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Regional climate change affects the state of inland water bodies and their water balance, which is determined by a number of hydrometeorological and hydrogeological factors. An integral characteristic of changes in the water balance is the behavior of the level of lakes and reservoirs, which not only largely determines the physical and ecological state of water bodies, but also significantly affects the coastal infrastructure and socio-economic development of the region. This paper investigates the interannual variability of the level of the Ladoga and Onega lakes, the largest lakes in Europe located in the northwest of Russia, according to satellite altimetry data for 1993–2020. For this purpose, we used three specialized altimetry databases: DAHITI, G-REALM, and HYDROWEB. Water level data from these altimetry databases were compared with in-situ records at water level gauge stations. Information on air temperature (1945–2019) and precipitation (1966–2019) acquired at three meteostations located at Ladoga and Onega lakes was used to investigate interannual trends in the regional climate change. Finally, we discuss the potential impact of the lake level rise and regional climate warming on the infrastructure and operability of railways in this region. [ABSTRACT FROM AUTHOR]

Nowadays, subjects such as eco-design requirements, product rating or code compliance with regard to energy efficiency are expanding towards a pan-European level. This leads to the necessity of defining zones within the European region, which share common climatic characteristics and will further facilitate the quick estimation of building energy performance. Towards this direction stands the current paper; it presents an approach for defining climatic zones in Europe on the basis of the amount of heating and cooling degree days. It is applied for the climate classification of selected European cities and is compared with the conventional scheme based solely on heating degree days. Since the approach is orientated mainly towards the assessment of building energy performance, its outcomes are evaluated with regard to the actual heating and cooling energy needs of a reference building unit with office use located in representative cities of the proposed climatic zones and facing the four cardinal orientations. The classification of climatic zones on the basis of both heating and cooling degree days leads to more realistic results, since nowadays cooling needs form a substantial part of the energy balance of the building, especially in the Mediterranean regions. [ABSTRACT FROM AUTHOR]

Mountains are highly sensitive to the effects of climate change, including extreme short- and long-term weather phenomena. Therefore, in spite of relatively high annual precipitation totals, mountains might become endangered by droughts. The paper presents drought trends in the Polish Carpathians located in Central Europe. Data from the period 1991–2020 from 12 meteorological stations located in various vertical climate zones of the mountains were used to define drought conditions using the following indices: Standardized Precipitation (SPI), Standardized Precipitation Evapotranspiration (SPEI), Relative Precipitation (RPI) and Sielianinov. Additionally, four forest drought indices were used in order to estimate the impact of drought on beech as a typical Carpathian tree species, i.e., the Ellenberg (EQ), Forestry Aridity (FAI), Mayr Tetratherm (MT) and De Martonne Aridity (AI) indices. Statistically significant but weak trends were obtained for the 6-month SPI for four stations (indicating an increase in seasonal to mid-term precipitation), for the 1-month SPEI for three stations, for the 3-month SPEI for four stations, and for MT for all stations (indicating an increase in drought intensity). The analysis of dry month frequency according to particular indices shows that at most of the stations during the last decade of the study period, the frequency of dry months was much higher than in previous decades, especially in the cold half-year. Two zones of the Polish Carpathians are the most prone to drought occurrence: the peak zone due to the shift in climatic vertical zones triggered by the air temperature increase, and the forelands and foothills, together with basins located about 200–400 m a.s.l., where the mean annual air temperature is the highest in all the vertical profile, the annual sums of precipitation are very diversified, and the conditions for beech are already unfavorable. [ABSTRACT FROM AUTHOR]

The diurnal cycle of both air temperature and wind speed is characterized by considerable differences, when comparing open site conditions to forests. In the course of this article, a new two-hourly, open-source dataset, covering a high spatial and temporal variability, is presented and analyzed. It contains air temperature measurements (128 station pairs (open/forest); six winter seasons; six study sites), wind speed measurements (64 station pairs; three winter seasons, four study sites) and related metadata in central Europe. Daily cycles of air temperature and wind speed, as well as further dependencies of the effective Leaf Area Index (effective LAI), the exposure in the context of forest effects, and the distance to the forest edge, are illustrated in this paper. The forest effects on air temperature can be seen particularly with increasing canopy density, in southern exposures, and in the late winter season, while wind speed depends on multiple factors such as effective LAI or the distance to the forest edge. New transfer functions, developed using linear and non-linear regression analysis, in a leave-one-out cross-validation, improve certain efficiency criteria (NSME; r2; RMSE; MAE) compared to existing transfer functions. The dataset enables multiple purposes and capabilities due to its diversity and sample size. [ABSTRACT FROM AUTHOR]

Temperature is widely known as one of the most important drivers to forecast electricity and gas variables, such as the load. Because of that reason, temperature forecasting is and has been for years of great interest for energy forecasters and several approaches and methods have been published. However, these methods usually do not consider temperature trend, which causes important error increases when dealing with medium- or long-term estimations. This paper presents several temperature forecasting methods based on time series decomposition and analyzes their results and the trends of 37 different European countries, proving their annual average temperature increase and their different behaviors regarding trend and seasonal components. [ABSTRACT FROM AUTHOR]