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Relative to drought and heat waves, the effect of winter warming on forest CO2 fluxes during the dormant season has less been investigated, despite its relevance for net CO2 uptake in colder regions with higher carbon content in soils. Our objective was to test the effect of the exceptionally warm winter in 2020 on the winter CO2 budget of cold-adapted evergreen needle-leaf forests across Europe, and identify the contribution of soil and air temperature to changes in winter CO2 fluxes in response to warming. Our hypothesis was that warming in winter leads to higher emissions across colder sites due to increased ecosystem respiration. To test this hypothesis, we used 98 site-year eddy covariance measurements across 14 evergreen needle-leaf forests (ENFs) distributed from north to south of Europe (from Sweden to Italy). We used a data-driven approach to quantify the effect of air and soil temperature on changes in net ecosystem productivity (NEP) during the warm winter of 2020. Our results showed that the impact of warming was different across sites, as in the lower altitude and lower latitude sites positive soil temperature anomalies were larger, while positive air temperature anomalies were larger in the northern latitude and high-altitude sites. Warming in winter led to a divergent response across the sites. Out of 14 sites only in 3 sites net ecosystem productivity declined in winter significantly in response to warming. In addition, we observed that in the colder sites daytime NEP (that is dominated by photosynthesis) declined with warming of the air in winter, whereas in the warmer sites daytime NEP increased with warming of the soil. This shows that warming of the air – if not translated into a direct warming of the soil– might not trigger productivity in winter if the soil within the rooting zone remains frozen. Forests within the same plant functional type category can exhibit differing reactions to winter warming and to predict their responses accurately it is crucial to account for variations in local climate, physiology, and structure simultaneously. [ABSTRACT FROM AUTHOR]

Relative to drought and heat waves, the effect of winter warming on forest CO2 fluxes during the dormant season has less been investigated, despite its relevance for net CO2 uptake in colder regions with higher carbon content in soils. Our objective was to test the effect of the exceptionally warm winter in 2020 on the winter CO2 budget of cold-adapted evergreen needleleaf forests across Europe, and identify the contribution of soil and air temperature to changes in winter CO2 fluxes in response to warming. Our hypothesis was that warming in winter leads to higher emissions across colder sites due to increased ecosystem respiration. To test this hypothesis, we used 98 site-year eddy covariance measurements across 14 evergreen needleleaf forests (ENFs) distributed from north to south of Europe (from Sweden to Italy). We used a data-driven approach to quantify the effect of air and soil temperature on changes in net ecosystem productivity (NEP) during the warm winter of 2020. Our results showed that the impact of warming was different across sites, as in the lower altitude and lower latitude sites positive soil temperature anomalies were larger, while positive air temperature anomalies were larger in the northern latitude and high-altitude sites. Warming in winter led to a divergent response across the sites. Out of 14 sites only in 3 sites net ecosystem productivity declined in winter significantly in response to warming. In addition, we observed that in the colder sites daytime NEP (that is dominated by photosynthesis) declined with warming of the air in winter, whereas in the warmer sites daytime NEP increased with warming of the soil. While warming increases ecosystem respiration, it might not trigger productivity in winter if the soil within the rooting zone remains frozen. Forests within the same plant functional type category can exhibit differing reactions to winter warming and to predict their responses accurately it is crucial to account for variations in local climate, physiology, and structure simultaneously. [ABSTRACT FROM AUTHOR]

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]

Irrigation is a crucial land use practice to adapt agriculture to unsuitable climate and soil conditions. Aiming for improving 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 for analyzing the effects of irrigation on land-atmosphere interaction, including the effects and feedbacks of vegetation. We developed a new parameterization for irrigation and implemented it into the REgional climate MOdel REMO2020, coupled with the interactive MOsaicbased 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 South-West Europe including the Mediterranean region on 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 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]

Droughts and heatwaves are among the most impactful climate extremes. Their co-occurrence can have devastating consequences on natural and human systems. Early information on seasonal timescales on their possible occurrence is beneficial for many stakeholders. Seasonal climate forecast has gradually become more used; but limited skill in certain regions and seasons still hinders a broader use. Here we show that a simple forecast metric from a multi-system ensemble, the signal to noise ratio, can help overcome some limitations in the boreal summer. Forecasts of maximum daily near surface air temperature and precipitation in boreal summers with high signal to noise ratio tend to coincide with observed larger deviations from the mean than years with small signal to noise ratio. The same metric also helps identify processes relevant to seasonal climate predictability. Here we show that a positive phase of a North Atlantic Sea surface dipole during boreal spring may favor the occurrence of dry and hot summers in Europe. [ABSTRACT FROM AUTHOR]

