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This paper discusses the radiation budget and its temporal variability over Poland. The data analysis is based on the MERRA-2 reanalysis for the years 1980–2020. During the last four decades, the enhancement of climate warming has been observed, which coincides with the changes in the radiation budget. Positive and statistically significant trends at the top of the atmosphere (TOA; 0.7 ± 0.2 W/m2/10 year) and on the Earth's surface (1.5 ± 0.2 W/m2/10 year) radiation budget (net downward flux) are mainly a consequence of changes in the amount of aerosol and greenhouse gases (GHG). According to MERRA-2, the AOD during this period decreased by − 0.19 (at 550 nm), which is 87% of the long-term (1980–2021) mean value (0.22). The reduction of AOD is due mainly to the decline of non-absorbing sulfate particles, which leads to a reduction of single-scattering albedo (SSA) by − 0.008 per decade and Angstrom exponent (AE) by − 0.06 per decade (both trends statistically significant). On the other hand, the GHG concentration increased by 4.9%/10 year and 3%/10 year, respectively, for CO2 and CH4. The total column of water vapor increased (1.3%/10 year), while ozone decreased (− 1%/10 year). Despite the fact that cloud cover and cloud optical depth (COD) decreased (− 1.8%/10 year and − 1.0%/10 year), the impact of cloud on temporal variability radiation budget is small. It can be explained by nearly compensated shortwave (SW) cooling and longwave (LW) heating effects. During the analysis period, near-surface air temperature increased by 2.0 °C. The estimated increase in SW net surface radiation (7.9 W/m2) leads to climate warming by 0.8 °C, which is a consequence mainly of the reduction of aerosol (0.4 °C) and cloud cover (0.2 °C). The impact of the change of SW radiation on air temperature is more pronounced during the warm season, while during the cold, air temperature change is controlled mainly by the variability of air mass advection. [ABSTRACT FROM AUTHOR]

The present paper analyzes long term (1960–2021) of the minimum, maximum, and average temperatures in Central Anatolia Region, corresponding middle part of Turkey, aiming to reveal how strongly the temperatures increase, which is a precondition for sustainable development in this region. For this purpose, temporal trends, variability, and anomalies in temperatures of 27 meteorological stations were detected using Mann–Kendall test (M-K), coefficient of variations, and Gaussian filter, respectively. Results show a statistically significant increasing trend in annual average temperatures at approximately 92% of all stations. This shows that the increasing trend in spring and summer temperatures plays an important role in amplifying the warming trend of annual temperatures. The coefficients of variation in annual average, maximum, and seasonal temperatures increase from west to east. Significant strong increasing trend (at 0.001 level) in winter temperatures was detected only at Seydişehir. While positive anomalies have been observed in the northwestern part of the region since 2007, they have been observed in other parts since 1995–1996. Since the strong increase in summer temperatures in Aksaray, Cihanbeyli, and Seydişehir is also observed in autumn, warm conditions continue until the end of autumn in these settlements. For this reason, four seasons do not prominently occur for all three settlements. Generally, annual maximum and minimum temperatures illustrate statistically significant increasing trends for all stations and 74% of all stations, respectively. According to the M-K test results, climate of the region has warmed on average by 1.44 °C in last 31 years. [ABSTRACT FROM AUTHOR]

Climate model, a complex numerical representation of the global climate system, has been developed to simulate current climate and used to project future climatic conditions. Simulated climatic variables from climate models often exhibit significant deviations from observations. In climate projections, different approaches were introduced to deal with systematic deviations and random model errors. This paper demonstrates the intercomparison of four bias correction approaches (linear scaling, delta change correction, distribution mapping, and variance scaling) underlying the assumptions of stationary output from climate models. Mean monthly temperatures derived from five global climate models were corrected by four bias correction approaches for five states of southern India. The suitability of correction approaches depends upon the climate models and regional framework. The applied approaches improve the mean values and other statistical properties. The results show that all four bias techniques significantly improved the simulated data, but distribution mapping and variance scaling were more effective in removing systematic model biases. [ABSTRACT FROM AUTHOR]

