for vehicle development and characterisation of energy consumption. This paper introduces a novel simulation approach to estimate the CO2 emissions from different hybrid architectures (series, parallel, power-split) and electrification degrees (mild, full, plug-in and range extender) that is relatively simple, flexible and accurate. The approach identifies the optimal power split between the energy converters for any given time in a driving cycle according to three evaluation levels: supervisor, ICE manager and optimiser. The latter relies on the Equivalent Consumption Minimisation Strategy (ECMS) and the limitations imposed by the other two layers. Six light-duty HEVs with different hybrid architectures were tested to support the development of the approach. The results show an indicative accuracy of ±5%, enabling to run assessments of hybrid powertrain solutions and supporting regulatory and consumer information initiatives. [ABSTRACT FROM AUTHOR]

Vehicle emission regulations in Europe and many Asian countries include a particle number limit. The number concentration is measured, typically, with condensation particle counters (CPCs). For research purposes, the size distributions provide useful information. Scanning mobility particle sizers (SMPSs) accurately provide the size distribution but are not suitable for transient aerosol. Engine (fast) exhaust particle sizers (EEPSs) cover this gap, but with less accuracy. Fast size distribution instruments are commonly used in the research and development of engines. In the last few years, instrument algorithms have been improved, but studies assessing the improvements are limited, in particular in their lower size range, around 10–20 nm, and for soot-like aerosol. In this paper, we compared the three instruments using salt, silver, diffusion flame soot (CAST), and spark discharge graphite particles. Moreover, vehicle exhaust number concentration measurements with EEPSs over a seven-year period were presented. In terms of particle concentration, EEPS overestimated, on average, 25% compared to CPC, in agreement with previous studies. Its accuracy for mean particle size determination was better than 5 nm compared to SMPS. The agreement between the instruments was satisfactory but the uncertainty increased at low concentrations and larger particle sizes, showing that there is still room for further improvements. Experimental challenges, such as low concentration levels of modern vehicles, losses in the diluters, use of photometric mode by the CPCs, and the material impact, are also discussed. [ABSTRACT FROM AUTHOR]

In this study, a 4-D, computerized ionospheric tomography algorithm, IONOLAB-Fusion, is developed to reconstruct electron density using both actual and virtual vertical and horizontal paths for all ionospheric states. The user-friendly algorithm only requires the coordinates of the region of interest and range with the desired spatio-temporal resolutions. The model ionosphere is formed using spherical voxels in a lexicographical order so that a 4-D ionosphere can be mapped to a 2-D matrix. The model matrix is formed automatically using a background ionospheric model with an optimized retrospective or near-real time manner. The singular value decomposition is applied to extract a subset of significant singular values and corresponding signal subspace basis vectors. The measurement vector is filled automatically with the optimized number of ground-based and space-based paths. The reconstruction is obtained in closed form in the least squares sense. When the performance of IONOLAB-Fusion across Europe was compared with ionosonde profiles, a 26.51% and 32.33% improvement was observed over the background ionospheric model for quiet and disturbed days, respectively. When compared with GIM-TEC, the agreement of IONOLAB-Fusion was 37.89% and 31.58% better than those achieved with the background model for quiet and disturbed days, respectively. [ABSTRACT FROM AUTHOR]

In a previous study, we assessed the efficiency of reducing either traffic or industrial emissions on various ozone metrics for several cities in Europe, based on the Air Control Toolbox surrogate model. Here, we perform various model parametrisation sensitivity analyses in order to assess the robustness of our results. We find that increasing the model resolution has a limited impact on the ozone response to emission changes when focusing on concentration peaks but strongly changes the response of the ozone daily mean with a switch to a titration regime for all zones with significant nitrogen oxide (NOx) emissions. The impact of pollution imported from outside the simulation domain was also studied and we show that if the first lever for action on ozone peaks remains as the reduction of local and regional emissions, in order to achieve higher levels of reduction, it is necessary to act at a European level. We also explore more up-to-date temporal profiles and sectoral emission speciation and find a shift towards a more NOx-limited regime in a number of cities. Overall, these sensitivity tests show that most of the differences are simulated in cities with high NOx emissions and little solar radiation but do not change the overall conclusions that were previously obtained. [ABSTRACT FROM AUTHOR]

Featured Application: Various studies have reported a teleconnection between the El Niño phenomenon in the southern Pacific Ocean and the North-Atlantic Oscillation, which governs the weather in the eastern side of the American continent and most parts of Europe, including the Mediterranean. Though such a relationship has been established to a large degree, it is still unknown whether the El Niño phenomenon can affect atmospheric processes in the mentioned regions. Therefore, the present study investigates the existence of any effect of El Niño on atmospheric radiation and atmospheric aerosols over the Mediterranean region. The Mediterranean area is considered a hot spot on our planet because it represents the crossroads of various aerosols. Several studies have shown that the weather in the region is affected by the North-Atlantic Oscillation, which, in turn, is well connected with the El Niño–Southern Oscillation (ENSO) phenomenon. Nevertheless, no study has investigated the ENSO effect on the solar radiation and atmospheric aerosols in this region. The present study considers a greater area around the Mediterranean Sea over the period 1980–2022. The results show that there exists a loose but significant dependence, in some cases, of the optical properties of aerosols (aerosol optical depth, Ångström exponent, cloud optical depth) and solar radiation (net short-wave and net long-wave radiation, direct aerosol radiative forcing) on ENSO events. The results of this study provide motivation for further investigations, since such results can increase the accuracy of general circulation models that deal with climate change. Besides the ENSO effect, the enrichment of the Mediterranean atmosphere in suspended particles from great volcanic eruptions is shown. The inter-annual variation of the examined parameters is presented. A classification of the existing aerosols over the area is also provided. [ABSTRACT FROM AUTHOR]

The state-of-the-art of atmospheric contaminant transport modeling provides accurate estimation of chemical concentrations. However, existing complex models, sophisticated in terms of process description and potentially highly accurate, may entail expensive setups and require very detailed input data. In contexts where detailed predictions are not needed (e.g., for regulatory risk assessment or life cycle impact assessment of chemicals), simple models allowing quick evaluation of contaminants may be preferable. The goal of this paper is to illustrate and critically discuss the use of a simple equation proposed by Pistocchi and Galmarini (2010), which can be implemented through basic GIS functions, to predict atmospheric concentrations of lindane (γ-HCH) in Europe from both local and remote sources. Concentrations were computed for 1995 and 2005 assuming different modes of use of lindane and consequently different spatial patterns of emissions. Results were compared with those from the well-established MSCE-POP model (2005) developed within EMEP (European Monitoring and Evaluation Programme), and with available monitoring data, showing acceptable correspondence in terms of the orders of magnitude and spatial distribution of concentrations, especially when the background effect of emissions from extracontinental sources, estimated using the same equation, is added to European emissions. [ABSTRACT FROM AUTHOR]

