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The Canadian Cordillera in the province of British Columbia witnesses numerous rock falls every year. Studies on the recorded rock fall data in this area show that rock fall hazard follows weather conditions, especially precipitation and freeze-thaw cycles. This relationship indicates that a weather-based approach can be implemented to estimate possible changes in the rock fall hazard due to climate change. In this paper, we used a statistical approach to quantify the relationship between monthly weather averages and rock fall frequencies for a section of a transportation corridor along the Fraser River in British Columbia, Canada. In this regard, von Mises distributions are used to find the best-fitted models to the monthly precipitation and freeze-thaw cycles, and proper relative weights are applied to the models in order to calibrate them to the rock fall monthly frequency. The calibrated model is used with input data from climatic predictions for 2041–2070 and 2071–2100 to see how rock fall distribution will be affected due to climate change in the future decades. Results show that between 9 and 19%, more rock fall is anticipated in future winters. Rock falls are expected to decrease in other months, especially in October, November, March, and April. This paper presents a method to predict changes in rock fall hazard seasonality due to climate change and illustrates the method with a case study along a section of the Canadian Cordillera. [ABSTRACT FROM AUTHOR]

While political debates on climate change become increasingly heated, our houses and city infrastructure continue to suffer from an increasing trend of damages due to adverse atmospheric events, from heavier-than-usual rainfalls to heat waves, droughts, and floods. Adapting our homes and critical infrastructure to sustain the effects of climate dynamics requires novel data-driven interdisciplinary approaches for efficient risk mitigation. We develop a new systematic framework based on the machinery of statistical and machine learning tools to evaluate water-related home insurance risks and quantify uncertainty due to varying climate model projections. Furthermore, we introduce the concept of data depth to the analysis of weather and climate ensembles, which remains a novel territory for statistical depth methodology as well as the field of environmental risk and ensemble forecasting in general. We illustrate the new data-driven methodology for risk analysis in application to rainfall-related home insurance in the Canadian Prairies over 2002–2011. Supplementary materials accompanying this paper appear online. [ABSTRACT FROM AUTHOR]

In the last years, the Mediterranean basin has been widely recognized as one of the most vulnerable areas in the world to climate change; because of its high concentration of urban and industrial settlements, it is one of the most impacted areas of the world in terms of water scarcity. The present paper aims at reviewing the main observed and predicted effects of climate change on hydrological processes directly related to water availability in the Mediterranean Basin, mainly focusing on the last ten years of research. While an in-depth discussion about possible future water scarcity problem in the Mediterranean area and the sources of uncertainty affecting future climate projections and impact assessments is presented in a companion paper (Noto et al., 2022), this study highlights how most of the more recent studies for the Mediterranean region are concordant and recognize a general increasing future trajectory in both the mean and extreme values of air temperatures. On the contrary, there is much less agreement about the intensity and directions of future projections for other variables, such as precipitation, evapotranspiration, and runoff, whose changes are less evident and variable in space. [ABSTRACT FROM AUTHOR]

This paper presents results from high-resolution climate change simulations that permit convection and resolve mesoscale orography at 3-km grid spacing over Fenno-Scandinavia using the HARMONIE-Climate (HCLIM) model. Two global climate models (GCMs) have been dynamically down-scaled for the RCP4.5 and RCP8.5 emission scenarios and for both near and far future periods in the 21st century. The warmer and moister climate conditions simulated in the GCMs lead to changes in precipitation characteristics. Higher precipitation amounts are simulated in fall, winter and spring, while in summer, precipitation increases in northern Fenno-Scandinavia and decreases in the southern parts of the domain. Both daily and sub-daily intense precipitation over Fenno-Scandinavia become more frequent at the expense of low-intensity events, with most pronounced shifts in summer. In the Scandinavian mountains, pronounced changes occur in the snow climate with a shift in precipitation falling as snow to rain, reduced snow cover and less days with a significant snow depth. HCLIM at 3-km grid spacing exhibits systematically different change responses in several aspects, e.g. a smaller shift from snow to rain in the western part of the Scandinavian mountains and a more consistent decrease in the urban heat island effect by the end of the 21st century. Most importantly, the high-resolution HCLIM shows a significantly stronger increase in summer hourly precipitation extremes compared to HCLIM at the intermediate 12-km grid spacing. In addition, an analysis of the statistical significance of precipitation changes indicates that simulated time periods of at least a couple of decades is recommended to achieve statistically robust results, a matter of important concern when running such high-resolution climate model experiments. The results presented here emphasizes the importance of using "convection-permitting" models to produce reliable climate change information over the Fenno-Scandinavian region. [ABSTRACT FROM AUTHOR]

Accurate climate projections help policymakers mitigate the negative effects of climatic changes and prioritize environmental issues based on scientific evidences. These projections rely heavily on the outputs of GCMs (General Circulation Models), but the large number of GCMs and their different outputs in each region confuses researchers in their selection. In this paper, we analyzed the performance of a CMIP6 (Climate Model Intercomparison Project Phase 6) multi-model ensemble for Pr (precipitation) data over NE (Northern Europe). First of all, we evaluated the overall performance of 12 CMIP6 models from GCMs in 30 years of 1985–2014. Furthermore, future projections were analyzed between 2071 and 2100 using SSP1-2.6 and SSP5-8.5 (Shared Socioeconomic Pathways). Then, simulations were statistically improved using an ensemble method to correct the systematic error of the CMIP6 models and then the capacity of postprocessed data to reproduce historical trends of climate events was investigated. Finally, the possible spatio-temporal changes of future Pr data were explored in Tana River Basin. The results of this study show that different CMIP6 models do not have the same accuracy in estimating Pr in the study area. However, the ensemble method can be effective in increasing the accuracy of the projections. The results of this study projected a change in the monthly Pr data over Tana River Basin by 2.46% and 2.06% from 2071 to 2100 compared to the historical period, based on SSP1-2.6 and SSP5-8.5, respectively. [ABSTRACT FROM AUTHOR]

Due to global warming, droughts have become one of the focal points of researchers in the field of climate and water, all over the world. The analyses in this paper include spatial pattern and temporal trend for the territory of Serbia, over the 1949–2016 period. The De Martonne aridity index and the Ped drought index have been applied. Eighteen pairs of temperature and precipitation stations all over the country have been analyzed. The obtained results show a tendency toward a drier condition, which are not yet drastic. Drought areas for the territory of Serbia are increasing, but drought intensity and frequency should certainly be lower than those predicted for the Mediterranean coastal area, except in regions with very high human water use. Comparing the obtained results from stations at the original altitude and calculated data for the same stations at fixed virtual altitudes has shown that the natural direction of drought, which decreases from west to southeast, has shifted to a north to south direction. [ABSTRACT FROM AUTHOR]

Research into weather circulation changes over the UK for future climate has mainly focused on changes in the Summer and Winter seasons, with less analysis on seasonality and the transition seasons. Using the 30 Met Office weather patterns we examine the influence of climate change on seasonality through atmospheric circulation using a number of climate models. Changes in seasonality are important as they can have large impacts on many sectors including agriculture, energy and tourism. This paper finds a noticeable increase in Autumn over the UK in the frequency of drier summer-type regimes and a decrease in stormy winter types that emerge as early as the 2020s. The change in circulation signal once isolated from the overall signal is responsible for a 4–12% decrease in Autumn mean rainfall on average for England by the end of this century (where the values in the range are dependent on the emissions scenario). This change is projected over English regions that are already experiencing water stress, and with predictions of drier summers over the UK in future, this could further increase drought risk. The change in circulation in Autumn also moderates the large increase in the number of large-scale extreme daily rainfall events over the same regions predicted due to climate change. While this future circulation change is replicated across all the climate models used, large differences remain in the strength of the signal between models. The climate models used replicate the frequency of the 30 weather patterns well for all seasons. [ABSTRACT FROM AUTHOR]