In the next 20 years, there will be an extensive investment in transport infrastructure. Although the cut and embankment slopes seem to have the same appearance, they have different responses to climate variations. Understanding their characteristics and performance is necessary to design a safer and more sustainable slope infrastructure. This paper provides a thorough examination of the seasonal performance of cut slopes and embankments. Furthermore, this study suggests an introduction to the impacts of climate change, amplifying seasonal shrinkage–swelling and progressive failure of slope construction under extreme drought and precipitation. Volumetric water content and pore water pressure fluctuations due to seasonal variation were analysed and compared from both the cut slope and the embankment. Moreover, stress path and slope deformation were also investigated in this study to understand the behaviour of the cut slope and the embankment. The results suggest that the cut slope retains more pore water pressure during the wet season due to its lower permeability than an embankment with respect to the construction history. However, pore water pressure and displacement in the cut slope tend to be increased due to the consolidation process after excavation, which requires more time to reach equilibrium. In addition, greater displacement in the cut slope can increase the possibility of delayed failure in the future. [ABSTRACT FROM AUTHOR]

The aim of the study was to determine the direction and rate of the projected changes of the start, end, and duration of the growing season in Poland in two-time horizons: 2021–2050 and 2071–2100. The main part of the paper was preceded by an analysis of changes in the start and end dates and the duration of the growing season in Poland in the period 1966–2020. The growing season in Poland is projected to be the shortest in mountain areas and in the north-eastern regions of Poland, where the date of growing season start is the latest and the date of the growing season end is the earliest. Whereas the longest growing season due to the projected earliest start and latest end dates is expected in the southwestern Poland. In the case of the coast, its late end will be of the greatest importance for its duration as a result of the warming effect of the sea in the autumn–winter period. The most intensive changes are forecasted in the long-term perspective in the case of the scenario regarding a high level of greenhouse gas emissions. The forecasts show that outside mountain areas, the growing season duration will vary from less than 255 days in the northeastern regions to more than 290 days in southwest and western Poland. In the duration of the mountains, the growing season will vary from 180 days on Kasprowy Wierch to 188 days on Śnieżka. This suggests significant changes in agroclimatic conditions in Poland. [ABSTRACT FROM AUTHOR]

Air temperature is one of the most important parameters that contribute to weather variability over time, being influenced by the flow of solar radiation, the general circulation of currents in the atmosphere relief. The present paper analyzes the minimum, maximum, and mean temperatures in Dobrogea, on the Romanian Black Sea coastal area, aiming to illustrate their evolution, which is a precondition for sustainable development in this region, from the perspective of regional and global climate changes. The weather stations included in this study are Constanta, Mangalia, Gura Portitei, Sfantu Gheorghe, and Sulina. The Pettit Test and the Standard Normal Homogeneity Test were used to determine changes in the evolution of the air temperature. For the period 1990–2020, the analysis of the change points, with a 95% confidence level, shows a particularly interesting situation supporting the general evolution of air temperature at global level. Nonparametric tests including linear regression, Mann–Kendall, and Sen's slope tests were used to analyze trends for monthly, seasonal, and annual series. Results showed an increasing trend in the annual minimum, maximum, and mean temperatures in all five weather stations. [ABSTRACT FROM AUTHOR]

The non-stationarity of hydrologic processes due to climate change or human activities is challenging for the researchers and practitioners. However, the practical requirements for taking into account non-stationarity as a support in decision-making procedures exceed the up-to-date development of the theory and the of software. Currently, the most popular and freely available software package that allows for non-stationary statistical analysis is the GAMLSS (generalized additive models for location, scale and shape) package. GAMLSS has been used in a variety of fields. There are also several papers recommending GAMLSS in hydrological problems; however, there are still important issues which have not previously been discussed concerning mainly GAMLSS applicability not only for research and academic purposes, but also in a design practice. In this paper, we present a summary of our experiences in the implementation of GAMLSS to non-stationary flood frequency analysis, highlighting its advantages and pointing out weaknesses with regard to methodological and practical topics. [ABSTRACT FROM AUTHOR]

