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Irrigation is a crucial land use practice to adapt agriculture to unsuitable climate and soil conditions. Aiming to improve the growth of plants, irrigation modifies the soil condition, which causes atmospheric effects and feedbacks through land–atmosphere interaction. These effects can be quantified with numerical climate models, as has been done in various studies. It could be shown that irrigation effects, such as air temperature reduction and humidity increase, are well understood and should not be neglected on local and regional scales. However, there is a lack of studies including the role of vegetation in the altered land–atmosphere interaction. With the increasing resolution of numerical climate models, these detailed processes have a chance to be better resolved and studied. This study aims to analyze the effects of irrigation on land–atmosphere interaction, including the effects and feedbacks of vegetation. We developed a new parameterization for irrigation, implemented it into the REgional climate MOdel (REMO2020), and coupled it with the interactive MOsaic-based VEgetation module (iMOVE). Following this new approach of a separate irrigated fraction, the parameterization is suitable as a subgrid parameterization for high-resolution studies and resolves irrigation effects on land, atmosphere, and vegetation. Further, the parameterization is designed with three different water application schemes in order to analyze different parameterization approaches and their influence on the representation of irrigation effects. We apply the irrigation parameterization for southwestern Europe including the Mediterranean region at a 0.11 ∘ horizontal resolution for hot extremes. The simulation results are evaluated in terms of the consistency of physical processes. We found direct effects of irrigation, like a changed surface energy balance with increased latent and decreased sensible heat fluxes, and a surface temperature reduction of more than -4 K as a mean during the growing season. Further, vegetation reacts to irrigation with direct effects, such as reduced water stress, but also with feedbacks, such as a delayed growing season caused by the reduction of the near-surface temperature. Furthermore, the results were compared to observational data, showing a significant bias reduction in the 2 m mean temperature when using the irrigation parameterization. [ABSTRACT FROM AUTHOR]

The increasing intensity and frequency of high-temperature events in response to climate change can potentially impact the aviation industry, since aircraft takeoff and landing performances depend on near-surface air temperature. Previous studies have combined climate data with aircraft technical data to estimate the future impact of rising high temperatures on aircraft takeoff. They found a decrease of maximum takeoff weights and the lengthening of takeoff distances. The Mediterranean region is a climate change "hot spot" area, specially concerned by extreme high-temperatures increase. In this study, the magnitude and trends of the daily maximum near-surface temperature extremes in summer were analysed over major airports in Southwestern Europe. Trends in the period 1961–2014 were analysed from observations and reanalysis. Future changes by 2021–2050 and 2071–2100, with respect to 1961–2005, were analysed from simulations performed with Regional and Global Climate Models (RCMs and GCMs). Before assessing future climate projections, climate models were evaluated in present climate, and the RCM and GCM ensembles were compared to each other. No clear added value was found for RCMs over GCMs in present climate at the airport scale in these terms. GCMs project larger temperature changes than RCMs over the same locations. Multi-model ensemble mean projected changes under the RCP8.5 scenario range between + 1.7 and + 3.2 ∘ C by the near term, and between + 4.9 and + 8.5 ∘ C by the long term, across the airports and the RCM and GCM ensembles. This increase of high-temperature extremes would impact airport operations. Adaptation or mitigation policies would become necessary. [ABSTRACT FROM AUTHOR]

Since our climate is in a rapid changing phase, it is crucial to get information about the regional patterns of basic climatic parameters and indices. The EURO-CORDEX project provides high-quality regional climate model outputs, but these raw datasets are not convenient for the application in wider geoscience studies. According to the authors' knowledge, there is a lack of published spatial information about basic climate parameters and indices in Central Europe and especially in the broader Carpathian region therefore the basic aim of this study to fill this gap. The study presents the future trends in daily air temperature and precipitation and various climatic indices in the broader Carpathian Basin region during the 21st century. The indices are calculated using multi-model average temperature and precipitation data from EURO-CORDEX model simulations for the future time periods (2021-2050, 2071-2100) and emission scenarios (RCP4.5, RCP8.5). The indices present the future trends of the heat load, energy demand as well as extreme precipitation and drought characteristics. Based on the results the temperature increase is obvious and the heat load and energy demand quantifying indices follow the temperature trend. However, the trend is difficult to evaluate in the case of precipitation. The changes in the precipitation and the related indices can be considered small and appear within the regions. The future changes are the most considerable in the Carpathian Basin, but the entire examined region faces crucial changes in the following decades. [ABSTRACT FROM AUTHOR]