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 also alter the properties of natural cirrus clouds by soot emissions which lead to more heterogeneous freezing. During the first COVID-19 lockdown in Europe, changes in the properties and occurrence of cirrus clouds were determined with the lidar measurements of CALIPSO, which are presumed to be caused by the corresponding reduction in civil aviation. In the 10 years before the COVID-19 outbreak, however, aviation grew strongly in terms of CO 2 emissions and flight densities in Europe. In this study, 10-year lidar measurements with CALIPSO are analysed to determine the seasonality and long-term trends in cirrus clouds as well as their correlations with the ambient temperatures and air traffic. The results show that there is a distinct seasonal cycle in the occurrence rates (ORs) and particle linear depolarization ratio (PLDR) of cirrus clouds. In addition, cirrus clouds appear within a broader altitude range in winter than in summer and they are characterized by larger OR and PLDR values in winter than in summer. The monthly medians of PLDR as well as their deseasonalized time series in the 10-year period before COVID-19 both show positive trends, which are statistically significant according to the Mann–Kendall (MK) significance test. However, the ORs of cirrus clouds show a negative trend, which might be connected with the background meteorological conditions. Since the cirrus PLDR strongly depends on the ambient temperatures, the contributions induced by temperature are further removed from the cirrus PLDR with a simple linear regression model. The derived residuals show significant positive trends according to the MK test. To compare the cirrus PLDR and air traffic (with the CO 2 emissions from aviation as a proxy), the deseasonalization of both datasets were previously conducted since the seasonal cycles in both are not consistent. The deseasonalized time series determined for the cirrus PLDR and CO 2 emissions from aviation both show increasing trends and their correlation coefficient is r=0.54 at the confidence level above 99.5 %. Finally, comparisons between the cirrus PLDR and aviation in every season were made and revealed a strong correlation in other seasons than in summer. [ABSTRACT FROM AUTHOR]

Afforestation is an important mitigation strategy to climate change due to its carbon sequestration potential. Besides this positive biogeochemical effect on global CO2 concentrations, afforestation also affects the regional climate by changing the biogeophysical land surface characteristics. In this study, we investigate the effects of an idealized global CO2 reduction to pre-industrial conditions by a Europe wide afforestation experiment on the regional longwave radiation balance, starting in the year 1986 from a continent entirely covered with grassland. Results show that the impact of biogeophysical processes on the surface temperatures is much stronger than of biogechemical processes. Furthermore, biogeophysically induced changes of the surface temperatures, atmospheric temperatures and moisture concentrations are as important for the regional greenhouse effect as the global CO2 reduction. While the greenhouse effect is strengthened in winter, it is weakened in summer. On annual total, a Europe-wide afforestation has a regional warming effect, despite reduced CO2 concentrations. Thus, even for an idealized reduction of the global CO2 concentrations to pre-industrial levels, the European climate response to afforestation would still be dominated by its biogeophysical effects. [ABSTRACT FROM AUTHOR]

The quantification of land–atmosphere coupling strength is still challenging, particularly in the atmospheric segment of the local coupling process chain. This is in part caused by a lack of spatially comprehensive observations of atmospheric temperature and specific humidity which form the verification basis for the common process-based coupling metrics. In this study, we aim at investigating where uncertainty in the atmospheric temperature and moisture affects the land–atmosphere coupling strength over Europe, and how changes in the mean temperature and moisture, as well as their vertical gradients, influence the coupling. For this purpose, we implemented systematic a posteriori modifications to the temperature and moisture fields from a regional climate simulation to create a spread in the atmospheric conditions. Afterwards, the process-based coupling metric convective triggering potential – low-level humidity index framework was applied to each modification case. Comparing all modification cases to the unmodified control case revealed that a strong coupling hotspot region in northeastern Europe was insensitive to temperature and moisture changes, although the number of potential coupling days varied by up to 20 d per summer season. The predominance of positive feedbacks remained unchanged in the northern part of the hotspot, and none of the modifications changed the frequent inhibition of feedbacks due to dry conditions in the atmosphere over the Mediterranean and the Iberian Peninsula. However, in the southern hotspot region in the north of the Black Sea, the dominant coupling class frequently switched between wet soil advantage and transition zone. Thus, both the coupling strength and the predominant sign of feedbacks were sensitive to changes in temperature and moisture in this region. This implies not only uncertainty in the quantification of land–atmosphere coupling strength but also the potential that climate-change-induced temperature and moisture changes considerably impact the climate there, because they also change the predominant atmospheric response to land surface wetness. [ABSTRACT FROM AUTHOR]

In this study we analyze drought features at the European level over the period 1901–2019 using three drought indices: the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), and the self-calibrated Palmer drought severity index (scPDSI). The results based on the SPEI and scPDSI point to the fact that Central Europe (CEU) and the Mediterranean region (MED) are becoming dryer due to an increase in the potential evapotranspiration and mean air temperature, while North Europe (NEU) is becoming wetter. By contrast, the SPI drought does not reveal these changes in the drought variability, mainly due to the fact that the precipitation does not exhibit a significant change, especially over CEU. The SPEI12 indicates a significant increase both in the drought frequency and area over the last three decades for MED and CEU, while SPI12 does not capture these features. Thus, the performance of the SPI may be insufficient for drought analysis studies over regions where there is a strong warming signal. By analyzing the frequency of compound events (e.g., high temperatures and droughts), we show that the potential evapotranspiration and the mean air temperature are becoming essential components for drought occurrence over CEU and MED. This, together with the projected increase in the potential evapotranspiration under a warming climate, has significant implications concerning the future occurrence of drought events, especially for the MED and CEU regions. [ABSTRACT FROM AUTHOR]