Environmental changes have led to a growing conflict between water supply and demand in Qinjiang River. This paper used the data of monthly rainfall, runoff, evaporation and air temperature during the period from 1956 to 2016 and combined 3-year running mean, linear regression method, Mann-Kendall test and R/S analysis method to analyze the change trend of each factor, combined Mann-Kendall test, cumulative anomaly method and slide t test to analyze the variation of each factor and combined Morlet continuous wavelet analysis to identify periodic oscillations. In this paper, the influences of climate change and human activities on the runoff of the Qinjiang River were qualitatively assessed from the aspects of trend, variation and periodicity and the contributions of climate change and human activities to runoff reduction were quantitatively assessed using evaporation difference method and an improved comparative method of the slope changing ratio of cumulative quantity (SCRCQ).The following results were obtained: (1) From 1956 to 2016, the rainfall showed a weak increasing trend, whereas the runoff depth and the evaporation exhibited significant decreasing trend and the air temperature exhibited a significant increasing trend. The rainfall and air temperature will continuously increase, whereas runoff and evaporation will continuously decrease in the future. (2) Rainfall exhibited no significant variation, whereas there were two variation points (1986 and 2003) in the runoff, three variation points (1974, 1986 and 2011) in evaporation and one variation point (1996) in air temperature. (3) Features of rainfall exhibited similarities to periodic changes in runoff, whereas rainfall exhibited significant difference with evaporation and air temperature. (4) Human activities contributed mainly to the runoff reduction. The contribution of human activities to runoff reduction increased from 43.78 to 61.17% in BR period (1983-2003) and increased from 61.17 to 72.66% in CR period (2004-2016). This indicated that the contribution of human activities to runoff reduction increased continuously. The impact of human activities on the reduction in runoff in the Qinjiang River Basin is mainly due to the irrigation, industrial and urban residents’ water use, which is caused by the growth of population and the growth of economic index. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various articles within the issue on topics including changes in hydrological extremes related to climatic and human-induced changes, future climate model projections and land-use development.

This paper focuses on sea surface temperature (SST) trends due to the importance of temperature difference in climate change impact research. These trends are not only essential for climate, but they are also important for marine ecosystem. Immigration of fish population due to the temperature changes is expected to cause unexpected economical results. For this purpose, both classical Mann–Kendall, (MK) (Mann in Econom: J Econom Soc 13:245–259, 1945; Kendall in Rank Correlation Methods, Charless Griffin, London, 1975) and innovative trend analysis (ITA) (Şen in J Hydrol Eng 17(9):1042–1046, 2012) methodologies are applied for the SST data records. Monthly SST data are considered along the Black, Marmara, Aegean, and Mediterranean coastal areas in Turkey. SST data are categorized into five clusters considering fish life as "hot," "warm-hot," "warm," "cold," and "very cold." According to ITA, SST in all coastal areas tends to increase except for winter season during "very cold" (0–10 °C) temperatures. The temperature changes in both winter and summer seasons are expected to change the marine life, fish population, tourism habit, precipitation regime, and drought feature. [ABSTRACT FROM AUTHOR]