[Display omitted] • The model performs good in capturing the seasonal pattern and peak values of river water temperature. • Air temperature and day of year are the major factorson modeling river water temperature. • The model is a promising tool to investigate the impact of climate change on river thermal dynamics. Water temperature is an important physical indicator of rivers because it impacts many other physical and biogeochemical processes and controls the metabolism of aquatic species in rivers. Having a good knowledge of river thermal dynamics is of great importance. In this study, an advanced machine learning based model that is fast, accurate and easy to use, namely the nonlinear autoregressive network with exogenous inputs (NARX) neural network, was coupled with Bayesian Optimization (BO) algorithm for optimizing the number of NARX hidden nodes and lagged input/target values and the Bayesian Regularization (BR) backpropagation algorithm for the NARX training, to forecast daily river water temperatures (RWT). Long-term observed data from 18 rivers of the Vistula River Basin, one of the largest rivers in Europe, were used for model testing, and model performance was compared with the air2stream model. The results showed that the NARX-based model performs significantly better than the air2stream model in the calibration and validation stages, and can better capture the seasonal pattern and peak values of RWT. Input combinations impact the performance of the NARX-based model in RWT modeling, and air temperature and the day of the year (DOY) are the major inputs, while streamflow and rainfall play a minor role on modeling RWT at the Vistula River Basin. Considering that future times series of air temperatures are easily accessible from climate models and DOY is easy to be considered in the model, the NARX-based model can serve as a promising tool to investigate the impact of climate change on river thermal dynamics. [ABSTRACT FROM AUTHOR]

Climate change increases the frequency and intensity of heat waves, bringing along multiple adverse impacts on ecosystems, human health, societies, and the economy. Groundwater influences the near surface air temperature evolution through land–atmosphere interactions. Using simplified and shallow groundwater representations, reproducing heat waves in a regional climate model (RCM) is challenging. Currently, RCMs applied over Europe exhibit a warm bias. This study analyzes heat waves over a 13‐year evaluation period, comparing the terrestrial systems modeling platform (TSMP) with an explicit groundwater representation to a EURO‐CORDEX RCM ensemble, the ERA5 reanalysis, and observations. The TSMP multiannual heat wave statistics are consistent with observations and reanalysis data. We attribute the lower absolute deviations of heat wave metrics simulated by TSMP to the improved hydrology including 3D groundwater flow. The findings emphasize the importance of hydrological process representation in RCMs. Plain Language Summary: Heat waves severely impact the ecosystem, society, and the economy. Climate change will amplify these events in the near future, urging a correct representation of heat waves in climate models. Especially during warm and dry periods, there is a strong connection from the groundwater stored in the subsurface through the land surface to the atmosphere. Commonly applied models have a simplified representation of groundwater and cannot establish a correct connection to the atmosphere, simulating too high temperatures over Europe. To show the advantage of a model with a complex groundwater representation, we compare such a model with 12 representative climate models. The results indicate lower deviations from heat wave statistics of observations with the inclusion of complex groundwater. Our findings emphasize the importance of including groundwater dynamics representation in climate models. Key Points: Multiannual heat wave statistics from a regional climate model including groundwater dynamics are consistent with observationsRegional climate models with simplified groundwater representations overestimate observed multiannual heat wave statisticsExplicit groundwater treatment increases the reliability of heat wave simulations with implications for regional climate projections [ABSTRACT FROM AUTHOR]

