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Extreme thermal conditions have been known for a long time as is evidenced by the oldest preserved historical accounts referring to weather. However, direct data, that is, air temperature measurements, which began in Europe in the 17th century, are the only reliable source of information. They provide insight into how climate evolved over the characteristic period of the climate timeline known as the Little Ice Age. This study focuses on extreme climatic phenomena, referred to here as exceptionally cold (EC) and exceptionally warm (EW) months and seasons that occurred in the early instrumental period (until 1830). The research is based on average monthly air temperature values (of different lengths) from five meteorological stations in Europe. The Central England Temperature series (CET) offers the longest series that spans 172 years whereas Padua has the shortest, 57 years. Consequently, the year 1659, which is the start date of the Central England Temperature series, marks the beginning of the study period for the research presented in this article. Thermally anomalous periods are identified based on the standard deviation of the average temperature from the corresponding long‐term average (1831–2020). The highlights of the study include the identification of the pronounced prevalence at all five stations of EC months and seasons when compared to EW months and seasons, especially in Western Europe (CET) during the Maunder Minimum. The study also finds a lack of synchronicity in the timing of the anomalous periods under investigation in the different parts of Europe. [ABSTRACT FROM AUTHOR]

Based on the ERA5 reanalysis since the 1950s, this study investigates the coherent inter‐decadal variations of the winter continental surface air temperature (SAT) between the Eurasian (EUA) and the North American continents in the past 70 years. The SAT variation over the two continents can be characterized with five typical periods successively from a 'both‐warmer' (1950s–1960s), to a 'both‐colder' (1960s–1980s), and then a 'EUA‐warmer' (1980s–1990s) followed by another 'both‐warmer' (1990s–2000s) and a 'EUA‐colder' (2000s–2010s) period. Such periodic variation of the SAT is closely coupled with changes of the low isentropic‐level meridional mass transport (IMMT), as manifested by the coupling relationship between the midlatitude SAT and the net IMMT out of the polar circle, in terms of their zonal patterns and geographical patterns. The SAT variation can be well reconstructed with the first two leading maximum covariance analysis (MCA) modes between the SAT and IMMT. The first leading MCA mode (MCA1) mainly dominates a 'EUA‐warmer/colder' pattern, while the second (MCA2) dominates the 'both‐warmer/colder' pattern. There exists a significant lead–lag correlation between the MCA1 and MCA2, which determines the changing SAT pattern in the five successive periods. Furthermore, the MCA1 and MCA2, especially their lead–lag coupling after the 1975 is significantly associated with the Pacific decadal oscillation (PDO) which dominates the much‐intensified MCA1 and the related 'EUA‐warmer/colder' SAT pattern since then. The Atlantic multi‐decadal oscillation mainly dominates the third leading MCA mode with it's effects on the SAT over Europe coincidently to amplify the PDO‐related SAT changes. [ABSTRACT FROM AUTHOR]

The CMIP6 projections constitute the basis of our latest understanding of the climate response to anthropogenic forcing. However, there is still considerable uncertainty in the projections, especially at the regional scale. One way to constrain the uncertainty is by comparing the models historical climate change signals against observations and investigate the physical reasons for divergences. Here, we assess the signal‐to‐noise ratio (S/N) of surface air temperature (SAT), precipitation (PREC) and soil moisture (SM) over Europe for a set of CMIP6 historical simulations and compare them against the E‐OBS observational product and the ERA5 reanalysis. We found considerable divergences between the CMIP6 ensemble mean S/N and that of E‐OBS and ERA5, as well as between ERA5 and E‐OBS. The latter indicates that the S/N is affected by data coverage. We show that the differences among model signals are associated with different atmospheric circulation responses. We also investigate the potential relationships between the models' signals and climatological biases, and we found evidence that the models with a warm climatological bias in southern Europe tend to have smaller SAT signals (warm less). Finally, we found no apparent relationship between SM biases and the warming signal, suggesting that the mechanism by which SM–atmosphere interactions affect climate variability does not explain the mean changes. However, there is a tendency for models with higher SM to dry faster than models with lower SM. [ABSTRACT FROM AUTHOR]

North Atlantic Oscillation (NAO) has a significant impact on surrounding winter weather and climate. However, the causes of its occasional reversal between early and late winter remain unclear. This study proposes a mechanism for the mid‐winter reversal of NAO from the perspective of local midlatitude air‐sea interaction. Strong sea surface temperature (SST) tripole events, which are defined by empirical orthogonal function of winter‐mean interannual North Atlantic SST anomalies, are primarily induced by NAO in early winter and peak in January. In late winter, the persistent SST tripole exerts active feedback on atmosphere through diabatic heat and transient eddy forcing. The resulting atmospheric circulation anomalies exhibit an almost reversed NAO pattern in February, which forms a wavetrain originating above the Gulf Stream and propagating to the Middle East and weakens the former SST tripole. Consequently, significant reversals of air temperature anomalies occur in Europe and the Caspian Sea area between February and December. Plain Language Summary: The North Atlantic Oscillation (NAO) is a crucial atmospheric system that significantly impacts the weather and climate of the surrounding regions during winter. However, it often reverses between early and late winter, and the reasons for its mid‐winter reversal remain unclear. The NAO behavior can be influenced by multiple factors, such as atmospheric internal processes, underlying surface, and remote climate system, which makes the issue more complex. This study highlights the role of underlying sea surface temperature anomalies (SSTAs) in the mid‐winter reversal of NAO. The North Atlantic SSTAs are closely associated with the NAO and exhibit a tripole pattern. For strong sea surface temperature (SST) tripole events, the NAO primarily induces the early winter North Atlantic SST tripole. The SSTAs develop in early winter, peak in January, and feedback on the atmospheric circulation in late winter. The atmospheric circulation anomalies exhibit an almost reversed NAO pattern in February, forming a wavetrain that propagates above the Gulf Stream to the Middle East. As a result, during the warm phase of the SST tripole, Europe experiences colder temperatures, and the Caspian Sea experiences warmer temperatures in February than usual, as opposed to the positive NAO's control over warm Europe and cold Caspian Sea in December. Key Points: In early winter, North Atlantic Oscillation (NAO) forces a North Atlantic sea surface temperature (SST) tripole, which persists and tends to induce a nearly reversed NAO pattern in FebruarySST tripole induces a wavetrain over the Gulf Stream to the Middle East via diabatic heating and transient eddy forcing in FebruaryAs a result, there are remarkable reversals of air temperature anomalies in Europe and Caspian Sea area between February and December [ABSTRACT FROM AUTHOR]

