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The aim of this paper is to identify the trends of changes in atmospheric precipitation percolation under the changing climate conditions of Lithuania (the East Baltic region) based on long-term lysimeter studies. Data from 1987–2022 research (n = 1296) was used to determine trends in precipitation infiltration changes. Two 10-year periods, 1989–1998 and 2011–2020, were selected from the whole observation period (1987–2022) to assess changes in precipitation infiltration due to climate change. The air temperature has increased significantly in November (+3.4 °C) and December (+3.3 °C), with a +2.2 °C increase in the standard climate normal. The distribution of yearly precipitation has changed, with the annual amount decreasing from 686 to 652 mm. Precipitation increased the most in July and August (10.9 and 22.9 mm). In autumn, the amount of precipitation decreased by 7.9–31.1 mm. The number of rainy days did not change during the year, but the frequency of heavy precipitation increased significantly in August. The annual percolation increased by 14.2% over 2011–2020 compared to 1989–1998. Percolation increased by 19.0, 22.3, and 20.1% during the spring, autumn, and winter, respectively, and decreased by 35.0% in summer. The increase in annual percolation is mostly related to the increase in temperature during the cold season: November and December. During these months, the likelihood of early freeze formation, which interrupts gravitational water percolation in soil, is significantly reduced. In the spring, the increase in average air temperatures in March leads to faster melting of the winter snow in a shorter period, which significantly increases percolation processes. In Lithuania, higher percolation in autumn and winter, when part of the agricultural land is not covered by vegetation, may lead to higher leaching of chemical elements. [ABSTRACT FROM AUTHOR]

This paper investigates the annual and seasonal variations in the minimum and maximum air temperature (Tmin and Tmax) and precipitation over Kashmir valley, Northwestern Himalayas from 1980–2019 by using the innovative trend analysis (ITA), Mann-Kendall (MK), and Sen's slope estimator methods. The results indicated that the annual and seasonal Tmin and Tmax are increasing for all the six climatic stations, whereas four of them exhibit significant increasing trends at (α = 0.05). Moreover, this increase in Tmin and Tmax was found more pronounced at higher altitude stations, i.e., Pahalgam (2650 m asl) and Gulmarg (2740 m asl). The annual and seasonal precipitation patterns for all climatic stations showed downward trends. For instance, Gulmarg station exhibited a significant downward trend for the annual, spring, and winter seasons (α = 0.05). Whereas, Qazigund showed a significant downward trend for the annual and spring seasons (α = 0.05). The overall analysis revealed that the increased Tmin and Tmax trends during the winter season are one of the reasons behind the early onset of melting of snow and the corresponding spring season. Furthermore, the observed decreased precipitation trends could result in making the region vulnerable towards drier climatic extremes. Such changes in the region's hydro-meteorological processes shall have severe implications on the delicate ecological balance of the fragile environment of the Kashmir valley. [ABSTRACT FROM AUTHOR]

As global warming produces dramatic climate changes, water management is facing increasingly serious challenges. Given to the process of climate change and its complex effects on watershed hydrology, this paper investigates the spatial and temporal variation characteristics of major climatic factors (i.e., precipitation and temperature) over the upper Yangtze River basin (UYRB), China. The statistical analyses are based on annual and seasonal scales during 1951–2020 with a recorded period of seven decades. The Mann–Kendall nonparametric test and R/S analysis are used to record the temporal trends (past and future) of climate variables; the Pettitt test, standard normal homogeneity test and Buishand test are used to detect the homogeneity in climate series. The sensitivities of the streamflow to climatic parameters are assessed at the watershed scale, especially considering the Three Gorges Dam's (TGD) effect on changing runoff. The results of the study indicate that the annual precipitation of 29 out of 34 series indicate homogeneity, while 31 out of 34 annual mean temperature series show heterogeneity, with jump points around 1997 in the mean temperature of 20 sites. Detectable changes in precipitation were not observed during 1951–2020; however, the temperature increased significantly in the whole basin on annual and seasonal scales, except for several stations in the eastern part. The magnitude of increase in air temperature in high altitudes (Tibet Plateau) is higher than that in low altitudes (Sichuan Plain) over the last seven decades, and future temperatures continue to sharply increase in high altitudes. The TGD plays an important role in explaining the seasonal variations in streamflow at Yichang station, with streamflow experiencing a sharp increase in winter and spring (dry season) and a decrease in summer and autumn (rainy season) compared to the pre-TGD period. The streamflow variation at an annual scale is mainly regulated by climate fluctuation (variation in precipitation). During the last seven decades, increasing air temperature and decreases in rainfall and runoff signify reduced water resources availability, and the climate tends to be warmer and drier over the basin. The sensitivity of the streamflow to watershed precipitation is higher than that to temperature, with variation in annual rainfall explaining 71% of annual runoff variability. [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]

Nature has been adversely affected by increasing industrialization, especially during the latter part of the last century, as a result of accelerating technological development, unplanned urbanization, incorrect agricultural policies and deforestation, which have contributed to the elevated concentration of the greenhouse gases (GHGs) in the environment. GHG accumulation has an adverse impact on meteorological and hydro-meteorological parameters, particularly temperature. Temperature plays a prominent and well-known role in evaporation, transpiration and changes in water demand, and thus significantly affects both water availability and food security. Therefore, a systematic understanding of temperature is important for fighting food insecurity and household poverty. Variations in temperature are often assessed and characterized through trend analysis. Hence, the objective of this paper is to determine long-term trends in mean monthly maximum and minimum air temperatures for the Maloti-Drakensberg region. The Mann–Kendall test, a non-parametric test, was applied on mean air temperature for the 1960–2016 period. A significant rising trend (p < 0.001) was detected with a yearly change in the long term annual mean maximum and mean minimum temperature by 0.03 °C/annum and 0.01 °C/annum, respectively. This knowledge has important implications for both the state of the environment and livelihoods in the region, since its use can be useful in planning and policymaking in water resource management, biodiversity conservation, agriculture, tourism and other sectors of the economy within the region. [ABSTRACT FROM AUTHOR]