Any hydro-meteorology variable includes different components, in general, such as periodicity, trend, possibly jump, and uncertain stochastic parts. Among these, the trend analysis gained importance in the last three decades due to global warming and climate change effects. The literature is full of monotonic trend applications by taking into consideration trend analysis methodologies such as Mann–Kendall trend identification, Sen trend slope calculation, and Şen innovative trend analysis (ITA). It is more important in practical studies to deal with less than one-year durations to assess the possible trend pieces for better practical uses such as agricultural productivity purposes. In this paper, a new concept is applied, known as the innovative polygon trend analysis (IPTA), to assess the trend component transitions between two successive months. The application of the methodology is presented for the coastal region of northeast Algerian precipitation records. The emanated results from this study provided information that El Taref station has the most unstable precipitation behavior among all the meteorology stations in the study area, moving from a month to another rather very unsystematically; whereas other meteorology stations have systematic movement from a month to the subsequent one. [ABSTRACT FROM AUTHOR]

Concurrent compound dry and hot events (CDHEs) amplified more damange on the ecosystems and human society than individual extremes. Under climate change, compound dry and hot events become more frequent on a global scale. This paper proposes a mathematical method to quantitatively attribute changes of CDHEs to changes of precipitation, change in temperature and change in the dependence between precipitation and temperature. The attribution is achieved by formulating the total differential equation of the return period of CDHEs among Meta-gaussian model. A case study of China is devised based on monthly precipitation and temperature data during the period from 1921 to 2020 for 80 major river basins. It is found that temperature is the main driving factor of increases in CDHEs for 49 major river basins in China, except for the upper and middle reaches of the Yangtze River. In West China, precipitation changes drove the increase in CDHEs in 18 river basins (23%), particularly in parts of North Xinjiang, Qinghai and Gansu. On the other hand, dependence between precipitation and temperature dominated changes of CDHEs in 13 river basins (16%) of China with other factors, including parts of South China, East China and Northwestern China. Furthermore, changes in both the mean and spread of precipitation and temperature can also contribute to changes in CDHEs. [ABSTRACT FROM AUTHOR]

Changes in patterns of meteorological parameters, like precipitations, temperature, wind, etc., are causing significant increases in various extreme events. And these extreme events, i.e., floods, heatwaves, hurricanes, droughts, etc., lead to a shortage of water resources, crop failures, wildfires, and economic losses. However, Global Circulation Models (GCMs) are considered the most important tools for quantifying climate change. Therefore, we selected 20 different GCMs of precipitation in our research, as the frequency of extreme events, like drought and flood, is highly related to changes in precipitation patterns. However, this research introduced a new weighting scheme — MCFSAWS-Ensemble: Monte Carlo Feature Selection Adaptive Weighting Scheme to Ensemble multiple GCMs, whereas, Monte Carlo Feature Selection (MCFS) is one of the most popular algorithms for discovering important variables. However, the proposed weighting scheme (MCFSAWS-Ensemble) is mainly based on two sources. Initially, it evaluates the prior performance of each GCM model to define their relative importance using MCFS. Then, it computes value by value difference between the observed and simulated model. In addition, the application of this paper is based on the monthly time series data of precipitation in the Tibet Plateau region of China. In addition, we used twenty GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to analyze the implications of the MCFSAWS-Ensemble. Further, we compared the performance of the MCFSAWS-Ensemble scheme with Simple Model Averaging (SMA) through Mean Average Error (MAE) and correlation statistics. The results of this research indicate that the proposed weighting scheme (MCFSAWS-Ensemble) is more accurate than the SMA approach. Consequently, we recommend the use of advanced machine learning algorithms such as MCFS for making accurate multi-model ensembles. [ABSTRACT FROM AUTHOR]

This paper presents a synthesis of the main characteristics of precipitation in the State of Rio de Janeiro (Brazil) based on extreme rainfall indicators. Daily precipitation data are derived from 56 rainfall stations during the second half of the twentieth century and the 2000s. Eight indices related to extreme precipitation were analyzed. The Mann–Kendall nonparametric test and the Sen's Curvature were employed to evaluate the significance and magnitude of trends. The primary climatological aspects and identified trends throughout the last decades are discussed, besides the hydrometeorological impacts associated with them. Lower values of annual total precipitation are recorded in northern Rio de Janeiro (around 800 mm) and higher in the southern State (up to 2,200 mm). The Serra do Mar affects the frequency of heavy precipitation, and the areas near the sea and high relief present the highest values of consecutive days with expressive rainfall (more than 150 mm in 5 days). These areas also showed a high concentration of flood and landslides events. Most of Rio de Janeiro exhibits precipitation intensity of about 13 mm/day. The maximum number of consecutive dry days shows a gradient from the coast (about 30 days) to the State's interior (around 50 days). Regarding trends, there is a growth of accumulated extreme precipitation in various stations near the ocean. The extreme rainfall in 24 h displays an increase in most Rio de Janeiro (+ 1 to + 5 mm/decade). The consecutive dry and rainy days present similar signs of decreasing trends, suggesting irregularly distributed precipitation in the State. This study is especially relevant for decision-makers who need detailed information in the short and long term to prevent natural hazards like floods and landslides and the related impacts in the environmental and socioeconomic sectors of the Rio de Janeiro. [ABSTRACT FROM AUTHOR]

The spatial and temporal variability of the main climatic indicators on the territory of the Volga Federal District in the 20th–21st centuries is considered. A general increasing trend in air temperature is revealed, and a heterogeneous pattern of precipitation changes is shown. The temperature variations until the end of the 21st century are analyzed on the example of Kazan using 40 CMIP6 climate models for four anthropogenic scenarios. In the paper, there is an assessment of the dynamics of agroclimatic resources on the territory of the Volga Federal District: the duration of the growing season, the sum of positive temperatures, total precipitation, and photosynthetic radiation. A correlation has been found between the temperature fluctuations in the region and the atmospheric circulation indices (NAO, AO, SCAND, and EAWR). For the territory of Tatarstan, a degree of aridity and waterlogging is evaluated using the agroclimatic indices: the Budyko's dryness index, the Selyaninov's hydrothermal coefficient, the Sapozhnikova's moisture index. It is shown that there is a tendency toward an increase in the duration of the growing season, its heat supply and aridity in the region in summer. A statistical estimation of the dependence of spring wheat yield on the agroclimatic indices on the territory of the Republic of Tatarstan is given. [ABSTRACT FROM AUTHOR]

In the paper, the frequency and spatial distribution of atmospheric and hydrological droughts over the territory of Belarus in 1945–2020 is assessed. Aridity is evaluated using the standardized precipitation and streamflow indices (SPI and SSFI). Trends in monthly total precipitation are determined, the features of the streamflow formation during the open-channel period are revealed. The frequency of anticyclones that determines hydrometeorological conditions on the territory of Belarus is calculated. The statistically significant increase in the number of the days with anticyclonic weather over the country during the warm season is found. The increasing frequency of dry conditions in summer months against the background of a rise in the precipitation intensity is highlighted. A simultaneous increase in the frequency of very-low-flow periods on rivers and an increase in the height of warm rainfall floods in some river basins are revealed. [ABSTRACT FROM AUTHOR]

The overview of papers dealing with the analysis of current and future climate change on the territory of Russia and their impact on the crop productivity is presented. Using the reanalysis data for 1950–2020, trends in air temperature and precipitation are estimated for different regions of Russia. A correlation was found between changes in temperature and atmospheric circulation indices. [ABSTRACT FROM AUTHOR]