This study examines the European heatwaves' predictability at subseasonal timescales. Land surface feedbacks and tropical convection, due to their variability at intraseasonal timescales, are taken into consideration and their potential role in extending the predictability beyond the medium range (10 days) is explored. A classification of European heatwaves into five heatwave types is used to discriminate the effects of surface feedbacks and of tropical variability among the different heatwave types. The classification is computed in terms of circulation patterns. By inferring the near‐surface temperature through atmospheric circulation, we aim to identify the predictable component of the heatwave events. All five heatwave circulation patterns are characterized by persistent anticyclonic anomalies located over the region with maximum temperatures. We show that soil moisture deficit is not a required precondition for the occurrence of heatwaves over most of Europe. However, heatwave events over southern Europe exhibit some sensitivity to dry conditions. We use a simplified index to describe the dominant mode of tropical convection at intraseasonal timescales. The index, based on precipitation anomalies, represents the evolution of the Boreal Summer Intraseasonal Oscillation (BSISO). We find that episodes with strong BSISO amplitudes characterized by enhanced convection over India, Bay of Bengal and China sea favour the occurrence of heatwave events over Russia. The results highlight the role of tropical intraseasonal variability in enhancing the predictability of some extreme temperature events over Europe. [ABSTRACT FROM AUTHOR]

The onset of periods with very high or low air temperatures has aroused general interest for a long time, which is understandable since it has many dangerous effects directly affecting humans. Such perilous climatic phenomena include exceptionally cold and exceptionally warm months, which this study investigates for all Europe and for its five physico‐geographic regions over the 190‐year period of 1831–2020. Therefore, the research in this paper includes two periods characteristic of the history of climate – the late Little Ice Age (LIA) and present‐day warming. The studies are based on average monthly air temperature values from 40 weather stations in Europe. In this paper, exceptionally cold months (ECMs) or exceptionally warm months (EWMs) are considered to have occurred when the average air temperature at a station differed from the respective long‐term average by at least two standard deviations. The highlights of the study include the identification of a drop in the number of ECMs by 20 over the entire 190‐year period, and a highly statistically significant increase in EWMs by 44 between 1980 and 2020. These changes proceeded with different intensities from one physico‐geographic region of Europe to another. [ABSTRACT FROM AUTHOR]

Future global temperature change will have significant effects on society and ecosystems. Earth system models (ESM) are the primary tools to explore future climate change. However, ESMs have great uncertainty and often run at a coarse spatial resolution (usually about 2°). Accurate high‐spatial‐resolution temperature dataset are needed to improve our understanding of temperature variations and for many other applications. We apply Super resolution (SR) in computer vision using deep learning (DL) to merge 31 ESMs data. The proposed method performs data merging, bias‐correction, and spatial downscaling simultaneously. The CRU TS (Climate Research Unit gridded Time Series) data is used as reference data in the model training process. To find a suitable DL method, we select five SR methodologies with different structures. We compare the performances of the methods based on mean square error (MSE), mean absolute error (MAE) and Pearson correlation coefficient (R). The best method is used to merge the projected monthly data (1850–1900), and monthly future scenarios data (2015–2100), at the high spatial resolution of 0.5°. Results show that the merged data have considerably improved performance compared with individual ESM data and their ensemble mean (EM), both spatially and temporally. The MAE shows significant improvement; the spatial distribution of the MAE widens along the latitudes in the Northern Hemisphere. The MAE of merged data is ranging from 0.60 to 1.50, the South American (SA) has the lowest error and the Europe has the highest error. The merged product has excellent performance when the observation data is smooth with few fluctuations in the time series. This work demonstrates the applicability and effectiveness of the DL methods in data merging, bias‐correction and spatial downscaling when enough training data are available. Data can be accessed at https://doi.org/10.5281/zenodo.5746632. [ABSTRACT FROM AUTHOR]

Future global temperature change will have significant effects on society and ecosystems. Earth system models (ESM) are the primary tools to explore future climate change. However, ESMs have great uncertainty and often run at a coarse spatial resolution (usually about 2°). Accurate high‐spatial‐resolution temperature dataset are needed to improve our understanding of temperature variations and for many other applications. We apply Super resolution (SR) in computer vision using deep learning (DL) to merge 31 ESMs data. The proposed method performs data merging, bias‐correction, and spatial downscaling simultaneously. The CRU TS (Climate Research Unit gridded Time Series) data is used as reference data in the model training process. To find a suitable DL method, we select five SR methodologies with different structures. We compare the performances of the methods based on mean square error (MSE), mean absolute error (MAE) and Pearson correlation coefficient (R). The best method is used to merge the projected monthly data (1850–1900), and monthly future scenarios data (2015–2100), at the high spatial resolution of 0.5°. Results show that the merged data have considerably improved performance compared with individual ESM data and their ensemble mean (EM), both spatially and temporally. The MAE shows significant improvement; the spatial distribution of the MAE widens along the latitudes in the Northern Hemisphere. The MAE of merged data is ranging from 0.60 to 1.50, the South American (SA) has the lowest error and the Europe has the highest error. The merged product has excellent performance when the observation data is smooth with few fluctuations in the time series. This work demonstrates the applicability and effectiveness of the DL methods in data merging, bias‐correction and spatial downscaling when enough training data are available. Data can be accessed at https://doi.org/10.5281/zenodo.5746632. [ABSTRACT FROM AUTHOR]