The purpose of this study was to analyze the influence of solar activity described by the sunspot number (SSN) on certain terrestrial variables that might impact the Southeastern European climate at different spatio-temporal scales (the North Atlantic Oscillation Index, NAOI, and the Greenland–Balkan Oscillation Index, GBOI—on a large scale; the Palmer Hydrological Drought Index, PHDI—on a regional scale; the Danube discharge at the Orsova (lower basin), Q, representative of the Southeastern European climate—on a local scale). The investigations were carried out for the 20th century using the annual and seasonal averages. To find the connections between terrestrial (atmospheric and hydrological) parameters and SSN, the wavelet coherence were used both globally and in the time–frequency domain. The analyses were carried out for the time series and considered simultaneously (in the same year or season), as well as with lags from 1 to 5 years between the analyzed variables. For the annual values, the type of correlation (linear/non-linear) was also tested using elements from information theory. The results clearly revealed non-linear links between the SSN and the terrestrial variables, even for the annual average values. By applying the wavelet transform to test the solar influence on the terrestrial variables, it was shown that the connections depend on both the terrestrial variable, as well as on the considered lags. Since, in the present study, they were analyzed using wavelet coherence, but only the cases in which the coherence was significant for almost the entire analyzed time interval (1901–2000) and the terrestrial variables were in phase or antiphase with the SSN were considered. Relatively few results had a high level of significance. The analysis of seasonal averages revealed significant information, in addition to the analysis of annual averages. Thus, for the climatic indices, the GBOI and NAOI, a significant coherence (>95%) with the solar activity, associated with the 22-year (Hale) solar cycle, was found for the autumn season for lag = 0 and 1 year. The Hale solar cycle, in the case of the PHDI, was present in the annual and summer season averages, more clearly at lag = 0. For the Danube discharge at Orsova, the most significant SSN signature (~95%) was observed at periods of 33 years (Brüuckner cycle) in the autumn season for lags from 0 to 3 years. An analysis of the redundancy–synergy index was also carried out on the combination of the terrestrial variables with the solar variable in order to find the best synergistic combination for estimating the Danube discharge in the lower basin. The results differed depending on the timescale and the solar activity. For the average annual values, the most significant synergistic index was obtained for the combination of the GBOI, PHDI, and SSN, considered 3 years before Q. [ABSTRACT FROM AUTHOR]

Irrigation is the best strategy to reduce the adverse effects of water stress on almond trees [Prunus dulcis (Mill) D.A. Web] and improve their productivity. However, in the current context of climatic change, in which the amount of water available for irrigation is increasingly limited, deficit irrigation (DI) strategies have become essential in the almond orchards of southern Europe. Other practices, such as the foliar application of reflective compounds, are being implemented. A three-year experiment (2019–2021) was set in a factorial design in which the effect of regulated deficit irrigation and foliar kaolin spray was evaluated on physiological (predawn leaf water potential, relative water content, leaf area, leaf gas exchange, and chlorophyll fluorescence) and agronomic parameters (yield, yield components, and water use efficiency (WUE)). The treatments include full irrigation (FI), which received 100% of ETc (crop evapotranspiration) during all irrigation seasons; regulated deficit irrigation (RDI), which received 100% of ETc until the kernel-filling stage, reducing the application to 35% ETc during the kernel-filling stage until harvest; and both irrigation regimes combined with kaolin application and two cultivars, Constantí and Vairo. More negative water potential values were observed in the RDI treatments compared to the FI treatments. There were no significant differences in the stomatal conductance, photosynthetic rate, or transpiration rate between treatments with RDI and FI, demonstrating the almond tree's good adaptation to irrigation reduction in the kernel-filling stage. The two cultivars had different responses in cumulative yield throughout the three years of the trial. The cv. Constantí did not present significant differences between the FI and RDI treatments, translating into improved WUE. In contrast, the cv. Vairo suffered a reduction in accumulated performance in the RDI treatments with respect to the FI. The foliar application of kaolin did not present differences in yield and very few in the physiological activity of the almond trees. With the results obtained, we can suggest that under the conditions of our experiment, the combination of RDI and the kaolin foliar application can help save irrigation water and produce almonds more sustainably. [ABSTRACT FROM AUTHOR]

Mountains are highly sensitive to the effects of climate change, including extreme short- and long-term weather phenomena. Therefore, in spite of relatively high annual precipitation totals, mountains might become endangered by droughts. The paper presents drought trends in the Polish Carpathians located in Central Europe. Data from the period 1991–2020 from 12 meteorological stations located in various vertical climate zones of the mountains were used to define drought conditions using the following indices: Standardized Precipitation (SPI), Standardized Precipitation Evapotranspiration (SPEI), Relative Precipitation (RPI) and Sielianinov. Additionally, four forest drought indices were used in order to estimate the impact of drought on beech as a typical Carpathian tree species, i.e., the Ellenberg (EQ), Forestry Aridity (FAI), Mayr Tetratherm (MT) and De Martonne Aridity (AI) indices. Statistically significant but weak trends were obtained for the 6-month SPI for four stations (indicating an increase in seasonal to mid-term precipitation), for the 1-month SPEI for three stations, for the 3-month SPEI for four stations, and for MT for all stations (indicating an increase in drought intensity). The analysis of dry month frequency according to particular indices shows that at most of the stations during the last decade of the study period, the frequency of dry months was much higher than in previous decades, especially in the cold half-year. Two zones of the Polish Carpathians are the most prone to drought occurrence: the peak zone due to the shift in climatic vertical zones triggered by the air temperature increase, and the forelands and foothills, together with basins located about 200–400 m a.s.l., where the mean annual air temperature is the highest in all the vertical profile, the annual sums of precipitation are very diversified, and the conditions for beech are already unfavorable. [ABSTRACT FROM AUTHOR]

Air pollution has a strong impact on human health, from respiratory and severe pulmonary diseases to heart attack and cancer. During the 3 years of the COVID-19 pandemic, several peaks of mortality occurred, which could be related to particulate matter (PM) pollution events. The possible effects of PM (PM10 and PM2.5, with diameters less than 10 and 2.5 µm, respectively) on COVID-19 mortality have now been established. To better understand this relationship at the European level for the period 2020–2022, data from 16 representative locations in Europe (81 million people) with PM2.5 levels (µg·m−3) ranging from low to high values were analyzed using statistical methods. The analysis confirms a temporal relation between the peaks of PM2.5 exposure and COVID-19 mortality. The best correlation was obtained considering the history of exposure to PM2.5 pollution during a 2-month integration time coupled with a one-week delay for the COVID-19 mortality. Although the trend of COVID-19 mortality vs. PM2.5 levels varies among locations, the global trend was similar, giving an estimated mean value of a 40 ± 20% mortality increase per µg·m−3 PM2.5 increase. The stronger the positive (negative) gradient of the PM peak, the stronger the positive (negative) gradient of the COVID-19 mortality. These results indicate that a succession of PM pollution peaks could be more dangerous than permanent exposure to moderate pollution levels. Finally, PM number concentrations should be used in the future rather than the PM2.5 mass concentrations (µg·m−3), with the consideration of PM composition to better evaluate the effect of submicron particles on human health, particularly for other respiratory diseases. These results must be considered in the management of future pandemics. [ABSTRACT FROM AUTHOR]

Radiative cooling is a natural process to cool down surfaces through the rejection of thermal radiation using the outer space as a cold sink, taking advantage of the transparency of the atmospheric windows (8–14 μm), which partially matches the infrared radiation band. With the development of new materials that have a high reflectivity of solar radiation, daytime radiative cooling can be achieved. This phenomenon depends on the optical properties of the surface and the local weather conditions. In this research, climatological data from 1791 weather stations were used to present detailed nighttime and all-day radiative cooling maps for the potential implementation of radiative cooling-based technologies. The paper offers a parametric study of the variation of the potential as a result of decreasing the solar reflectivity. The results show that southern Europe is the region with the highest potential while northern Europe holds more hours of available radiative cooling. After varying the solar reflectivity from 1 to 0.5 the average power reduces from 60.18 to 45.32 W/m2, and energy from 527.10 to 264.87 kWh/m2·year. For solar reflectivity lower than 0.5, all-day radiative coolers behave as nighttime radiative coolers, but power and energy values improve significantly for high values of solar reflectivity. Small variations of solar reflectivity have greater impacts on the potential at higher reflectivity values than at lower ones. [ABSTRACT FROM AUTHOR]