Global warming and climate change impacts intensify hydrological cycle and consequently unprecedented drought and flood appear in different parts of the world. Meteorological drought assessments are widely evaluated by the concept of standardized precipitation index (SPI), which provides drought classification. Its application is based on the probabilistic standardization procedure, but in the literature, there is a confusion with the statistical standardization procedure. This paper provides distinctive differences between the two approaches and provides the application of a better method. As a novel approach, SPI classification is coupled with fuzzy clustering procedure, which provides drought evaluation procedure based on two variables jointly, precipitation and temperature, which is referred to as the standard precipitation-temperature index (SPTI). The final product is in the form of fuzzy c-means clustering in five clusters with exposition of annual drought membership degrees (MDs) for each cluster and resulting objective function. The application of the proposed fuzzy methodology is presented for the long-term annual precipitation and temperature records from New Jersey Statewide records. [ABSTRACT FROM AUTHOR]

The Sierra Nevada and Southern Cascades—California's snowy mountains—are primary freshwater sources and natural reservoirs for the states of California and Nevada. These mountains receive precipitation overwhelmingly from wintertime storms including atmospheric rivers (ARs), much of it falling as snow at the higher elevations. Using a seven-decade record of daily observed temperature and precipitation as well as a snow reanalysis and downscaled climate projections, we documented historical and future changes in snow accumulation and snowlines. In four key subregions of California's snowy mountains, we quantified the progressing contribution of ARs and non-AR storms to the evolving and projected snow accumulation and snowlines (elevation of the snow-to-rain transition), exploring their climatology, variability and trends. Historically, snow makes up roughly a third of the precipitation affecting California's mountains. While ARs make up only a quarter of all precipitating days and, due to their relative warmth, produce snowlines higher than do other storms, they contribute over 40% of the total seasonal snow. Under projected unabated warming, snow accumulation would decline to less than half of historical by the late twenty-first century, with the greatest snow loss at mid elevations (from 1500 to 3300 m by the mountain sub-regions) during fall and spring. Central and Southern Sierra Nevada peaks above 3400 m might see occasionally extreme snow accumulations in January–February resulting entirely from wetter ARs. AR-related snowlines are projected to increase by more than 700 m, compared to about 500 m for other storms. We discuss likely impacts of the changing climate for water resources as well as for winter recreation. [ABSTRACT FROM AUTHOR]

This study investigates possible rainfall and drought trends using data from 38 rainfall stations in the Medjerda basin (northeast of Algeria) over 54 years (1965–2018). Drought-related data were calculated with the Standardized precipitation index (SPI). The Mann–Kendall test was used to find positive or negative precipitation trends. The magnitude of these trends was calculated using Sen's slope method. According to the analysis, a decrease during the spring precipitation season was observed. Furthermore, the authors found the maximum increasing (decreasing) precipitation magnitude to be 2.14 mm/season (− 4.41 mm/season) in winter (spring). In addition, the magnitude of the precipitation trend per year ranged from − 6.26 to 2.54 mm/year, with an average reduction of 39% for the entire basin. From the outcomes of drought trend analysis, it can be inferred that for a short-time scale, the innovative trend analysis method exhibited a negative trend for the minimum and maximum SPI values. Drought severity was found to have increased during severe and extreme wet episodes, directly affecting Algeria's frequently drought-affected agricultural regions, such as the Merdja plain and the irrigated perimeters of Sedrata and Zouabi. Considering the long-time scales, an increase was detected in drought severity and a decline during severe and extreme wet episodes. These findings show that the southeastern and central parts of the Medjerda basin's long-term water resources have been severely affected, which negatively impacts the newly-constructed Ouldjet Mellegue dam in Tébessa province. [ABSTRACT FROM AUTHOR]

Trend analysis benefits collecting and analyzing reliable data in climate change studies. In this context, long-term temperature and precipitation data analysis, two variables sensitive to climate change, is essential. This study aims to holistically and partially determine the annual trends of precipitation and temperature time series for 1970–2019 at nine selected stations in the Susurluk Basin, Turkey. The innovative trend significance test (ITST), innovative crossing trend analysis (ICTA) method, and Mann-Kendall (MK) test were used to determine holistic trends. Also, partial trends were determined using successive average methodology (SAM). For the precipitation variable, while an increasing trend was determined for the ITST, there was mostly no trend for the other methods. While a strong increasing trend was detected for the temperature according to the ITST and MK methods, no trend was observed in any station according to the ICTA method. According to the SAM results, the maximum trend durations for the peak and trough change points were 4.9 (10.3) and 5.3 (8.4) years, respectively, for precipitation (temperature). The strong temperature trends in the basin will likely continue, requiring precautions against extreme events such as drought. [ABSTRACT FROM AUTHOR]

The present study investigated future temperature and precipitation changes over Greece using the Weather Research and Forecasting (WRF) model. WRF was driven by EC-EARTH over Greece at very high resolution for the historical period (1980–2004), along with projected simulations, in the near future (2025–2049) and far future (2075–2099) under the Representative Concentration Pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). Climatic variables were produced at 5-km grid spacing and 6-h interval. The historical simulation was evaluated against the available station observations. The analysis showed that the model underestimated the maximum temperatures and slightly overestimated the minimum temperatures. Also, the model simulated a small dry bias in precipitation with an excellent representation of the spatial patterns. The model projections for temperature under the two emission scenarios compared to the historical simulation revealed a robust magnitude of future warming with the most pronounced changes predominantly over the eastern areas of the country under the RCP8.5 in the far future. Projected precipitation changes were more evident in the far future with an overall decrease of the annual precipitation all over the eastern part of the country (with islands included) with the most dramatic reductions (above 40%) of seasonal precipitation observed under RCP8.5. Increases in the number of hot days were found everywhere with more pronounced changes over the plain areas under RCP8.5 in the far future. Significant increases of dry days were projected over the eastern part of the mainland and more intensely under RCP8.5 in the far future. [ABSTRACT FROM AUTHOR]

The northern zone of Cameroon, which depends mainly on agriculture, is considered one of the most vulnerable regions in the country to climate change. Few studies based on field data have examined the changes in climatic conditions that affect agriculture. This research focuses on fluctuations in precipitation that determine dry and wet seasons. From 1973 to 2020, data were collected from weather stations located in three major cities in northern Cameroon: Ngaoundere, Garoua and Maroua. Data were tested for homogeneity using the Pettitt and Buishand tests. Trends were analyzed using the Mann–Kendall test, Sen's slope estimator and the regression line, while drought severity was assessed using the standardized rainfall index method. These data homogeneity tests were performed using two statistical tools, SPSS and XLSTA software. According to Pettitt's test, rainfall increased by 29.6% in Ngaoundere from 1997 to 2020 compared to the previous years of 1973–1996; in Garoua, rainfall increased by 36.2% from 1988 to 2020 compared to the previous years of 1973–1987. However, from 1973 to 2020, the average rainfall in Maroua remained stable at approximately 716.5 mm, with a decreasing trend according to the Mann–Kendall test. In conclusion, this study shows that rainfall has increased significantly in the cities of Ngaoundere and Garoua, making these areas favorable for seasonal and market gardening. However, in Maroua, caution is advised, as rainfall is reportedly decreasing in this locality, increasing the risk of food insecurity. A credible climate warning system must be implemented on a large scale to guide farmers. [ABSTRACT FROM AUTHOR]