The study specifies the circulation conditions, the frequency of occurrence, long‐term changes, and thermal characteristics of air masses over east‐central Europe in the years 1951–2020. The division of air masses utilized by The Polish Institute of Meteorology and Water Management was used, where, based on the geographical location of the source areas, Arctic (A), Polar maritime fresh (mPf), Polar maritime old (transformed) (mPo), Polar maritime warm (mPw), Polar continental (cP), and Tropical (T) air masses are distinguished. It has been shown that western circulation dominates in this area (60% of days on average), during which the advection of maritime air masses occurs. The share of Arctic air mass flowing from the north (about 12% of days a year) and Tropical air mass from the southern sector (4% of days) is clearly smaller. The results of the research have shown that the frequency of the majority of the analysed air masses was subject to short‐term changes in the studied period. On the other hand, long‐term changes in this frequency concerned two air masses flowing from lower latitudes (mPw and T). In the case of mPw, in the period 1951–2020 there was a significant increase in frequency, not only on a yearly basis, but also in all seasons. In the last two decades, the frequency of Tropical air mass has also increased significantly, while the increase took place only in the summer period. Therefore, the increase in air temperature recorded in east‐central Europe since the 1990s, mainly in the warm half of the year, should to a large extent be attributed to both the greater frequency of the inflow of air masses from lower latitudes (mPw and T) and the increase in temperature in virtually all separated air masses, which in turn is a result of progressing global warming. [ABSTRACT FROM AUTHOR]

The response of the Euro‐Atlantic wintertime circulation to climate change is deeply uncertain. The Atlantic jet is caught in a "tug‐of‐war" between rapid warming trends in both the tropics and the Arctic leading to debate over the changing "waviness" of the jet, which is subject to strong non‐linearity and internal variability. From the complementary perspective of weather regimes, there is considerable uncertainty in how atmospheric blocking will alter under climate change. By applying the hybrid approach of geopotential‐jet regimes to 6th phase of the coupled model inter‐comparison project projections, we show that the centers of action of anticyclonic regimes hardly alter even under severe warming. Instead, regimes are expected to become less persistent, with zonal flow conditions becoming more prevalent, although models disagree on the details of regime changes. Finally, we show the regime response can be captured qualitatively in a simple Lorenz‐like model, emphasizing the conceptual link between observed regimes and those in basic mathematical systems. Plain Language Summary: The impact of climate change on European weather can be broken into two components: a thermodynamic part relating to increasing air temperature and humidity, and a dynamic part relating to changes in the atmospheric circulation such as the direction and strength of prevailing winds. While the thermodynamic part is relatively well understood, the dynamic part is very uncertain and this is a major problem in constraining European climate projections. Looking at the winter season, we study the dynamic response of CMIP6 models under climate change using so‐called "regimes," and show that the types of prevailing circulation are not predicted to change strongly. However the regimes are projected to be less long lived. We also show that these features can be well captured in a simple 5 equation model of regime dynamics, providing a potentially useful tool for understanding regime systems in more detail. Key Points: The spatial structure of anticyclonic circulations over Europe are projected to stay the same under climate changeThe persistence of anticyclonic circulations are in general expected to decrease, although there is considerable inter‐model variabilityWe show that these qualitative features of the atmospheric response can be reproduced in a simple forced regime model [ABSTRACT FROM AUTHOR]

Variability of the North Atlantic Oscillation (NAO) drives wintertime temperature anomalies in the Northern Hemisphere. Dynamical seasonal prediction systems can skilfully predict the winter NAO. However, prediction of the NAO‐dependent air temperature anomalies remains elusive, partially due to the low variability of predicted NAO. Here, we demonstrate a hidden potential of a multi‐model ensemble of operational seasonal prediction systems for predicting wintertime temperature by increasing the variability of predicted NAO. We identify and subsample those ensemble members which are close to NAO index statistically estimated from initial autumn conditions. In our novel multi‐model approach, the correlation prediction skill for wintertime Central Europe temperature is improved from 0.25 to 0.66, accompanied by an increased winter NAO prediction skill of 0.9. Thereby, temperature anomalies can be skilfully predicted for the upcoming winter over a large part of the Northern Hemisphere through increased variability and skill of predicted NAO. Plain Language Summary: Wintertime temperature in the Northern Hemisphere is regulated by the variations of atmospheric pressure, represented by the so‐called North Atlantic Oscillation (NAO). The NAO's phase—negative or positive—is associated with the pathways of cold and warm air masses leading to cold or warm winters in Europe. While the NAO phase can be predicted well, predictions of the NAO‐dependent air temperature remain elusive. Specifically, it is challenging to predict the strength of the NAO, the most important requirement for the accurate prediction of wintertime temperature. Here, we improve wintertime temperature prediction by increasing the strength of the predicted NAO. We use observation based autumn Northern Hemisphere ocean and air temperature, as well as ice and snow cover for statistical estimation of the first guess NAO for the upcoming winter. Then, we sub‐select only those simulations from the multi‐model ensemble, which are consistent with our first guess NAO. As a result, based on these selected members, the wintertime temperature prediction is substantially improved over a large part of the Northern Hemisphere. Key Points: Amplitude and skill of predicted North Atlantic Oscillation (NAO) improve significantly by subsampling of ensemble of existing seasonal prediction systemsAmplified NAO variability leads to significant improvement in predicting the upcoming winter temperature anomalies in the Northern Hemisphere [ABSTRACT FROM AUTHOR]