Global warming is a biggest issue around the world. In this research paper, the temporal and spatial trend analysis of seasonal and annual rainfall on Bhogavo River watersheds in Sabarmati lower basin of Gujarat state of India has been analysed using the data of 11 rain gauge stations installed in Bhogavo watershed. Linear regression, Mann–Kendall Test, Sen's slope test and innovative trend analysis methods are used to carry out monthly and annual rainfall trend analysis. In addition to the rainfall analysis, a number of rainy days change in magnitude as a percentage of mean rainfall have also been analysed using linear regression and Sen's slope method, respectively. The IDW method is used to develop a spatial distribution of annual and seasonal rainfall trend over the study area. From the results, it is concluded that annual rainfall shown increasing (positive) trend at nine stations out of 11 stations. The highest value of change in magnitude of trend as a percentage of mean monthly rainfall has been obtained in the month of July, attributing increasing trend at Sayla station and lowest value magnitude of trend as a percentage of mean rainfall in the monthly rainfall has been obtained in the month of August, attributing decreasing trend at Bavla station. [ABSTRACT FROM AUTHOR]

The present paper examines variability of characteristics of snow cover (snow cover depth, number of days with snow cover and dates of beginning and end of snow cover) in Poland. The study makes use of a set of 43 long time series of observation records from the stations in Poland, from 1952 to 2013. To describe temporal changes in snow cover characteristics, the intervals of 1952-1990 and of 1991-2013 are compared and trends in analysed data are sought (e.g., using the Mann-Kendall test). Observed behaviour of time series of snow-related variables is complex and not easy to interpret, for instance because of the location of the research area in the zone of transitional moderate climate, where strong variability of climate events is one of the main attributes. A statistical link between the North Atlantic Oscillation (NAO) index and the snow cover depth, as well as the number of snow cover days is found. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between selected percentiles, return periods and the concepts of rare and extreme events in climate and hydrological series, considering both regular and irregular datasets, and discusses the IPCC and WMO indications. IPCC (Annex II: Glossary. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, 2014) establishes that an extreme event should be rare and exceed selected upper and lower thresholds (10th and 90th percentiles); WMO (Guidelines on the definition and monitoring of extreme weather and climate events—TT-DEWCE WMO 4/14/2016. World Meteorological Organization, Geneva, 2016) suggests thresholds near the ends of the range, but leaves them undetermined. The concept of "rare" relates the extreme events to the time domain and is typically expressed in terms of return period (RP). The key is to find the combination between "rare", percentile and return period. In particular, two crucial items are analysed: (1) how the return period may vary in response to the choice of the threshold, in particular when it is expressed in terms of percentiles; (2) how the choice of producing a regular or irregular dataset may affect the yearly frequency and the related return periods. Some weather variables (e.g. temperature) are regular and recorded at fixed time intervals, while other phenomena (e.g. tornadoes) occur at times. Precipitation may be considered either regular, all-days being characterized by a precipitation amount from 0 (no precipitation) to the top of the range, or irregular (rainy-days only) considering a precipitation day over a selected instrumental or percentile threshold. These two modes of interpreting precipitation include a different number of events per year (365 or less) and generate different return periods. Every climatic information may be affected by this definition. The 90th percentile applied to observations with daily frequency produces 10-day return period and the percentiles necessary to get 1 year, 10 years or other return periods are calculated. The general case of events with selected or variable frequencies, and selected percentiles, is also considered with an example of a precipitation series, two-century long. [ABSTRACT FROM AUTHOR]

West Africa plays key roles in global climate and shows one of the strongest variations in hydro-climatic conditions. As it turns out, the region appears to be underrepresented in the existing compendium of Earth science and hydrology-focused journal papers when it comes to significant discussion on terrestrial hydrology and freshwater science. This prominent gap is largely precipitated by increasing number of constraints that include lack of considerable and robust investments in gauge measurements for meteorological and hydrological applications, poor funding of research institutions and other disincentives, among other factors. In this manuscript, the challenges and problems in large-scale terrestrial hydrology-focused investigation in West Africa are reviewed. Using a dossier of some recent contributions in the field of remote sensing hydrology, this review also highlights some of the progress in terrestrial hydrology and the opportunities that exist for hydro-geodetic research in West Africa that leverage on sustained investments in satellite geodetic missions. It is noted that West Africa is still a pristine environment for hydrology-focused research and can benefit from recent advancements in sophisticated space agency programs such as the Gravity Recovery and Climate Experiment, which undoubtedly has revolutionized terrestrial hydrology research around the world for nearly two decades. Given the poor density of gauge stations and limited ground observations, hydrological research in West Africa is expected to benefit more from independent space observations and multi-resolution data. This is because the lack of sufficient in-situ data for the parameterizations and adequate initialization of outputs from hydrological models and reanalysis data for hydrological applications results in poor representation of the West African land surface and hydrological state variables. To further improve our contemporary understanding of West Africa's terrestrial hydrology, the continued evaluation/validation of these observations and space-borne measurements is advocated. [ABSTRACT FROM AUTHOR]