The Horn of Africa is the most food insecure region in the world. More than 40 percent of the population in the region is malnourished. This study aims to examine the effects of climate change on food insecurity using panel data from the Horn of Africa. The GMM estimator of the dynamic panel model was used to analyze the impact of climate change. The study findings show that food insecurity in the Horn of Africa is adversely affected by temperature. Keeping all other inputs constant, an increasing the mean temperature and carbon dioxide emissions by 1percent results in an increase in food insecurity of 0.357 percent and 0.026 percent, respectively. It was also observed that a 1 percent increase in precipitation resulted in a 0.023 percent decrease in food insecurity. The study results indicate that cereal yield, food production index, and political stability were significant and negatively influenced food insecurity. This study concluded that climate change results in food insecurity in the Horn of Africa, and food availability is expected to be reduced in the region. In order to cope with the adverse consequences of climate change, adopting high-temperature and drought-resistant varieties of improved food crops is advisable to ensure food availability and food security for the region. [ABSTRACT FROM AUTHOR]

The corresponding relationships between temperature, precipitation, and polycyclic aromatic hydrocarbon (PAH) concentration in a typical ombrotrophic peatland in Dajiuhu, Shennongjia, were quantitatively characterized by field sampling tests validated with simulation experiments. The PAH concentrations of peat cores in Dajiuhu peatland ranged from 262 to 977 ng·g−1, with a mean value of 536 ± 284 ng·g−1. PAHs were mainly composed of 2–3 ring PAHs, accounting for 31.7% ± 2.00% and 31.7% ± 5.00%, respectively. The concentration of PAHs in peat cores showed a significant decrease with increasing temperature, while the low molecular weight PAHs (LMW-PAHs) were more sensitive to temperature changes compared to the high molecular weight PAHs (HMW-PAHs). Besides, with the increase of quantity and velocity of leaching liquid, PAHs in peat were first transferred in the form of attached large-size particles and then gradually entered the aqueous phase. According to the IPCC projections of global warming, Dajiuhu peatland will release 956 ± 26.3 kg·°C−1 PAHs into gas phase during 2030–2052, and a conservative projection based on local temperature trends showed that 459 ± 12.6 kg·°C−1 PAHs will be released into gas phase by 2047 in Dajiuhu peatland. The projected release fluxes of PAHs in Dajiuhu peatland with precipitation volume and precipitation velocity are 381 ± 201 kg·100 mm−1 and 1052 ± 167 kg·min·mL−1, respectively, which are primarily from peat into particulate and aqueous phase. [ABSTRACT FROM AUTHOR]

Predicting forest carbon cycling requires the accurate assessment of large-scale patterns of fine root seasonal dynamics, and thorough comprehension of how biotic and abiotic factors exert direct and/or indirect control over the variation in fine root biomass (FB), necromass stocks (FN) and the biomass/necromass ratio (FBN). We analyzed 67 studies with 1119 observations of FB and FN and used structural equation modeling to examine the relative contributions of the forest biome (boreal versus temperate versus tropical), evolutionary division (angiosperms versus gymnosperms), climate (monthly versus annual), edaphic and geomorphic properties in determining FB, FN and FBN. Temperate forests had a greater FB but lower FN than tropical and boreal forests. Compared with angiosperm forests, gymnosperm forests had a significantly smaller FB and FN but a similar FBN on the global scale. Angiosperm forests had different seasonal patterns of FB, FN and FBN compared to gymnosperm forests in tropical and temperate biomes throughout a year. Climatic and edaphic variables had dominant effects on fine root dynamics. Geomorphic properties directly and/or indirectly mediated fine root dynamics by influencing soil and climatic conditions. Temperature and precipitation at the monthly and annual scales exhibited strong direct effects on FB, FN and FBN, and indirect effects mediated through soil properties. Our synthesis provides evidence that responses of fine roots to environmental factors vary with both evolutionary division and forest biome, suggesting that future climate changes may alter the competition relations among co-existing species (for example, angiosperms versus gymnosperms), belowground carbon stocks, and also ecosystem composition and diversity. [ABSTRACT FROM AUTHOR]

Little guidance is available to assist wetland managers in developing climate adaptation plans. To facilitate development of recommendations for adaptation strategies, it is essential to first determine if or how wetland managers are addressing these challenges. We used an online survey to solicit feedback from wetland managers and biologists in the Southern Great Plains of North America to gain information on perceptions of wetland managers regarding climate change; assess how the effects of climate change are being addressed through management; and identify barriers to implementing climate change adaptation. The majority of wetland managers (63%) agreed they are currently experiencing effects of climate change in wetlands, and most respondents (76%) reported that changes in the timing of water availability throughout the year was the most likely impact. Managers reported using a diversity of approaches in managing for changing precipitation, with management of native and invasive plant species being the two most common practices. Lack of funding and personnel were the most commonly identified factors limiting manager's response to changing precipitation patterns. In addition, >50% of managers indicated uncertainty about the effects of climate change on wetlands as a barrier to management, which may relate to limited access to peer-reviewed science. While most of the management practices reported were short-term measures and may not reflect long-term adaptation for climate change, the fact that many managers are considering climate change in their management suggests that there is considerable opportunities to continue developing capacity for climate change adaptation in the region. [ABSTRACT FROM AUTHOR]

Dams are studied not only for potential advantages but also for possible environmental repercussions. The objective of this case study is to see the effects caused by Gomal Zam Dam on temperature, humidity and precipitation in their surroundings, both spatially and temporally. The meteorology parameters' characteristics have been detected using two different approaches, Mann–Kendall statistical test and Sen's slope estimator. Data stations chosen were those that have been close to the dam and sufficiently far away from the dam. As a consequence, although temporal changes in mean heat were established, periodic and regional disparities in humidity readings were found. [ABSTRACT FROM AUTHOR]

Precipitation and temperature, the two most important climate variables, must be thoroughly studied in order to comprehend the hydrological response of any watershed to climate variability. The Himalayan watersheds, in particular, are extremely sensitive to even minor climate changes due to their fragile ecosystem, affecting the socioeconomic conditions and the pristine environments. The goal of this study is to investigate the spatial, temporal, and climate variability of a data-sparse Himalayan watershed. The spatial patterns of the two variables are analysed at monthly, seasonal, and annual time scales. The Mann–Kendall (MK) test and Sen's slope estimator are employed to detect the trends and their respective magnitudes for precipitation and temperature at different time scales. The findings imply that orographic factors influence precipitation patterns, while elevation variations influence temperature trends in the study area. The western disturbances account for around 68% of annual precipitation in the watershed, while the Indian summer monsoon accounts for 32%. The results of the trend analysis show that both temperature and precipitation are increasing on an annual scale, which could lead to glacier melting, decreased snowfall, and the occurrence of extreme events in the future. Because the region is data-scarce, the study will be helpful in better understanding its hydrology. It can also aid in the more effective execution of rainfall-runoff hydrological modelling. [ABSTRACT FROM AUTHOR]

In this study, monthly meteorological parameters of temperature, precipitation, and wind speed recorded at 104 synoptic weather stations scattered across Iran were analyzed to construct annual time series of the meteorological data for a 30-year period (1988–2017) using the Mann–Kendall test and the Sen's slope estimator. Based on the de Martonne aridity index () classification, Iran's climate is mostly categorized as dry and semi-dry. The results indicated annual temperature significantly increased at about 61% of stations and annual precipitation significantly decreased at 21% of stations (at the 95% and 99% significance level). The decline in precipitation occurred in mostly the dry (27%) and semi-dry (21%) regions of Iran. Approximately half of the stations experienced significant increases in wind speed with arid areas experiencing broadest increase. Prediction of future impacts of climate change is needed for this region to mitigate negative effects. [ABSTRACT FROM AUTHOR]