Long‐term satellite land surface temperature (LST) data are desirable to augment 2m air temperatures (T2m) measured in situ and as an independent measure of surface temperature change. However, previous studies show variable agreement between LST and T2m time series. The objective of this study is to assess the stability and trends in six new LST data sets from the European Space Agency's Climate Change Initiative for LST (LST_cci). LST anomalies are compared with homogenized station T2m anomalies over Europe, which verifies all six data sets are well coupled (LST vs T2m anomaly correlations and slopes: 0.6–0.9). The temporal stability of the LST_cci data is assessed through a comparison with the T2m anomaly time series. Only the LST_cci data sets for the MODerate resolution Imaging Spectroradiometer (MODIS) onboard Aqua and the Advanced Along‐Track Scanning Radiometer (AATSR) appear stable; the MODIS/Terra, ATSR‐2, and multisensor InfraRed and MicroWave data sets show non‐climatic discontinuities associated with changes in sensor and/or drift over time. For MODIS/Aqua (2002–2018), significant trends in LST of 0.64–0.66 K/decade compare well with the equivalent T2m trends of 0.52–0.59 K/decade. The LST and T2m trends for AATSR (2002–2012) are found to be statistically insignificant, likely due to the comparatively short study period and specific years available for analysis. No evidence is found to suggest that trends calculated using cloud‐free InfraRed observations are affected by clear‐sky bias. This study suggests that satellite LST data can be used to assess warming trends over land and for other climate applications if the required homogeneity is assured. Plain Language Summary: Long‐term changes in surface temperature due to climate change are usually studied using near‐surface air temperatures (T2m) from weather stations. However, these data are not available everywhere and changes in T2m are poorly understood in some regions (e.g., parts of Africa). This study assesses the potential for satellite‐observed land surface temperatures (LST) to help fill these gaps. The study finds that LST and T2m provide very similar information on surface temperatures and therefore LST can provide useful information where T2m data are unavailable. However, some of the LST data sets are found to be "unstable" and suffer from jumps and changes over time that result from for example, changes in satellite instrument or a change in the orbit of the satellite platform. These unstable LST data sets cannot be used to measure changes in surface temperature. However, the study finds that for "stable" LST data sets, which do not suffer from these non‐climatic jumps and changes, the changes in LST over time are very similar to, or even the same as, the changes in T2m. Therefore, this work suggests that satellite LST data could be used to measure changes in surface temperature where there are not enough stations to make these measurements using T2m. Key Points: The stability of six satellite land surface temperature data sets is assessed using homogenized station air temperatures over EuropeOnly two data sets are stable; the other four show non‐climatic discontinuities associated with a change in sensor and/or drift over timeSignificant trends in land surface temperature of ∼0.65 K/decade over Europe are found for one of the stable data sets over 2002–2018 [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) index is often characterized by independent positive and negative NAO events with a characteristic spatial pattern and a typical lifetime of around 1 week. These events are separated by periods of near‐neutral NAO conditions. Here, we challenge this view by showing in reanalysis and observed data that the strength and spatial shape of NAO events depends on the NAO index prior to the window of 1 week and this dependency is most pronounced for negative NAO events. The influence is seen in the mean sea level pressure, and in other important features, including blocking frequency and jet stream characteristics, and also in air surface temperature and precipitation in parts of Europe. This new appreciation is important for efforts to improve methods for subseasonal‐to‐seasonal predictions of NAO. Plain Language Summary: Northern European winters differ. Some are mild and moist with prevailing westerly winds and some are cold and dry, dominated by the Siberian air masses from East. When the Northern European winters are mild, the winter in Greenland is cold, and vice versa. This is the North Atlantic Oscillation (NAO) and its companion, the Europe–Greenland temperature seesaw. They were described in qualitative terms already in the late eighteenth century. Nowadays, the NAO is often described as a series of independent positive or negative events with a duration of around 1 week with intermittent periods of near‐neutral conditions and variable duration. The net result of these events determines the NAO strength of the winter. We show that this picture is too simplified because the NAO outside the time horizon of 1 week influences the strength of the individual NAO events. This is most pronounced for the negative events where this influence can both distort and amplify or diminish the pattern of the event. Also the typical temperatures and precipitation patterns associated with NAO are influenced significantly by this effect. One important consequence for our discovery is the improved prospects of doing subseasonal‐to‐seasonal predictions. Key Points: The daily North Atlantic Oscillation (NAO) index consists of positive and negative events of duration around 1 week separated by periods of near‐neutral conditionsThe strength and spatial shape of negative NAO events depends on NAO‐index values prior to the eventBlocking frequencies, jet strength and position, and surface temperature and precipitation have similar dependencies [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]

The aims of the study were to assess the multiannual variability and trends of cold episodes in summer in Central Europe and to determine circulation conditions favouring their occurrence. The research was conducted based on data obtained for stations from Germany and Poland during the period 1966–2015. Cold episodes were understood as single cold days and cold spells. A cold day is defined as a day on which the maximum air temperature is lower than the 5th percentile of the local function of probability density determined from observation, and a cold spell was defined as at least two consecutive cold days. The observed increase in the air temperature in summer translated into a decrease in the number of cold episodes. The greatest changes in their number were recorded in the southern regions of the study area. On average, during the occurrence of cold episodes in summer in Central Europe, lower than usual sea level pressure was recorded, as well as lower persistence of the 300 hPa geopotential level, indicating the presence of cold air masses. Based on the minimum variance method, known as the Ward method, three circulation types were designated to cause the occurrence of cold episodes. The designated baric conditions caused advection of cold air masses from the northern sector. In each type, the largest T850 anomalies were recorded in Central Europe, reaching even less than −5°C. [ABSTRACT FROM AUTHOR]

Ecological research heavily relies on coarse‐gridded climate data based on standardized temperature measurements recorded at 2 m height in open landscapes. However, many organisms experience environmental conditions that differ substantially from those captured by these macroclimatic (i.e. free air) temperature grids. In forests, the tree canopy functions as a thermal insulator and buffers sub‐canopy microclimatic conditions, thereby affecting biological and ecological processes. To improve the assessment of climatic conditions and climate‐change‐related impacts on forest‐floor biodiversity and functioning, high‐resolution temperature grids reflecting forest microclimates are thus urgently needed. Combining more than 1200 time series of in situ near‐surface forest temperature with topographical, biological and macroclimatic variables in a machine learning model, we predicted the mean monthly offset between sub‐canopy temperature at 15 cm above the surface and free‐air temperature over the period 2000–2020 at a spatial resolution of 25 m across Europe. This offset was used to evaluate the difference between microclimate and macroclimate across space and seasons and finally enabled us to calculate mean annual and monthly temperatures for European forest understories. We found that sub‐canopy air temperatures differ substantially from free‐air temperatures, being on average 2.1°C (standard deviation ± 1.6°C) lower in summer and 2.0°C higher (±0.7°C) in winter across Europe. Additionally, our high‐resolution maps expose considerable microclimatic variation within landscapes, not captured by the gridded macroclimatic products. The provided forest sub‐canopy temperature maps will enable future research to model below‐canopy biological processes and patterns, as well as species distributions more accurately. [ABSTRACT FROM AUTHOR]

