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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]

The homogenization of climate observational series is a needed process before undertaking confidently any study of their internal variability, since changes in the observation methods or in the surroundings of the observatories, for instance, can introduce biases in the data of the same order of magnitude than the underlying climate variations and trends. Many methods have been proposed in the past to remove the unwanted perturbations from the climatic series, and some of them have been implemented in software packages freely available on the Internet. The Spanish project MULTITEST was intended to test their performance in an automatic way with synthetic monthly series of air temperature and atmospheric precipitation, to update inter‐comparison results from former projects, especially those of the COST Action ES0601. Several networks representing different climates and station densities were used to test a variety of homogenization packages on hundreds of random samples. Results were evaluated mainly in the form of root mean squared errors and errors in the trend of the series, showing that ACMANT, followed by Climatol, minimized these errors. However, other packages performed also relatively well, even outperforming them when there were simultaneous biases of the same sign in most or all the test series. [ABSTRACT FROM AUTHOR]

Recent studies show an increase in the frequency of compound extremes in air temperature and precipitation in many parts of the world, especially under dry and hot conditions. Compound extremes have a significant impact on all spheres of human activity, such as health, agriculture, and energy. Features of atmospheric circulation are closely related to the occurrence of anomalies in air temperature and precipitation. The article analyzes the relationship of atmospheric circulation modes with compound extremes that have had the greatest impact on the Atlantic–European region over the territory of Eastern Europe over the past 60 years on extreme air temperature and precipitation. Combinations of extreme temperature and humidity conditions (indices)—cold-dry (CD), cold-wet (CW), warm-dry (WD) and warm-wet (WW)—were used as compound extremes. Indices of compound extremes were calculated according to the E-OBS reanalysis data. Estimates of the relationship between two time series were carried out using standard correlation and composite analyses, as well as cross wavelet analysis. Phase relationships and time intervals for different climatic indices were different. The period of most fluctuations in the indices of compound extremes was from 4 to 12 years and was observed during 1970–2000. The coherent fluctuations in the time series of the WD and WW indices and the North Atlantic oscillation (NAO) index occurred rather in phase, those in the time series of the CD and WD indices and the Arctic oscillation (AO) index occurred in antiphase, and those in the time series of the WD and WW indices and the Scandinavia pattern (SCAND) index occurred in antiphase. Statistically significant increase in the number of warm compound extremes was found for the northern parts of the study region in the winter season with positive NAO and AO phases. [ABSTRACT FROM AUTHOR]

This article discusses the expected climate changes in Belarus as a result of two types of land transformation—rewetting degraded peatlands and increasing forest cover. The analysis was performed for the growing season (May–September) based on long-term earth remote sensing data, mesoscale modeling of atmospheric processes, and balance calculations using ERA5 reanalysis. It is shown that, as a result of waterlogging, the daytime temperature of the land surface for the southern part of Belarus (below the latitude of Minsk) decreases within 1.5°С due to increased evaporation and, for the northern part, 0.5 increased due to albedo regularity. At night, waterlogging, depending on the soil and climatic conditions, can cause both an increase and decrease a specific value of the land surface temperature (LST) within 1°C. Evapotranspiration due to waterlogging in the northern regions of Belarus decreases and it increases in the southern regions, which is associated with a significant ratio between evaporation and transpiration in these regions. During the afforestation of cropland, the daytime LST of Belarus decreases within 2°C and, at night, increase. The total evapotranspiration for the growing season due to the increase in forest cover reaches 100 mm, and potential (maximum possible) evaporation remains at the same level, which contributes to an increase in soil moisture at an increased amount of atmospheric precipitation. The above changes in the physical characteristics of the land surface as a result of reclamation cause a decrease in the surface air temperature in the reclamated region within 0.4°C and an increase in the amount of atmospheric precipitation within 2% of the climatic normals. At the same time, the maximum in the spatial distribution of secondary precipitation due to western transport shifts to the east relative to the reclaimed region. [ABSTRACT FROM AUTHOR]