A comprehensive assessment of twenty-first century climate change in the European Alps is presented. The analysis is based on the EURO-CORDEX regional climate model ensemble available at two grid spacings (12.5 and 50 km) and for three different greenhouse gas emission scenarios (RCPs 2.6, 4.5 and 8.5). The core simulation ensemble has been subject to a dedicated evaluation exercise carried out in the frame of the CH2018 Climate Scenarios for Switzerland. Results reveal that the entire Alpine region will face a warmer climate in the course of the twenty-first century for all emission scenarios considered. Strongest warming is projected for the summer season, for regions south of the main Alpine ridge and for the high-end RCP 8.5 scenario. Depending on the season, medium to high elevations might experience an amplified warming. Model uncertainty can be considerable, but the major warming patterns are consistent across the ensemble. For precipitation, a seasonal shift of precipitation amounts from summer to winter over most parts of the domain is projected. However, model uncertainty is high and individual simulations can show change signals of opposite sign. Daily precipitation intensity is projected to increase in all seasons and all sub-domains, while the wet-day frequency will decrease in the summer season. The projected temperature change in summer is negatively correlated with the precipitation change, i.e. simulations and/or regions with a strong seasonal mean warming typically show a stronger precipitation decrease. By contrast, a positive correlation between temperature change and precipitation change is found for winter. Among other indicators, snow cover will be strongly affected by the projected climatic changes and will be subject to a widespread decrease except for very high elevation settings. In general and for all indicators, the magnitude of the change signals increases with the assumed greenhouse gas forcing, i.e., is smallest for RCP 2.6 and largest for RCP 8.5 with RCP 4.5 being located in between. These results largely agree with previous works based on older generations of RCM ensembles but, due to the comparatively large ensemble size and the high spatial resolution, allow for a more decent assessment of inherent projection uncertainties and of spatial details of future Alpine climate change. [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 present study aims to investigate the combined effects of temperature, precipitation, ecological footprint, carbon footprints, rice plant area harvested, and fertilizer use on Nigeria's rice production by using data from 1971 to 2018. The study used the bounds test for cointegration and the novel dynamic ARDL (DYNARDL) simulation approach. The bounds test shows a long-run relationship. The empirical results show that temperature has a positive long-run effect on rice production; however, this result is insignificant. Furthermore, rainfall has a negative long-run effect on rice production. The ecological footprint has a positive long-run effect on rice production. In contrast, carbon footprint has a negative long-run effect on rice production. For non-climatic input factors, potash fertilizer has positive short-run and long-run effects on rice production, and rice area harvested has a positive but insignificant long-run effect on rice production. The study provides valuable policy directions for the policymakers in Nigeria. [ABSTRACT FROM AUTHOR]

A study is made of the changes in climatic characteristics such as air temperature, atmospheric pressure, and precipitation and their relationship with the large-scale atmospheric circulation over Siberia for the climatically significant time interval of 1979‒2018. The study area is limited to 50°‒70° N and 60°‒110° E. Daily observational data from NOAA GSOD are used in calculating the series of territory-averaged values of surface temperature, atmospheric pressure, and average precipitation. The characteristics of baric formations of cyclones and anticyclones are determined on the basis of surface synoptic maps for standard meteorological periods. It is found that, by the end of the study period, the trend in surface temperature and precipitation is positive and the trend in atmospheric pressure is negative. The trend in characteristics of baric formations, such as the number of cyclones and anticyclones, is positive, as is the pressure trend in the centers of anticyclones. On the contrary, the pressure trend in the centers of cyclones is negative, as is the trend in the duration of the impact of cyclones and anticyclones. It is shown that these trends underwent the most dramatic changes during 2012‒2018, with a change of sign of the trend in pressure in the centers of anticyclones. Taking into consideration the close relationship between climatic characteristics and large-scale atmospheric circulation, it can be suggested that the warming in Siberia before 2012 was due to a weakening of anticyclonic activity and after 2012 it was due to an increase in cyclonic activity. [ABSTRACT FROM AUTHOR]

Intensification of hydrologic cycle, and consequence rise of intense short-term precipitation, are considered as the manifestations of climate change. This may lead to an alteration in Intensity–Duration–Frequency (IDF) relationship that may change other hydrological processes as well. The IDF relationship also serves as a crucial information for the design of any water infrastructure. This study investigates the spatiotemporal changes in IDF relationship involving hourly precipitation events between past and future climate at various return periods across India that spans over a wide range of climatology. Contrast between historical (1979–2014), using two reanalysis data, and future periods (immediate future: 2015–2039, near-future: 2040–2059 and far-future: 2060–2100) is explored along with its spatial (re-) distribution. The future simulations of precipitation are derived from three climate models, participating in 6th phase of Coupled Model Intercomparison Project (CMIP6), for three shared socio-economic pathways (SSPs), i.e., SSP126, SSP245 and SSP585. The results show that almost entire Indian mainland will experience an increase (~41–44%) in the hourly precipitation intensity under the worst climate change scenario (SSP585) with a return period as low as 2 years (almost a regular incidence). Furthermore, even under a moderate climate change scenario (SSP245), almost entire Indian mainland (~82–99% of spatial extent) will be affected from a significant increase (on an average 19%) in the hourly precipitation intensity. It is true for higher return periods as well. Findings of the study are alarming for many water infrastructures. This study develops new set of IDF curves across India considering a changing climate that will be useful to set a revised design criteria for water infrastructure. [ABSTRACT FROM AUTHOR]

Precipitation changes over the Tibetan Plateau (TP), "Asian Water Tower", greatly affect water resources of the surrounding countries. A dipole pattern in summer precipitation trend over the TP is observed for 1961–2013, increasing over the north TP (NTP) and decreasing over the south TP (STP). Since the TP is one of the most vulnerable regions to climate change in the world, it is of great importance to investigate the role of anthropogenic forcing in the TP precipitation changes. Moisture budget analysis based on reanalysis reveals that the precipitation trends over NTP and STP are dominated by thermodynamic and dynamic terms of vertical moisture advection, respectively. Southward shift in the summer subtropical Asian westerly jet (AWJ) over the west of TP and northward shift in AWJ over the east of TP collaboratively result in the increase and decrease in dynamic component over NTP and STP, respectively. Here, we successfully detect the anthropogenic contribution to the NTP summer precipitation trends using the attribution experiments from the CLIVAR Climate of the 20th Century Plus Project (C20C+). The drying trends over STP are mainly controlled by internal variability, and the anthropogenic forcing is favorable for the drying trends. The impacts of anthropogenic forcing are twofold. First, human activity induced warming increases the specific humidity over TP, increasing the thermodynamic component of moisture budget. Second, the warming trend caused by anthropogenic forcing is unevenly distributed over the Eurasian continent, leading to the southward (northward) shift of AWJ over the west (east) of TP, favoring more precipitation over the NTP but less precipitation over the STP. This study provides evidence of the importance of anthropogenic forcing on the water cycle changes over the TP. [ABSTRACT FROM AUTHOR]

The ongoing global warming has caused unprecedented changes in the climate system, leading to an increase in the intensity and frequency of weather and climate extremes. This study uses the sixth phase of Coupled Model Intercomparison Project (CMIP6) data to investigate projected changes in drought events over East Africa (EA) under four Shared Socioeconomic Pathway (SSP) emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-4.0, and SSP5-8.5). The CMIP6 data are bias-corrected using a quantile mapping method, with the Climatic Research Unit's precipitation dataset as reference. Drought is quantified using the standardized precipitation index and different measures of drought are estimated: drought duration, drought frequency, drought severity, and drought intensity. Evaluating the accuracy and reliability of historical data before and after bias correction demonstrates the importance of the approach. The overall distribution after bias correction depicts a close agreement with observation. Moreover, the multi-model ensemble mean demonstrate superiority over individual Global Circulation Models. Projected future changes show enhancement in precipitation over most parts of EA in the far future under different SSP scenarios. However, the arid and semi-arid regions are expected to receive less amount of precipitation, whereas the highlands and lake regions are expected to receive a larger amount of precipitation increase. Furthermore, the dry areas of EA are likely to experience more frequent drought events with longer duration, stronger intensity, and severity in the far future. Overall, this study identifies possible drought hotspots over EA, enabling early preparation for such events. [ABSTRACT FROM AUTHOR]

