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Common ragweed (Ambrosia artemisiifolia L.) is a highly allergenic and invasive plant in Europe. Its pollen can be transported over large distances and has been recognized as a significant cause of hayfever and asthma (D'Amato et al., 2007; Burbach et al., 2009). To simulate production and dispersion of common ragweed pollen, we implement a pollen emission and transport module in the Regional Climate Model (RegCM) version 4 using the framework of the Community Land Model (CLM) version 4.5. In the online model environment where climate is integrated with dispersion and vegetation production, pollen emissions are calculated based on the modelling of plant distribution, pollen production, species-specific phenology, flowering probability, and flux response to meteorological conditions. A pollen tracer model is used to describe pollen advective transport, turbulent mixing, dry and wet deposition. The model is then applied and evaluated on a European domain for the period 2000-2010. To reduce the large uncertainties notably due to ragweed density distribution on pollen emission, a calibration based on airborne pollen observations is used. Resulting simulations show that the model captures the gross features of the pollen concentrations found in Europe, and reproduce reasonably both the spatial and temporal patterns of flowering season and associated pollen concentrations measured over Europe. The model can explain 68.6, 39.2, and 34.3 % of the observed variance in starting, central, and ending dates of the pollen season with associated root mean square error (RMSE) equal to 4.7, 3.9, and 7.0 days, respectively. The correlation between simulated and observed daily concentrations time series reaches 0.69. Statistical scores show that the model performs better over the central Europe source region where pollen loads are larger. From these simulations health risks associated common ragweed pollen spread are then evaluated through calculation of exposure time above health-relevant threshold levels. The total risk area with concentration above 5 grains m-3 takes up 29.5 % of domain. The longest exposure time occurs on Pannonian Plain, where the number of days per year with the daily concentration above 20 grains m-3 exceeds 30. [ABSTRACT FROM AUTHOR]

Complex dynamic models of carbon and nitrogen are often used to investigate the consequences of climate change on agricultural production and greenhouse gas emissions from agriculture. These models require high temporal resolution input data regarding the timing of field operations. This paper describes the Timelines model, which predicts the timelines of key field operations across Europe. The evaluation of the model suggests that it is broadly capable of simulating the timing of field operations for a range of arable crops at different locations. Systematic variations in the date of harvesting and in the timing of the first application of N fertiliser to winter crops need to be corrected and the prediction of soil workability and traffcability might enable the prediction of ploughing and applications of solid manure in preparation for spring crops. The data concerning the thermal time thresholds for sowing and harvesting underlying the model should be updated and extended to a wider range of crops. [ABSTRACT FROM AUTHOR]

The impact of climate and emissions changes on the deposition of reactive nitrogen (Nr) over Europe was studied using four offline regional chemistry transport models (CTMs) driven by the same global projection of future climate over the period 2000- 2050. Anthropogenic emissions for the years 2005 and 2050 were used for simulations of both present and future periods in order to isolate the impact of climate change, hemispheric boundary conditions and emissions, and to assess the robustness of the result across the different models. The results from these four CTMs clearly show that the main driver of future N deposition changes is the specified emission change. Under the specified emission scenario for 2050, emissions of oxidised nitrogen were reduced substantially, whereas emissions of NH3 increase to some extent, and these changes are largely reflected in the modelled concentrations and depositions. The lack of sulphur and oxidised nitrogen in the future atmosphere results in a much larger fraction of NHx being present in the form of gaseous ammonia. Predictions for wet and total deposition were broadly consistent, although the three fine-scale models resolve European emission areas and changes better than the hemispheric-scale model. The biggest difference in the models is for predictions of individual N-compounds. One model (EMEP) was used to explore changes in critical 20 loads, also in conjunction with speculative climate-induced increases in NH3 emissions. These calculations suggest that the area of ecosystems which exceed critical loads is reduced from 64% for year 2005 emissions levels to 50% for currently estimated 2050 levels. A possible climate-induced increase in NH3 emissions could worsen the situation, with areas exceeded increasing again to 57%(for a 30%NH3 emission increase). [ABSTRACT FROM AUTHOR]

The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m² m-2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0-54.2%), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0-20.1 and ~9.4-22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6-86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model. [ABSTRACT FROM AUTHOR]

A large shortcoming of current chemistry transport models for simulating the fate of ammonia in the atmosphere is the lack of a description of the bi-directional surfaceatmosphere exchange. In this paper, results of an update of the dry deposition module DEPAC in the LOTOS-EUROS model are discussed. It is shown that with the new description, which includes bi-directional surface-atmosphere exchange, the modeled ammonia concentrations increase almost everywhere, in particular in agricultural source areas. The reason is that by using a compensation point the ammonia life time and transport distance is increased. As a consequence, deposition of ammonia and ammonium decreases in agricultural source areas, while it increases in large nature areas and remote regions especially in Southern Scandinavia. The inclusion of a compensation point for water reduces the dry deposition over sea and allows reproducing the observed marine background concentrations at coastal locations to a better extend. A comparison with measurements shows that the model results better represent the measured ammonia concentrations. The concentrations in nature areas are slightly overestimated, while the concentrations in agricultural source areas are still underestimated. Although the introduction of the compensation point improves the model performance, the modeling of ammonia remains challenging. Important aspects are emission patterns in space and time as well as a proper approach to deal with the high concentration gradients in relation to model resolution. In short, the inclusion of a bi-directional surface atmosphere exchange is a significant step forward for modeling ammonia. [ABSTRACT FROM AUTHOR]

Climate change and land management practices are projected to significantly affect soil organic carbon (SOC) dynamics and dissolved organic carbon (DOC) leaching from soils. In this modelling study, we adopted the Century model to simulate past (1906-2012), present, and future (2013-2100) SOC and DOC levels for sandy and loamy soils typical for Northwestern European conditions under three land use types (forest, grassland and arable land) and several future scenarios addressing climate change and land management change. To our knowledge, this is the first time that the Century model has been applied to assess the effects of climate change and land management on DOC concentrations and leaching rates, which, in combination with SOC, play a major role in metal transport through soil. The simulated current SOC levels were generally in line with the observed values for the different kinds of soil and land use types. The climate change scenarios result in a decrease in both SOC and DOC for the agricultural systems, whereas for the forest systems, SOC is projected to slightly increase and DOC to decrease. An analysis of the sole effects of changes in temperature and changes in precipitation showed that, for SOC, the temperature effect predominates over the precipitation effect, whereas for DOC, the precipitation effect is more prominent. A reduction in the application rates of fertilizers under the land management scenario leads to a decrease in the SOC stocks and the DOC leaching rates for the arable land systems, but has a negligible effect on SOC and DOC levels for the grassland systems. Our study demonstrated the ability of the Century model to simulate climate change and agricultural management effects on SOC dynamics and DOC leaching, providing a robust tool for the assessment of carbon sequestration and the implications for contaminant transport in soils. [ABSTRACT FROM AUTHOR]

The article discusses a study conducted to update ECOCLIMAP-I in Europe. It is evident that ECOCLIMAP-I is a database designed to cater needs of meteorological community to examine natural and managed ecosystems in association with weather forecasting and climate change modelling. It discusses methods, datasets and characteristics of producing ECOCLIMAPII/Europe.

Currently, up to 30% of global carbon emission is estimated to originate from land use and land changes. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modeling techniques and the integration of land conversion types allow us to create accurate, high resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km² (15.5 %) of land cover in Europe changes over the period 1950 to 2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19 %). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socioeconomic transitions were studied. The analysis indicate that the main drivers of land change over the studied period were urbanization, the reforestation program after the timber shortage since the Second World War, the fall of the Iron Curtain, Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method takes stock of the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristic allow the data to be used to support and improve ongoing GHG inventories and climate research. [ABSTRACT FROM AUTHOR]

Fire weather indices predict fire extent from meteorological conditions assuming a monotonic function; this approach is frequently used to predict future fire patterns under climate change scenarios using linear extrapolation. However, the relationship between weather and fire extent may potentially depend on the existence of fuel humidity thresholds above which this relationship changes dramatically, challenging this statistical approach. Here we combine the continuous and the threshold approaches to analyze satellite-detected fires in Europe during 2001-2010 in relation to meteorological conditions, showing that fire size response to increasing dryness follows a ramp function, i.e. with two plateaus separated by a phase of monotonic increase. This study confirms that at a continental and a high-resolution temporal scales, large fires are very unlikely to occur under moist conditions, but it also reveals that fire size stops to be controlled by fuel humidity above a given threshold of dryness. Thus, fuel humidity control only applies when fire is not limited by other factors such as fuel load, as large fires are virtually absent in dry regions with less than 500mm of average annual rainfall, i.e. where fuel amount is insufficient. In regions with sufficient fuel, other factors such as fire suppression or fuel discontinuity can impede large fires even under very dry weather conditions. These findings are relevant under current climatic trends in which the fire season length, in terms of number of days with DC (drought code) values above the observed thresholds (break points), is increasing in many parts of the Mediterranean, while it is decreasing in Eastern Europe and remains unchanged in Central Europe. [ABSTRACT FROM AUTHOR]