The present paper offers a brief assessment of climate change and associated impact in Poland, based on selected results of the Polish-Norwegian CHASE-PL project. Impacts are examined in selected sectors, such as water resources, natural hazard risk reduction, environment, agriculture and health. Results of change detection in long time series of observed climate and climate impact variables in Poland are presented. Also, projections of climate variability and change are provided for time horizons of 2021-2050 and 2071-2100 for two emission scenarios, RCP4.5 and RCP8.5 in comparison with control period, 1971-2000. Based on climate projections, examination of future impacts on sectors is also carried out. Selected uncertainty issues relevant to observations, understanding and projections are tackled as well. [ABSTRACT FROM AUTHOR]

A decrease of flood damages in the future requires not only adaptation to flood caused by present day climate, but also climate change effects on floods should be taken into account. The paper illustrates the need to take into account changing climate conditions in flood adaptation strategies and to apply in practice the concept of integrated water resource management (IWRM). IWRM is based on a number of policy instruments, economic instruments, political signals, and also, on the effects of climate change on floods and collaboration across national, regional and local administrative units. The guidelines for a country adaptation to floods in a changing climate are outlined. A comparison of the adaptive capacities in Poland and Norway is used to illustrate the need for the implementation of proposed guidelines to assure flood risk management under climate change in a sustainable way. [ABSTRACT FROM AUTHOR]

This paper presents the background, objectives, and preliminary outcomes from the first year of activities of the Polish-Norwegian project CHIHE (Climate Change Impact on Hydrological Extremes). The project aims to estimate the influence of climate changes on extreme river flows (low and high) and to evaluate the impact on the frequency of occurrence of hydrological extremes. Eight "twinned" catchments in Poland and Norway serve as case studies. We present the procedures of the catchment selection applied in Norway and Poland and a database consisting of near-natural ten Polish and eight Norwegian catchments constructed for the purpose of climate impact assessment. Climate projections for selected catchments are described and compared with observations of temperature and precipitation available for the reference period. Future changes based on those projections are analysed and assessed for two periods, the near future (2021-2050) and the far-future (2071-2100). The results indicate increases in precipitation and temperature in the periods and regions studied both in Poland and Norway. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the trends and shifts of the circulation types over Romania for 50-year period (1961-2010) on seasonal basis. In order to achieve this, two objective catalogues, namely GWT and WLK, from COST733 Action were employed. Daily circulation types were grouped according to the cyclonicity and anticyclonicity and were used to calculate the seasonal occurrence frequency of cyclonic and anticyclonic types. The trend of seasonal time series was investigated by using Mann-Kendall test and the shifts points were determined by using Pettitt test. The results reveal that the occurrence frequency of anticyclonic types increases in summer and winter seasons and the occurrence frequency of cyclonic ones decreases for the summer season (for alpha = 0.05). [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the influence of the North Atlantic Oscillation on the pattern of lake ice phenology in Poland. The research embraced 22 lakes in Poland over the period 1961-2010. Strong relations were found to hold between NAO and individual characteristics of ice phenology. In a negative NAO phase, one can observe a later appearance of ice phenomena and ice cover compared with the average values, ice cover persisting even 30 days longer and being thicker even by more than 10 cm. In turn, in a positive NAO phase the duration of ice phenomena and ice cover is shorter, the cover being less thick and solid. The observed spatial differences in the effect of NAO on the pattern of ice phenomena in Poland show this matter to be fairly complex. The most significant factor changes in climatic conditions, which manifest themselves in the continentality of the climate growing eastwards. [ABSTRACT FROM AUTHOR]