Under global warming, according to results obtained from offline drought indices driven by projections of general circulation models (GCMs), future droughts in China will worsen but the results are not consistent. We analyzed changes in droughts covering the entire hydrologic cycle using outputs of GCMs of the 6th Coupled Model Intercomparison Project (CMIP6) for SSP2-4.5 and SSP5-8.5 climate scenarios, and compared the results with that of popular, offline drought indices [the self-calibrating Palmer Drought Severity Index (scPDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Actual Evapotranspiration Index (SPAEI)]. Among meteorological, agricultural, and hydrological drought indices tested under both SSP scenarios, the results obtained from SPAEI and scPDSI agree better with univariate drought indices than SPEI. scPDSI generally agrees well with agricultural droughts (Standardized Soil Moisture Index with the surface soil moisture content; SSIS). Future droughts estimated using soil moisture analysis are more widespread than that from precipitation and runoff analysis in humid regions of South China by the end of the twenty-first century. In arid northwestern China and Inner Mongolia, drought areas and severity based on scPDSI and SSIS forced with the SSP scenarios show obvious decreasing trends, in contrast to increasing trends projected in South China. Trends projected using SPEI contradict those projected by other drought indices in non-humid regions. Therefore, selecting appropriate drought indices is crucial in project representative future droughts and provides meaningful information needed to achieve effective regional drought mitigation strategies under climate warming impact. [ABSTRACT FROM AUTHOR]

Global circulation models have been used to project future climate changes, which encourage experts to design mitigation measures. Still, it is challenging to use the raw data at a local scale without downscaling. Hence, this study applied a statistical downscaling model to downscale daily data generated from the second generation of the Canadian Earth System Model under two Representative Concentration Pathways scenarios (RCP4.5 and RCP8.5) using observed data for model calibration and validation. The downscaled results showed that the maximum temperature likely to increases in the range of 2.04–2.50 °C for RCP4.5 in the 2050s (2041–2070) and 2080s (2071–2099), respectively, and the minimum temperature indicate an increase by 0.87 °C in 2050s and 1.56 °C in 2080s averaged over the watershed level. The projected mean annual and seasonal air temperatures are likely to increase up to the end of the twenty-first century at all stations. The utmost annual rainfall change is projected to be 14.5% in the 2080s for RCP4.5 at Modjo. The highest seasonal precipitation change is projected to be 30.9% (RCP8.5) in the main rainy season (Kiremt) at Chefedonsa. Seasonal-based future projection of the precipitation shows non-significant trends, except the Kiremt season. The study revealed that the temperature was highly influenced by altitude and slightly affected by corresponding land use land cover type. In general, the increase in temperature could worsen the environmental conditions in warm seasons; and an increase in precipitation in the Kiremt season is expected to bring a likely risk of flooding. [ABSTRACT FROM AUTHOR]

The manuscript provides an assessment of precipitation changes in Kazakhstan over the period 1941–2020, also calculated the trend component for the period 1976–2018. Prediction of rainfall amount based on two scenarios RCP 2.6 and 4.5. The study is very important for Kazakhstan, which is vulnerable to present and future climate change. There are many lakes in the Republic of Kazakhstan with different quality and quantity of water. In this regard, in work the features of the temporal distribution of precipitation in 6 water basins, where the monitoring lakes of Kazakhstan are located. In winter, the tendency to increase in atmospheric precipitation for the period 1976–2020 is traced in all water basins, with exception of the Shu-Talas basin, and a statistically significant increase in precipitation by 5.2 mm/10 years observed only on the territory of the Balkash-Alakol basin. According to the forecast data, an increase in precipitation is also expected in winter, with the exception of a statistically significant decrease in precipitation (10–20%, RCP 2.6) in the Balkash-Alakol basin. In spring, a statistically significant increase in the amount of atmospheric precipitation is noted in the Zhaiyk-Caspian, Esil basins in the range from 7.9 ... to 8.9%/10 years. Under the RCP 4.5 scenario, an upward trend in precipitation is also expected in these areas. In summer, in the Nura-Sarysu basin, there is a positive trend of precipitation by 7.3%/10 years, and according to both scenarios precipitation in the Nura-Sarysu, basin will increase by 10–50%. In autumn, a decrease in the amount of atmospheric precipitation is traced in the Zhaiyk-Caspian basin by 4.9%/10 years; according to the forecast in November (RCP 2.6) and October (RCP 4.5), a decrease in precipitation is expected by 20–30%. [ABSTRACT FROM AUTHOR]

Ecosystem carbon balance might be affected by the variability of seasonal distribution of precipitation under global climate change. Using the eddy covariance (EC) technique, long-term observations of ecosystem net CO2 exchange (NEE) were acquired over Lijiang alpine meadow in the southeastern Tibetan Plateau from January 2014 to August 2019. During the wet season (from June to October), Lijiang meadow functioned as a carbon sink (− 37.6 ± 22.5 g C m−2 month−1), while in dry season, the meadow varied between a weak carbon source and sink with an average monthly NEE of − 3.9 ± 11.9 g C m−2 month−1. Monthly CO2 fluxes were mainly controlled by air temperature and soil water content. A large annual variation of CO2 uptake was observed. The annual NEE was − 140.3 g C m−2 year−1 in 2014 while − 247.0 g C m−2 year−1 in 2016. Correspondingly, the precipitation in wet season accounted 90% of annual precipitation in 2014 and 74% of that in 2016 despite the annual precipitation was larger than 1200 mm in both years. More precipitation in dry season can lead to longer period of net CO2 uptake, while more precipitation concentrated in wet season depressed the meadow's light response through the decrease of the magnitude of light-saturated net CO2 exchange (NEEsat) at the onset and the end of growing season. [ABSTRACT FROM AUTHOR]

The availability of quality precipitation records in the current climate situation is of great importance in the scientific-technical field but also for the public institutions that manage the meteorological networks. This work has implemented a comprehensive spatial quality control procedure in the semiarid region of Andalusia (Southern Spain), using precipitation time series from 1947 stations from three meteorological networks: Spanish Meteorological Agency (AEMET), Agroclimatic Information Network of Andalusia (RIA), and Phytosanitary Information Alert Network (RAIF). The method consists of three consecutive steps: basic, absolute, and relative quality control processes. The latter step compares data from neighboring stations taking into account their proximity, height difference, and correlation, leading to a complete evaluation of each daily value. Finally, the quality of each year at each station can be declared as acceptable, good, or excellent. The automatic weather station networks RIA and RAIF gave absolute quality index Q above 85% for almost 87% of their stations, while only 57% of AEMET network reached this percentage. However, one of the longest AEMET datasets, San Fernando-Cádiz, obtained, except for 1 year, Q values over 90% in all available years for more than a century of measurements, since 1870 until 2000. From a total of more than 15 million daily records, almost 82% was flagged as correct. Despite the limitations of Andalusia region (low density of stations and its structural water deficit), the complete quality control procedure has been satisfactorily applied. Finally, related to the number of outliers, no temporal trend was found across the region. [ABSTRACT FROM AUTHOR]