In this study we analyze the drought features at European level over the period 1901-2019, using three drought indices: the Standardized precipitation (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrated Palmer Drought Severity Index (scPDSI). The results based on the SPEI and scPDSI indices point out to the fact that central Europe (CEU) and the Mediterranean region (MED) are becoming dryer, due to an increase in the potential evapotranspiration and the mean air temperature, while the northern part of Europe (NEU) is becoming wetter. By contrast, the SPI drought index does not reveal these changes in the drought variability, mainly due to the fact that the precipitation does not exhibit a significant change, especially over CEU. SPEI12 indicates a significant increase both in the frequency and area over the last three decades for MED and CEU, while SPI12 is not capturing these features. By analyzing the joint probability of compound events (e.g. high temperatures/droughts), we show that the potential evapotranspiration and the mean air temperature are becoming essential components for drought occurrence over CEU and MED. This, together with the projected increase in the potential evapotranspiration under a warming climate, has significant implications concerning the future occurrence of drought events, especially for MED and CEU regions. [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 description and analysis of compound extremes affecting mid and high latitudes in the winter requires an accurate estimation of snowfall. Such variable is often missing for in-situ observations, and biased in climate model outputs, both in magnitude and number of events. While climate models can be adjusted using bias correction (BC), snowfall presents additional challenges compared to other variables, preventing from applying traditional univariate BC methods. We extend the existing literature on the estimation of the snowfall fraction from near-surface temperature, which usually involves binary thresholds or fitting parametric nonlinear functions. We show that, combining breakpoint search algorithms to define threshold temperatures and segmented regression models, it is possible to obtain accurate out-of-sample estimates of snowfall over Europe in ERA5 reanalysis, and to perform effective BC on the IPSL-WRF high resolution EURO-CORDEX climate model only relying on bias adjusted temperature and precipitation. This method offers a feasible way to reconstruct or adjust snowfall observations without requiring multivariate or conditional bias correction and stochastic generation of unobserved events. [ABSTRACT FROM AUTHOR]

Forecasting atmospheric CO2 concentrations on synoptic timescales (∼ days) can benefit the planning of field campaigns by better predicting the location of important gradients. One aspect of this, accurately predicting the day-to-day variation in biospheric fluxes, poses a major challenge. This study aims to investigate the feasibility of using a diagnostic light-use-efficiency model, the Vegetation Photosynthesis Respiration Model (VPRM), to forecast biospheric CO2 fluxes on the timescale of a few days. As input, the VPRM model requires downward shortwave radiation, 2 m temperature, and enhanced vegetation index (EVI) and land surface water index (LSWI), both of which are calculated from MODIS reflectance measurements. Flux forecasts were performed by extrapolating the model input into the future, i.e., using downward shortwave radiation and temperature from a numerical weather prediction (NWP) model, as well as extrapolating the MODIS indices to calculate future biospheric CO2 fluxes with VPRM. A hindcast for biospheric CO2 fluxes in Europe in 2014 has been done and compared to eddy covariance flux measurements to assess the uncertainty from different aspects of the forecasting system. In total the range-normalized mean absolute error (normalized) of the 5 d flux forecast at daily timescales is 7.1 %, while the error for the model itself is 15.9 %. The largest forecast error source comes from the meteorological data, in which error from shortwave radiation contributes slightly more than the error from air temperature. The error contribution from all error sources is similar at each flux observation site and is not significantly dependent on vegetation type. [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]

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]

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]

This work presents the Guadalfeo Monitoring Network in Sierra Nevada (Spain), a snow monitoring network in the Guadalfeo Experimental Catchment, a semiarid area in southern Europe representative of snowpacks with highly variable dynamics on both annual and seasonal scales and significant topographic gradients. The network includes weather stations that cover the high mountain area in the catchment and time-lapse cameras to capture the variability of the ablation phases on different spatial scales. The data sets consist of continuous meteorological high-frequency records at five automatic weather stations located at different altitudes ranging from 1300 to 2600 m a.s.l. that include precipitation, air temperature, wind speed, air relative humidity and the short- and longwave components of the incoming radiation, dating from 2004 for the oldest station (2510 m a.s.l.) (10.1594/PANGAEA.895236); additionally, daily data sets of the imagery from two time-lapse cameras are presented, with different scene area (30 m × 30 m, and 2 km 2 , respectively) and spatial resolution, that consist of fractional snow cover area and snow depth from 2009 (10.1594/PANGAEA.871706) and snow cover maps for selected dates from 2011 (10.1594/PANGAEA.898374). Some research applications of these data sets are also included to highlight the value of high-resolution data sources to improve the understanding of snow processes and distribution in highly variable environments. The data sets are available from different open-source sites and provide both the snow hydrology scientific community and other research fields, such as terrestrial ecology, riverine ecosystems or water quality in high mountains, with valuable information of high potential in snow-dominated areas in semiarid regions. [ABSTRACT FROM AUTHOR]

Mediterranean ecosystems are significant carbon sinks but are also particularly sensitive to climate change but the carbon dynamic in such ecosystem is still not fully understood. An improved understanding of the drivers of the carbon fixation by plants is needed to better predict how such ecosystems will respond to climate change. Here, for the first time, a large dataset collected through the FLUXNET network is used to estimate how the gross primary production (GPP) of different Mediterranean ecosystems was affected by air temperature and precipitation between the years 1996 and 2013. We showed that annual precipitation was not a significant driver of annual GPP. Our results also indicated that seasonal variations of air temperature significantly affected seasonal variations of GPP but without major impact on inter annual variations. Inter-annual variations of GPP seemed largely controlled by the precipitation during early spring (March-April), making this period crucial for the future of Mediterranean ecosystems. Finally, we also observed that the sensitivity of GPP in Mediterranean ecosystems to climate drivers is not ecosystem type dependent. [ABSTRACT FROM AUTHOR]