Aim: Distribution ranges of temperate tree species are shifting poleward and upslope into cooler environments due to global warming. Successful regeneration is crucial for population persistence and range expansion. Thus, we aimed to identify environmental variables that affect germination and seedling establishment of Europe's dominant forest tree, to compare the importance of plasticity and genetic variation for regeneration, and to evaluate the regeneration potential at and beyond the southern and northern distribution margins. Location: Europe. Time period: 2016–2018. Major taxa studied: European beech (Fagus sylvatica (L.)). Methods: We investigated how germination, establishment and juvenile survival change across a reciprocal transplantation experiment using over 9,000 seeds of beech from 7 populations from its southern to its northern distribution range margins. Results: Germination and establishment at the seedling stage were highly plastic in response to environmental conditions. Germination success increased with warmer and declined with colder air temperature, whereas establishment and survival were hampered under warmer and drier conditions. Germination differed among populations and was positively influenced by seed weight. However, there was no evidence of local adaptation in any trait. Main conclusions: The high plasticity in the early life‐history traits found irrespective of seed origin may allow for short‐term acclimatization. However, our results also indicate that this plasticity might not be sufficient to ensure the regeneration of beech in the future due to the low survival found under dry and hot conditions. The future climatic conditions in parts of the distribution centre and at the rear edge might thus become limiting for natural regeneration, as the likelihood of extreme heat and drought events will increase. By contrast, at the cold distribution margin, the high plasticity in the early life‐history traits may allow for increasing germination success with increasing temperatures and may thus facilitate natural regeneration in the future. [ABSTRACT FROM AUTHOR]

Hourly precipitation extremes can intensify with temperature at higher rates than expected from thermodynamic increases explained by the Clausius‐Clapeyron (CC) relationship (∼6.5%/K), but local scaling with surface air temperature is highly variable. Here we use daily dew point temperature, a direct proxy of absolute humidity, to estimate at‐gauge local scaling across six macro‐regions for a global data set of over 7,000 hourly precipitation gauges. We find scaling rates from CC to 2 × CC at more than 60% of gauges, peaking in the tropics at a median rate of ∼1.5CC. Moreover, regional scaling rates show surprisingly universal behavior at around CC, with higher scaling in Europe. Importantly for impacts, hourly scaling is persistently higher than scaling for daily extreme precipitation. Our results indicate greater consistency in global scaling than previous work, usually at or above CC, with positive scaling in the (sub)tropics. This demonstrates the relevance of DPT scaling to understanding future changes. Plain Language Summary: Globally, hourly precipitation extremes have increased during recent decades and are projected to intensify more in the future. Therefore, understanding the relationship of precipitation extremes with temperature may be helpful for risk assessment and in decision making for climate adaptions. Using station‐based observations of hourly precipitation and daily dewpoint temperature, we show that precipitation extremes increase with the increase in dewpoint temperature consistently at a regional scale, and even with a higher rate at the gauge‐level. This rate of increment is much higher than that for daily extreme precipitation. Our results have implications for understanding drivers of changes to extreme precipitation at different spatial scales. Key Points: Hourly extreme precipitation consistently follows at least the CC rate at a regional scale, and often a super‐CC rate at the gauge‐levelThe median scaling is greater than CC rate for gauges in wet and dry regionsRegional scaling curves consistently follow the CC rate in the temperate climate zone [ABSTRACT FROM AUTHOR]

The year 2018 was affected by very long‐lasting, stable summer conditions in vast parts of Europe, in many regions already starting in April and lasting until October. We investigate the thermal characteristics of this year in a secular time perspective, using a spatially well‐distributed dataset of 67 European stations (west of ~30°E) with daily long‐term air temperature observations. Our dataset comprises many of the longest and most reliable (homogenous) temperature measurements available in Europe, mainly starting already in the 19th or rarely even 18th century. Individual time series length is considered to analyse the summer 2018 temperatures into a more than two‐century time perspective, while European time series are presented for the period 1855–2018 and records of five European regions are considered from 1881 onwards. The extreme long duration of the 2018 summer most clearly manifested itself in pronounced new continental maxima of summer half year (April–September) temperature averages and the number of days with maximum temperatures ≥20 and ≥25°C. Furthermore, those indices reached new local maxima at about half of our investigated stations. Records of other temperature indices, rather representing intense heat conditions, were particularly broken in the extended Baltic Sea region, supported by distinct and long‐lasting anticyclonic conditions in this area. However, the extreme summer of 2003 still dominates the ranking of most of these indices on the continental level, even though it is now generally closely followed by summer 2018. We show that long‐term variations of teleconnection indices and the Atlantic Multidecadal Oscillation, as well as seasonal and anthropogenic effects, supported both the recent hot summers and the extreme summer of 2018. [ABSTRACT FROM AUTHOR]

Aim: A progressive increase in air temperature is recognized as the most important mechanistic driver of species range shifts. However, only a few studies have simultaneously considered the influence of both extrinsic and intrinsic mechanistic drivers; there are still no studies on the roles of extrinsic and intrinsic drivers that regulate such species changes. We investigated how species will shift their geographical ranges to cope with future climate change and analysed the relative importance of the mechanistic drivers in governing species range shifts. Location: Sixteen countries in South, West and North Europe. Methods: We used ensemble species distribution models on the European continental scale to predict 105 odonate species in response to climate change in the future decades until 2080s under three emission scenarios. We evaluated the projected changes in four community metrics (distribution area, optimum position, leading edge and trailing edge) and investigated how these changes are driven by extrinsic and intrinsic factors. Results: The odonate species were predicted to shift their range margins poleward, with a higher migration rate towards the trailing edge (2.38‒10.34 km/year) than the leading edge (1.13‒2.00 km/year). Contrary to the assumption that the response of the odonate species to climate change will linearly accelerate over time, the distribution areas of odonate species were predicted to increase until 2050s and then decline until 2080s under RCP 2.6 (representative concentration pathway). However, their distributions under RCP 4.5 and RCP 8.5 were predicted to decrease over time, with a higher rate under RCP 8.5. Overall, environmental preference and habitat override dispersal ability govern the range shift of odonate species. Main conclusions: Quantifying the relative importance of extrinsic and intrinsic factors across a large spatial scale under different emission scenarios can help understand the mechanistic processes to facilitate species range shifts. [ABSTRACT FROM AUTHOR]