Climate change and air pollution, interact with altering forest management and landuse change to produce short and long-term changes to forest in Europe. The impact of these changes on the forest greenhouse gas (GHG) balance is currently difficult to predict. To improve the mechanistic understanding of the ongoing changes, we studied the response of GHG (N2O, CH4) exchange from forest soils at twelve experimental or natural gradient forest sites, representing anticipated future forest change. The experimental manipulations one or more per site included nitrogen (N) addition (4 sites), changes of climate (temperature, 1 site; precipitation, 2 sites), soil hydrology (3 sites), harvest intensity (1 site), wood ash fertilization (1 site), pH gradient in peat (1 site) and afforestation of cropland (1 site). In most of the investigated treatments N2O emissions increased by 7±3 (range 0-30) µg N2O-N m-2 h-1 across all treatments on mineral soils, but by up to 10 times the mineral soil maximum on an acidic organic soil. Soil moisture together with mineral soil C/N ratio and pH were found to significantly influence N2O emissions across all treatments. Emissions increased with N availability and decreased with soil C/N ratio, especially in interaction with increased soil moisture. High pH reduced the formation of N2O, even under otherwise favourable soil conditions. Oxidation (uptake) of CH4 was reduced from 16±2 to 4±6 µg CH4-C m-2 h-1 by the investigated treatments. The CH4 exchange was significantly influenced by soil moisture and soil C/N ratio across all treatments, and CH4 emissions occurred only in wet or water-saturated conditions. For most of the investigated forest manipulations or natural gradients, the response of both N2O and CH4 fluxes was towards reducing the overall GHG forest sink. The most resilient forests were dry Mediterranean forests, as well as forests with high soil C/N ratio or high soil pH. Mitigation strategies may focus on (I) sustainable management of wet forest areas and forested peat lands, (ii) continuous forest cover management, (iii) reducing atmospheric N input and, thus, N availability, and (iv) improving neutralisation capacity of acid soils (e.g. wood ash application). [ABSTRACT FROM AUTHOR]

The article focuses on potential feedback mechanism regarding land use and climate change. It states that potential regional feedbacks were explored in four hot-spots including the Amazon Basin, sub-Saharan Africa (SSA), and Europe. It mentions that in Amazon, drought events can lead to further reduction of rainfall when the recycling processes of water are affected.

Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems. [ABSTRACT FROM AUTHOR]

Potential mobilization and transport of Dissolved Organic Carbon (DOC) in subarctic river basins towards the oceans is enormous, because 23-48% of the worlds Soil Organic Carbon (SOC) is stored in northern regions. As climate changes, the amount and composition of DOC exported from these basins are expected to change. The transfer of organic carbon between soils and rivers results in fractionation of organic carbon compounds. The aim of this research is to determine the DOC concentrations, its fractions, i.e. humic (HA), fulvic (FA), and hydrophilic (HY) acids, and soil characteristics that influence the DOC sorptive properties of different soil types within a tundra and taiga catchment of Northern European Russia. DOC in taiga and tundra soil profiles (soil solution) consisted only of HY and FA, where HY became more abundant with increasing depth. Adsorption of DOC on mineral phases is the key geochemical process for release and removal of DOC from potentially soluble carbon pool. We found that adsorbed organic carbon may desorb easily and can release DOC quickly, without being dependent on mineralization and degradation. Although Extractable Organic Carbon (EOC) comprise only a small part of SOC, it is a significant buffering pool for DOC. We found that about 80-90% of released EOC was previously adsorbed. Fractionation of EOC is also influenced by the fact that predominantly HA and FA adsorbed to soil and therefore also are the main compounds released when desorbed. Flowpaths vary between taiga and tundra and through seasons, which likely affects DOC concentration found in streams. As climate changes, also flowpaths of water through soils may change, especially in tundra caused by thawing soils. Therefore, adsorptive properties of thawing soils exert a major control on DOC leaching to rivers. To better understand the process of DOC ad- and de-sorption in soils, process based soil chemical modelling, which could bring more insight in solution speciation, mineral solubility, and adsorption reactions, is appropriate. [ABSTRACT FROM AUTHOR]

Drought and heat events are becoming more frequent in Europe due to human-induced climate change, affecting many aspects of human well-being and ecosystem functioning. However, the intensity of these drought and heat events is not spatially and temporally uniform. Understanding the spatial variability of drought impacts is important information for decision makers, supporting both planning and preparations to cope with the changing climatic conditions. Currently, data relating to the damage caused by extended drought episodes is scattered across languages and sources such as scientific publications, governmental reports and the media. In this review paper, we compiled data of damages caused by the drought and heat of 2018 until 2022 in forest ecosystems and relate it to large European data sets, providing support for decision making both on the regional and European levels. We partitioned data from 16 European countries to the following regions: Northern, Central, Alpine, and South. We focused on drought and heat damage to forests, and categorized them as (1) physiological (2) pest, and (3) fire damage. We were able to identify the following key trends: (1) Relative defoliation rates of broadleaves is higher than of conifers in every country with the exception of Czech Republic (2) the incidence of wood destroyed by insects is extremely high in Central Europe and Sweden (3) Although forest fires can be related to heat and drought, they are superimposed by other anthropogenic influences (4) In this period (2018–2022), forests in central Europe are particularly affected, while forests in the Northern and Alpine zones are less affected, and adaptations to heat and drought can still be observed in the Southern zone. (5) Although in several regions 2021 was an average year still high levels of damages were observed indicating strong legacy effects of 2018–2020. We note that the inventory should be continuously updated as new data appear. [ABSTRACT FROM AUTHOR]

In recent years, instrumental observations have become increasingly important in climate research, allowing past daily-to-decadal climate variability and weather extremes to be explored in greater detail. The 18th century saw the formation of several short-lived meteorological networks of which the one organised by the Societas Meteorologica Palatina is arguably the most well known. This network stood out as one of the few that efficiently managed to control its members, integrating, refining, and publishing measurements taken from numerous stations around Europe and beyond. Although much has been written about the network in both history, science, and individual prominent series used for climatological studies, the actual measurements have not yet been digitised and published in extenso. This paper represents an important step towards filling this perceived gap in research. Here, we provide an inventory listing the availability of observed variables for the 37 stations that belonged to the society's network and discuss their historical context. Most of these observations have been digitised, and a considerable fraction has been converted and formatted. In this paper, we focus on the temperature and pressure measurements, which have been corrected and homogenised. We then demonstrate their potential for climate research by analysing two cases of extreme weather. The recovered series will have wide applications and could contribute to a better understanding of the mechanisms behind climatic variations and extremes as well as the societal reactions to adverse weather. Even the shorter series could be ingested into reanalyses and improve the quality of large-scale reconstructions. [ABSTRACT FROM AUTHOR]

European cities are currently facing one of the main evolutions of the last fifty years. 'Cities for the citizens' is the new leitmotiv of modern societies, and citizens are demanding, among others, a greener environment including non-polluted air. Improved sensors and improved communication systems open the door to the design of new systems based on citizen science to better monitor the air quality. In this paper, we present a system that relies on the already available Copernicus Environment Service, on Air Quality Monitoring reference stations and on a cluster of new low-cost, low-energy sensor nodes that will improve the resolution of air quality maps. The data collected by this system will be stored in a time series database, and it will be available both to city council managers for decision making and to citizens for informative purposes. In this paper, we present the main challenges imposed by Air Quality Monitoring systems, our proposal to overcome those challenges, and the results of our preliminary tests. [ABSTRACT FROM AUTHOR]