This analysis presents the results of observation episodes for high-level clouds consisting of ice crystals with different orientations in space, using the EARLINET lidar network and MODIS data over Europe from 2015 to 2022. The technique used involves identifying specular reflecting layers through ground-based laser soundings of the atmosphere and finding synchronous images from space, followed by the retrieval of cirrus cloud parameters. The study considers several properties of high-level clouds, including reflection ratio (ρ), effective emissivity (ε), optical thickness, effective particle radius, water path, and top height, according to MODIS data. The results of retrieving these properties for cirrus clouds with different orientations of ice crystals over individual EARLINET lidar stations and over Europe as a whole are discussed. The study indicates that high-level clouds with ρ ≥ 0.15 and ε ≥ 0.4 definitely contain specular reflecting layers. [ABSTRACT FROM AUTHOR]

Substantial reductions in human and economic activities such as road traffic for several months in 2020 were one of the consequences of the Coronavirus pandemic. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown across 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5), as well as on land surface temperature (LST) and the surface urban heat island intensity (SUHII) using satellite, modeled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change in the variables under study. In general, the results indicate a substantial decrease in NO2 concentrations in most of the studied cities compared with the reference period of 2015–2019. However, reductions could not be attributed to mobility changes such as less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown in accordance with the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar to the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences. [ABSTRACT FROM AUTHOR]

Southeast Europe is considered one of the most vulnerable regions in the context of climate change, and projected future summer warming is expected to exceed global rates significantly. Despite the importance of this problem, there have been few studies that utilized Coupled Model Intercomparison Project Phase 5 (CMIP5) Global Circulation Models (GCMs) and the multi-model ensemble approach to examine extreme heat events on a regional scale. Additionally, the NEX-GDDP dataset, successfully applied in other parts of the world to assess extreme heat, has not yet been utilized for Southeast Europe. This study aims to fill that gap, presenting the time evolution and spatial distribution of extreme heat events in Southeast Europe for the historical period 1950–2005 and for the expected future climate up to the end of the 21st century based on the NEX-GDDP dataset. In order to leverage the strengths of the multi-model ensemble approach, a set of purpose-tailored indicators, such as the annual number of hot days, the maximum number of consecutive hot days, and hot spell duration at different thresholds, is computed by the daily maximum temperature data from all datasets, produced by NEX-GDDP (21 for the historical period and 42 for the future period). The E-OBS dataset is used as a reference for evaluating the NEX-GDDP's capability to simulate the features of the observed historical extreme heat events. The results show that the multi-model ensemble can satisfactorily capture the occurrence of extreme heat events in the historical period, and therefore it is reasonable to assume that the NEX-GDDP dataset has the potential to reproduce such extremes in the projected future. The study provides clear evidence that the persistence and spatial extent of extreme heat will increase significantly. Some indicators that were not relevant for the historical period due to the high-temperature threshold will become helpful in assessing extreme heat in Southeast Europe in the latter part of the century. Thus, under the RCP8.5 scenario, the area-averaged duration of hot spells at 32 °C and 34 °C will increase from near zero in 1976–2005 to 60 and 45 days, respectively, by the end of the century. The indicators used in the study may be helpful for decision-makers to implement climate change mitigation strategies and actions adequately. The findings are consistent with general tendencies in maximum temperatures considered in our previous works but also with the outcomes of recent studies dedicated to the future climate of the region. [ABSTRACT FROM AUTHOR]

Trends in atmospheric boundary layer height may represent an indication of climate changes. The related modified interaction between the surface and free atmosphere affects both thermodynamics variables and dilution of chemical constituents. Boundary layer is also a major player in various feedback mechanisms of interest for climate models. This paper investigates trends in the nocturnal and convective boundary layer height at mid-latitudes in Europe using radiosounding profiles from the Integrated Global Radiosounding Archive (IGRA). Atmospheric data from the European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis v5 (ERA5) and from the GCOS Reference Upper-Air Network (GRUAN) Lindenberg station are used as intercomparison datasets for the study of structural and parametric uncertainties in the trend analysis. Trends are calculated after the removal of the lag-1 autocorrelation term for each time series. The study confirms the large differences reported in literature between the boundary layer height estimates obtained with the two different algorithms used for IGRA and ERA5 data: ERA5 shows a density distribution with median values of 350 m and 1150 m for the night and the daytime data, respectively, while the corresponding IGRA median values are of 1150 m and 1750 m. An overall good agreement between the estimated trends is found for nighttime data, while daytime ERA5 boundary layer height estimates over Europe are characterized by a lower spatial homogeneity than IGRA. Parametric uncertainties due to missing data in both the time and space domain are also investigated: the former is not exceeding 1.5 m, while the latter are within 10 m during night and 17 m during the day. Recommendations on dataset filtering based on time series completeness are provided. Finally, the comparison between the Lindenberg data as processed at high-resolution by GRUAN and as provided to IGRA at a lower resolution, shows the significant impact of using high-resolution data in the determination of the boundary layer height, with differences from about 200 m to 450 m for both night and day, as well as a large deviation in the estimated trend. [ABSTRACT FROM AUTHOR]

During the last few decades, European legislation has driven progress in reducing air pollution in Europe through emission mitigation measures. In this paper, we use a chemistry transport model to assess the impact on ambient air quality of the measures considered for 2030 in the for the scenarios with existing (WEM2030) and additional measures (WAM2030). The study estimates a general improvement of air quality for the WAM2030 scenario, with no non-compliant air quality zones for NO2, SO2, and PM indicators. Despite an improvement for O3, the model still estimates non-compliant areas. For this pollutant, the WAM2030 scenario leads to different impacts depending on the indicator considered. Although the model estimates a reduction in maximum hourly O3 concentrations, small increases in O3 concentrations in winter and nighttime in the summer lead to increases in the annual mean in some areas and increases in other indicators (SOMO35 for health impacts and AOT40 for impacts on vegetation) in some urban areas. The results suggest that the lower NOx emissions in the WEM and WAM scenarios lead to less removal of O3 by NO titration, especially background ozone in winter and both background and locally produced ozone in summer, in areas with high NOx emissions. [ABSTRACT FROM AUTHOR]

Numerous extreme heatwaves producing large impacts on human health, agriculture, water resources, energy demand, regional economies, and forest ecosystems occurred during the first twenty years of the 21st century. The present study strives to provide a systematic review of recent studies of warm biometeorological extremes in Europe. The main aim of this paper is to provide a methodical summary of the observed changes in warm extremes, duration, and variability in different parts of Europe. During the last decade, much attention has been paid to the negative impacts of heat and humidity on human health. Therefore, the human biometeorology is required to appraise the human thermal environment in a way that human thermoregulation is taken into account. In many European countries and regions, future heat exposure will indeed exceed critical levels, and a steep increase in biometeorological heatwaves and warm extremes are expected. The indices that take into account human energy balance along with weather conditions should be used to examine the impacts of extreme heatwaves on human health and should be used as a basis for the determination of acclimatization to high-heat-stress conditions. A detailed description of recent studies that have used biometeorological indices such as Physiological Equivalent Temperature (PET) and Universal Thermal Climate Index (UTCI) for the estimation of warm extremes and their influence on human health is provided. Additionally, a short overview of the existence of the heat-health warning systems (HHWS), their conceptualization, and implementation across the European continent is considered, as well as the possibilities for further investigations and implementation of effective measures and programs that could reduce the adverse health impacts. [ABSTRACT FROM AUTHOR]