Under present climate conditions, Ips typographus (L.) is Europe's most critical disturbance agent for mature Norway spruce (Picea abies). With ongoing climate change, the bark beetle will most probably become more prominent as a pest. The aim of this study was to analyse the dispersal performance of I. typographus under various weather conditions, especially hot days with a maximum air temperature above 30°C. In a field study, marked bark beetles were released from breeding logs and could be retraced in traps distributed across the survey area. With daily collections of the trapped beetles, it was possible to analyse the flight activity and the average flight distance of the bark beetles during hot, moderate and cool days. The numbers of daily catches and the average flight distance during the hottest days (air temperature maximum ≥30°C) did not significantly differ from the moderate days (air temperature maximum ≥22°C and <30°C). The numbers of daily catches and the average flight distance during the cool days (air temperature maximum <22°C) were significantly lower than during hot and moderate days. The results give an insight on the dispersal capacity of I. typographus under climate change driven future conditions. Increased air temperatures do not seem to impair the flight performance of I. typographus. A small proportion of cool days during the swarming period even seems to favour dispersal of I. typographus. [ABSTRACT FROM AUTHOR]

Increasing CO2 concentration ([CO2]) is thought to induce climate change and thereby increase air temperatures and the risk of drought stress, the latter impairing crop growth. The objective of this study was to investigate the effects of elevated [CO2] and drought stress on root growth of one maize genotype (Zea mays cv. Simao) and two sorghum genotypes (Sorghum bicolor cv. Bulldozer and Sorghum bicolor × Sorghum sudanense cv. Inka) under the cool moderate climate of Central Europe. It was hypothesized that root growth stimulation due to elevated [CO2] compensates for a reduced root growth under drought stress. Therefore, we established an experiment within a free‐air carbon dioxide enrichment system (FACE) in 2010 and 2011. Sorghum and maize genotypes were grown under ambient [CO2] (385 ppm CO2) and elevated [CO2] (600 ppm CO2) and in combination with restricted and sufficient water supply. Elevated [CO2] decreased root length density (RLD) in the upper soil layers for all genotypes, but increased it in deeper layers. Higher [CO2] enhanced specific root length (SRL) of "Simao" and "Bulldozer," however, did not affect that of "Inka." "Simao" achieved a higher SRL than the sorghum genotypes, indicating an efficient investment in root dry matter. Although elevated [CO2] affected the root growth, no interaction with the water treatment and, consequently, no compensatory effect of elevated [CO2] could be identified. [ABSTRACT FROM AUTHOR]

The aim of the article was to provide a detailed analysis of pressure conditions, employing the anomalies of geopotential heights, during the occurrence of heat waves in Central Europe, but also in the days preceding and following their occurrence. The study uses data from 1966 to 2015 from the Institute of Meteorology and Water Management—National Research Institute, Deutscher Wetterdienst and the National Centre for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR). A heat wave was defined as a sequence of at least 3 days with a maximum daily air temperature of >30°C. The study showed an increase in the number of hot days, which was statistically significant in the majority of the area. In the analysed years, an increasing number of heat waves were recorded, and this occurrence was associated with high pressure systems. Anticyclonic blocking in the summer inhibits the zonal flow of air masses and intensifies meridional flow, which in Central Europe in the summer means the presence of polar continental and tropical air masses. During heat waves, there were positive anomalies of isobaric surface heights over the study area with a maximum in the upper troposphere. On average, anomalies at the 300 hPa pressure level began to form over the Atlantic Ocean. Determining atmospheric preconditions of persisting blocking events in summer resulting in heat waves may be helpful in predicting thereof. [ABSTRACT FROM AUTHOR]

Conifer trees possess a typical anatomical tree‐ring structure characterized by a transition from large and thin‐walled earlywood tracheids to narrow and thick‐walled latewood tracheids. However, little is known on how this characteristic structure is maintained across contrasting environmental conditions, due to its crucial role to ensure sap ascent and mechanical support. In this study, we monitored weekly wood cell formation for up to 7 years in two temperate conifer species (i.e., Picea abies (L.) Karst and Larix decidua Mill.) across an 8°C thermal gradient from 800 to 2,200 m a.s.l. in central Europe to investigate the impact of air temperature on rate and duration of wood cell formation. Results indicated that towards colder sites, forming tracheids compensate a decreased rate of differentiation (cell enlarging and wall thickening) by an extended duration, except for the last cells of the latewood in the wall‐thickening phase. This compensation allows conifer trees to mitigate the influence of air temperature on the final tree‐ring structure, with important implications for the functioning and resilience of the xylem to varying environmental conditions. The disappearing compensation in the thickening latewood cells might also explain the higher climatic sensitivity usually found in maximum latewood density. The structure of conifer wood cells depends on the speed and duration of processes shaping their formation. In this study, we show for the first time that cells growing at colder sites increase their duration of their processes to compensate for a speed reduction. This compensation allows conifers to mitigate the effect of air temperature to maintain a more similar tree‐ring structure despite contrasting conditions. [ABSTRACT FROM AUTHOR]

The potential of early warning for severe cold conditions is explored using the Subseasonal to Seasonal (S2S) Prediction research project data archive. We explore the use of a two‐dimensional phase space based on the leading empirical orthogonal functions (EOFs) of mid‐tropospheric flow computed over the Euro‐Atlantic region in order to study the time evolution of flow patterns associated with high‐impact temperature anomalies. We find that the phase space is an effective tool for monitoring predictions of regime transitions at medium and extended ranges. We show that a number of S2S systems have some skill in the prediction of cold spells over Europe, even beyond the medium range. In particular, the ECMWF (European Centre for Medium‐Range Weather Forecasts) model represents well the observed preferential transition paths. We reveal that the impact of the Madden–Julian Oscillation (MJO) on the predictive skill of large‐scale flow over Europe is asymmetric. The impact of the MJO on the Brier skill scores and reliability is significantly positive for predictions of the negative phase of the North Atlantic Oscillation (NAO): beyond week one, forecasts with the MJO in their initial state are significantly more reliable than forecasts with no MJO in their initial conditions. In contrast, the predictive skill for positive NAO shows little sensitivity to the MJO. Subseasonal predictions provide enormous potential for early warnings of severe cold events over Europe. As the image shows, several forecasting systems can provide skillful predictions of large‐scale patterns, typically associated with severe cold events over Europe, more than 10 days in advance. However, the success of forecasting weeks ahead changes in large‐scale flow that lead to cold conditions depends on the type of transitions. [ABSTRACT FROM AUTHOR]