This paper investigates the influence of multi-decadal climatic variability on the temporal evolution of root zone storage capacities (Sr,max) and its implications for streamflow predictions at the catchment scale. Through a comprehensive analysis of 286 catchments across Europe and the US, we analyse the deviations in evaporative ratios (IE) from expected values based on catchment aridity (IA) and their subsequent impact on Sr,max predictions. Our findings reveal that while catchments do not strictly adhere to their specific parametric Budyko curves over time, the deviations in IE are generally very minor, with an average ΔIE = 0.01 and an interquartile range IQR= -0.01 to 0.03. Consequently, these minor deviations lead to limited changes in predictions of Sr,max, mostly ranging between -10.5 and +21.5 mm (-5.1 % to +9.9 %). When these uncertainties in Sr,max are incorporated into hydrological models, the impact on streamflow predictions is found to be marginal, with the most significant shifts in monthly evaporation and streamflow not exceeding 4 % and 12 %, respectively. Our study underscores the utility of parametric Budyko-style equations for first order estimates of future Sr,max in hydrological models, even in the face of climate change and variability. This research contributes to a more nuanced understanding of hydrological responses to changing climatic conditions and offers valuable insights for future climate impact studies in hydrology. [ABSTRACT FROM AUTHOR]

Adopting soil and crop management practices that conserve or enhance 1 soil structure is critical for supporting the sustainable adaptation of agriculture to climate change, as it should help maintain agricultural production in the face of increasing drought or water excess without impairing environmental quality. In this paper, we evaluate the evidence for this assertion by synthesizing the results of 34 published meta-analyses of the effects of such practices on soil physical and hydraulic properties relevant for climate change adaptation in European agriculture. We also review an additional 127 meta-analyses that investigated synergies and trade-offs or help to explain the effects of soil and crop management in terms of the underlying processes and mechanisms. Finally, we identify how responses to alternative soil-crop management systems vary under contrasting agro9 environmental conditions across Europe. This information may help practitioners and policymakers to draw context-specific conclusions concerning the efficacy of management practices as climate adaptation tools. Our synthesis demonstrates that organic soil amendments and the adoption of practices that maintain "continuous living cover" result in significant benefits for the water regulation function of soils, mostly arising from the additional carbon inputs to soil and the stimulation of biological processes. These effects are clearly related to improved soil aggregation and enhanced bio-porosity, both of which reduce surface runoff and increase infiltration. One potentially negative consequence of these systems is a reduction in soil water storage and groundwater recharge, which may be problematic in dry climates. Some important synergies are reductions in nitrate leaching to groundwater and greenhouse gas emissions for non-leguminous cover crop systems. The benefits of reducing tillage intensity appear much less clear-cut. Increases in soil bulk density due to traffic compaction are commonly reported. However, biological activity is enhanced under reduced tillage intensity, which should improve soil structure, infiltration capacity, and reduce surface runoff and the losses of agro chemicals to surface water. However, the evidence for these beneficial effects is inconclusive, while significant trade-offs include yield penalties and increases in greenhouse gas emissions and the risks of leaching of pesticides and nitrate. [ABSTRACT FROM AUTHOR]

Large multiscenario multimodel ensembles (MMEs) of regional climate model (RCM) experiments driven by global climate models (GCMs) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse scenario–GCM–RCM matrices, these large ensembles, however, are very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest MME based on regional climate models ever produced in Europe. This analysis provides a detailed description of this MME, including (i) balanced estimates of mean changes for near-surface temperature and precipitation in Europe, (ii) the total uncertainty of projections and its partition as a function of time, and (iii) the list of the most important contributors to the model uncertainty. For changes in total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071–2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in central–eastern Europe for instance, the difference between balanced and direct estimates is up to 0.8 ∘ C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century. [ABSTRACT FROM AUTHOR]

Our ability to predict future climate change relies on our understanding of current and future CO2 fluxes, particularly on a regional scale (100-1000 km). CO2 regional sources and sinks are still poorly understood. Inverse transport modeling, a method often used to quantify these fluxes, relies on atmospheric CO2 measurements. One of the main challenges for the transport models used in the inversions is to properly reproduce CO2 vertical gradients between the boundary layer and the free troposphere, as these gradients impact on the partitioning of the calculated fluxes between the different model regions. Vertical CO2 profiles are very well suited to assess the performances of the models. In this paper, we conduct a comparison between observed and modeled CO 2 profiles recorded during two CAATER campaigns that occurred in May 2001 and October 2002 over Western Europe, as described in a companion paper. We test different combinations between a global transport model (LMDZt), a mesoscale transport model (CHIMERE), and different sets of biospheric fluxes, all chosen with a diurnal cycle (CASA, SiB2 and ORCHIDEE). The vertical profile comparison shows that: 1) in most cases the influence of the biospheric flux is small but sometimes not negligible, ORCHIDEE giving the best results in the present study; 2) LMDZt is most of the time too diffuse, as it simulates a too high boundary layer height; 3) CHIMERE better reproduces the observed gradients between the boundary layer and the free troposphere, but is sometimes too variable and gives rise to incoherent structures. We conclude there is a need for more vertical profiles to conduct further studies to improve the parameterization of vertical transport in the models used for CO 2 flux inversions. Furthermore, we use a modeling method to quantify CO 2 fluxes at the regional scale from a chosen observing point, coupling influence functions from the transport model LMDZt (that works quite well at the synoptic scale) with information on the space-time distribution of fluxes. This modeling method is compared to a dual tracer method (the so-called Radon method) for a case study on 25 May 2001 during which simultaneous well-correlated in situ CO2 and Radon 222 measurements have been collected. Both methods give a similar result: a flux within the Radon 222 method uncertainty (35%), that is an atmospheric CO2 sink of -4.2 -2 -1 to -4.4 gCm-1 day-1 . We have estimated the uncertainty of the modeling method to be at least 33% on average, and even more for specific individual events. This method allows the determination of the area that contributed to the CO 2 observed concentration. In our case, the observation point located at 1700ma.s.l. in the north of France, is influenced by an area of 1500x700 km² that covers the Benelux region, part of Germany and western Poland. Furthermore, this method allows deconvolution between the different contributing fluxes. In this case study, the biospheric sink contributes 73% of the total flux, fossil fuel emissions for 27%, the oceanic flux being negligible. However, the uncertainties of the influence function method need to be better assessed. This could be possible by applying it to other cases where the calculated fluxes can be checked independently, for example at tall towers where simultaneous CO2 and Radon 222 measurements can be conducted. The use of optimized fluxes (from atmospheric inversions) and of mesoscale models for atmospheric transport may also significantly reduce the uncertainties. [ABSTRACT FROM AUTHOR]

The article discusses the importance of the COST Action 725 from 2004 to 2009 towards the collaboration of the European COoperation in the field of Scientific and Technical Research. The COST725 attained the common system, phenological observations, and utilizing data in scientific peer reviewed papers. It notes the accomplishments of the program including the phenological response to climate and the launching of project in 2010 under European network of meteorological services (EUMETNET/ECSN).

Deep learning techniques (in particular convolutional neural networks, CNNs) have recently emerged as a promising approach for statistical downscaling due to their ability to learn spatial features from huge spatiotemporal datasets. However, existing studies are based on complex models, applied to particular case studies and using simple validation frameworks, which makes a proper assessment of the (possible) added value offered by these techniques difficult. As a result, these models are usually seen as black boxes, generating distrust among the climate community, particularly in climate change applications. In this paper we undertake a comprehensive assessment of deep learning techniques for continental-scale statistical downscaling, building on the VALUE validation framework. In particular, different CNN models of increasing complexity are applied to downscale temperature and precipitation over Europe, comparing them with a few standard benchmark methods from VALUE (linear and generalized linear models) which have been traditionally used for this purpose. Besides analyzing the adequacy of different components and topologies, we also focus on their extrapolation capability, a critical point for their potential application in climate change studies. To do this, we use a warm test period as a surrogate for possible future climate conditions. Our results show that, while the added value of CNNs is mostly limited to the reproduction of extremes for temperature, these techniques do outperform the classic ones in the case of precipitation for most aspects considered. This overall good performance, together with the fact that they can be suitably applied to large regions (e.g., continents) without worrying about the spatial features being considered as predictors, can foster the use of statistical approaches in international initiatives such as Coordinated Regional Climate Downscaling Experiment (CORDEX). [ABSTRACT FROM AUTHOR]

Winter windstorms are among the most significant natural hazards in Europe linked to fatalities and substantial damage. However, projections of windstorm impact in Europe under climate change are highly uncertain. This study combines climate projections from 30 general circulation models participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) with the climate risk assessment model CLIMADA to obtain projections of windstorm-induced damage over Europe in a changing climate. We conduct an uncertainty–sensitivity analysis and find large uncertainties in the projected changes in the damage, with climate model uncertainty being the dominant factor of uncertainty in the projections. We investigate the spatial patterns of the climate change-induced modifications in windstorm damage and find an increase in the damage in northwestern and northern central Europe and a decrease over the rest of Europe, in agreement with an eastward extension of the North Atlantic storm track into Europe. We combine all 30 available climate models in an ensemble-of-opportunity approach and find evidence for an intensification of future climate windstorm damage, in which damage with return periods of 100 years under current climate conditions becomes damage with return periods of 28 years under future SSP585 climate scenarios. Our findings demonstrate the importance of climate model uncertainty for the CMIP6 projections of windstorms in Europe and emphasize the increasing need for risk mitigation due to extreme weather in the future. [ABSTRACT FROM AUTHOR]