Although traffic exhaust emissions in Europe have been drastically reduced, airborne particle emissions caused by brakes and tires are still increasing with the number of vehicles. The measurement of non-exhaust emissions is an emerging technological challenge. We present a custom measurement setup to investigate the brake- and tire-wear emissions of an in-use battery electric vehicle. A separate brake housing and HEPA ventilation enabled airborne brake wear emissions to be measured under realistic conditions without external influences. The emission tests on a chassis dynamometer included particle number concentrations and particle size distribution for diameters of 4 nm to 10 μm. Emission indices were determined for three driving cycles: WLTC Class 3b, WLTC Brake Part 10, and a real driving cycle. Further investigations focused on emission control through regenerative braking and brake coating. Driving with regenerative braking reduced emissions by up to 89.9%, which related to the concentration of particles in the ultrafine/fine size range. Hard-metal brake coating led to a further significant reduction in emissions of up to 78.9%. The results point the way to future RDE measurement of non-exhaust emissions and show the potential of regenerative braking and brake coating to reduce airborne brake wear emissions. [ABSTRACT FROM AUTHOR]

Aerosol optical depth (AOD) is one of the basic characteristics of atmospheric aerosol. A global ground-based network of sun and sky photometers, the Aerosol Robotic Network (AERONET) provides AOD data with low uncertainty. However, AERONET observations are sparse in space and time. To improve data density, we merged AERONET observations with a GEOS-Chem chemical transport model prediction using an optimal interpolation (OI) method. According to OI, we estimated AOD as a linear combination of observational data and a model forecast, with weighting coefficients chosen to minimize a mean-square error in the calculation, assuming a negligible error of AERONET AOD observations. To obtain weight coefficients, we used correlations between model errors in different grid points. In contrast with classical OI, where only spatial correlations are considered, we developed the spatial-temporal optimal interpolation (STOI) technique for atmospheric applications with the use of spatial and temporal correlation functions. Using STOI, we obtained estimates of the daily mean AOD distribution over Europe. To validate the results, we compared daily mean AOD estimated by STOI with independent AERONET observations for two months and three sites. Compared with the GEOS-Chem model results, the averaged reduction of the root-mean-square error of the AOD estimate based on the STOI method is about 25%. The study shows that STOI provides a significant improvement in AOD estimates. [ABSTRACT FROM AUTHOR]

Precipitation extrema over the Barents Sea and the neighbouring locations in Europe were analysed using data obtained from station observations and a highly detailed ERA5 re-analysis dataset. These data did not always spatially coincide (on average, coincidence was ~50%). Daily amounts of precipitation were typically higher in the observation data, although there may be a reverse picture. The analysis revealed that at several stations and in many of the ERA5 grids, the set of precipitation extremes exists as a mixture of two different subsets. The cumulative distribution functions (CDF) of the largest population in the context of both the re-analysis and observational data are well described by Pareto's law. However, very rare cases exist in which the values deviate and exceed this base distribution value in regions possessing large values. These super-large anomalies do not obey the statistical law common to all other extremes. However, this does not mean that the extremes can be arbitrarily large. They do not exceed the marginal values that are typical for this type of climate and season. The analysis confirms that extreme precipitation in the western sector of the Arctic is caused by the penetration of moist air masses from the Atlantic in the circulation systems of intense cyclones. At certain times, mesoscale convective systems are embedded in atmospheric fronts and can significantly contribute to the formation of precipitation. Intensification of such cyclones corresponding to global warming should lead to a transformation of typical CDF, as modern outliers will become regular components of the Pareto law. This change in the statistics of extreme events reflects the nonstationarity of the climate state. The influence of polar lows on the formation of large daily precipitation amounts is not felt. [ABSTRACT FROM AUTHOR]

A novel integrated water vapor (IWV) product from TROPOspheric Monitoring Instrument (TROPOMI) is validated together with a Global Ozone Monitoring Instrument-2 (GOME-2) standard product. As reference, ground-based Global Navigation Satellite Systems (GNSS) IWV data in 235 European stations from May 2018 to May 2019 are used. Under cloud free situations, a general comparison is carried out. It suggests that TROPOMI IWV exhibits less bias than GOME-2 and better results in the dispersion and regression parameters. Moreover, TROPOMI presents more homogeneous results along the different stations. However, TROPOMI is found to be overestimating the IWV uncertainties and being, therefore, too conservative in the confidence interval considered. The dependence of satellite product performance on several variables is also discussed. TROPOMI IWV shows wet bias of 5.7% or less for IWV < 10 mm (TROPOMI) and dry bias of up to −3% (TROPOMI). In contrast, GOME-2 shows wet bias of 30% or less for IWV < 25 mm (GOME-2) and dry bias of −12.3% for IWV > 25 mm. In addition, relative standard deviation (rSD) increases as IWV increases. In addition, the dependence on solar zenith angle (SZA) was also analyzed, as solar radiation bands are used in the retrieval algorithm of both instruments. Relative mean bias error (rMBE) shows positive values for GOME-2, slightly increasing with SZA, while TROPOMI shows more stable values. However, under high SZA, GOME-2 IWV exhibits a steep increase in rMBE (overestimation), while TROPOMI IWV exhibits a moderate decrease (underestimation). rSD is slightly increasing with SZA. The influence of cloudiness on satellite IWV observations is such that TROPOMI tends to overestimate IWV more as cloudiness increases, especially for high IWV. In the case of GOME-2, the rSD slightly increases with cloudiness, but TROPOMI rSD has a marked increase with increasing cloudiness. TROPOMI IWV is an important source of information about moisture, but its algorithm could still benefit from further improvement to respond better to cloudy situations. [ABSTRACT FROM AUTHOR]

The European climate is changing displaying profound impacts on agriculture, thus strongly reaching the scientific community's attention. In this review, the compilation of selected scientific research on the agroclimatic conditions' changes and their impact on the productivity parameters (phenology timing, product quality and quantity) of grapevines and on the spatiotemporal characteristics of the viticultural areas are attempted for the first time. For this purpose, a thorough investigation through multiple search queries was conducted for the period (2005–2021). Overall, increasing (decreasing) trends in critical temperature (precipitation) parameters are the reality of the recent past with visible impacts on viticulture. The observed climate warming already enforces emerging phenomena related to the modification of the developmental rate (earlier phenological events, shortening of phenological intervals, lengthening of the growing season, earlier harvest), the alteration of product quality, the heterogeneous effects on grapevine yield and the emergence of new cool-climate viticulture areas highlighting the cultivation's rebirth in the northern and central parts of the continent. The vulnerability of the wine-growing ecosystem urges the integration of innovative and sustainable solutions for confronting the impacts of climate change and safeguarding the production (quantity and quality) capacity of viticultural systems in Europe under a continuously changing environment. [ABSTRACT FROM AUTHOR]