ABSTRACT This study compares the multivariate predictions of daily temperature, temperature range, precipitation, surface wind and solar radiation of a single-model analogue approach with an original multi-model analogy over 12 regions in Europe and Maghreb. Both approaches are based on two-level analogue models where atmospheric predictors are either dynamic or thermodynamic. In the multi-model approach, independent analogue models with predictand-specific predictors are used. In the single-model one, a unique analogue model and its associated set of predictors is applied to all predictands. Testing numerous large-scale predictors, we first identify the best predictor sets for each modelling strategy. Those obtained for the single-model approach are significantly different from those of the predictand-specific models. This is especially the case for local temperature and wind speed. Both methods perform similarly for precipitation, temperature range and radiation. We next assess the ability of both approaches to simulate physically coherent multivariate weather scenarios. With the single-model method, weather scenarios are obtained for each prediction day from observations sampled simultaneously on one analogue day. The physical consistency between variables is thus automatically fulfilled each day. This allows the single-model method to reproduce well the observed inter-predictand correlations, especially the significant correlations between radiation and precipitation and between radiation and temperature range. These results suggest a hybrid analogue model using a single-model for radiation, temperature range and precipitation, combined with a univariate approach for wind. Two options are proposed for temperature for which either the predictand-specific method or a single-model approach with an additional correction are conceivable. This hybrid approach leads to a possible compromise between reasonable univariate prediction skills and realistic inter-predictands correlations, both classically required for many impact studies. [ABSTRACT FROM AUTHOR]

ABSTRACT In 2015, large parts of Europe were characterized by extraordinary high summer temperatures, accompanied by very dry conditions, particularly in central-eastern Europe. Several major heat episodes occurred from the end of June until mid-September. We provide an ad-hoc evaluation of the observed climatological extremes in a secular context, by using a set of long station time series in daily resolution. Our data set comprises 42 temperature and 43 precipitation records, predominantly starting already in the 19th century. To investigate local record values, the individual full record length is analysed for each station, while regionally averaged analyses are presented for the core study period of 1901-2015. The study area covers Europe's central latitudes (44° to 52°N), extending from England in the west up to the central Ukraine in the east. During summer 2015, various indices representing extremely high maximum and minimum temperatures (strongly) exceeded previous record high values, mainly in an area extending from eastern Germany to western Ukraine. Additionally, severely to extremely dry conditions with unusually frequent dry days were prevailing particularly in the (central-) eastern part of the study area. Drought indices combining temperature and precipitation revealed drought conditions comparable or even worse than those of former extreme summers like 2003. [ABSTRACT FROM AUTHOR]

ABSTRACT Due to imperfections inherent to numerical climate simulations, projections of climate change need to be accompanied with an uncertainty estimate, typically derived from multi-model ensembles. Here, an analysis of regional climate model outputs spread and its temporal evolution is presented, for the European air temperatures simulated over the 21st century. To quantify the overall uncertainty, standard deviation (sd) is used and compared to median absolute deviation and inter-quartile range. The outcomes are shown for annual and seasonal means of air temperature at 2 m, 850 hPa, 700 hPa, 500 hPa and 300 hPa levels, simulated by ENSEMBLES regional climate models for eight geographical areas across Europe. Our results indicate that the estimated uncertainty of simulated air temperature changes over Europe generally increases during the 21st century, and typically decreases with height of the studied vertical level. The influence of driving global climate model on the regional simulation generally increases with height of the studied vertical level. In lower tropospheric levels, the clustering of regional climate models according to driving global climate model is stronger in winter than in summer. [ABSTRACT FROM AUTHOR]

Little use has been made up till now of the concept of climate analogues to link the present and the past, i.e. places whose current climate ('target' locations) is similar to that experienced some decades ago at distant locations ('reference' sites). Indeed, most research up till now has focused on analogues between present and future climates. Here we assess at what period of time the climate at a target station in Europe has reached-or will reach-that of a reference location, and show that the velocity of northward-moving isotherms can attain 15 km year−1. Such displacements in space imply that temperatures at many target sites in Europe have already exceeded those experienced by stations located 300-500 km to the south in the last half-century. Such results can serve to better portray what a rapidly changing climate means to a lay audience, and can provide useful information to the policy-making community. [ABSTRACT FROM AUTHOR]

In a changing climate, it is likely that precipitation patterns will experience shifts in amount and seasonality, with a tendency towards increased drought in many parts of Europe. In order to investigate what could be some of the feedbacks of dry conditions on temperature, this paper has investigated close to 30 European locations to assess the influence of observed dry summer days on daily maximum temperature ( Tmax) as well as a clustering of rainless days, and finally the temperature impact related to drought conditions as defined by the Standardized Precipitation Index. The results show that for the three main European climatic regions investigated ('Mediterranean', 'Maritime', 'Continental'), the influence of rainless days is discernible, with an average difference between mean summer Tmax and Tmax during rainless days only of up to 1.5 °C. A further aim of the study is to determine whether recent shifts in the occurrence of rainless days during the summer have a bearing on temperature trends. Results show that shifts in rainless days explain only a fraction of the observed temperature change at the locations studied, thereby hinting that the enhanced greenhouse effect remains the dominant mechanism for temperature change. Finally, using a regional climate model, very preliminary insight into a 'greenhouse climate' highlights the fact that changes in dry conditions seem to confirm the findings for current climate, i.e. they account for only a fraction of the increase in temperatures. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Common juniper ( Juniperus communis L.) populations in northwest European lowlands are currently declining in size and number. An important cause of this decline is a lack of natural regeneration. Low seed viability seems to be one of the main bottlenecks in this process. Previous research revealed a negative relation between seed viability and both temperature and nitrogen deposition. Additionally, the seeds of common juniper have a variable ripening time, which possibly influences seed viability. However, the underlying mechanisms remain unresolved. In order to elucidate this puzzle, it is important to understand in which phases of seed production the main defects are situated, together with the influence of ripening time. In this study, we compared seed viability of populations with and without successful recruitment. We examined three seed phases: (i) gamete development; (ii) fertilisation and early-embryo development; and (iii) late-embryo development. After the first two phases, we found no difference in the percentage viable seeds between populations with or without recruitment. After late-embryo development, populations without recruitment showed a significantly lower percentage of viable seeds. These results suggest that late-embryo development is a bottleneck in seed development. However, the complex interaction between seed viability and ripening time suggest that the causes should be in the second seed phase, as the accelerated development of male and female gametophytes may disturb the male-female synchrony for successful mating. [ABSTRACT FROM AUTHOR]