Millennial-scale climate variations during the last glacial period, such as Dansgaard–Oeschger (DO) cycles and Heinrich events, have been extensively studied using ice core and marine proxy records. However, there is a limited understanding of the magnitude of these temperature fluctuations in continental regions, and questions remain about the seasonal signal of these climate events. This study presents a 60 000-year-long temperature reconstruction based on branched glycerol dialkyl glycerol tetraethers (brGDGTs) extracted from lake sediments from the Eifel Volcanic Field, Germany. brGDGTs are bacterial membrane-spanning lipids that are known to have a strong relationship with temperature, making them suitable for temperature reconstructions. We test several temperature calibration models on modern samples taken from soils and multiple maar lakes. We find a negative bias in brGDGT-based temperature estimates associated with water depth and anoxic conditions that can be corrected for by accounting for a brGDGT isomer that is only produced in anoxic conditions. The corrected temperature reconstruction correlates with proxy and climate model estimates of temperature spanning the same time period, validating the calibration approach we selected. However, millennial-scale variability is significantly dampened in the brGDGT record, and in contrast to other Northern Hemisphere climate records, during several Heinrich stadials, temperatures actually increase. We demonstrate that these apparent discrepancies can be explained by the unique seasonal response of the brGDGT paleothermometer to temperatures of months above freezing (TMAF). Our data support the view that warm-season temperatures in Europe varied minimally during the last glacial period and that abrupt millennial-scale events were defined by colder, longer winters. Our continuous high-resolution temperature reconstruction provides important information about the magnitude of seasonal climate variability during the last glacial period that can be used to test climate models and inform studies of paleoecological change. [ABSTRACT FROM AUTHOR]

The improvement in resolution of climate models has always been mentioned as one of the most important factors when investigating past climatic conditions, especially in order to evaluate and compare the results against proxy data. Despite this, only a few studies have tried to directly estimate the possible advantages of highly resolved simulations for the study of past climate change. Motivated by such considerations, in this paper we present a set of high-resolution simulations for different time slices of the mid-to-late Holocene performed over Europe using the state-of-the-art regional climate model COSMO-CLM. After proposing and testing a model configuration suitable for paleoclimate applications, the aforementioned midto- late Holocene simulations are compared against a new pollen-based climate reconstruction data set, covering almost all of Europe, with two main objectives: testing the advantages of high-resolution simulations for paleoclimatic applications, and investigating the response of temperature to variations in the seasonal cycle of insolation during the mid-tolate Holocene. With the aim of giving physically plausible interpretations of the mismatches between model and reconstructions, possible uncertainties of the pollen-based reconstructions are taken into consideration. Focusing our analysis on near-surface temperature, we can demonstrate that concrete advantages arise in the use of highly resolved data for the comparison against proxyreconstructions and the investigation of past climate change. Additionally, our results reinforce previous findings showing that summertime temperatures during the mid-to-late Holocene were driven mainly by changes in insolation and that the model is too sensitive to such changes over Southern Europe, resulting in drier and warmer conditions. However, in winter, the model does not correctly reproduce the same amplitude of changes evident in the reconstructions, even if it captures the main pattern of the pollen data set over most of the domain for the time periods under investigation. Through the analysis of variations in atmospheric circulation we suggest that, even though the wintertime discrepancies between the two data sets in some areas are most likely due to high pollen uncertainties, in general the model seems to underestimate the changes in the amplitude of the North Atlantic Oscillation, overestimating the contribution of secondary modes of variability. [ABSTRACT FROM AUTHOR]

This paper presents a novel data set of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. The data set provides a unique and physically consistent data set, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100 × 10-year simulations and 25 × 10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. The changes in four climate indices for temperature targets of 1.5 °C and 2.0 °C global warming are quantified: number of days per year with daily mean near-surface apparent temperature of > 28 °C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-yr return period (RI50yr); and the annual Consecutive Dry Days (CDD). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at a policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 °C. [ABSTRACT FROM AUTHOR]

Wildfires have reached an unprecedented scale in the Northern Hemisphere. The summers of 2022 and 2023 demonstrated the destructive power of wildfires, especially in North America and southern Europe. Global warming leads to changes in fire danger. Specifically, fire seasons are assumed to become more extreme and will extend to more temperate regions in northern latitudes in the future. However, the extent to which the seasonality and severity of fire danger in regions of central Europe will change in the future remains to be investigated. Multiple studies claim that natural variability and model uncertainty hide the trend of increasing fire danger in multi-model climate simulations for future potentially fire-prone areas. Such a trend might be isolated with single-model initial-condition large ensembles (SMILEs), which help scientists to distinguish the forced response from natural variability. So far, the SMILE framework has only been applied for fire danger estimation on a global scale. To date, only a few dynamically downscaled regional SMILEs exist, although they enhance the spatial representation of climatic patterns on a regional or local scale. In this study, we use a regional SMILE of the Canadian Regional Climate Model version 5 Large Ensemble (CRCM5-LE) over a region in central Europe under the RCP8.5 (Representative Concentration Pathway) scenario from 1980 to 2099 to analyze changes in fire danger in an area that is currently not fire prone. We use the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. The study area covers four heterogeneous landscapes, namely the Alps, the Alpine Foreland, the lowlands of the South German Escarpment, and the Eastern Mountain Ranges of the Bavarian Forest. We demonstrate that the CRCM5-LE is a dataset suitable for disentangling climate trends from natural variability in a multi-variate fire danger metric. Our results show the strongest increases in the median (50th) and extreme (90th) quantiles of the FWI in the northern parts (South German Escarpment and Eastern Mountain Ranges) of the study area in the summer months of July and August. There, high fire danger becomes the median condition by the end of the century, and levels of high fire danger occur earlier in the fire season. The southern parts (Alps and Alpine Foreland) are less strongly affected by changes in fire danger than the northern parts. However, these regions reach their time of emergence (TOE) in the early 2040s because of very low current fire danger. In the northern parts, the climate change trend exceeds natural variability only in the late 2040s. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by the end of the century. Our results highlight the potential for severe future fire events in central Europe, which is currently not very fire prone, and demonstrate the need for fire management even in regions with a temperate climate. [ABSTRACT FROM AUTHOR]

Afforestation affects the earth's climate system by changing the biogeochemical and biogeophysical characteristics of the land surface. While the regional effects of afforestation are well understood in the tropics and the high latitudes, its climate impact on the midlatitudes is still the subject of scientific discussions. The general impact of afforestation on the regional climate conditions in Europe during the last decades is investigated in this study. For this purpose, regional climate simulations are performed with different forest cover fractions over Europe. In a first simulation, afforestation in Europe is considered, while this is not the case for a second simulation. We focus on the years 1986–2015, a period in which the forest cover in Europe increased comparatively strongly, accompanied by a strong general warming over the continent. Results show that afforestation has both local and non-local effects on the regional climate system in Europe. Due to an increased transport of turbulent heat (latent + sensible) into the atmosphere, afforestation leads to a significant reduction of the mean local surface temperatures in summer. In northern Europe, mean local surface temperatures were reduced about - 0.3 K with afforestation, in central Europe about - 0.5 K, and in southern Europe about - 0.8 K. During heat periods, this local cooling effect can reach - 1.9 K. In winter, afforestation results in a slight local warming in both northern and southern Europe because of the albedo effect of forests. However, this effect is rather small and the mean temperature changes are not significant. In the downwind direction, locally increased evapotranspiration rates with afforestation increase the general cloud cover, which results in a slight non-local warming in winter in several regions of Europe, particularly during cold spells. Thus, afforestation had a discernible impact on the climate change signal in Europe during the period 1986–2015, which may have mitigated the general warming trend in Europe, especially on the local scale in summer. [ABSTRACT FROM AUTHOR]