We used the objective analysis method in conjunction with the successive correction method to assimilate MODerate resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) data into the Chimère model in order to improve the modeling of fine particulate matter (PM 2.5 ) concentrations and AOD field over Europe. A data assimilation module was developed to adjust the daily initial total column aerosol concentrations based on a forecast-analysis cycling scheme. The model is then evaluated during one-month winter period to examine how such a data assimilation technique pushes the model results closer to surface observations. This comparison showed that the mean biases of both surface PM 2.5 concentrations and the AOD field could be reduced from − 34 to −15% and from −45 to −27%. The assimilation, however, leads to false alarms because of the difficulty in distributing AOD 550 over different particle sizes. The impact of the influence radius is found to be small and depends on the density of satellite data. This work, although preliminary, is important in terms of near-real time air quality forecasting using the Chimère model and can be further developed to improve modeled PM 2.5 and ozone concentrations. [ABSTRACT FROM AUTHOR]

The present study evaluates the National Aeronautics Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset that provides statistically downscaled CMIP5 historical and future climate projections of the daily precipitation sum and extreme temperatures at high spatial resolution. A multimodel ensemble from all 21 available models is composed and compared against gridded observations from E-OBS. The study is performed over Southeast Europe for the whole time span of the historical period of NEX-GDDP 1950–2005. The performance of the NEX-GDDP data was evaluated at multiple time scales such as annual, seasonal, monthly, and daily. The skill of the multimodel ensemble to reproduce the interannual variability, as well as the long-term trend, is also evaluated. Moreover, key climate indices of the Expert Team on Climate Change Detection and Indices (ETCCDI), derived from the ensemble extreme temperatures and precipitation are superimposed on their counterparts based on the reference dataset E-OBS. Findings of the performed research indicate that NEX-GDDP parameters are in good agreement with the reference over the considered period on monthly, seasonal and annual scales which agrees with the outcomes from similar studies for other parts of the world. There are also no systematic differences in the pattern of the biases of the minimum and maximum temperature. Generally, the multimodel ensemble reproduces the extreme temperatures significantly better than the precipitation sum. The analysis reveals also the nonnegligible inefficiency of the NEX-GDDP ensemble to reproduce the long-term trend of the considered parameters as well as the climate extremes expressed with the ETCCDI indices. [ABSTRACT FROM AUTHOR]

This paper presents the methodology and results of impact assessment of renewable energy policies on atmospheric emissions of mercury in Europe. The modeling exercise described here involves an interaction of several models. First, a set of energy scenarios has been developed with the REMix (Renewable Energy Mix) model that simulates different levels of penetration of renewable energies in the European power sector. The energy scenarios were input to the GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) model, which prepared projections of mercury releases to the atmosphere through 2050, based on the current air pollution control policies in each country. Data on mercury emissions from individual sectors were subsequently disaggregated to a fine spatial resolution using various proxy parameters. Finally, the dispersion of mercury in the atmosphere was computed by the chemistry transport model, implemented to the air quality system, Polyphemus. The simulations provided information on changes in concentrations and depositions of various forms of mercury over Europe. Scenarios that simulate a substantial expansion of renewable energies within the power sector indicate extensive co-benefits for mercury abatement, due to the restructuring of the energy system and changes in the fuel mix. The potential for mercury reductions in Europe depends on the rate of fuel switches and renewable technology deployment, but is also influenced by the stringency and timing of the air quality measures. The overall scope for co-benefits is therefore higher in regions relying on coal combustion as a major energy source. [ABSTRACT FROM AUTHOR]

The diurnal cycle of both air temperature and wind speed is characterized by considerable differences, when comparing open site conditions to forests. In the course of this article, a new two-hourly, open-source dataset, covering a high spatial and temporal variability, is presented and analyzed. It contains air temperature measurements (128 station pairs (open/forest); six winter seasons; six study sites), wind speed measurements (64 station pairs; three winter seasons, four study sites) and related metadata in central Europe. Daily cycles of air temperature and wind speed, as well as further dependencies of the effective Leaf Area Index (effective LAI), the exposure in the context of forest effects, and the distance to the forest edge, are illustrated in this paper. The forest effects on air temperature can be seen particularly with increasing canopy density, in southern exposures, and in the late winter season, while wind speed depends on multiple factors such as effective LAI or the distance to the forest edge. New transfer functions, developed using linear and non-linear regression analysis, in a leave-one-out cross-validation, improve certain efficiency criteria (NSME; r2; RMSE; MAE) compared to existing transfer functions. The dataset enables multiple purposes and capabilities due to its diversity and sample size. [ABSTRACT FROM AUTHOR]

Water vapor plays a major role in the process of radiation, cloud formation, energy exchange within a system, and remains a key component of the Earth's atmosphere. The purpose of this study is to examine the water vapor content of the troposphere over Europe and the Northern Atlantic. Both temporal and spatial differences were examined for total column water vapor (TCWV) and vertically integrated water vapor flux (IWVF) based on ERA-Interim reanalysis data. The statistical relationship between circulation patterns, as expressed by empirical orthogonal function (EOF) modes, and TCWV were examined, as were statistical relationships between distinguished advection types and TCWV and IWVF. The study confirmed the significance of atmospheric circulation in the formation of moisture content in the winter season (i.e., January) and its markedly lower impact in other seasons. The relationships noted in the study are characterized by statistically significant spatial differentiation. Spatial pattern analysis was used to identify six regions with different moisture content over the course of the year. The boundaries of the regions confirm the significant role of local factors impacting moisture content. [ABSTRACT FROM AUTHOR]

Ozone concentrations in the Mediterranean area regularly exceed the maximum levels set by the EU Air Quality Directive, 2008/50/CE, a maximum 8-h mean of 120 µg⋅m-3, in the summer, with consequences for both human health and agriculture. There are a number of reasons for this: the particular geographical and meteorological conditions in the Mediterranean play a part, as do anthropogenic ozone precursor emissions from around the Mediterranean and continental Europe. Ozone concentrations measured on-board the Italian Research Council's R. V. Urania during summer oceanographic campaigns between 2000 and 2010 regularly exceeded 60 ppb, even at night. The WRF/Chem (Weather Research and Forecasting (WRF) model coupled with Chemistry) model has been used to simulate tropospheric chemistry during the periods of the measurement campaigns, and then, the same simulations were repeated, excluding the contribution of maritime traffic in the Mediterranean to the anthropogenic emissions inventory. The differences in the model output suggest that, in large parts of the coastal zone of the Mediterranean, ship emissions contribute to 3 and 12 ppb to ground level daily average ozone concentrations. Near busy shipping lanes, up to 40 ppb differences in the hourly average ozone concentrations were found. It seems that ship emissions could be a significant factor in the exceedance of the EU directive on air quality in large areas of the Mediterranean Basin. [ABSTRACT FROM AUTHOR]