Winter (October to March) precipitation δ18OP and δDP values in central Europe correlate with the winter North Atlantic Oscillation index (wNAOi), but the causal mechanisms remain poorly understood. Here we analyse the relationships between precipitation-weighted δ18OP and δDP datasets (δ18Opw and δDpw) from European GNIP and ANIP stations and the wNAOi, with a focus on isotope gradients. We demonstrate that longitudinal δ18Opw and δDpw gradients across Europe ("continental effect") depend on the wNAOi state, with steeper gradients associated with more negative wNAOi states. Changing gradients reflect a combination of air temperature and variable amounts of precipitable water as a function of the wNAOi. The relationships between the wNAOi, δ18Opw and δDpw can provide additional information from palaeoclimate archives such as European speleothems that primarily record winter δ18Opw. Comparisons between present-day and past European longitudinal δ18O gradients inferred from Holocene speleothems suggest that atmospheric pressure configurations akin to negative wNAO modes dominated the early Holocene, whereas patterns resembling positive wNAO modes were more common in the late Holocene, possibly caused by persistent shifts in the relative locations of the Azores High and the Icelandic Low. [ABSTRACT FROM AUTHOR]

A 9 yr air quality simulation is conducted from 2000 to 2008 over Europe using the Polyphemus/Polair3D chemical-transport model (CTM) and then evaluated against the measurements of the European Monitoring and Evaluation Programme (EMEP). The spatial distribution of PM2.5 over Europe shows high concentrations over northern Italy (36 µgm-3) and some areas of Eastern Europe, France, and Benelux, and low concentrations over Scandinavia, Spain, and the easternmost part of Europe. PM2.5 composition differs among regions. The operational evaluation shows satisfactory model performance for ozone (O3). PM2.5, PM10, and sulfate (SO=4 ) meet the performance goal of Boylan and Russell (2006). Nitrate (NO-3 ) and ammonium (NH+4 ) are overestimated, although NH+4 meets the performance criterion. The correlation coefficients between simulated and observed data are 63% for O3, 57% for PM10, 59% for PM2.5, 57% for SO=4, 42% for NO-3, and 58% for NH+4 . The comparison with other recent 1 yr model simulations shows that all models overestimate nitrate. The performance of PM2.5, sulfate, and ammonium is comparable to that of the other models. The dynamic evaluation shows that the response of PM2.5 to changes in meteorology differs depending on location and the meteorological variable considered. Wind speed and precipitation show a strong negative day-to-day correlation with PM2.5 and its components (except for sea salt, which shows a positive correlation), which tends towards 0 as the day lag increases. On the other hand, the correlation coefficient is near constant for temperature, for any day lag and PM2.5 species, but it may be positive or negative depending on the species and, for sulfate, depending on the location. The effects of precipitation and wind speed on PM2.5 and its components are better reproduced by the model than the effects of temperature This is mainly due to the fact that temperature has different effects on the PM2.5 components, unlike precipitation and wind speed, which impact most of the PM2.5 components in the same way. These results suggest that state-of-the-science air quality models reproduce satisfactorily the effect of meteorology on PM2.5 and therefore are suitable to investigate the effects of climate change on particulate air quality, although uncertainties remain concerning semivolatile PM2.5 components. [ABSTRACT FROM AUTHOR]

PMCAMx-2008, a three dimensional chemical transport model (CTM), was applied in Europe to quantify the changes in fine particle (PM2.5) concentration in response to different emission reductions as well as to temperature increase. A summer and a winter simulation period were used, to investigate the seasonal dependence of the PM2.5 response to 50% reductions of sulfur dioxide (SO2), ammonia (NH3), nitrogen oxides (NOx), anthropogenic volatile organic compounds (VOCs) and anthropogenic primary organic aerosol (POA) emissions and also to temperature increases of 2.5 and 5 K. Reduction of NH3 emissions seems to be the most effective control strategy for reducing PM2.5, in both periods, resulting in a decrease of PM2.5 up to 5.1 μgm.3 and 1.8 μgm.3 (5.5% and 4% on average) during summer and winter respectively, mainly due to reduction of ammonium nitrate (NH4NO3) (20% on average in both periods). The reduction of SO2 emissions decreases PM2.5 in both periods having a significant effect over the Balkans (up to 1.6 μgm.3) during the modeled summer period, mainly due to decrease of sulfate (34% on average over the Balkans). The anthropogenic POA control strategy reduces total OA by 15% during the modeled winter period and 8% in the summer period. The reduction of total OA is higher in urban areas close to its emissions sources. A slight decrease of OA (8% in the modeled summer period and 4% in the modeled winter period) is also predicted after a 50% reduction of VOCs emissions due to the decrease of anthropogenic SOA. The reduction of NOx emissions reduces PM2.5 (up to 3.4 μgm.3) during the summer period, due to a decrease of NH4NO3, causing although an increase of ozone concentration in major urban areas and over Western Europe. Additionally, the NOx control strategy actually increases PM2.5 levels during the winter period, due to more oxidants becoming available to react with SO2 and VOCs. The increase of temperature results in a decrease of PM2.5 in both periods over Central Europe, mainly due to a decrease of NH4NO3 during summer (18 %) and fresh POA during wintertime (35 %). Significant increases of OA are predicted during the summer due mainly to the increase of biogenic VOC emissions. On the contrary, OA is predicted to decrease in the modeled winter period due to the dominance of fresh POA reduction and the small biogenic SOA contribution to OA. The resulting increase of oxidant levels from the temperature rise lead to an increase of sulfate levels in both periods, mainly over North Europe and the Atlantic Ocean. The substantial reduction of PM2.5 components due to emissions reductions of their precursors outlines the importance of emissions for improving air quality, while the sensitivity of PM2.5 concentrations to temperature changes indicate that climate interactions need to be considered when predicting future levels of PM, with different net effects in different parts of Europe. [ABSTRACT FROM AUTHOR]