The prediction of climate on time scales of years to decades is attracting the interest of both climate researchers and stakeholders. The German Ministry for Education and Research (BMBF) has launched a major research programme on decadal climate prediction called MiKlip (Mittelfristige Klimaprognosen, Decadal Climate Prediction) in order to investigate the prediction potential of global and regional climate models (RCMs). In this paper we describe a regional predictive hindcast ensemble, its validation, and the added value of regional downscaling. Global predictions are obtained from an ensemble of simulations by the MPI-ESM-LR model (baseline 0 runs), which were downscaled for Europe using the COSMO-CLM regional model. Decadal hindcasts were produced for the 5 decades starting in 1961 until 2001. Observations were taken from the E-OBS data set. To identify decadal variability and predictability, we removed the long-term mean, as well as the long-term linear trend from the data. We split the resulting anomaly time series into two parts, the first including lead times of 1-5 years, reflecting the skill which originates mainly from the initialisation, and the second including lead times from 6-10 years, which are more related to the representation of low frequency climate variability and the effects of external forcing. We investigated temperature averages and precipitation sums for the summer and winter half-year. Skill assessment was based on correlation coefficient and reliability. We found that regional downscaling preserves, but mostly does not improve the skill and the reliability of the global predictions for summer half-year temperature anomalies. In contrast, regionalisation improves global decadal predictions of half-year precipitation sums in most parts of Europe. The added value results from an increased predictive skill on grid-point basis together with an improvement of the ensemble spread, i.e. the reliability. [ABSTRACT FROM AUTHOR]

The Earth's climate is driven by surface incident solar radiation (Rs). Direct measurements have shown that Rs has undergone significant decadal variations. However, a large fraction of the global land surface is not covered by these observations. Satellite-derived Rs has a good global coverage but is of low accuracy in its depiction of decadal variability. This paper shows that daily to decadal variations of Rs, from both aerosols and cloud properties, can be accurately estimated using globally available measurements of Sunshine Duration (SunDu). In particular, SunDu shows that since the late 1980's Rs has brightened over Europe due to decreases in aerosols but dimmed over China due to their increases. We found that variation of cloud cover determines Rs at a monthly scale but that aerosols determine the variability of Rs at a decadal time scale, in particular, over Europe and China. Because of its global availability and long-term history, SunDu can provide an accurate and continuous proxy record of Rs, filling in values for the blank areas that are not covered by direct measurements. Compared to its direct measurement, Rs from SunDu appears to be less sensitive to instrument replacement and calibration, and shows that the widely reported sharp increase in Rs during the early 1990s in China was a result of instrument replacement. By merging direct measurements collected by Global Energy Budget Archive with those derived from SunDu, we obtained a good coverage of Rs over the Northern Hemisphere. From this data, the average increase of Rs from 1982 to 2008 is estimated to be 0.87Wm-2 per decade. [ABSTRACT FROM AUTHOR]

Deep learning techniques (in particular convolutional neural networks, CNNs) have recently emerged as a promising approach for statistical downscaling due to their ability to learn spatial features from huge spatio-temporal datasets. However, existing studies are based on complex models, applied to particular case studies and using simple validation frameworks, which makes difficult a proper assessment of the (possible) added value offered by these techniques. As a result, these models are usually seen as black-boxes generating distrust among the climate community, particularly in climate change problems. In this paper we undertake a comprehensive assessment of deep learning techniques for continental-scale statistical downscaling, building on the VALUE validation framework. In particular, different CNN models of increasing complexity are applied for downscaling temperature and precipitation over Europe, comparing them with a few standard benchmark methods from VALUE (linear and generalized linear models) which have been traditionally used for this purpose. Besides analyzing the adequacy of different components and topologies, we also focus on their extrapolation capability, a critical point for their possible application in climate change studies. To do this, we use a warm test period as surrogate of possible future climate conditions. Our results show that, whilst the added value of CNNs is mostly limited to the reproduction of extremes for temperature, these techniques do outperform the classic ones for the case of precipitation for most aspects considered. This overall good performance, together with the fact that they can be suitably applied to large regions (e.g. continents) without worrying about the spatial features being considered as predictors, can foster the use of statistical approaches in international initiatives such as CORDEX. [ABSTRACT FROM AUTHOR]

Due to the growing wish and necessity to simulate the possible effects of climate change on the discharge regime on large rivers such as the Rhine in Europe, there is a need for well performing hydrological models that can be applied in climate change scenario studies. There exists large variety in available models and there is an ongoing debate in research on rainfall-runoff modelling on whether or not physically based distributed models better represent observed discharges than conceptual lumped model approaches do. In addition, it is argued that Land Surface Models (LSMs) carry the potential to accurately estimate hydrological partitioning, because they solve the coupled water and energy balance. In this paper, the hydrological models HBV and VIC were compared for the Rhine basin by testing their performance in simulating discharge. Overall, the semi-distributed conceptual HBV model performed much better than the distributed land surface model VIC (E=0.62, r²=0.65 vs. E=0.31, r²=0.54 at Lobith). It is argued here that even for a well-documented river basin such as the Rhine, more complex modelling does not automatically lead to better results. Moreover, it is concluded that meteorological forcing data has a considerable influence on model performance, irrespectively to the type of model structure and the need for ground-based meteorological measurements is emphasized. [ABSTRACT FROM AUTHOR]

Central Europe, the focus region of this study, is a region in transition, climatically from maritime to continental and politically from formerly more planning-oriented to more market-oriented management regimes, and in terms of climate change from regions of increasing precipitation in the west and north of Europe to regions of decreasing precipitation in central and southern Europe. The Elbe basin, a trans-boundary catchment flowing from the Czech Republic through Germany into the North Sea, was selected to investigate the possible impacts of global change on crop yields and water resources in this region. For technical reasons, the paper has been split into two parts, the first showing the overall model concept, the model set-up for the agricultural sector, and first results linking eco-hydrological and agro-economic tools for the German part of the basin. The second part describes the model setup for simulating water supply and demand linking ecohydrological and water management tools for the entire basin including the Czech part. [ABSTRACT FROM AUTHOR]

Atmospheric circulation indices can be used to explain the variability of runoff on a continental scale. Beside well-known regional anomalies of precipitation and runoff that correlate with phases of the North Atlantic Oscillation (NAO) there are also drifting fields of annual discharge anomalies. Following the trend of the NAO, these fields move along a longitudinal axis from western Europe to the Lena catchment in Siberia and back again. The same pattern is observable in the changing flow regimes. This paper describes the origin and causes of these anomaly fields and explains them as the results of important climate variations in the northern hemisphere. [ABSTRACT FROM AUTHOR]

Central European winters have warmed markedly since the mid-20th century. Yet cold winters are still associated with severe societal impacts on energy systems, infrastructure and public health. It is therefore crucial to anticipate storylines of worst-case cold winter conditions, and to understand whether an extremely cold winter, such as the coldest winter in the historical record of Germany in 1963 (−6.3 °C or −3.4 σ seasonal DJF temperature anomaly relative to 1981–2010), is still possible in a warming climate. Here, we first show based on multiple attribution methods that a winter of similar circulation conditions to 1963 would still lead to an extreme seasonal cold anomaly of about −4.9 to −4.7 °C (best estimates across methods) under present-day climate. This would rank as second-coldest winter in the last 75 years. Second, we conceive storylines of worst-case cold winter conditions based on two independent rare event sampling methods (climate model boosting and empirical importance sampling): winter as cold as 1963 is still physically possible in Central Europe today, albeit very unlikely. While cold winter hazards become less frequent and less intense in a warming climate overall, it remains crucial to anticipate the possibility of an extreme cold winter to avoid potential maladaptation and increased vulnerability. [ABSTRACT FROM AUTHOR]

Climatic changes in southern Europe during the Holocene are characterized by a strong spatial and temporal heterogeneity whose patterns are still poorly understood, notably the presence or not of a Holocene thermal maximum (HTM; 10 000–6000 cal BP). The climatic patterns also differ according to the proxies used (e.g. pollen, chironomid) and the latitude of the record. Here, a multi-proxy approach combining pollen and lipid biomarkers (branched glycerol dialkyl glycerol tetraethers, brGDGTs) is applied to the Canroute sedimentological sequence (Massif Central, France) to reconstruct the climatic variation over the last 15 000 years in southern Europe. This area is poorly documented in terms of vegetation and climate change. To provide reliable climate reconstructions, we have (1) performed a multi-method approach applied to pollen (modern analogue technique, MAT; weighted averaging partial least squares regression, WA-PLS; boosted regression trees, BRT; and random forest, RF) and molecular biomarkers brGDGTs (five calibrations) and (2) investigated the role of modern databases and calibrations in climate reconstructions. Three different databases were tested for pollen data: one global database based on a Eurasian pollen database and two regional databases corresponding to Mediterranean–Temperate Europe and Temperate Europe–Scandinavian databases respectively. Five global calibrations were tested for lipid biomarkers including four for soil and one for peat. Results show that the use of different modern databases highlights the importance of considering environmental and ecological constraints when using transfer functions on pollen sequences. Pollen- and brGDGT-inferred climate trends are consistent, notably for the Late Glacial and the Early and Late Holocene. However, the reconstructions notably differ concerning the presence of a Holocene thermal maximum with the MAT pollen-based method, but no difference is apparent with the BRT pollen method nor brGDGT. The temperature reconstructions estimated from the two independent pollen and lipid proxies are then compared to regional climate signals (chironomids, pollen, molecular biomarkers) to better understand global regional climatic patterns in southern Europe. Altogether, our results from the Canroute sequence and those already available in southern Europe reveal that for the Late Glacial and Early Holocene, the regional climate trends are consistent between sites and proxies, supporting the reliability of their reconstructions despite some discrepancies. During the Holocene, the temperature signal of Canroute does not indicate the clear presence of a pronounced HTM, but rather stable temperatures. [ABSTRACT FROM AUTHOR]