For the first time, the Limited-Area Mode of the new ICON (Icosahedral Nonhydrostatic) weather and climate model has been used for a continuous long-term regional climate simulation over Europe. Built upon the Limited-Area Mode of ICON (ICON-LAM), ICON-CLM (ICON in Climate Limited-area Mode, hereafter ICON-CLM, available in ICON release version 2.6.1) is an adaptation for climate applications. A first version of ICON-CLM is now available and has already been integrated into a starter package (ICON-CLM_SP beta1). The starter package provides users with a technical infrastructure that facilitates long-term simulations as well as model evaluation and test routines. ICON-CLM and ICON-CLM_SP were successfully installed and tested on two different computing systems. Tests with different domain decompositions showed bit-identical results, and no systematic outstanding differences were found in the results with different model time steps. ICON-CLM was also able to reproduce the large-scale atmospheric information from the global driving model. Comparison was done between ICON-CLM and the COnsortium for Small-scale MOdeling (COSMO)-CLM (the recommended model configuration by the CLM-Community) performance. For that, an evaluation run of ICON-CLM with ERA-Interim boundary conditions was carried out with the setup similar to the COSMO-CLM recommended optimal setup. ICON-CLM results showed biases in the same range as those of COSMO-CLM for all evaluated surface variables. While this COSMO-CLM simulation was carried out with the latest model version which has been developed and was carefully tuned for climate simulations on the European domain, ICON-CLM was not tuned yet. Nevertheless, ICON-CLM showed a better performance for air temperature and its daily extremes, and slightly better performance for total cloud cover. For precipitation and mean sea level pressure, COSMO-CLM was closer to observations than ICON-CLM. However, as ICON-CLM is still in the early stage of development, there is still much room for improvement. [ABSTRACT FROM AUTHOR]

The majority of regional climate change assessments for the Euro-CORDEX region is based on high resolution atmosphere models. These models use prescribed lower boundary conditions, such as sea surface temperatures (SST) from global ocean General Circulation Models (GCMs), that do not respond to changes simulated by the regional atmosphere model, thus lacking an important feedback to the atmosphere. However, research during the past decade indicated that the use of coupled atmosphere–ocean models can lead to significantly altered model solutions compared to standalone atmosphere models for the present day climate imposing some uncertainty on the widely used uncoupled future scenarios. We here present the first multi-model and multi scenario (RCP2.6, RCP4.5, RCP8.5) ensemble of future climate change scenarios downscaled with a coupled atmosphere—ocean model in which sea surface temperature and sea ice fields are explicitly simulated by a coupled state-of-the-art high resolution ocean model and communicated to the atmosphere at 3-hourly time steps. Our ensemble generally confirms results of previous uncoupled ensembles over land areas implying that the coupling effect is restricted mainly to the coupled area and the adjacent coastal zone. By contrast, over the North Sea and Baltic Sea small scale processes point to important coupling effects that mediate the response to climate change and that can not be simulated by uncoupled models. Our results therefore impose general uncertainty on the usage of regional climate change data from uncoupled ensembles over marine areas such as for purposes of offshore wind or mussel farming, the planing of marine protected areas, and marine recreation along the coastal zone. It further sets in question the usage of uncoupled scenario data (such as Euro-CORDEX) to force high resolution ocean models. Comparing coupled and uncoupled hindcast simulations reveals that the coupling effect over land is most pronounced during the warm season when prescribed and modelled sea surface temperatures (SST) differ strongest. In addition, a generally weaker wind regime in summer damps the heat dispersion in the atmosphere so that air temperature anomalies can extent further over land compared to winter. Future projections are discussed under consideration of land-sea warming characteristics for selected climate indices as well as mean seasonal climate change. At the end of the century a clear land-sea pattern is seen in all scenarios with stronger warming over land than over open sea areas. On average land areas warm at a rate 1.5 times faster than areas over the open ocean. Over the coupled area, i.e. the North Sea and Baltic Sea tropical nights are impacted strongest and the Baltic Sea turns out to be a hot spot in future climate. This has been unrecognized in previous studies using high resolution atmosphere models with prescribed SSTs from global models which do not represent small scale ocean processes in the Baltic Sea adequately. [ABSTRACT FROM AUTHOR]