Sodium-K, Na-Ca, Na-Mg, and Na-Sr exchange isotherms were performed at a total Cl concentration of about 0.005 mol L-1 on the fine fraction (<2 μm) of MX8O montmorillonite, mixed-layer1 illite smectite minerals (IS), and clayey stones from European underground research laboratories. The derived selectivity coefficients for Na-K, Na-Ca, Na-Mg, and Na- Sr were found to vary very significantly as a function of the exchanger composition. A model was built to reproduce the data, taking into account the change of selectivity coefficient as a function the exchanger composition of smectite. Model parameters were fitted using data from the present study and data from the literature obtained on smectite minerals. The addition of parameters for cation-anion pairs was found to improve the fitting results. The model 1.vas then successfully tested to reproduce published cation-exchange features on natural clayey materials and soils suspended in fresh or saline water. Finally, it is shown that the simple combination of this smectite exchange model with a previously published illite exchange model is quite successful although perfectible in reproducing exchange data on IS. [ABSTRACT FROM AUTHOR]

The article investigates the number of days with snow cover at 268 Alpine climate stations during winter period, from 1961-2000, and its relation with the mean winter temperature over Europe. A physical-statistical model of snow duration, along with hyperbolic tangent function to generate the logistic curve for the snow-temperature relationship were used. Results of the study proves to be valid for the Alpine region and independent against a linear temperature trend. Findings reveal that the snow-temperature sensitivity in the Alpine region is in accordance with earlier estimates for Austria and Switzerland.

Global climate change impacts can already be tracked in many physical and biological systems; in particular, terrestrial ecosystems provide a consistent picture of observed changes. One of the preferred indicators is phenology, the science of natural recurring events, as their recorded dates provide a high-temporal resolution of ongoing changes. Thus, numerous analyses have demonstrated an earlier onset of spring events for mid and higher latitudes and a lengthening of the growing season. However, published single-site or single-species studies are particularly open to suspicion of being biased towards predominantly reporting climate change-induced impacts. No comprehensive study or meta-analysis has so far examined the possible lack of evidence for changes or shifts at sites where no temperature change is observed. We used an enormous systematic phenological network data set of more than 125 000 observational series of 542 plant and 19 animal species in 21 European countries (1971–2000). Our results showed that 78% of all leafing, flowering and fruiting records advanced (30% significantly) and only 3% were significantly delayed, whereas the signal of leaf colouring/fall is ambiguous. We conclude that previously published results of phenological changes were not biased by reporting or publication predisposition: the average advance of spring/summer was 2.5 days decade−1 in Europe. Our analysis of 254 mean national time series undoubtedly demonstrates that species' phenology is responsive to temperature of the preceding months (mean advance of spring/summer by 2.5 days°C−1, delay of leaf colouring and fall by 1.0 day°C−1). The pattern of observed change in spring efficiently matches measured national warming across 19 European countries (correlation coefficient r=−0.69, P<0.001). [ABSTRACT FROM AUTHOR]

The variability of winter extreme low-temperature events and summer extreme high-temperature events was investigated using daily temperature series (1901–98) from 11 sites in central and southern Europe. An extreme temperature event (EXTE) is defined by various threshold values of daily temperature or daily temperature anomaly. Systematic changes in the frequencies of EXTEs are investigated by the Mann–Kendall test and a method based on the Wilcoxon test. The catalogue of macrocirculation types over central Europe (the Hess–Brezowsky classification) is applied to investigate the connections between EXTEs and large-scale circulation. Circulation classes (HBC) are defined, and mostly spatial averages of EXTEs are examined. There were large long-term fluctuations in the frequencies of both winter extreme cold events (EXCEs) and summer extreme warm events (EXWEs) during the 20th century. The systematic changes referring to the entire period indicate a slight warming tendency, but only a few of the changes, mostly in the northernmost sites, are statistically significant. Strong connections are present between the frequencies of EXTEs and the large-scale circulation on various time scales, particularly for EXCEs. The spatial differences of EXTE fluctuations and EXTE–HBC connections are small within the study area. Northerlies and easterlies, as well as meridional and anticyclonic situations, are favourable for EXCEs, whereas southerlies and persistent anticyclonic situations are favourable for EXWE occurrences. In the latest decades, a decline in the frequency of EXCEs and a sharp increase in the frequency of EXWEs happened, and the residence times of the circulation patterns over central Europe became longer both in winter and summer. Copyright © 2003 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Examines a possible mechanism leading to late-winter warming, and thus to an early spring in Europe. Details of research using ocean-surface winds over the eastern North Atlantic, and air temperatures at the surface for the years 1948-99 in late-winter and spring; Data indicating that maritime air advection is no longer associated closely with the surface-air warming; Correlations indicating that the flow of warm maritime-air from the North Atlantic is predominantly at lower tropospheric level; Results suggesting the interval from mid-February to mid-March as the end of-winter period in which the southwesterlies over the eastern North Atlantic become stronger and the surface-air temperatures in Europe rise markedly, the lapse rate becomes steeper; View of researchers that the observed late-winter warming and the concomitant advancement of spring in Europe resulting from stronger southwesterlies over the North Atlantic merits further investigations.