The representations of cloud processing of gases and aerosols in some of the current state-of-the-art regional air quality models in North America and Europe are reviewed. Key processes reviewed include aerosol activation (or nucleation scavenging of aerosols), aqueous-phase chemistry, and wet deposition/removal of atmospheric tracers. It was found that models vary considerably in the parameterizations or algorithms used in representing these processes. As an emerging area of research, the current understanding of the uptake of water soluble organics by cloud droplets and the potential aqueous-phase reaction pathways leading to the atmospheric secondary organic aerosol (SOA) formation is also reviewed. Sensitivity tests using the AURAMS model have been conducted in order to assess the impact on modeled regional particulate matter (PM) from: (1) the different aerosol activation schemes, (2) the different below-cloud particle scavenging algorithms, and (3) the inclusion of cloud processing of water soluble organics as a potential pathway for the formation of atmospheric SOA. It was found that the modeled droplet number concentrations and ambient PM size distributions were strongly affected by the use of different aerosol activation schemes. The impact on the modeled average ambient PM mass concentration was found to be limited in terms of averaged PM2.5 concentration (~a few percents) but more significant in terms of PM1.0 (up to 10 percents). The modeled ambient PM was found to be moderately sensitive to the below-cloud particle scavenging algorithms, with relative differences up to 10% and 20% in terms of PM2.5 and PM10, respectively, when using the two different algorithms for the scavenging coefficient Λ) corresponding to the lower and upper bounds in the parameterization for Λ. The model simulation with the additional cloud uptake and processing of water-soluble organic gases was shown to improve the evaluation statistics for modeled PM2.5 OA compared to the IMPROVE network data, and it was demonstrated that the cloud processing of water-soluble organics can indeed be an important mechanism in addition to the traditional secondary organic gas uptake to the particle organic phase. [ABSTRACT FROM AUTHOR]

The question of how sensitive the regional and local climates are to different land cover maps and fractions is important, as land cover affects the atmospheric circulation via its influence on heat, moisture, and momentum transfer, as well as the chemical composition of the atmosphere. In this study, we used three independent land cover data sets, GlobCover 2009, GLC2000 and ESACCI-LC, as the lower boundary of the regional climate model COSMO-CLM (Consortium for Small Scale Modeling in Climate Mode, v5.0-clm15) to perform convection-permitting regional climate simulations over the large part of Europe covering the years 1999 and 2000 at a 0.0275° horizontal resolution. We studied how the sensitivity of the impacts on regional and local climates is represented by different land cover maps and fractions, especially between warm (summer) and cold (winter) seasons. We show that the simulated regional climate is sensitive to different land cover maps and fractions. The simulated temperature and observational data are generally in good agreement, though with differences between the seasons. In comparison to winter, the summer simulations are more heterogeneous across the study region. The largest deviation is found for the alpine area (−3 to +3 °C), which might be among different reasons due to different classification systems in land cover maps and orographical aspects in the COSMO-CLM model. The leaf area index and plant cover also showed different responses based on various land cover types, especially over the area with high vegetation coverage. While relating the differences of land cover fractions and the COSMO-CLM simulation results (the leaf area index, and plant coverage) respectively, the differences in land cover fractions did not necessarily lead to corresponding bias in the simulation results. We finally provide a comparative analysis of how sensitive the simulation outputs (temperature, leaf area index, plant cover) are related to different land cover maps and fractions. The different regional representations of COSMO-CLM indicate that the soil moisture, atmospheric circulation, evaporative demand, elevation, and snow cover schemes need to be considered in the regional climate simulation with a high horizontal resolution. [ABSTRACT FROM AUTHOR]

Extreme weather phenomena such as wind gusts, heavy precipitation, hail, thunderstorms, tornadoes, and many others usually occur when there is a change in air mass and the passing of a weather front over a certain region. The climatology of weather fronts is difficult, since they are usually drawn onto maps manually by forecasters; therefore, the data concerning them are limited and the process itself is very subjective in nature. In this article, we propose an objective method for determining the position of weather fronts based on the random forest machine learning technique, digitized fronts from the DWD database, and ERA5 meteorological reanalysis. Several aspects leading to the improvement of scores are presented, such as adding new fields or dates to the training database or using the gradients of fields. [ABSTRACT FROM AUTHOR]

Compressed natural gas (CNG) and liquefied petroleum gas (LPG) are included in the group of promoted transport fuel alternatives for traditional fossil fuels in Europe. Both CNG and LPG fueled vehicles are believed to have low particle number and mass emissions. Here, we studied the solid particle number (SPN) emissions >4 nm, >10 nm and >23 nm of bi-fuel vehicles applying CNG, LPG and gasoline fuels in laboratory at 23 °C and sub-zero (−7 °C) ambient temperature conditions. The SPN23 emissions in CNG or LPG operation modality at 23 °C were below the regulated SPN23 limit of diesel and gasoline direct injection vehicles 6 × 10 11 1/km. Nevertheless, the limit was exceeded at sub-zero temperatures, when sub-23 nm particles were included, or when gasoline was used as a fuel. The key message of this study is that gas-fueled vehicles produced particles mainly <23 nm and the current methodology might not be appropriate. However, only in a few cases absolute SPN >10 nm emission levels exceeded 6 × 10 11 1/km when >23 nm levels were below 6 × 10 11 1/km. Setting a limit of 1 × 10 11 1/km for >10 nm particles would also limit most of the >4 nm SPN levels below 6 × 10 11 1/km. [ABSTRACT FROM AUTHOR]

Extremely hot or warm weather over the course of the year may have significant impacts on many aspects of human life, the economy, and the natural environment. Until now a thorough assessment of changes of extreme heat or warm events in Europe was hindered by the number of metrics employed, time periods examined, and most studies being conducted in the summer season only. Here, we employ the Extremity Index (EI) to investigate long-term trends in extremely hot or warm days in Europe over the course of the year, with a special focus on their frequency, spatial extent, and intensity. An extreme temperature event (ETE) is defined as a day with an unusually high temperature for a given location and season, even if such a temperature would not be considered extremely high in an absolute sense. The research is conducted in five spatial domains that together cover a large portion of Europe. The period of the most recent 70 years is considered. In all examined regions, mainly significant increasing trends since 1950 are evident for seasonal EI; therefore, also for ETE frequency, intensity, and spatial range. Yet, every region is characterized by its own event pattern, and trends across the continent strongly vary geographically and seasonally. Our study highlights that examined trends of temperature extremes are accelerating and in the last 40 years the rate of change has been even more than three times greater than in the entire study period. The greatest changes were noted for the summer season in Central Europe and Eastern Europe for the most recent 40-year period. [ABSTRACT FROM AUTHOR]

The ionospheric weather is affected not only from above by the Sun but also from below by processes in the lower-lying atmospheric layers. One of the most pronounced atmospheric phenomena is the sudden stratospheric warming (SSW). Three major SSW events from the periods of very low solar activity during January 2009, February 2018, and December 2018/January 2019 were studied to evaluate this effect of the neutral atmosphere on the thermosphere and the ionosphere. The main question is to what extent the ionosphere responds to the SSW events with focus on middle latitudes over Europe. The source of the ionospheric data was ground-based measurements by Digisondes, and the total electron content (TEC). In all three events, the ionospheric response was demonstrated as an increase in electron density around the peak height of the F2 region, in TEC, and presence of wave activity. We presume that neutral atmosphere forcing and geomagnetic activity contributed differently in individual events. The ionospheric response during SSW 2009 was predominantly influenced by the neutral lower atmosphere. The ionospheric changes observed during 2018 and 2018/2019 SSWs are a combination of both geomagnetic and SSW forcing. The ionospheric response to geomagnetic forcing was noticeably lower during time intervals outside of SSWs. [ABSTRACT FROM AUTHOR]