Global climate change is increasingly associated with the increase and/or the intensification of extreme weather such as heat waves, droughts, or heavy precipitation events. However, the characteristics and severity of these changes can vary considerably by region and season. This study focuses on heavy and extreme precipitation events over Europe for the time period 1951–2099. The main objective is to identify regions which show a robust and therefore reliable change in such events with ongoing climate change. The study is based on daily precipitation values from 40 regional climate simulations of the EURO-CORDEX ensemble with a spatial resolution of 12 km (EUR-11). Future changes were investigated using four different metrics, which are sensitive to alterations in the number and intensity of the detected events and consider an accumulated precipitation amount over a selected threshold and two return values for a 10- and a 100-year return period. Differences were detected between the climate scenarios RCP4.5 and RCP8.5, between summer and winter half-year, and between three different methods used to identify and quantify temporal changes from a reference period (1951–1980) to a future climate period (2070–2099). Furthermore, two criteria characterizing the robustness of the changes were used, i.e. a dominant agreement on the sign and a majority of significant changes within the full simulation ensemble. The analysis provided relative and absolute changes of the four metrics being used and the area fractions that exhibited a robust change. With all methods applied, our study clearly confirms a significant increase in heavy and extreme precipitation in northern, central, and eastern Europe and a robust decrease in heavy, but not very extreme events in the southwest of the Euro-CORDEX domain associated with projected future climate change. For large parts of Southern Europe and the Mediterranean, a tendency towards decreasing intensities (down to -11 mm/year for the accumulated threshold exceedance) become visible but without the evidence of robustness. Both, the intensity and the area with robust changes in heavy and extreme events prove to be significantly stronger in the RCP8.5 than in the RCP4.5 scenario. For Central Europe, for example, the accumulated threshold exceedance increases from 15 mm/year to 24 mm/year and the 100-year return value from 21 mm/day to 30 mm/day. The related robust area fractions extend from 31 % to 99 % and from 61 % to 95 %, respectively. The relative changes are substantial, even averaged over larger areas, with values greater than 100 % (50 %) for the severe events and up to 40 % (30 %) for the very extreme events in the RCP8.5 (RCP4.5) scenario. Heavy events increase relatively more in winter (for Central Europe +117 % for the accumulated threshold exceedance in RCP 8.5) than in summer (+81 %). The opposite is true for the extreme events with a weaker increase in winter than in summer (e.g. for Central Europe +26 % for the 100-year return value in winter and +43 % in summer). [ABSTRACT FROM AUTHOR]

Droughts are natural hazards that lead to severe impacts in the agricultural sector. Mountain regions are thought to have abundant water, but have experienced unprecedented drought conditions as climate change is affecting their environments more rapidly than other places. The effect radiates by reducing water availability well beyond the mountains' geographical locations. This study aims to improve the understanding of agriculture's vulnerability to drought in Europe's pre-Alpine region, considering two case studies that have been severely impacted in the past. We applied a mixed-method approach combining the knowledge of regional experts with quantitative data analyses in order to define the region-specific vulnerability based on experts' identified factors. We implemented two aggregation methods by combining the vulnerability factors that could be supported with subregional data. Whereas the equal weighting method combines all factors with the same weight, the expert weighting method combines the factors with varying weight based on the expert's opinion. These two methods resulted in vulnerability maps with the expert weighting showing a higher vulnerability, and partly relocating the medium and lower vulnerabilities to other subregions within the case study regions. In general, the experts confirmed the resulting subregions with higher vulnerability. They also acknowledged the value of mapping vulnerability by adopting different aggregation methods confirming that this can serve as a sensitivity analysis. The identified factors contributing most to the regions' vulnerability point to the potential of adaptation strategies decreasing the agriculture's vulnerability to drought that could enable better preparedness. Apart from region-specific differences, in both study regions the presence of irrigation infrastructure and soil texture are among the most important conditions that could be managed to some extent in order to decrease the regions' vulnerability. Throughout the analyses, the study benefited from the exchange with the experts by getting an in-depth understanding of the regional context with feedback relations between the factors contributing to vulnerability. Qualitative narratives provided during the semi-structured interviews supported a better characterization of local vulnerability conditions and helped to better identify quantitative indicators as proxies to describe the selected vulnerability factors. Thus, we recommend applying this mixed-method approach to close the gap between science and practitioners. [ABSTRACT FROM AUTHOR]

Disentangling the effects of internal variability and anthropogenic forcing on regional climate trends remains a key challenge with far-reaching implications. Due to its largely unpredictable nature on timescales longer than a decade, internal climate variability limits the accuracy of climate model projections, introduces challenges in attributing past climate changes, and complicates climate model evaluation. Here, we highlight recent advances in climate modeling and physical understanding that have led to novel insights about these key issues. In particular, we synthesize new findings from large-ensemble simulations with Earth system models, observational large ensembles, and dynamical adjustment methodologies, with a focus on European climate. [ABSTRACT FROM AUTHOR]

Climate reconstructions give insights into monthly and seasonal climate variability of the past few hundred years. However, for understanding past extreme weather events and for relating them to impacts, for example to periods of extreme floods or to yield losses, reconstructions on a daily time scale are needed. Here, we present a data set of 250 years of daily temperature and precipitation fields for Switzerland from 1763 to 2020, which has been created using early instrumental data. The temperature reconstruction shows even for an early period before 1800 with scarce data availability good results, especially in the Swiss Plateau. For the precipitation reconstruction, skills are considerably lower, which can be related to the few precipitation measurements available and the heterogeneous nature of precipitation. By means of a case study on the wet and cold years from 1769 to 1772, which triggered wide-spread famine across Europe, we show that this dataset allows more detailed analyses than hitherto possible. [ABSTRACT FROM AUTHOR]

Aircrafts emit exhaust gases and soot into the atmosphere, which may increase global cirrus cloudiness and as well change the properties of already existing cirrus. In the first COVID-19 lockdown in Europe, changes in cirrus cloud occurrence and properties were detected with the lidar measurements of CALIPSO, which is supposed to be caused by the reduction in civil aviation accordingly. In the last 10 years before COVID, however, aviation grew strongly in terms of CO2 emissions and flight densities in Europe. In the current study, 10-year lidar measurements of cirrus clouds with CALIPSO are analyzed. The Linear contrails and contrail cirrus induced by global aviation have long been known to contribute to climate change by warming the atmosphere. Besides increasing global cirrus cloudiness, aviation may change the properties of the natural cirrus clouds by soot emissions which leads to increased heterogeneous freezing. In the first COVID-19 lockdown in Europe, changes in cirrus cloud properties and occurrence were detected with the lidar measurements of CALIPSO, which is supposed to be caused by the reduction in civil aviation accordingly. In the last 10 years before COVID, however, aviation grew strongly in terms of CO2 emissions and flight densities in Europe. In this study, 10-year lidar measurements of cirrus clouds with CALIPSO are analyzed to determine the seasonality and long-term trends in cirrus clouds as well as their correlations with the ambient temperatures and air traffic. Cirrus clouds follow a distinct seasonal cycle in their occurrence rate (OR) and particle linear depolarization ratio (PLDR) δ p. Cirrus clouds appear within a broader altitude range in winter than in summer and they are characterized by larger OR and δ p values in winter than in summer. The monthly medians of δ p as well as the deseasonalized time series of them in the 10-year period before COVID show both positive trends which are statistically significant according to the Mann-Kendall (MK) significance test. However, the cirrus occurrence shows a negative trend, which might be connected with the background meteorological conditions. Since the cirrus δ p strongly depends on the ambient temperatures in cirrus, we further remove the contributions induced by temperatures from the cirrus δ p with a simple linear regression model. The derived residuals show significant positive trends with the MK test. To compare the cirrus δ p and the air traffic densities, the deseasonalization of the data have previously been conducted since the seasonal cycles in both are not consistent. The deseasonalized time series of the cirrus δ p and CO2 emissions from aviation both show an increasing trend and their correlation coefficients are r = 0.54 at the confidence level above 99.5 %. Finally, the comparisons between the cirrus δ p and aviation in every season were carried out and revealed a strong correlation in other seasons than in summer. [ABSTRACT FROM AUTHOR]