We present here a dynamical method for modelling temporal and geographical variations in ammonia emissions in regional-scale chemistry transport models (CTMs) and chemistry climate models (CCMs). The method is based on the meteorology in the models and gridded inventories. We use the dynamical method to investigate the spatiotemporal variability of ammonia emissions across part of Europe and study how these emissions are related to geographical and year-to-year variations in atmospheric temperature alone. For simplicity we focus on the emission from a storage facility related to a standard Danish pig stable with 1000 animals and display how emissions from this source would vary geographically throughout central and northern Europe and from year to year. In view of future climate changes, we also evaluate the potential future changes in emission by including temperature projections from an ensemble of climate models. The results point towards four overall issues. (1) Emissions can easily vary by 20 % for different geographical locations within a country due to overall variations in climate. The largest uncertainties are seen for large countries such as the UK, Germany and France. (2) Annual variations in overall climate can at specific locations cause uncertainties in the range of 20%. (3) Climate change may increase emissions by 0-4-0 % in central to northern Europe. (4) Gradients in existing emission inventories that are seen between neighbour countries (e.g. between the UK and France) can be reduced by using a dynamical methodology for calculating emissions. Acting together these four factors can cause substantial uncertainties in emission. Emissions are generally considered among the largest uncertainties in the model calculations made with CTM and CCM models. Efforts to reduce uncertainties are therefore highly relevant. It is therefore recommended that both CCMs and CTMs implement a dynamical methodology for simulating ammonia emissions in a similar way as for biogenic volatile organic compound (BVOCs) - a method that has been used for more than a decade in CTMs. Finally, the climate penalty on ammonia emissions should be taken into account at the policy level such as the NEC and IPPC directives. [ABSTRACT FROM AUTHOR]

The longest six instrumental temperature records of monthly means reach back maximally to 1757AD and were recorded in Europe. All six show a V-shape, with temperature drop in the 19th and rise in the 20th century. Proxy temperature time series of Antarctic ice cores show this same characteristic shape, indicating this pattern as a global phenomenon. We used the mean of the six instrumental records for analysis by discrete Fourier transform (DFT), wavelets, and the detrended fluctuation analysis (DFA). For comparison, a stalagmite record was also analyzed by DFT. The harmonic decomposition of the abovementioned mean shows only six significant frequencies above periods over 30 yr. The Pearson correlation between the mean, smoothed by a 15-yr running average (boxcar) and the reconstruction using the six significant frequencies, yields r = 0.961. This good agreement has a > 99.9% confidence level confirmed by Monte Carlo simulations. It shows that the climate dynamics is governed at present by periodic oscillations. We find indications that observed periodicities result from intrinsic dynamics. [ABSTRACT FROM AUTHOR]

The heat of summer 2003 in Western and Central Europe was claimed to be unprecedented since the Middle Ages on the basis of grape harvest data (GHD) and late wood maximum density (MXD) data from trees in the Alps. This paper shows that the authors of these studies overlooked the fact that the heat and drought in Switzerland in 1540 likely exceeded the amplitude of the previous hottest summer of 2003, because the persistent temperature and precipitation anomaly in that year, described in an abundant and coherent body of documentary evidence, severely affected the reliability of GHD and tree-rings as proxy-indicators for temperature estimates. Spring-summer (AMJJ) temperature anomalies of 4.7 ℃ to 6.8 ℃ being significantly higher than in 2003 were assessed for 1540 from a new long Swiss GHD series (1444 to 2011). During the climax of the heat wave in early August the grapes desiccated on the vine, which caused many vine-growers to interrupt or postpone the harvest despite full grape maturity until after the next spell of rain. Likewise, the leaves of many trees withered and fell to the ground under extreme drought stress as would usually be expected in late autumn. It remains to be determined by further research whether and how far this result obtained from local analyses can be spatially extrapolated. Based on the temperature estimates for Switzerland it is assumed from a great number of coherent qualitative documentary evidence about the outstanding heat drought in 1540 that AMJJ temperatures were likely more extreme in neighbouring regions of Western and Central Europe than in 2003. Considering the significance of soil moisture deficits for record breaking heat waves, these results still need to be validated with estimated seasonal precipitation. It is concluded that biological proxy data may not properly reveal record breaking heat and drought events. Such assessments thus need to be complemented with the critical study of contemporary evidence from documentary sources which provide coherent and detailed data about weather extremes and related impacts on human, ecological and social systems [ABSTRACT FROM AUTHOR]