A one-dimensional simulation model that simulates daily mean soil temperature on a daily time-step basis, named AGRISOTES (AGRIcultural SOil TEmperature Simulation), is described. It considers ground coverage by biomass or a snow layer and accounts for the freeze/thaw effect of soil water. The model is designed for use on agricultural land with limited (and mostly easily available) input data, for estimating soil temperature spatial patterns, for single sites (as a stand-alone version), or in context with agrometeorological and agronomic models. The calibration and validation of the model are carried out on measured soil temperatures in experimental fields and other measurement sites with various climates, agricultural land uses and soil conditions in Europe. The model validation shows good results, but they are determined strongly by the quality and representativeness of the measured or estimated input parameters to which the model is most sensitive, particularly soil cover dynamics (biomass and snow cover), soil pore volume, soil texture and water content over the soil column. [ABSTRACT FROM AUTHOR]

Recently, the European Centre for Medium Range Weather Forecast (ECMWF) has released a new generation of reanalysis, acknowledged as ERA5, representing at the present the most plausible picture for the current climate. Although ERA5 enhancements, in some cases, its coarse spatial resolution (~31 km) could still discourage a direct use of precipitation fields. Such a gap could be faced dynamically downscaling ERA5 at convection permitting scale (resolution < 4 km). On this regard, the selection of the most appropriate nesting strategy (direct one-step against nested two-step) represents a pivotal issue for saving time and computational resources. Two questions may be raised within this context: (i) may the dynamical downscaling of ERA5 accurately represents past precipitation patterns? and (ii) at what extent may the direct nesting strategy performances be adequately for this scope? This work addresses these questions evaluating two ERA5-driven experiments at ~2.2 km grid spacing over part of the central Europe, run using the regional climate model COSMO-CLM with different nesting strategies, for the period 2007–2011. Precipitation data are analysed at different temporal and spatial scales with respect to gridded observational datasets (i.e., E-OBS and RADKLIM-RW) and existing reanalysis products (i.e., ERA5-Land and UERRA). The present work demonstrates that the one-step experiment tendentially outperforms the two-step one when there is no spectral nudging, providing results at different spatial and temporal scales in line with the other existing reanalysis products. However, the results can be highly model and event dependent as some different aspects might need to be considered (i.e., the nesting strategies) during the configuration phase of the climate experiments. For this reason, a clear and consolidated recommendation on this topic cannot be stated. Such a level of confidence could be achieved in future works by increasing the number of cities and events analysed. Nevertheless, these promising results represent a starting point for the optimal experimental configuration assessment, in the frame of future climate studies. [ABSTRACT FROM AUTHOR]

In this study, the role of AD 1258 Samalas mega volcanic eruption in the summer hydroclimate change over Europe and the corresponding mechanisms are investigated through multi-member ensemble climate simulation experiments based on the Community Earth System Model (CESM). The results show that the CESM simulations are consistent with the reconstructed Palmer Drought Severity Index (PDSI) and the historical records of European climate. Europe experiences significant summer cooling in the first three years after the Samalas mega volcanic eruption, peaking at −3.61 °C, −4.02 °C, and −3.21 °C in year 1 over the whole Europe, Southern Europe, and Northern Europe, respectively. The summer surface air temperature (SAT, °C) changes over the European continent are mainly due to the direct weakening of shortwave solar radiation induced by volcanic aerosol. The summer precipitation over the European continent shows an obvious dipole distribution characteristic of north-south reverse phase. The precipitation increases up to 0.42 mm/d in year 1 over Southern Europe, while it decreases by −0.28 mm/d in year 1 over Northern Europe, respectively. Both simulations and reconstructions show that the centers with the strongest increase in precipitation have always been located in the Balkans and Apennine peninsulas along the Mediterranean coast over Southern Europe, and the centers with the strongest precipitation reduction are mainly located in the British Isles and Scandinavia over northwestern Europe. The negative response of North Atlantic Oscillation (NAO) with significant positive sea level pressure (SLP) anomaly in the north and negative SLP anomaly in the south is excited in summer. The low tropospheric wind anomaly caused by the negative phase of NAO in summer affects the water vapor transport to Europe, resulting in the distribution pattern of summer precipitation in Europe, which is drying in the north and wetting in the south. The knowledge gained from this study is crucial to better understand and predict the potential impacts of single mega volcanic eruption on the future summer hydroclimate change in Europe. [ABSTRACT FROM AUTHOR]

Convective scale processes and, therefore, thunderstorm-related hazards cannot be simulated using regional climate models with horizontal grid spacing in the order of 10 km. However, larger-scale environmental conditions of these local high-impact phenomena can be diagnosed to assess their frequency in current and future climates. In this study, we present a daytime climatology of severe thunderstorm environments and its evolution for a wide Euro-Mediterranean domain through the 21st century, using regional climate model simulations forced by Representative Concentration Pathway (RCP) 8.5 scenario. Currently, severe convective weather is more frequently favored around Central Europe and the Mediterranean Sea. Our results suggest that with a steady progress until the end of the century, Mediterranean coasts are projected to experience a significantly higher frequency of severe thunderstorm environments, while a slight decrease over parts of continental Europe is evaluated. The increase across the Mediterranean is mostly owed to the warming sea surface, which strengthens thermodynamic conditions in the wintertime, while local factors arguably keep the shear frequency relatively higher than the entire region. On the other hand, future northward extension of the subtropical belt over Europe in the warm season reduces the number of days with severe thunderstorm environments. [ABSTRACT FROM AUTHOR]

Observational and reanalysis data show that the surface air temperature (SAT) over most parts of Europe in June of 2019 broke the highest temperature on record. In this study, we investigate the factors for the formation of this record-breaking high temperature over Europe, focusing on the role of atmospheric circulation anomalies. A strong anomalous anticyclone appeared over Europe, with a quasi-barotropic vertical structure. On one hand, the downward motion anomalies associated with this anomalous anticyclone led to less cloud cover and an increase in downward shortwave radiation, which contributed to the SAT warming over Europe. On the other hand, southerly wind anomalies to the west side of the anomalous anticyclone also resulted in SAT warming via carrying warmer and wetter air northward from lower latitudes. The formation of the anticyclonic anomaly over Europe in June of 2019 was closely related to an atmospheric wave train propagating eastward from the mid-high latitudes of the North Atlantic to Eurasia. The atmospheric wave train over the North Atlantic–Eurasia region is suggested to be mainly related to the Atlantic–Eurasia teleconnection pattern. Further analysis indicates that a decrease in the local soil moisture over Europe may also have escalated the surface temperature warming through a positive land–atmosphere feedback. [ABSTRACT FROM AUTHOR]

Climate change can influence infectious disease dynamics both directly, by affecting the disease ecology, and indirectly, through altering economic systems. However, despite that climate-driven human plague dynamics have been extensively studied in recent years, little is known about the relative importance of the direct and indirect effects of climate change on plague outbreak. By using Structural Equation Modeling, we estimated the direct influence of climate change on human plague dynamics and the impact of climate-driven economic change on human plague outbreak. After studying human plague outbreak in Europe during AD1347–1760, we detected no direct climatic effect on plague dynamics; instead, all of the climatic impacts on plague dynamics were indirect, and were operationalized via economic changes. Through a series of sensitivity checks, we further proved that temperature-induced economic changes drove plague dynamics during cold and wet periods, while precipitation-induced economic changes drove plague dynamics during the cold periods. Our results suggest that we should not dismiss the role of economic systems when examining how climate change altered plague dynamics in human history. [ABSTRACT FROM AUTHOR]

IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society's ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem-solving in the water sector. The work and discussions carried out during the project nurtured further reflections toward a common vision for hydrological prediction. In this article, we summarized the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we first presented a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learned from IMPREX were discussed. The key findings were the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Last, a vision for how to improve these forecast systems/products in the future was expounded, including advancing numerical weather and hydrological models, improved earth monitoring and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skillful, thus leading to socioeconomic benefits for the citizens of Europe and beyond. [ABSTRACT FROM AUTHOR]