This study investigates present and future European heat wave magnitudes, represented by the Heat Wave Magnitude Index-daily (HWMId), for regional climate models (RCMs) and the driving global climate models (GCMs) over Europe. A subset of the large EURO-CORDEX ensemble is employed to study sources of uncertainties related to the choice of GCMs, RCMs, and their combinations. We initially compare the evaluation runs of the RCMs driven by ERA-interim reanalysis to E-OBS (observation-based estimates), finding that the RCMs can capture most of the observed spatial and temporal features of HWMId. With their higher resolution compared to GCMs, RCMs can reveal spatial features of HWMId associated with small-scale processes (e.g., orographic effects); moreover, RCMs represent large-scale features of HWMId satisfactorily (e.g., by reproducing the general pattern revealed by E-OBS with high values at western coastal regions and low values at the eastern part). Our results indicate a clear added value of the RCMs compared to the driving GCMs. Forced with the emission scenario RCP8.5, all the GCM and RCM simulations consistently project a rise in HWMId at an exponential rate. However, the climate change signals projected by the GCMs are generally attenuated when downscaled by the RCMs, with the spatial pattern also altered. The uncertainty in a simulated future change of heat wave magnitudes following global warming can be attributed almost equally to the difference in model physics (as represented by different RCMs) and to the driving data associated with different GCMs. Regarding the uncertainty associated with RCM choice, a major factor is the different representation of the orographic effects. No consistent spatial pattern in the ensemble spread associated with different GCMs is observed between the RCMs, suggesting GCM uncertainties are transformed by RCMs in a complex manner due to the nonlinear nature of model dynamics and physics. In summary, our results support the use of dynamical downscaling for deriving regional climate realization regarding heat wave magnitudes. [ABSTRACT FROM AUTHOR]

We present an updated perspective on near-global total ozone trends for the period 1995–2020. We use the GOME-type (Global Ozone Monitoring Experiment) Total Ozone Essential Climate Variable (GTO-ECV) satellite data record which has been extended and generated as part of the European Space Agency's Climate Change Initiative (ESA-CCI) and European Union Copernicus Climate Change Service (EU-C3S) ozone projects. The focus of our work is to examine the regional patterns and seasonal dependency of the ozone trend. In the Southern Hemisphere we found regions that indicate statistically significant positive trends increasing from 0.6 ± 0.5(2σ) % per decade in the subtropics to 1.0 ± 0.9 % per decade in the middle latitudes and 2.8 ± 2.6 % per decade in the latitude band 60–70 ∘ S. In the middle latitudes of the Northern Hemisphere the trend exhibits distinct regional patterns, i.e., latitudinal and longitudinal structures. Significant positive trends (∼ 1.5 ± 1.0 % per decade) over the North Atlantic region, as well as barely significant negative trends (−1.0 ± 1.0 % per decade) over eastern Europe, were found. Moreover, these trends correlate with long-term changes in tropopause pressure. Total ozone trends in the tropics are not statistically significant. Regarding the seasonal dependence of the trends we found only very small variations over the course of the year. However, we identified different behavior depending on latitude. In the latitude band 40–70 ∘ N the positive trend maximizes in boreal winter from December to February. In the middle latitudes of the Southern Hemisphere (35–50 ∘ S) the trend is maximum from March to May. Further south toward the high latitudes (55–70 ∘ S) the trend exhibits a relatively strong seasonal cycle which varies from 2 % per decade in December and January to 3.8 % per decade in June and July. [ABSTRACT FROM AUTHOR]

It is well established that using kilometer scale grid resolution for simulations of weather systems in weather and climate models enhances their realism. This study explores heavy- and extreme-precipitation characteristics over the Nordic region generated by the regional climate model HARMONIE-Climate (HCLIM). Two model setups of HCLIM are used: ERA-Interim-driven HCLIM12 spanning over Europe at 12 km grid spacing with a convection parameterization scheme and HCLIM3 spanning over the Nordic region with 3 km grid spacing and explicitly resolved deep convection. The HCLIM simulations are evaluated against a unique and comprehensive set of gridded and in situ observation datasets for the warm season from April to September regarding their ability to reproduce sub-daily and daily heavy-precipitation statistics across the Nordic region. Both model setups are able to capture the daily heavy-precipitation characteristics in the analyzed region. At the sub-daily scale, HCLIM3 clearly improves the statistics of occurrence of the most intense heavy-precipitation events and the amplitude and timing of the diurnal cycle of these events compared to its forcing of HCLIM12. Extreme value analysis shows that HCLIM3 provides added value in capturing sub-daily return levels compared to HCLIM12, which fails to produce the most extreme events. The results indicate clear benefits of the convection-permitting model in simulating heavy and extreme precipitation in the present-day climate, therefore, offering a motivating way forward to investigate the climate change impacts in the region. [ABSTRACT FROM AUTHOR]

The current intensive use of agricultural land is affecting the land quality and contributes to climate change. Feeding the world's growing population under changing climatic conditions demands a global transition to more sustainable agricultural systems. This requires efficient models and data to monitor land cultivation practices at the field to global scale. This study outlines a spatially distributed version of the field-scale crop model AquaCrop version 6.1 to simulate agricultural biomass production and soil moisture variability over Europe at a relatively fine resolution of 30 arcsec (∼1 km). A highly efficient parallel processing system is implemented to run the model regionally with global meteorological input data from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), soil textural information from the Harmonized World Soil Database version 1.2 (HWSDv1.2), and generic crop information. The setup with a generic crop is chosen as a baseline for a future satellite-based data assimilation system. The relative temporal variability in daily crop biomass production is evaluated with the Copernicus Global Land Service dry matter productivity (CGLS-DMP) data. Surface soil moisture is compared against NASA Soil Moisture Active–Passive surface soil moisture (SMAP-SSM) retrievals, the Copernicus Global Land Service surface soil moisture (CGLS-SSM) product derived from Sentinel-1, and in situ data from the International Soil Moisture Network (ISMN). Over central Europe, the regional AquaCrop model is able to capture the temporal variability in both biomass production and soil moisture, with a spatial mean temporal correlation of 0.8 (CGLS-DMP), 0.74 (SMAP-SSM), and 0.52 (CGLS-SSM). The higher performance when evaluating with SMAP-SSM compared to Sentinel-1 CGLS-SSM is largely due to the lower quality of CGLS-SSM satellite retrievals under growing vegetation. The regional model further captures the short-term and inter-annual variability, with a mean anomaly correlation of 0.46 for daily biomass and mean anomaly correlations of 0.65 (SMAP-SSM) and 0.50 (CGLS-SSM) for soil moisture. It is shown that soil textural characteristics and irrigated areas influence the model performance. Overall, the regional AquaCrop model adequately simulates crop production and soil moisture and provides a suitable setup for subsequent satellite-based data assimilation. [ABSTRACT FROM AUTHOR]

Solar photovoltaics (PV) plays an essential role in decarbonizing the European energy system. However, climate change affects surface solar radiation and will therefore directly influence future PV power generation. We use scenarios from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for a mitigation (SSP1-2.6) and a fossil-fuel-dependent (SSP5-8.5) pathway in order to quantify climate risk for solar PV in Europe as simulated by the Global Solar Energy Estimator (GSEE). We find that PV potential increases by around 5 % in the mitigation scenario, suggesting a positive feedback loop between climate change mitigation and PV potential. While increased clear-sky radiation and reduced cloud cover go hand in hand in SSP1-2.6, the effect of a decrease in clear-sky radiation is outweighed by a decrease in cloud cover in SSP5-8.5, resulting in an increase in all-sky radiation. Moreover, we find that the seasonal cycle of PV generation changes in most places, as generation grows more strongly in winter than in summer (SSP1-2.6) or increases in summer and declines in winter (SSP5-8.5). We further analyze climate change impacts on the spatial variability of PV power generation. Similar to the effects anticipated for wind energy, we report an increase in the spatial correlations of daily PV production with large inter-model agreement yet relatively small amplitude, implying that PV power balancing between different regions in continental Europe will become more difficult in the future. Thus, based on the most recent climate simulations, this research supports the notion that climate change will only marginally impact renewable energy potential, while changes in the spatiotemporal generation structure are to be expected and should be included in power system design. [ABSTRACT FROM AUTHOR]