In this study, we compare annual fluxes of methane (CH4), nitrous oxide (N2O) and soil respiratory carbon dioxide (CO2) measured at nine European peatlands (n = 4) and shrublands (n = 5). The sites range from northern Sweden to Spain, covering a span in mean annual air temperature from 0 to 16 °C, and in annual precipitation from 300 to 1300mmyr-1. The effects of climate change, including temperature increase and prolonged drought, were tested at five shrubland sites. At one peatland site, the long-term (>30 yr) effect of drainage was assessed, while increased nitrogen deposition was investigated at three peatland sites. The shrublands were generally sinks for atmospheric CH4, whereas the peatlands were CH4 sources, with fluxes ranging from --519 to +6890 mgCH4-Cm-2 yr-1 across the studied ecosystems. At the peatland sites, annual CH4 emission increased with mean annual air temperature, while a negative relationship was found between net CH4 uptake and the soil carbon stock at the shrubland sites. Annual N2O fluxes were generally small ranging from --14 to 42 mgN2O-Nm-2 yr-1. Highest N2O emission occurred at the sites that had highest nitrate (NO3-) concentration in the soil water. Furthermore, experimentally increased NO3- deposition led to increased N2O efflux, whereas prolonged drought and long-term drainage reduced the N2O ef- flux. Soil CO2 emissions in control plots ranged from 310 to 732 gCO2-Cm-2 yr-1. Drought and long-term drainage generally reduced the soil CO2 efflux, except at a hydric shrubland where drought tended to increase soil respiration. In terms of fractional importance of each greenhouse gas to the total numerical global warming response, the change in CO2 efflux dominated the response in all treatments (ranging 71--96 %), except for NO3- addition where 89% was due to change in CH4 emissions. Thus, in European peatlands and shrublands the effect on global warming induced by the investigated anthropogenic disturbances will be dominated by variations in soil CO2 fluxes. [ABSTRACT FROM AUTHOR]

A simulation of the last millennium is compared to a recent spatio-temporal reconstruction of summer temperature over Europe. The focus is on the response to solar forcing over the pre-industrial era. Although the correlation between solar forcing and the reconstruction remains small, the spatial regression over solar forcing shows statistically significant regions. The meridional pattern of this regression is found to be similar in the model and in the reconstruction. This pattern exhibits a large warming over Northern and Mediterranean Europe and a lesser amplitude response over Central and Eastern Europe. The mechanisms explaining this pattern in the simulation are mainly related to evapotranspiration fluxes. It is shown that the evapotranspiration is larger in summer over Central and Eastern Europe when solar forcing increases, while it decreases over the Mediterranean area. The explanation for the evapotranspiration increase over Central and Eastern Europe is found in the increase of winter precipitation there, leading to a soil moisture increase in spring. As a consequence, the evapotranspiration is larger in summer, which leads to an increase in cloud cover over this region, reducing the surface shortwave flux there and leading to less warming. Over the Mediterranean area, the surface shortwave flux increases with solar forcing, the soil becomes dryer and the evapotranspiration is reduced in summer leading to a larger increase in temperature. This effect appears to be overestimated in the model as compared to the reconstruction. Finally, the warming of Northern Europe is related to the albedo feedback due to sea-ice cover retreat with increasing solar forcing. [ABSTRACT FROM AUTHOR]

This study originated from recent results reported in literature, which support the existence of long-range (power-law) persistence in atmospheric temperature fluctuations on monthly and inter-annual scales. We investigated the results of Detrended Fluctuation Analysis (DFA) carried out on twenty-two historical daily time series recorded in Europe in order to evaluate the reliability of such findings in depth. More detailed inspections emphasized systematic deviations from power-law and high statistical confidence for functional form misspecification. Rigorous analyses did not support scale-free correlation as an operative concept for Climate modelling, as instead suggested in literature. In order to understand the physical implications of our results better, we designed a bivariate Markov process, parameterised on the basis of the atmospheric observational data by introducing a slow dummy variable. The time series generated by this model, analysed both in time and frequency domains, tallied with the real ones very well. They accounted for both the deceptive scaling found in literature and the correlation details enhanced by our analysis. Our results seem to evidence the presence of slow fluctuations from another climatic sub-system such as ocean, which inflates temperature variance up to several months. They advise more precise re-analyses of temperature time series before suggesting dynamical paradigms useful for Climate modelling and for the assessment of Climate Change. [ABSTRACT FROM AUTHOR]