The article presents the results of a study on the assessment of modern space–time trends of extreme values of air temperature and precipitation in 42 meteorological stations throughout Kazakhstan for the period from 1971 to 2020. Spatial and temporal analysis of the distribution of specialized climatic indices was recommended by the WMO climatology commission and an assessment of their trends was carried out. Spatial heterogeneity was revealed in terms of the degree of manifestation of changes and trends. Temperature indices are shown to confirm the overall warming trend. The division of the territory of Kazakhstan by the degree of manifestation of climate change into the southwestern and northeastern half was revealed. Extreme trends are most pronounced in the southwestern half, where a significant trend has been identified both for an increase in extremely high daytime and extremely low night temperatures. The calculated trends in temperature indices are generally significant, but the significance is mainly not ubiquitous; the trends are significant only in certain parts of Kazakhstan. WSDI and CSDI trends were found to confirm a widespread increase in the overall duration of heat waves and a reduction in the overall duration of cold waves. No significant extreme effects were found in the sediments. It is confirmed that Kazakhstan has weak, statistically insignificant, positive and negative trends in the maximum duration of the non-traveling period. Precipitation index trends, unlike temperature ones, are statistically insignificant in most of the country. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the performance of six models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in reproducing the monthly cycle of precipitation and maximum surface air temperature of the Hodna region in central Algeria during the baseline period 1901–2014. The six climate models selected are as follows: ACCESS-ESM4, BCC-CSM2-MR, CanESM5, GFDL-ESM1-5, IPSL-EM6A-LR, and MIROC6. The best-performing models are determined by comparing observation (CRU-TS) and historical data. The evaluation procedure is performed using the compromise programming method and multiple statistical metrics including mean bias error (MB), root mean square error (RMSE), and pattern determination coefficient (R2). The first two best-performing models are used for precipitation (IPSL-EM6A-LR) and maximum surface air temperature (GFDL-ESM4). Four future periods are considered: 2021–2040, 2041–2060, 2061–2080, and 2081–2100 for SSP1-2.6 and SSP3-7.0. For the most optimist scenario, the maximum surface air temperature may increase in the next decades in comparison with observed and simulated values by 2 °C, but then almost stabilizes and reaches an average monthly increase of 28.53 °C. The same is shown in the precipitation projection of 48.75 mm/month by 2100. Eventually, the SSP1-2.6 scenario does not show any current signs in the current Hodna basin climate on a global scale. Future precipitation projections under Hodna's SSP3-7.0 may decrease with an average value of 10 mm in a monthly scale. This decrease becomes mostly in the center and southeastern parts. Maximum surface air temperature can rise steadily from 28 to 31 °C and reach its maximum of 4.5 °C by 2100. The outcomes of this study will evaluate how projected changes will affect droughts and floods. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is often called the "Water Tower of Asia," which contains the largest amount of snow and glaciers outside the polar regions. As an important and variable feature of the land surface, snow coverage on the TP has great impacts on regional climate. However, the commonly used ERA5 reanalysis in dynamical downscaling largely overestimates the snow depth for the TP. To improve the representation of snow cover in ERA5, a new ERA5‐driven downscaling data set (High Asia Refined analysis version 2, HAR v2) was generated by the Weather Research and Forecasting (WRF) model with the bias‐corrected snow depth. This study aims to identify and better understand the impact of bias‐corrected initial snow conditions on simulated regional climate, by comparing the HAR v2 with a 5‐year ERA5 forced WRF simulation without bias correction of initial snow depth (referred to as WRF_ERA5). The results show that the bias correction significantly improves the simulation of 2 m air temperature (T2), with regional mean cold bias reduced by 0.2°C–2.4°C, but no significant improvement in precipitation simulation is found. Further comparative analysis reveals that higher snow depth in WRF_ERA5 leads to T2, mean daily precipitation, summer extreme precipitation, and contributions of convective precipitation to summer mean daily precipitation decrease by 0°C–4°C, 0%–60%, 0%–40%, and 0%–10%, respectively, in most areas of the TP. In addition, the bias‐corrected initial snow depth also has impacts on simulated diurnal cycles of precipitation and T2 and leads to peak hours one hour earlier. Overall, this study confirms the importance of snow cover for the climate in the TP. Key Points: Bias correction of ERA5 initial snow depth (BCISD) can significantly improve the simulation of 2 m air temperature (T2) over the TPBCISD (i.e., less snow) has a great effect on thermodynamic variables, resulting in increased precipitation (prcp) and higher T2BCISD also has impacts on simulated diurnal cycle of prcp and T2 and leads to peak hours one hour earlier [ABSTRACT FROM AUTHOR]

It is unambiguous that climate change alters the intensity and frequency of precipitation and temperature distribution at the global and local levels. The rate of change in temperature in the northern latitudes is higher than the worldwide average. The annual distribution of precipitation over the Himalayas in the northern latitudes shows substantial spatial and temporal heterogeneity. Precipitation and temperature are the major driving factors that impact the streamflow and water availability in the basin, illustrating the importance of research on the impact of climate change on streamflow by varying the precipitation and temperature in the Thuli Bheri River Basin (TBRB). Multiple climate models were used to project and evaluate the precipitation and temperature distribution changes in temporal and spatial domains. To analyze the potential impact of climate change on the streamflow in the basin, the Soil and Water Assessment Tool (SWAT) hydrological model was used. The climate projection was carried out in three future time windows. The result shows that the precipitation fluctuates between approximately +12% and +50%, the maximum temperature varies between [ABSTRACT FROM AUTHOR]