We sought to understand the role that water availability (expressed as an aridity index) plays in determining regional and global patterns of richness and evenness, and in turn how these water availability–diversity relationships may result in different richness–evenness relationships at regional and global scales. We examined relationships between water availability, richness and evenness for eight grassy biomes spanning broad water availability gradients on five continents. Our study found that relationships between richness and water availability switched from positive for drier (South Africa, Tibet and USA) vs. negative for wetter (India) biomes, though were not significant for the remaining biomes. In contrast, only the India biome showed a significant relationship between water availability and evenness, which was negative. Globally, the richness–water availability relationship was hump-shaped, however, not significant for evenness. At the regional scale, a positive richness–evenness relationship was found for grassy biomes in India and Inner Mongolia, China. In contrast, this relationship was weakly concave-up globally. These results suggest that different, independent factors are determining patterns of species richness and evenness in grassy biomes, resulting in differing richness–evenness relationships at regional and global scales. As a consequence, richness and evenness may respond very differently across spatial gradients to anthropogenic changes, such as climate change. [ABSTRACT FROM AUTHOR]

Changes in precipitation pattern can lead to widespread impacts across natural and human systems. This study assesses precipitation variability as well as anthropogenic and natural factors responsible for the precipitation variability over India in the twentieth and twenty-first centuries using the Coupled Model Intercomparison Project (CMIP5) and observational data sets. We specifically quantify the impact of natural (volcanic and solar radiation) (NAT), greenhouse gas (GHG), anthropogenic aerosol (AA), and land use (LU) forcings on precipitation changes over India. In the observational record, a decrease in precipitation is observed during monsoon and winter seasons, whereas an increase is noticed in pre- and post-monsoon seasons. These observed changes are likely dominated by changes to GHGs and a reduction in AA during the twentieth century compared to those of the LU and NAT forcings. Anthropogenic aerosol plays a dominant role in reducing rainfall in the summer monsoon, leading to drying trends over the second half of the twentieth century in India. The projected simulations indicate an increasing trend during the twenty-first century. The temporal and spatial variability of precipitation displays substantial changes over India during different seasons at different periods under the Representative Concentration Pathway (RCP) 2.6 and 8.5 emission scenarios. Overall, model simulations based on RCP 8.5 show increases in future precipitation throughout the twenty-first century over India. [ABSTRACT FROM AUTHOR]

Given the extensive impacts of climate change on the agricultural sector and their interactions, the climate change is known as one of the main factors influencing agricultural production. The present study aims to explore the short- and long-term impacts of climate change on the yield of irrigated barley in 28 Iranian provinces over the 1999–2015 period. The research uses panel data and dynamic ordinary least squares (DOLS) method. The study also estimated the threshold levels of temperature and rainfall which confirmed an inverted U-shaped relationship between climate change variables and irrigated barley yield. The threshold levels of temperature and rainfall are estimated to be 15.48 °C and 239 mm, respectively; beyond these threshold levels, the increase in temperature and rainfall have negative impact on barley yield in Iran. The long-term elasticity of temperature shows that the yield will be reduced with the increase in temperature in the long run. Same is the case with the precipitation and barley yield. The findings of the study suggest the need of a comprehensive national climate change policy and alignment of sectoral policies with it mitigate and adapt the climate change and global warming. Moreover, it also provided the guidelines for the government and policy-makers to introduce the use of modern eco-friendly and resource saving technologies such as water-saving methods of irrigation, use of fertilizer in required quantities, and improved seeds use. The government should also introduce the climate change awareness programs especially for farmers. [ABSTRACT FROM AUTHOR]

Tracking and quantifying the moisture sources of precipitation in different drainage basins in the Tibetan Plateau (TP) help to reveal basin-scale hydrological cycle characteristics under the interactions between the westerlies and Indian summer monsoon (ISM) systems and to improve our understanding on the mechanisms of water resource changes in the 'Asian Water Tower' under climate changes. Based on a Eulerian moisture tracking model (WAM-2) and three atmospheric reanalysis products (ERA-I, MERRA-2, and JRA-55), the contributions of moisture sources to the precipitation in six major sub-basins in the TP were tracked during an approximately 35-year period (1979/1980–2015). The results showed that in the upper Indus (UI), upper Tarim River (UT), and Qaidam Basin (QB), the moisture sources mainly extended westward along the mid-latitude westerlies to the western part of the Eurasian continent. In contrast, in the Yarlung Zangbo River Basin (YB), inner TP (ITP), and the source area of three eastern rivers (TER, including the Nujiang River, Lancang River, and Yangtze River), the moisture sources extended both westward and southward, but mainly southward along the ISM. In winter and spring, all of the sub-basins were dominated by western moisture sources. In summer, the western sources migrated northward with the zonal movement of the westerlies, and simultaneously the southern sources of the YB, ITP, and TER expanded largely toward the Indian Ocean along the ISM. In autumn, the moisture sources of the UI, UT, and QB shrank to the western sources, and the moisture sources of the YB, ITP, and TER shrank to the central-southern TP and the Indian subcontinent. By quantifying the moisture contributions from multiple sources, we found that the terrestrial moisture dominated in all of the sub-basins, particularly in the UT and QB (62–73%). The oceanic contributions were relatively high in the UI (38–42%) and YB (38–41%). In winter, evaporation from the large western water bodies (such as the Mediterranean, Red Sea, and Persian Gulf) was significantly higher than that from the continental areas. This contributed to the peak (valley) values of the oceanic (terrestrial) moisture contributions to all of the sub-basins. In summer, the terrestrial moisture contributions to the UI, UT, and QB reached their annual maximum, but the abundant oceanic moisture transported by the ISM restrained the appearance of land source contribution peaks in the YB, ITP, and TER, resulting in almost equal moisture contributions in the YB from the ocean and land. [ABSTRACT FROM AUTHOR]

Climate change is one of the most important challenges for humanity at present, and its impacts are especially profound in semi-arid regions such as the Arabian Peninsula and Saudi Arabia in particular, as it directly impacts the fragile ecosystem of the region. The present study explores the changes in future temperature and precipitation patterns over the Arabian Peninsula for the two future time slices 2036–2065 and 2071–2100 with respect to the reference period (1976–2005), using state-of-the-art regional climate model simulations. Three global climate model (GCM) simulations from the WCRP Coupled Model Intercomparison Project Phase 5 (CMIP5) are downscaled with the International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM4) over the Arabian Peninsula. Results indicate that the central parts of the Arabian Peninsula should get hotter in future compared to other parts of the Peninsula. This projected increase in temperature seems to happen mainly at the end of the twenty-first century. The projected temperature changes during mid-century fall in the range 1.0–1.5 °C under the RCP4.5 scenario and 2.0–2.5 °C under RCP8.5. Temperature changes by the end of the century are in the range 4–4.5 °C under RCP4.5 and 4.5–5.5 °C under RCP8.5. At the same time, this increase in temperature will affect the annual precipitation cycle as the precipitation during the dry season is expected to increase while the precipitation during the wet season is expected to decrease. RegCM simulations driven with boundary conditions from three GCMs are not consistent in producing future changes in precipitation over Saudi Arabia, which indicates that a careful interpretation of projected precipitation is required for its further use in impact and adaptation studies related to climate change. [ABSTRACT FROM AUTHOR]