The European heat wave of July 2006 was caused by advection of very hot and dry air from North Africa. Air masses were transported on the western edge of the high pressure system, centred over Eastern Europe, resulting in exceptionally high air temperatures over large areas of the continent. In the first two weeks of July 2006 a severe heat wave affected Central and North-Eastern Europe. We present a synoptic analysis of the July 2006 European heat wave, resulting formation and transport of photooxidants over Europe as simulated by the on-line tropospheric chemistry model GEM-AQ. The model was executed on a global variable grid with ∼15 km resolution over the entire European continent. Modelling results have been compared with surface observations and vertical soundings of meteorological and air quality parameters. We find that the calculated error measures, as well as analysis of time series and trends for selected quantities, indicate good model performance over the simulation period. The spatial pattern of two exposure indicators - SOMO35 and AOT40 - showed similarities with the high temperatures distribution. The zone of highest exposure was located over Central Europe along the advection path of the hot African air mass. The exposure to high ozone concentrations in higher latitudes was reduced by the dilution and aging of polluted air masses advected from over Central Europe. [ABSTRACT FROM AUTHOR]

Local-scale climate information is increasingly needed for the study of past, present and future climate changes. In this study we develop a non-linear statistical downscaling method to generate local temperatures and precipitation values from large-scale variables of a Earth System Model of Intermediate Complexity (here CLIMBER). Our statistical downscaling scheme is based on the concept of Generalized Additive Models (GAMs), capturing nonlinearities via non-parametric techniques. Our GAMs are calibrated on the present Western Europe climate. For this region, annual GAMs (i.e. models based on 12 monthly values per location) are fitted by combining two types of largescale explanatory variables: geographical (e.g. topographical information) and physical (i.e. entirely simulated by the CLIMBER model). To evaluate the adequacy of the non-linear transfer functions fitted on the present Western European climate, they are applied to different spatial and temporal large-scale conditions. Local projections for present North America and Northern Europe climates are obtained and compared to local observations. This partially addresses the issue of spatial robustness of our transfer functions by answering the question "does our statistical model remain valid when applied to large-scale climate conditions from a region different from the one used for calibration?". To asses their temporal performances, local projections for the Last Glacial Maximum period are derived and compared to local reconstructions and General Circulation Model outputs. Our downscaling methodology performs adequately for the Western Europe climate. Concerning the spatial and temporal evaluations, it does not behave as well for Northern America and Northern Europe climates because the calibration domain may be too different from the targeted regions. The physical explanatory variables alone are not capable of downscaling realistic values. However, the inclusion of geographical-type variables - such as altitude, advective continentality and moutains effect on wind (W-slope) - as GAM explanatory variables clearly improves our local projections. [ABSTRACT FROM AUTHOR]

The temperatures in large parts of Europe have been record high during the meteorological autumn of 2006. Compared to 1961-1990, the 2 m temperature was more than three degrees Celsius above normal from the North side of the Alps to southern Norway. This made it by far the warmest autumn on record in the United Kingdom, Belgium, the Netherlands, Denmark, Germany and Switzerland, with the records in Central England going back to 1659, in the Netherlands to 1706 and in Denmark to 1768. The deviations were so large that under the obviously false assumption that the climate does not change, the observed temperatures for 2006 would occur with a probability of less than once every 10 000 years in a large part of Europe, given the distribution defined by the temperatures in the autumn 1901-2005. A better description of the temperature distribution is to assume that the mean changes proportional to the global mean temperature, but the shape of the distribution remains the same. This includes to first order the effects of global warming. Even under this assumption the autumn temperatures were very unusual, with estimates of the return time of 200 to 2000 years in this region. The lower bound of the 95% confidence interval is more than 100 to 300 years. Apart from global warming, linear effects of a southerly circulation are found to give the largest contributions, explaining about half of the anomalies. SST anomalies in the North Sea were also important along the coast. Climate models that simulate the current atmospheric circulation well underestimate the observed mean rise in autumn temperatures. They do not simulate a change in the shape of the distribution that would increase the probability of warm events under global warming. This implies that the warm autumn 2006 either was a very rare coincidence, or the local temperature rise is much stronger than modelled, or non-linear physics that is missing from these models increases the probability of warm extremes. [ABSTRACT FROM AUTHOR]

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]

Groundwater is the primary source of water supply for sustaining the lives of billion ofpeople and surrounding ecosystems around the Globe. Climate change and variabilitythreaten the sustainable use of renewable groundwater resources in many regions across theWorld. Yet the assessment on the effects of global warming on projected estimates ofrenewable groundwater resources and uncertainties surrounding those estimates at alocally relevant scale is lacking. Here, we provide a comprehensive, continental-scaleassessment of past, present, and future changes in renewable groundwater resources(as a form of groundwater recharge after being suitably aggregated to longer timescales) across Europe at an unprecedented spatial resolution of (5 X 5) km2 andlocal groundwater bodies as per the European Water Framework Directive (WFD).Specifically our aim here is to understand the response of Europe-wide groundwaterresources to different global warming levels in accordance to 2015 IPCC Parisagreement. Our analyses are based on multi-model ensemble simulations from theEDgE1 and HOKLIM2 projects (funded by ECMWF and BMBF-Germany) whichcomprises of four hydrologic and land-surface models (HMs: mHM, Noah-MP,PCR-GLOBWB, and VIC) driven by a suitably downscaled, observation basedE-OBS forcing data for the historical records (1950-2015) and five bias correctedCMIP5 GCMs datasets for the near-past to future climate conditions (1970-2100)under three representative concentration pathways (RCPs: 2.6, 6.0, and 8.5). Atime-sampling approach is applied to identify 30-year periods with distinct warming levelscorresponding to global surface air temperature increase of 1.5, 2.0, and 3.0 K compared tothe pre-industrial levels. We contrast the changes in the multi-model ensemblerecharge between the periods of distinct warming levels and to the contemporaryconditions (1971-2000). Our analyses show a clear North-South gradient of changes inmean annual recharge across Europe with declining trends being observed in theMediterranean region, and increased availability of groundwater resources in theNorth Scandinavian region with increased warming (at end of the Century). Thecontinental part of the Europe shows relatively lower changes in the mean renewablegroundwater resources. A greater sensitivity/amplifications in changes are noticed in theMediterranean region to the response of increased warming levels. Though limited, but ourensemble simulations allow disentangling the different sources of uncertainties(HMs vs. GCMs) – which generally pointed out a larger chunk of uncertainty inmodeling results arises due to differences among GCMs (forcings); but there are clearlyareas where the uncertainty due to (different process representation of) HMs issubstantial, and can not be neglected. Overall, our study underscores the need formulti-model ensembles for the assessment of future changes in renewable groundwaterresources across Europe, and discuss about related impacts avoided in higher warmingworlds. 1. www.edge.climate.copernicus.eu 2. www.ufz.de/hoklim [ABSTRACT FROM AUTHOR]