This paper presents the effect of the North Atlantic Oscillation (NAO) on the thermal characteristics of lakes in Poland. In the analysis, the use was made of monthly air temperatures recorded at fifteen meteorological stations, water temperatures of twelve lakes, and Hurrell's winter NAO indices. Over the study period (1971-2010), there was a marked increase in the temperatures of both, air and lake waters. Depending on the NAO phase, water temperatures were observed to depart from mean values, being markedly higher than average (even by 1°C) in the positive winter NAO phase. The differences in water temperatures were statistically significant in the winter-spring season. In turn, in the negative NAODJFM phase lake water temperatures in winter and spring were markedly lower than average (in March even by 1.0°C). The unique response of some lakes depends on their morphometric parameters, including their mean depth. [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]

Interpretation of changes of global temperature is important for our understanding of the climate system and for our confidence in projections for the future. Massive efforts have been devoted to improve the accuracy of reproducing the global temperature by the available climate models, but the hindcasts are still inaccurate. Notwithstanding the need to further advance climate models, one may consider data-driven approaches, providing practically useful results in a simpler and faster way. Without assuming any prior knowledge about physics and without imposing a model structure that encapsulates the existing knowledge about the underlying processes, we hindcast global temperature by automatically identified evolutionary computation models. We use 60 years of records of global temperature and climate drivers, with training and testing periods being 1950-1999 and 2000-2009, respectively. This paper demonstrates that the global temperature observed in the past is mimicked with reasonably good accuracy. Evolutionary computation holds promise for modeling the global climate system, which looks hopelessly complex in classical perspective. [ABSTRACT FROM AUTHOR]

Since several destructive floods have occurred in Germany in the last decades, it is of considerable interest and relevance ( e.g., when undertaking flood defense design) to take a closer look at the climatic factors driving the changes in flood hazard in Germany. Even if there also exist non-climatic factors controlling the flood hazard, the present paper demonstrates that climate change is one main driver responsible for the increasing number of floods. Increasing trends in temperature have been found to be ubiquitous in Germany, with impact on air humidity and changes in (intense) precipitation. Growing trends in flood prone circulation pattern and heavy precipitation are significant in many regions of Germany over a multi-decade interval and this can be translated into the rise of flood hazard and flood risk. [ABSTRACT FROM AUTHOR]

The awareness of global warming is well established and results from the observations made on thousands of stations. This paper complements the large-scale results by examining a long time-series of high-quality temperature data from the Secular Meteorological Station in Potsdam, where observation records over the last 117 years, i.e., from January 1893 are available. Tendencies of change in seasonal temperature-related climate extremes are demonstrated. 'Cold' extremes have become less frequent and less severe than in the past, while 'warm' extremes have become more frequent and more severe. Moreover, the interval of the occurrence of frost has been decreasing, while the interval of the occurrence of hot days has been increasing. However, many changes are not statistically significant, since the variability of temperature indices at the Potsdam station has been very strong. [ABSTRACT FROM AUTHOR]

Climate change is a global phenomenon impacting all countries. In order to mitigate against the impacts of climate change, it is necessary to take measures to minimise the impacts that will affect the human habitat especially the built environment in the future. In the light of the inequality of development over the world, including varying rates of economic growth, it will be difficult for developing countries to combat the effects of climate change due to the limited capital investment, varying levels of leadership and political commitment and technology levels. All the countries have to share responsibility for the historical and current global emissions of greenhouse gases originating from both developed and undeveloped countries. This studies the built environment and adapts the impacts to be increased in the climate change and this analysis the constraints the opportunities for managing impacts for human sustainability. [ABSTRACT FROM AUTHOR]

