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Vertical temperature profiles influence the wind power generation of large offshore wind farms through stability-dependent effects such as blockage and gravity waves. However, numerical tools that are used to model these effects are often computationally too expensive to cover the large variety of atmospheric states occurring over time. Generally, an informed decision about which representative nonidealized situations to simulate is missing because of the lack of easily available information on representative vertical profiles, taking into account their spatiotemporal variability. Therefore, we present a novel framework that allows a smart selection of vertical temperature profiles. The framework consists of an improved analytical temperature model for the atmospheric boundary layer and lower troposphere, a subsequent clustering of these profiles to identify representatives, and last, a determination of areas with similar spatiotemporal characteristics of vertical profiles. When applying this framework on European ERA5 data, physically realistic representatives were identified for Europe, excluding the Mediterranean. Two or three profiles were found to be dominant for the open ocean, whereas more profiles prevail for land. Over the open ocean, weak temperature gradients in the boundary layer and a clear capping inversions are widespread, and stable profiles are absent except in the region of the East Icelandic Current. Interestingly, according to the ERA5 data, at its resolution, coastal areas and seas surrounded by land behave more similar to the land areas than to the open ocean, implying that a larger set of model integrations are needed for these areas to obtain representative results for offshore wind power assessments in comparison with the open ocean. SIGNIFICANCE STATEMENT: Numerical tools used to simulate the effect of large, offshore wind farms on neighboring farms and the atmosphere are very expensive. Therefore, they can only be computed for a limited number of cases. As temperature is one of the most important parameters in these kinds of simulations, this work provides a new vertical temperature model and an analysis framework that allows for a smart selection of these cases such that they ideally represent the full variation of the atmosphere's temperature profiles. [ABSTRACT FROM AUTHOR]

A suitable indoor climate positively affects the lifespan of historical building structures. The path to an agreeable climate begins with monitoring current conditions. Considerable attention is given to monitoring the indoor climate of historical buildings. The motivation for monitoring air temperature and surface temperatures, relative air humidity or airflow can be, for example, the installation of heating, the occurrence of biotic damage, and others. Through the analysis of the most frequently used keywords, a strong connection was found, for example, between thermal comfort and the church. This review also summarises the various reasons for conducting microclimate monitoring studies in historical religious buildings on the European continent. It is supplemented with an evaluation of the monitoring methodology from the chosen period of the year point of view, the measured parameters, and the length of the interval between the recordings of quantities. It was found that in more than one-third of the cases, the recording time was less than or equal to 15 min, but mostly less than or equal to 1 h. Quite often, monitoring results are used to calibrate a simulation model describing the hydrothermal behaviour of a historical object under various operation alternatives (e.g., influence of ventilation, climate change, occupancy, etc.). This way, it is possible to test various intelligent systems in the virtual world without much risk before they are used in an actual building application. [ABSTRACT FROM AUTHOR]

The study discusses changes in the average annual air temperature over Europe in the years 1931-2020. The results of the research show that in 1987-1989, there was a sudden change in the thermal regime over Europe and a discontinuity appeared in the course of this climatic element. In the years 1931-1988, despite the high inter-annual variability, the temperature trend was zero. A positive, statistically significant, temperature trend appeared after 1988. The entire warming in Europe, which can be estimated at ~2.3 deg, occurred after 1988. The discontinuity in the course was caused by an abrupt change in macro-circulation conditions in the Atlantic-Eurasian circulation sector, which manifests itself as a fundamental change in the frequency of the macrotypes of the mid-tropospheric circulation (500 hPa) according to the Wangengejm-Girs classification, causing an equally fundamental change in the weather structure. The change in macro-circulation conditions was forced by a change in the thermal state of the North Atlantic - a sharp increase in the intensity of oceanic heat transport to the north. The analysis showed that the annual variability of temperature over Europe was mainly influenced by natural processes, the variability of which explains ~65% of its variance. Radiative forcing, which is a function of anthropogenic increase in CO2 concentration in the atmosphere, explains only 7-8% of the variability of the average annual temperature over Europe, being a secondary or tertiary factor in shaping its changes. [ABSTRACT FROM AUTHOR]