Europe has experienced many extreme heat waves over the past few decades. In this study, the physical processes underlying these long-lasting and wide-ranging heat wave events are investigated based on a case study in Europe in June 2021. Heat waves are associated with barotropic anticyclonic anomalies accompanied by positive geopotential height anomalies locally. These anomalies persist under the conditions of increased meridional air temperature gradients of the mid–upper troposphere in the high latitudes of Eurasia and the formation of the Arctic front jet. The shrinking high-latitude snow cover in April–May favors higher surface temperatures and larger meridional temperature gradients in June in the mid–upper troposphere due to the soil moisture–evaporation–temperature positive feedback process. The summer Arctic front jet is then strengthened, and the mid-latitude westerly winds are weakened. This atmospheric circulation background favors waveguide formation and wave resonance that produces high-amplitude atmospheric waves and the stagnation of ridges in the mid-latitudes. Numerical experiments using the Community Atmosphere Model version 5 verify the proposed physical mechanisms, with the climatic responses in sensitivity experiments to anomalous snowfall rates closely resembling the observational results. Therefore, in June 2021, under the identified atmospheric circulation background and the perturbation of the upstream positive phase of the North Atlantic Oscillation, the large-scale barotropic high pressure and barotropic anticyclonic circulation in the study region tended to be stable and persistent, which is favorable for the production of long-lasting and wide-ranging heat wave events. • Physical mechanisms underlying heat waves are investigated based on a case study in Europe in June 2021. • Shrinking Eurasian snow cover in spring favors the strengthened summer Arctic front jet that produces high-amplitude waves. • Upstream positive NAO in June 2021 favors a sequence of waves downstream and affect persistent anticyclone for heat waves. [ABSTRACT FROM AUTHOR]

Central European weather and climate are closely related to atmospheric mass advection triggered by the North Atlantic Oscillation (NAO), which is a relevant index for quantifying internal climate variability on multi-annual timescales. It remains unclear, however, how large-scale circulation variability affects local climate characteristics when downscaled using a regional climate model. In this study, 50 members of a single-model initial-condition large ensemble (LE) of a nested regional climate model are analyzed for a NAO–climate relationship. The overall goal of the study is to assess whether the range of NAO internal variability is represented consistently between the driving global climate model (GCM; the Canadian Earth System Model version 2 – CanESM2) and the nested regional climate model (RCM; the Canadian Regional Climate Model version 5 – CRCM5). Responses of mean surface air temperature and total precipitation to changes in the NAO index value are examined in a central European domain in both CanESM2-LE and CRCM5-LE via Pearson correlation coefficients and the change per unit index change for historical (1981–2010) and future (2070–2099) winters. Results show that statistically robust NAO patterns are found in the CanESM2-LE under current forcing conditions. NAO flow pattern reproductions in the CanESM2-LE trigger responses in the high-resolution CRCM5-LE that are comparable to reanalysis data. NAO–response relationships weaken in the future period, but their inter-member spread shows no significant change. The results stress the value of single-model ensembles for the evaluation of internal variability by pointing out the large differences of NAO–response relationships among individual members. They also strengthen the validity of the nested ensemble for further impact modeling using RCM data only, since important large-scale teleconnections present in the driving data propagate properly to the fine-scale dynamics in the RCM. [ABSTRACT FROM AUTHOR]