The 4 per 1000 initiative aims to maintain and increase soil organic carbon (SOC) stocks for soil fertility, food security, and climate change adaptation and mitigation. One way to enhance SOC stocks is to increase carbon (C) inputs to the soil. In this study, we assessed the amount of organic C inputs that are necessary to reach a target of SOC stocks increase by 4 ‰yr-1 on average, for 30 years, at 14 long-term agricultural sites in Europe. We used the Century model to simulate SOC stocks and assessed the required level of additional C inputs to reach the 4 per 1000 target at these sites. Then, we analyzed how this would change under future scenarios of temperature increase. Initial stocks were simulated assuming steady state. We compared modeled C inputs to different treatments of additional C used on the experimental sites (exogenous organic matter addition and one treatment with different crop rotations). The model was calibrated to fit the control plots, i.e. conventional management without additional C inputs from exogenous organic matter or changes in crop rotations, and was able to reproduce the SOC stock dynamics. We found that, on average among the selected experimental sites, annual C inputs will have to increase by 43.15 ± 5.05 %, which is 0.66 ± 0.23 MgCha-1yr-1 (mean ± standard error), with respect to the initial C inputs in the control treatment. The simulated amount of C input required to reach the 4 ‰ SOC increase was lower than or similar to the amount of C input actually used in the majority of the additional C input treatments of the long-term experiments. However, Century might be overestimating the effect of additional C inputs on SOC stocks. At the experimental sites, we found that treatments with additional C inputs were increasing by 0.25 % on average. This means that the C inputs required to reach the 4 per 1000 target might actually be much higher. Furthermore, we estimated that annual C inputs will have to increase even more due to climate warming, that is 54 % more and 120 % more for a 1 and 5 ∘Cpage3982 warming, respectively. We showed that modeled C inputs required to reach the target depended linearly on the initial SOC stocks, raising concern on the feasibility of the 4 per 1000 objective in soils with a higher potential contribution to C sequestration, that is soils with high SOC stocks. Our work highlights the challenge of increasing SOC stocks at a large scale and in a future with a warmer climate. [ABSTRACT FROM AUTHOR]

This study investigates, through regional climate modelling, the surface mass concentration and AOD (aerosol optical depth) evolution of the various (anthropogenic and natural) aerosols over the Euro-Mediterranean region between the end of the 20th century and the mid-21st century. The direct aerosol radiative forcing (DRF) as well as the future Euro-Mediterranean climate sensitivity to aerosols have also been analysed. Different regional climate simulations were carried out with the CNRM-ALADIN63 regional climate model, driven by the global CNRM-ESM2-1 Earth system model (used in CMIP6) and coupled to the TACTIC (Tropospheric Aerosols for ClimaTe In CNRM) interactive aerosol scheme. These simulations follow several future scenarios called shared socioeconomic pathways (SSP 1-1.9, SSP 3-7.0 and SSP 5-8.5), which have been chosen to analyse a wide range of possible future scenarios in terms of aerosol or particle precursor emissions. Between the historical and the future period, results show a total AOD decrease between 30 % and 40 % over Europe for the three scenarios, mainly due to the sulfate AOD decrease (between -85 and -93 %), that is partly offset by the nitrate and ammonium particles AOD increase (between +90 and +120 %). According to these three scenarios, nitrate aerosols become the largest contributor to the total AOD during the future period over Europe, with a contribution between 43.5 % and 47.5 %. It is important to note that one of the precursors of nitrate and ammonium aerosols, nitric acid, has been implemented in the model as a constant climatology over time. Concerning natural aerosols, their contribution to the total AOD increases slightly between the two periods. The different evolution of aerosols therefore impacts their DRF, with a significant sulfate DRF decrease between 2.4 and 2.8 W m -2 and a moderate nitrate and ammonium DRF increase between 1.3 and 1.5 W m -2 , depending on the three scenarios over Europe. These changes, which are similar under the different scenarios, explain about 65 % of the annual shortwave radiation change but also about 6 % (in annual average) of the warming expected over Europe by the middle of the century. This study shows, with SSP 5-8.5, that the extra warming attributable to the anthropogenic aerosol evolution over Central Europe and the Iberian Peninsula during the summer period is due to "aerosol–radiation" as well as "aerosol–cloud" interaction processes. The extra warming of about 0.2 ∘ C over Central Europe is explained by a surface radiation increase of 5.8 W m -2 over this region, due to both a surface aerosol DRF decrease of 4.4 W m -2 associated with a positive effective radiative forcing due to aerosol–radiation interactions (ERFari) of 2.7 W m -2 at the top of the atmosphere (TOA) and a cloud optical depth (COD) decrease of 1.3. In parallel, the simulated extra warming of 0.2 ∘ C observed over the Iberian Peninsula is due to a COD decrease of 1.3, leading to a positive effective radiative forcing due to aerosol–cloud interactions (ERFaci) of 2.6 W m -2 at the TOA but also to an atmospheric dynamics change leading to a cloud cover decrease of about 1.7 % and drier air in the lower layers, which is a signature of the semi-direct forcing. This study thus highlights the necessity of taking into account the evolution of aerosols in future regional climate simulations. [ABSTRACT FROM AUTHOR]

Many climate extremes, including heatwaves and heavy precipitation events, are projected to worsen under climate change, with important impacts for society. Future projections required for adaptation are often based on climate model simulations. Given finite resources, trade-offs must be made concerning model resolution, ensemble size, and level of model complexity. Here we focus on the resolution component. A given resolution can be achieved over a region using either global climate models (GCMs) or at lower cost using regional climate models (RCMs) that dynamically downscale coarser GCMs. Both approaches to increasing resolution may better capture small-scale processes and features (downscaling effect), but increased GCM resolution may also improve the representation of the large-scale atmospheric circulation (upscaling effect). The size of this upscaling effect is therefore important for deciding modelling strategies. Here we evaluate the benefits of increased model resolution for both global and regional climate models for simulating temperature, precipitation, and wind extremes over Europe at resolutions that could currently be realistically used for coordinated sets of climate projections at the pan-European scale. First we examine the benefits of regional downscaling by comparing EURO-CORDEX simulations at 12.5 and 50 km resolution to their coarser CMIP5 driving simulations. Secondly, we compare global-scale HadGEM3-A simulations at three resolutions (130, 60, and 25 km). Finally, we separate out resolution-dependent differences for HadGEM3-A into downscaling and upscaling components using a circulation analogue technique. Results suggest limited benefits of increased resolution for heatwaves, except in reducing hot biases over mountainous regions. Precipitation extremes are sensitive to resolution, particularly over complex orography, with larger totals and heavier tails of the distribution at higher resolution, particularly in the CORDEX vs. CMIP5 analysis. CMIP5 models underestimate precipitation extremes, whilst CORDEX simulations overestimate compared to E-OBS, particularly at 12.5 km, but results are sensitive to the observational dataset used, with the MESAN reanalysis giving higher totals and heavier tails than E-OBS. Wind extremes are somewhat stronger and heavier tailed at higher resolution, except in coastal regions where large coastal grid boxes spread strong ocean winds further over land. The circulation analogue analysis suggests that differences with resolution for the HadGEM3-A GCM are primarily due to downscaling effects. [ABSTRACT FROM AUTHOR]

The climate of east-central Europe (ECE) is the result of a combination of influences originating in the wider North Atlantic realm, the Mediterranean Sea, and the western Asian and Siberian regions. Previous studies have shown that the complex interplay between the large-scale atmospheric patterns across the region results in strongly dissimilar summer and winter conditions on timescales ranging from decades to millennia. To put these into a wider context, long-term climate reconstructions are required, but, largely due to historical reasons, these are lacking in ECE. We address these issues by presenting a high-resolution, radiocarbon-dated record of summer temperature variations during the last millennium in ECE, based on stable isotope analysis of a 4.84 m long ice core extracted from Focul Viu Ice Cave (Western Carpathians, Romania). Comparisons with both instrumental and proxy-based data indicate that the stable isotope composition of cave ice records the changes in summer air temperature and has a similar temporal evolution to that of the Atlantic Multidecadal Oscillation on decadal to multidecadal timescales, suggesting that changes in the North Atlantic are transferred, likely via atmospheric processes towards the wider Northern Hemisphere. On centennial timescales, the data show little summer temperature differences between the Medieval Warm Period (MWP) and the Little Ice Age (LIA) in eastern Europe. These findings are contrary to those that show a marked contrast between the two periods in terms of both winter and annual air temperatures, suggesting that cooling during the LIA was primarily the result of wintertime climatic changes. [ABSTRACT FROM AUTHOR]