Recent years have seen a significant increase in weather anomalies in Central Europe (51°22′ N, 22°64′ E), which makes it more difficult to predict yields of winter wheat and to estimate prices on world exchanges. Eight-year (2007–2015) field observations of winter wheat cv. Turnia were carried out in order to determine the relationship between selected meteorological indicators (e.g., the values of average daily air temperature, daily sums of precipitation, and the number of days with precipitation) and the biometric traits and seed yield of winter wheat. In addition, an attempt was made to identify the meteorological parameters that determine an increase in stem elongation during the growing season. The relationship between yield parameters and biometric parameters was evaluated using Spearman's non-parametric correlation coefficients. The regression models for analysis of the dependence of yield parameters and biometric parameters on meteorological elements (temperature, precipitation totals, and days with precipitation) in each development period was used. The study showed that from the beginning of vegetative growth to the flowering stage, growth and development were most advanced in plants for which the average temperature was about 8–9 °C, and the number of days with precipitation was about 41. During generative growth, spike length is 80% determined by the precipitation total. Grain weight is 68% negatively determined by the temperature during dormancy (the higher the temperature during dormancy, the lower the weight of the kernel). A positive relationship was shown between yield and the precipitation total during the period from sowing to the onset of dormancy (r = 0.37). Winter wheat yield was 69% dependent on the density at harvest (the greater the density, the higher the final yield). On the basis of the 8-year results of the study, we conclude that the weather is highly variable from year to year, and therefore breeders should direct their research towards creating variants with much greater plasticity and high tolerance for unfavourable weather patterns. [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]

Presently, the forests of one of the most economically important tree species in Europe—Norway spruce [Picea abies (L.) Karst.]—have been disrupted and are in rapid decline due to a combination of several natural factors: extreme drought, heatwaves, and secondary damage caused by bark beetle outbreaks. The vulnerability of these forests has increased considerably over the past decade, and remote sensing methods can theoretically improve the identification of endangered forest stands. The main objective was to determine the relationship between remotely sensed characteristics of vegetation (using the normalized difference vegetation index—NDVI) and annual tree-ring growth in 180 trees through precipitation and air temperature. The research was conducted at six research plots in lowland spruce forests (319–425 m a.s.l.) in the central Czech Republic. No significant correlation between NDVI and annual ring width was observed. The primary factor limiting radial growth was lack of precipitation in the growing season; subsequently, spruce trees reacted negatively to air temperatures. A higher correlation with NDVI was observed on sites susceptible to drought, but overall, NDVI and RWI did not show similarities. This result describes that NDVI is a poor indicator for identifying low radial growth in Norway spruce stands on non-native localities in the studied area. [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]

Nearly every study dealing with temperature extremes underscores the lack of a universal and broadly used method of identifying such events. The most popular are relative methods, which are based on the empirical distribution of temperature at each location (i.e., percentiles). The aim of this study was to evaluate the effects of the various percentile-based methods of defining hot days on the analysis of their frequency of occurrence, trends, and geographic patterns in summer in Europe. The basis for the research consists of daily maximum (TX) and minimum (TN) values of air temperature for 1961–2017 for Europe obtained from the E-OBS database. A hot day occurs when air temperature exceeds the 90th percentile–based threshold. These thresholds are determined using the following: (I) various temperature metrics (TX and TN), (II) various baseline periods (1961–1990, 1971–2000, 1981–2010), and (III) different timeframes within the year that the percentile is calculated for (summer season, separate summer months, and each calendar day). Our results indicate that the use of different variants of the percentile-based definition leads to differences in the geographic patterns of frequencies of and trends in summer hot days in Europe. The differences are especially substantial within the results obtained using various temperature metrics and baseline periods, and they are relatively small when different timeframes within the year that the percentile is calculated for are considered. On the example of the case study, we also show how the use of different research approaches may affect the intensity and spatial extent of an extreme temperature event. [ABSTRACT FROM AUTHOR]