Central European weather and climate is closely related to atmospheric mass advection triggered by the North Atlantic Oscillation (NAO) which is a relevant index for quantifying natural variability on multi-annual time scales. It remains unclear, though, how large-scale circulation variability affects local climate characteristics when downscaled using a regional climate model. In this study, 50 members of a single-model initial-condition large ensemble (LE) (http://www.climex-project.org/) are analyzed for a climate-NAO relationship, especially its inter-member spread and its transfer from the driving model CanESM2 into the driven model CRCM5. The NAO pressure dipole is quantified in the CanESM2-LE by an extended station-based index; responses of mean surface air temperature and total precipitation to changes in the index value are determined for a Central European domain (CEUR) in both the CanESM2-LE and CRCM5-LE. NAO-response relationships are expressed via Pearson correlation coefficients (strength) and the change per unit index change for historical (1981-2010) and future (2070-2099) winters. Results show that (a) statistically robust NAO patterns are found in the CanESM2-LE under current forcing conditions and (b) impulses from the NAO in the CanESM2-LE produce correct responses in the high-resolution CRCM5-LE. Relationships weaken in the future period, but the amplitude of their inter-member spread shows no significant change. Among others, the results strengthen the validity of the climate module in the ClimEx model chain for further impact modelling and stress the importance of single-model ensembles for evaluating internal variability. [ABSTRACT FROM AUTHOR]

Cyclic volatile methylsiloxanes (cVMS) and short-chain chlorinated paraffins (SCCPs) use has been restricted in recent years due to environmental health concerns. Both of these classes of emerging contaminants possess long range transport potential (LRTP), highlighting the need for continuous monitoring to assess effectiveness of implemented regulations. However, emission source elucidation and understanding processes affecting atmospheric transport remain challenging. Atmospheric levels of cVMSs and SCCPs were simultaneously monitored at a background monitoring site in Norway from January–July 2020. Concentrations obtained from active air samplers ranged from 49.9 to 845 (mean: 208) pg/m3 for ƩSCCPs and from 0.4 to 3.5 (mean: 1.5), 1.1–15 (mean: 5.6) and 0.1–0.9 (mean: 0.4) ng/m3 for octamethylcyclotetrasiloxane (D4), decamethylcyclopentasiloxane (D5) and dodecamethylcyclohexasiloxane (D6), respectively. As SCCPs pose several challenges to analysts, different quantification methodologies and blank handling procedures were investigated to ensure reliable environmental measurements. Simulations using a Lagrangian atmospheric transport model (FLEXPART) revealed air masses impacting sampling measurements were of Oceanic origin, but periodic emission events from Europe and Russia were also observed. Seasonal pattern in cVMS concentrations was mainly driven by atmospheric degradation via hydroxyl radical reaction, whereas SCCP concentrations were more influenced by periodic anthropogenic inputs from local and continental Europe. No clear correlation could be observed with SCCP atmospheric concentrations and temperature over the entire sampling campaign. However, increased volatilization at elevated temperatures may be important with emissions originating from local sources. Higher chlorinated homologue groups dominated during the winter season and declined towards spring and summer, whereas reverse was found for the lower and more volatile chlorinated homologue groups. [Display omitted] • LRT of cVMS primarily driven by seasonal atmospheric degradation. • SCCP LRT primarily driven by anthropogenic inputs from continental Europe. • Seasonal changes in SCCP composition pattern were observed. • Proper quantification and blank handling procedures crucial for reporting SCCP. [ABSTRACT FROM AUTHOR]

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution. [ABSTRACT FROM AUTHOR]