A twentieth century-long coupled atmosphere-ocean regional climate simulation with COSMO-CLM (Consortium for Small-Scale Modeling, Climate Limited-area Model) and NEMO (Nucleus for European Modelling of the Ocean) is studied here to evaluate the added value of coupled marginal seas over continental regions. The interactive coupling of the marginal seas, namely the Mediterranean, the North and the Baltic Seas, to the atmosphere in the European region gives a comprehensive modelling system. It is expected to be able to describe the climatological features of this geographically complex area even more precisely than an atmosphere-only climate model. The investigated variables are precipitation and 2 m temperature. Sensitivity studies are used to assess the impact of SST (sea surface temperature) changes over land areas. The different SST values affect the continental precipitation more than the 2 m temperature. The simulated variables are compared to the CRU (Climatic Research Unit) observational data, and also to the HOAPS/GPCC (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data, Global Precipitation Climatology Centre) data. In the coupled simulation, added skill is found primarily during winter over the eastern part of Europe. Our analysis shows that, over this region, the coupled system is dryer than the uncoupled system, both in terms of precipitation and soil moisture, which means a decrease in the bias of the system. Thus, the coupling improves the simulation of precipitation over the eastern part of Europe, due to cooler SST values and in consequence, drier soil. [ABSTRACT FROM AUTHOR]

In this study, AERONET (Aerosol Robotic Network) and EARLINET (European Aerosol Research Lidar Network) data from 17 collocated lidar and sun photometer stations were used to characterize the optical properties of aerosol and their types for the 2008–2018 period in various regions of Europe. The analysis was done on six cluster domains defined using circulation types around each station and their common circulation features. As concluded from the lidar photometer measurements, the typical aerosol particles observed during 2008–2018 over Europe were medium-sized, medium absorbing particles with low spectral dependence. The highest mean values for the lidar ratio at 532 nm were recorded over Northeastern Europe and were associated with Smoke particles, while the lowest mean values for the Angstrom exponent were identified over the Southwest cluster and were associated with Dust and Marine particles. Smoke (37%) and Continental (25%) aerosol types were the predominant aerosol types in Europe, followed by Continental Polluted (17%), Dust (10%), and Marine/Cloud (10%) types. The seasonal variability was insignificant at the continental scale, showing a small increase in the percentage of Smoke during spring and a small increase of Dust during autumn. The aerosol optical depth (AOD) slightly decreased with time, while the Angstrom exponent oscillated between "hot and smoky" years (2011–2015) on the one hand and "dusty" years (2008–2010) and "wet" years (2017–2018) on the other hand. The high variability from year to year showed that aerosol transport in the troposphere became more and more important in the overall balance of the columnar aerosol load. [ABSTRACT FROM AUTHOR]

Intensification of extreme temperatures combined with other socioeconomic factors may exacerbate human thermal risk. The disastrous impacts of extreme weather during the last two decades demonstrated the increased vulnerability of populations even in developed countries from Europe, which are expected to efficiently manage adverse weather. The study aims to assess trends in the exposure of European populations to extreme weather using updated historical climatic data in large European cities of different local climates and a set of climatic and bioclimatic indices. Colder cities experience higher warming rates in winter (exceeding 1 °C/decade since the mid-1970s) and warmer cities in summer. Hot extremes have almost tripled in most cities during the last two or three decades with simultaneous advancing of hot weather, while northernmost cities have experienced an unprecedented increase in the heat waves frequency only during the last decade. Bioclimatic indices suggested a robust tendency towards less cold-related stress (mainly in cold cities) and more heat-related stress in all cities. A doubling or tripling in the frequency of heat-related 'great discomfort' was found in southern cities, while in the cities of northern Europe, heat-related 'discomfort' conditions are becoming increasingly more frequent and have nearly quadrupled during the last decade. [ABSTRACT FROM AUTHOR]

Within the CO2 time series measured at the Environmental Research Station Schneefernerhaus (UFS), Germany, as part of the Global Atmospheric Watch (GAW) program, pollution episodes are traced back to local and regional emissions, identified by δ13C(CO2) as well as ratios of CO and CH4 to CO2 mixing ratios. Seven episodes of sudden enhancements in the tropospheric CO2 mixing ratio are identified in the measurements of mixing/isotopic ratios during five winter months from October 2012 to February 2013. The short-term CO2 variations are closely correlated with changes in CO and CH4 mixing ratios, achieving mean values of 6.0 ± 0.2 ppb/ppm for CO/CO2 and 6.0 ± 0.1 ppb/ppm for CH4/CO2. The estimated isotopic signature of CO2 sources (δs) ranges between −35‰ and −24‰, with higher values indicating contributions from coal combustion or wood burning, and lower values being the result of natural gas or gasoline. Moving Keeling plots with site-specific data selection criteria are applied to detect these pollution events. Furthermore, the HYSPLIT trajectory model is utilized to identify the trajectories during periods with CO2 peak events. Short trajectories are found covering Western and Central Europe, while clean air masses flow from the Atlantic Ocean and the Arctic Ocean. [ABSTRACT FROM AUTHOR]

The Operational Program on the Exchange of Weather Radar Information (OPERA) has co-ordinated radar co-operation among national weather services in Europe for more than 20 years. It has introduced its own, manufacturer-independent data model, runs its own data center, and produces Pan-European radar composites. The applications using this data vary from data assimilation to flood warnings and the monitoring of animal migration. It has used several approaches to provide a homogeneous combination of disparate raw data and to indicate the reliability of its products. In particular, if a pixel shows no precipitation, it is important to know if that pixel is dry or if the measurement was missing. [ABSTRACT FROM AUTHOR]

We analyse and quantify the recurrences of European temperature extremes using 32 historical simulations (1900–1999) of the fifth Coupled Model Intercomparison Project (CMIP5) and 8 historical simulations (1971–2005) from the EUROCORDEX experiment. We compare the former simulations to the 20th Century Reanalysis (20CRv2c) dataset to compute recurrence spectra of temperature in Europe. We find that, (1) the spectra obtained by the model ensemble mean are generally consistent with those of 20CR; (2) spectra biases have a strong regional dependence; (3) the resolution does not change the order of magnitude of spectral biases between models and reanalysis, (4) the spread in recurrence biases is larger for cold extremes. Our analysis of biases provides a new way of selecting a subset of the CMIP5 ensemble to obtain an optimal estimate of temperature recurrences for a range of time-scales. [ABSTRACT FROM AUTHOR]

Confounding factors like urbanization and land-use change could introduce uncertainty to the estimation of global temperature trends related to climate change. In this work, we introduce a new way to investigate the nexus between temporal trends of temperature and urbanization data at the global scale in the period from 1992 to 2013. We analyze air temperature data recorded from more than 5000 weather stations worldwide and nightlight satellite measurements as a proxy for urbanization. By means of a range of statistical methods, our results quantify and outline that the temporal evolution of urbanization affects temperature trends at multiple spatial scales with significant differences at regional and continental scales. A statistically significant agreement in temperature and nightlight trends is detected, especially in low and middle-income regions, where urbanization is rapidly growing. Conversely, in continents such as Europe and North America, increases in temperature trends are typically detected along with non-significant nightlight trends. [ABSTRACT FROM AUTHOR]