Snow plays a critical role in the water cycle of many mountain regions and heavily populated areas downstream. In this study, changes of snow water equivalent (SWE) time series from long-term stations in five Alpine countries are analyzed. The sites are located between 500 and 3000 m above mean sea level, and the analysis is mainly based on measurement series from 1 February (winter) and 1 April (spring). The investigation was performed over different time periods, including the last six decades. The large majority of the SWE time series demonstrate a reduction in snow mass, which is more pronounced for spring than for winter. The observed SWE decrease is independent of latitude or longitude, despite the different climate regions in the Alpine domain. In contrast to measurement series from other mountain ranges, even the highest sites revealed a decline in spring SWE. A comparison with a 100-yr mass balance series from a glacier in the central Alps demonstrates that the peak SWEs have been on a record-low level since around the beginning of the twenty-first century at high Alpine sites. In the long term, clearly increasing temperatures and a coincident weak reduction in precipitation are the main drivers for the pronounced snow mass loss in the past. [ABSTRACT FROM AUTHOR]

ERA5 is widely considered as a valid proxy of observation at region scales. Surface air temperature from the E-OBS database and 196 meteorological stations across Europe are being applied for evaluation of the fifth-generation ECMWF reanalysis ERA5 temperature data in the period of 1981–2010. In general, ERA5 captures the mean and extreme temperatures very well and ERA5 is reliable for climate investigation over Europe. High correlations ranging from 0.995 to 1.000 indicate that ERA5 could capture the annual cycle very well. However, the high mean biases and high Root Mean Square Error (RMSE) for some European sub-regions (e.g., the Alps, the Mediterranean) reveal that ERA5 underestimates temperatures. The biases can be mainly attributed to the altitude differences between ERA5 grid points and stations. Comparing ERA5 with the other two datasets, ERA5 temperature presents more extreme temperature and small outliers for regions southern of 40° latitude and less extreme temperatures in areas over the Black Sea. In Scandinavia, ERA5 temperatures are more frequently extreme than the observational ones. [ABSTRACT FROM AUTHOR]

Much progress has recently been made in reconstructing European temperature variability over centuries to millennia. In contrast, there are only a few attempts at long-term precipitation and/or drought reconstruction, which are spatially less significant. Here we discuss the possibility of using climate reconstructions from tree-ring density and width to make spatially explicit estimates of European temperature and drought variability, respectively. Four experiments were performed to assess spatial field correlations of (1) parameter-specific mean reconstructions, (2) individual site reconstructions, (3) instrumental stations, and (4) model analogues. The simple mean of 4 temperature reconstructions from northern Scandinavia and high-elevation sites in the Tatra, Alps, and Pyrenees revealed a significant positive correlation (r > 0.4) with the gridded Central European summer temperature south of 55° N and west of 25° E. In contrast, the mean of 11 hydro-climatic reconstructions located between Sweden and Turkey had a significant positive correlation with only a handful of small patches scattered along an east-west corridor from the British Isles over Germany to the Baltic. The significant positive correlation increased to 71% of the European landmass between 35-70° N and 10° W 40° E when using the individual 4 temperature reconstructions instead. The 11 individual hydro-climatic reconstructions had a significant positive correlation with summer drought over only 16% of the area. The proxy-based correlation fields are greatly supported by the spatial significance of instrumental station measurements and model analogues corresponding to the initial tree-ring site locations. [ABSTRACT FROM AUTHOR]

We took daily near-surface air temperature data from across Europe to calculate a series of 12 biologically relevant temperature summaries. Mean values for two 30 yr periods, 1941-1970 and 1971-2000, were compared and rates of change calculated for those meteorological stations with sufficient data. We generated contour maps for these temperature summaries for both 30 yr periods and for the difference between them; we believe these are the first such maps for over a century. Change was most pronounced and most consistent in those variables describing the onset of spring. Between 1971 and 2000, the thermal start of the growing season began on average 0.36 d yr-1 earlier and ended 0.10 d yr-1 later, suggesting an 11 d earlier beginning and 3 d later end of the growing season over the 30 yr period. For all but one of the temperature summaries, change has accelerated in recent time; however, change was not uniform across Europe. [ABSTRACT FROM AUTHOR]

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

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]