Future anthropogenic climate change is likely to increase the air temperature ( T) across Europe and increase the frequency, duration and magnitude of severe heat stress events. Heat stress events are generally associated with clear-sky conditions and high T, which give rise to high radiant heat load, i.e. mean radiant temperature ( T). In urban environments, T is strongly influenced by urban geometry. The present study examines the effect of urban geometry on daytime heat stress in three European cities (Gothenburg in Sweden, Frankfurt in Germany and Porto in Portugal) under present and future climates, using T as an indicator of heat stress. It is found that severe heat stress occurs in all three cities. Similar maximum daytime T is found in open areas in all three cities despite of the latitudinal differences in average daytime T. In contrast, dense urban structures like narrow street canyons are able to mitigate heat stress in the summer, without causing substantial changes in T in the winter. Although the T averages are similar for the north-south and east-west street canyons in each city, the number of hours when T exceeds the threshold values of 55.5 and 59.4 °C-used as indicators of moderate and severe heat stress-in the north-south canyons is much higher than that in the east-west canyons. Using statistically downscaled data from a regional climate model, it is found that the study sites were generally warmer in the future scenario, especially Porto, which would further exacerbate heat stress in urban areas. However, a decrease in solar radiation in Gothenburg and Frankfurt reduces T in the spring, while the reduction in T is somewhat offset by increasing T in other seasons. It suggests that changes in the T under the future scenario are dominated by variations in T. Nonetheless, the intra-urban differences remain relatively stable in the future. These findings suggest that dense urban structure can reduce daytime heat stress since it reduces the number of hours of high T in the summer and does not cause substantial changes in average and minimum T in the winter. In dense urban settings, a more diverse urban thermal environment is also preferred to compensate for reduced solar access in the winter. The extent to which the urban geometry can be optimized for the future climate is also influenced by local urban characteristics. [ABSTRACT FROM AUTHOR]

This study aims at sharpening the existing knowledge of expected seasonal mean climate change and its uncertainty over Europe for the two key climate variables air temperature and precipitation amount until the mid-twentyfirst century. For this purpose, we assess and compensate the global climate model (GCM) sampling bias of the ENSEMBLES regional climate model (RCM) projections by combining them with the full set of the CMIP3 GCM ensemble. We first apply a cross-validation in order to assess the skill of different statistical data reconstruction methods in reproducing ensemble mean and standard deviation. We then select the most appropriate reconstruction method in order to fill the missing values of the ENSEMBLES simulation matrix and further extend the matrix by all available CMIP3 GCM simulations forced by the A1B emission scenario. Cross-validation identifies a randomized scaling approach as superior in reconstructing the ensemble spread. Errors in ensemble mean and standard deviation are mostly less than 0.1 K and 1.0 % for air temperature and precipitation amount, respectively. Reconstruction of the missing values reveals that expected seasonal mean climate change of the ENSEMBLES RCM projections is not significantly biased and that the associated uncertainty is not underestimated due to sampling of only a few driving GCMs. In contrast, the spread of the extended simulation matrix is partly significantly lower, sharpening our knowledge about future climate change over Europe by reducing uncertainty in some regions. Furthermore, this study gives substantial weight to recent climate change impact studies based on the ENSEMBLES projections, since it confirms the robustness of the climate forcing of these studies concerning GCM sampling. [ABSTRACT FROM AUTHOR]

The occurrence and intensity of heatwaves is expected to increase with climate change. Early warnings of hot summers have therefore a great socio-economical value. Previous studies have shown that hot summers are preceded by a Southern European rainfall deficit during winter, and higher spring temperatures. Changes in the surface energy budget are believed to drive this evolution, in particular changes in the latent and sensible heat fluxes. However these have rarely been investigated due to the lack of long-term reliable observation data. In this study, we analyzed several data-derived gridded products of latent and sensible heat fluxes, based on flux tower observations, together with re-analyses and regional climate model simulations over Europe. We find that warm summers are preceded by an increase in latent heat flux in early spring. During warm summers, an increase in available energy results in an excess of both latent and sensible heat fluxes over most of Europe, but a latent heat flux decrease over the Iberian Peninsula. This indicates that, on average, a summertime soil-moisture limited evapotranspiration regime only prevails in the Iberian Peninsula. In general, the models that we analyzed overestimate latent heat and underestimate sensible heat as compared to the flux tower derived data-product. Most models show considerable drying during warm seasons, leading to the establishment of a soil-moisture limited regime across Europe in summer. This over-estimation by the current generation of models of latent heat and hence of soil moisture deficit over Europe in summer has potential consequences for future summertime climate projections and the projected frequency of heat waves. We also show that a northward propagation of drought during warm summers is found in model results, a phenomenon which is also seen in the flux tower data-product. Our results lead to a better understanding of the role of latent and sensible heat flux in summer heatwaves, and provide a framework for benchmark of modeling studies. [ABSTRACT FROM AUTHOR]