Climate change is expected to affect substantially future water availability and temperature across many watersheds in Europe potentially impacting hydropower generation and cooling efficiency of thermo-nuclear power plants. On the other hand, increasing Renewable Energy Sources (RES) penetration will substantially modify energy portfolios across Europe. As a consequence, prices will become more volatile, requiring more system flexibility. This study aims to explore the following key questions for supporting the definition and implementation of EU transition policies driving investments in the energy sector: 1) How climate change impacts on the hydrological system propagate to the energy system? 2) Can hydropower provide additional flexibility to a high RES-based energy system? To answer these questions, we developed an integrated modelling approaches combining a conceptual hydrological model (HBV) and an energy system model (PRIMES-IEM). Based on daily air temperature and precipitation, HBV computes daily streamflow for each power plant. Water temperature is obtained from air temperature using an empirical formula. These two variables are used to define the constraints to the energy model PRIMES-IEM, a power market simulator of the European electricity markets.Our analysis focuses on Iberian Peninsula and Danube region in 2040. Both regions' energy mix have a significant share of hydropower and rely significantly on thermo-nuclear power plants. In addition, both systems have already been under stress conditions due to heatwaves and droughts over the last years. On the climate side, we downscaled projected air temperature and precipitation projections for the RCP2.6 and RCP8.5 scenarios, covering the full range of possible climate futures from very low emission pathways to very high ones. On the energy side, we also consider two scenarios representative of the current system and of a future decarbonized system complying with European climate targets at 2030 and 2050. Despite some differences across the two regions, numerical results suggest some general trends: hot and dry climate futures significantly impact on the energy system because either increasing water temperature produces heavy stress due to thermonuclear generation curtailment or declining water availability limits hydropower generation forcing the energy system to shift to other technologies in order to maintain its reliability. [ABSTRACT FROM AUTHOR]

The extratropical cyclone is one of the basic systems that characterize the weather and climate in mid-latitude areas, where the mean meridional temperature gradient is large. As for in Europe's middle or higher latitude areas. Although the climatological mean meridional gradient of the air temperature there is rather weak compared to that from autumn to spring around Japan in East Asia, many extratropical cyclones appear throughout a year. Thus it would still be necessary to re-examine the seasonal cycle of the daily cyclone and anticyclone activities around Europe, paying attention also to their intraseasonal variations and the effects on the behaviors of daily cyclone and anticyclone systems together with the variety of their characteristics. Our previous case studies for 2000 (Kuwana et al., EGU2017 and 2018) pointed out that daily cyclones and anticyclones were greatly reflected by the alternation of the intraseasonal-scale ones with equivalent barotropic structure in northwestern Europe in summer. In addition, the intraseasonal and daily behaviors of the Icelandic low in the seasonal cycle showed the seasonal progression from autumn to the next spring.The present study will further examine the detailed features on the above mentioned topics, together with their relationship to the weather conditions in Europe, mainly based on the NCEP/NCAR re-analysis data. From late May to August, intraseasonal-scale low and high areas (as for the deviation fields) with the equivalent barotropic structure extended from the Norwegian Sea to Northern Germany. In the negative deviation period (stage with the intraseasonal-scale low there), baroclinic zone in the lower layer just on the south of that low was periodically enhanced. It is interesting that, in one of the negative periods, the southward shift of intraseasonal-scale baroclinic zone seemed to be related to the temporal activity of baroclinic ibstability wave cyclones, or the rather lower air temperature stage in central Europe. The detailed description on there will be made at the poster presentation. As for the asymmetric seasonal progression, not only the differences of intraseasonal features of the Icelandic lows between the former half and latter half of winter as shown in EGU2018, but also the differences of the daily variations between early summer and early autumn were notable. As for early autumn, amplitude of the short-period SLP variation in northern Europe, corresponding to the temporal appearance of the "Icelandic low-like" cyclone with relatively short persistency, increased greatly one month earlier than the formation timing of the seasonal mean Icelandic low in middle October. Interestingly, that event occurred just when the air temperature began to decrease seasonally. [ABSTRACT FROM AUTHOR]