In this study, air temperature and precipitation seasonality and their correlation with large-scale atmospheric circulations over the Sava River Basin (SRB), i.e., over the areas of Slovenia, Croatia, and Serbia, are analyzed. We used daily air temperature and precipitation measurements from 12 meteorological stations for the period from 1981 to 2010. In addition, mean (Ta), maximum (Tmax), and minimum (Tmin) daily temperatures and daily precipitation (P) were included in the analysis. Temperature values were correlated with atmospheric circulation patterns (ACPs), i.e., daily indices Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Mediterranean Oscillation (MO) for the same study period. The daily air temperature and precipitation data were obtained from European Climate Assessment & Dataset (ECA&D). The results generally show increasing trends in air temperatures, mainly during the spring and summer seasons, but also non-significant trends for precipitation. Moreover, the correlation results show no or weak influence of ACPs on seasonal air temperatures and precipitation, but the dominant effects differ by ACP type as well as at different seasonal levels. Among the selected ACPs, MO proved to be the most significant for the Sava River Basin. [ABSTRACT FROM AUTHOR]

Climate change is adversely affecting the development, management, and planning of surface and groundwater resources. The meteorological drought becomes a severe natural problem, and it can occur in any climatic region of the world. Thus, monitoring and minimizing drought is crucial for analyzing and predicting drought impacts. The meteorological drought is considered basin or region-specific since atmospheric conditions are highly variable from region to region. However, agricultural drought links the various characteristics of hydrological or meteorological drought to agricultural impacts focusing on groundwater deficit, soil moisture deficit, etc. A single drought index cannot assess each aspect of the meteorological drought. In this study, we considered seven drought indices such as the Standardized Precipitation Index (SPI), China Z Index (CZI), Modified China Z Index (MCZI), Percent Normal Drought Index (PNI), Deciles Index (DI), Rainfall Anomaly Index (RAI), and Z-score Index (ZSI). The drought was analyzed for 3, 6, 9, and 12 months' time step, and drought classification and threshold values were estimated. SPI showed maximum correlation values (0.389, 0.412, 0.560, and 0.996) for 3, 6, 9, and 12 month time steps compared to the other drought indices. The value of correlation is increased with the increase in time step for all drought indices; therefore, the accuracy of drought assessment also increases with an increase in time step. The Mann–Kendall's trend test was analyzed at a 5% significance level for drought assessments. The drought magnitude and the severity of the Betwa River basin were estimated based on the meteorological data (Rainfall) from 1970 to 2014. [ABSTRACT FROM AUTHOR]

The present study focuses on examining the changes in land use land cover and their impact on socio-environmental parameters using multitemporal satellite and observatory data. The Wular Lake, which is one of the largest freshwater lakes in Asia, has experienced drastic changes. To explore the changes in land use land cover from 1979 to 2018 over lake catchment, Landsat Multi-Spectral Scanner (MSS) for the year 1979, Landsat Enhanced Thematic Mapper (ETM) plus for the year 2001 and Landsat 8 OLI (Operational Land Imager) for the year 2018 were used for generating different land use land cover classes over lake catchment using visual interpretation in the GIS environment. For the same period, the changes in land use land cover were linked with the decadal changes in precipitation, temperature and black carbon. Significant reductions in the water area and agriculture area have been reported over the lake and its catchment. We report an increase in built-up, aquatic vegetation, horticulture, marshy land, plantation and river area over the catchment. The water area of Wular Lake has been decreased by 74.99%. A decadal decrease of about 1.22% in river discharge over the Jhelum River has been reported. Precipitation over the catchment shows a decadal decrease of about 0.54%. A decrease of about 23.62% in agriculture has been reported over the lake catchment. Built-up area, aquatic vegetation, horticulture, river area and marshy land show increases of about 223.73%, 17.57%, 45.68%, 15.88% and 2384.1%, respectively from 1979 to 2018. Black carbon concentration shows a decadal increase of about 2.214% over the region from 1980 to 2018. The research reports the changes in land use and land cover over the region and explores the impact of these changes over the study area. Results reported in this study highlight the importance of implementation of strict policies for the conservation of the Wular Lake and highlight the importance of carefully monitoring of discharge of river Jhelum. [ABSTRACT FROM AUTHOR]

Quantification of grassland carbon (C) variations is necessary for understanding how grazing and climate change interact to regulate carbon capture and release. Central Asia (CA) has the largest temperate grassland belt in the world and unique temperate dryland ecosystems, which experienced severe climate change and grazing-induced disturbances. However, the impact of grazing on C dynamics is highly uncertain owing to climate variations. Here, an arid ecosystem model (AEM) supplemented with a grazing module that specifically addressed physiological and ecological characteristics of dryland vegetation was developed to quantitatively simulate grassland C dynamics in response to changes in precipitation, temperature, grazing intensity, and CO2 level in the past decades. The regional simulation results showed that net primary productivity (NPP) was affected mainly by precipitation (in 59% of the studied area). Grazing had a negative effect on NPP and C stocks, whereas overcompensation occurred in 25.71% of the studied area, mainly in the dry western parts. The complex interaction effects of climate, CO2, and grazing negatively affected productivity, with a grassland NPP decrease of − 1.14 g C/m2/a and high interannual variability. We found that the temporal pattern of cumulative C sequestration, especially total C and vegetation C (VEGC), closely followed the annual fluctuations of precipitation. VEGC stocks decreased from 182.22 to 177.82 g C/m2, with a very low value between 1998 and 2008, when precipitation significantly decreased. The results indicate that southern Xinjiang and the Turgay Plateau of Kazakhstan are ecologically fragile areas due to grassland degradation. [ABSTRACT FROM AUTHOR]

Global assessment of vegetation response to climate change (VRCC) studies was conducted to reveal the research evolution, current research hotspots and better understanding of dominant themes in VRCC areas of research from 1992 to 2019 through the use of bibliometrics. A total of 186 articles with the search term "Vegetation response to Climate change" were retrieved using the Web of Science (WOS) database. The annual growth rate of 10.3% connotes that research on VRCC has been increasing over time during the survey period. Average citations per article experienced many fluctuations over the years rather than maintaining the same growth rate, which connotes that this field of research reached was unstable in terms of average total citation per document. Results show that China ranked first followed by the USA and the UK, and this shows the dominance of these countries on VRCC studies over the years in review. Results from corresponding authors' nationalities show that multiple-country publications are relatively low compared to articles from single-country publications which showed a dominant trend. Hence, we can infer that most studies on VRCC were sustained by single-country publications. Results from this study revealed top-cited articles, the top global distribution of documents, academic collaboration, most relevant keywords and Word TreeMap of high-frequency keywords. The findings of this study show that "temperature" is in a central position in all keywords with the largest significant appearance in the field. In conclusion, the findings from this study may be applicable for planning and managing vegetation and forest ecosystem research and provide hints for future development. [ABSTRACT FROM AUTHOR]

Historical records truthfully document human life and environment associated with climate changes. We quantify official historical records of China dating back last 2000 years to examine the disasters due to anomalous temperatures of cold or hot, irregular precipitations of wet or dry, and floods in inland/coastal or Northern/Southern areas in four seasons that possibly linked to solar activities during 1-1825 CE (Common Era). It is found that the proportion of disaster years is positively associated with the time periods, and therefore, both the cases with high and low solar activity (HSA and LSA) leading are under study. Statistical results show that extreme cold weather occurs particularly in the Winter and Spring during LSA periods. Irregularities precipitations, including heavy rain/hail/snow and severe drought are significantly frequent during LSA periods, while floods on inland and coastal river basins tend to occur more frequently in LSA and HSA periods, respectively. The disasters owing to irregularities precipitations and floods frequently happen in Summer and Autumn, which suggests that the irregular precipitations could cause the floods. All the disasters occur significantly in the Northern China, which suggests the climate boundary of the Qinling–Huaihe Line along at about 33°N being essential. In total, all the disasters due to the anomalously cold temperatures, irregular precipitations, and floods tend to occur during the LSA periods. [ABSTRACT FROM AUTHOR]