The study evaluates relationships between the North Atlantic Oscillation (NAO) index and winter temperatures (including indices of extremes) over Europe in an ensemble of transient simulations of current global climate models (GCMs). We focus on identification of areas in which the NAO index is linked to winter temperatures and temperature extremes in simulations of the recent climate (1961-2000), and evaluate how these relationships change in climate change scenarios for the late 21st century (2071-2100). Most GCMs are able to reproduce main features of the observed links. The NAO index is more important for cold than warm extremes, which is also reproduced by the GCMs. However, all GCMs underestimate the magnitude of the NAO influence on cold extremes when averaged over northern and western Europe. For future scenarios, the links between the NAO and temperatures are mostly analogous to those in the recent climate, except for one GCM (CM3) in which the influence of the NAO on temperature almost disappears over whole Europe. This suggests that future scenarios from this particular GCM should be evaluated with caution. The NAO index is found to represent a useful covariate that explains an important fraction of variability of cold extremes in winter, and its incorporation into extreme value models for daily temperatures (and their possible changes under climate change) may improve performance of these models and reliability of estimates of extremes and their uncertainty. [ABSTRACT FROM AUTHOR]

Abstract: Summer 2007 was abnormally warm for many areas of southeastern Europe, the Balkan peninsula and parts of Asia Minor with departures from the seasonal means exceeding 4 °C in some areas but also distinct periods of extremely hot weather. Greece experienced very likely the warmest summer of its instrumental history with record breaking temperatures being observed at a number of stations. The historical air temperature record of the National Observatory of Athens (NOA), extending back to the 19th century, was used in order to highlight the rarity of the event. Seasonal (June to August) temperature anomalies at NOA exceeded 3 °C corresponding to more than 3 standard deviations with respect to the 1961–1990 reference period. The record value of 44.8 °C was observed at NOA on 26 June 2007 (previous record 43 °C in June 1916) during the first and most intense heat wave that affected the area. The study places summer 2007 in the climatology of the previous century and also examines whether the statistics of summer 2007 have similarities with Mediterranean summers of the future. An ensemble of regional climate model simulations undertaken for the European domain indicate that summer 2007 reflects the daily maximum temperatures that are projected to occur in the latter part of the 21st century. The analysis of temperature data from other less urbanized stations indicates that the urban heat effect in Athens contributed positively to the anomalies of the nocturnal temperatures. The abnormally hot summer of 2007 is perhaps not the proof but a strong indicator of what eastern Mediterranean summers could resemble in future. [Copyright &y& Elsevier]

Surface air Temperature variations (DT) on the short time scale (from 1 to 7/15/30 days), defined as the difference of daily temperature between one day and a next one, can have strong impacts on human health and plant development. This analysis investigates EURO-CORDEX Regional Climate Model simulations data, at the highest horizontal resolution available (EUR-11 domain: about 11 km) collected within the EU H2020 project COACCH. The Mediterranean regions appears as the most prone to DT increase, in a warmer climate, within the European domain. Based on a multi-model multi-scenario approach we aim to quantify such changes and the related uncertainty within the current century. Changes in the length of the seasons are also inspected to verify potential linkages to the DT changes. The model validation is based on JRA-55 reanalysis covering the 1985-2015 period. Future tendencies of the aforementioned parameter are inspected following three Representative Concentration Pathways (RCPs) taking part to the fifth Coupled Model Intercomparison Project (CMIP5): RCP2.6, RCP4.5 and RCP8.5. A comparison of the results obtained based on bias corrected and raw temperature data is provided and discussed.The Keywords: Temperature, Europe, Future Scenarios, CORDEX [ABSTRACT FROM AUTHOR]