Significant research has been done on estimating reference evapotranspiration ( E T 0) from limited climatic measurements using machine learning (ML) to facilitate the acquirement of E T 0 values in areas with limited access to weather stations. However, the spatial generalizability of E T 0 estimating ML models is still questionable, especially in regions with significant climatic variation like Turkey. Aiming at exploring this generalizability, this study compares two E T 0 modeling approaches: (1) one general model covering all of Turkey, (2) seven regional models, one model for each of Turkey's seven regions. In both approaches, E T 0 was predicted using 16 input combinations and 3 ML methods: support vector regression (SVR), Gaussian process regression (GPR), and random forest (RF). A cross-station evaluation was used to evaluate the models. Results showed that the use of regional models created using SVR and GPR methods resulted in a reduction in root mean squared error (RMSE) in comparison with the general model approach. Models created using the RF method suffered from overfitting in the regional models' approach. Furthermore, a randomization test showed that the reduction in RMSE when using these regional models was statistically significant. These results emphasize the importance of defining the spatial extent of E T 0 estimating models to maintain their generalizability. [ABSTRACT FROM AUTHOR]

The HY-2A satellite is the first ocean dynamic environment monitoring satellite of China. Centimeter-level radial accuracy is a fundamental requirement for its scientific research and applications. To achieve this goal, we designed the strategies of precise orbit determination (POD) in detail. To achieve the relative optimal orbit for HY-2A, we carried out POD using DORIS-only, SLR-only, and DORIS + SLR tracking data, respectively. POD tests demonstrated that the consistency level of DORIS-only and SLR-only orbits with respect to the CNES orbits were about 1.81 cm and 3.34 cm in radial direction in the dynamic sense, respectively. We designed 6 cases of different weight combinations for DORIS and SLR data, and found that the optimal relative weight group was 0.2 mm/s for DORIS and 15.0 cm for SLR, and RMS of orbit differences with respect to the CNES orbits in radial direction and three-dimensional (3D) were 1.37 cm and 5.87 cm, respectively. These tests indicated that the relative radial and 3D accuracies computed using DORIS + SLR data with the optimal relative weight set were obviously higher than those computed using DORIS-only and SLR-only data, and satisfied the requirement of designed precision. The POD for HY-2A will provide the invaluable experience for the following HY-2B, HY-2C, and HY-2D satellites. [ABSTRACT FROM AUTHOR]

India economy depends on agriculture with severe climatic changes and a heavy infestation of diseases depleting food crop yield substantially. Rapid identification and real-time infestation feedback that affects plants are accomplished through computer vision and IoT, thereby providing a reliable system for farmers to increase the season's growth yield. With LSTM, CNN provides an efficient way of identifying diseases specific leaf in plants through image recognition techniques. An extensive collection of plant leaf images is trained to recognize season-specific diseases like early blight and late blight, leaf mold, and yellow leaf curl. The proposed CNN model identifies the infestation with high accuracy and precision with significantly fewer training epochs. The proposed model provides an efficient way of identifying leaf borne infestation pertained to a particular agricultural region. Furthermore, there is a need to increase and improve different region-specific infestations that arise due to climatic and seasonal changes. [ABSTRACT FROM AUTHOR]

Population growth and increasing demand for water have posed a significant challenge to access to safe water resources. Climate change and land use in the not-too-distant future add to the complexity of this challenge. Therefore, it is essential to achieve reliable methods for predicting changes in aquifer storage to plan for the sustainable use of groundwater resources. This study aimed to investigate the management, protection, and sustainable use of groundwater resources under climate change and land use change conditions. In this regard, groundwater supply and demand in one of the important plains in Iran (Hashtgerd plain) for 2020 as the base year was simulated to forecast the trends until 2050 by considering climate change and land use to develop management scenarios to adapt to these conditions using the WEAP model. First, climate change prediction was performed using the HadGEM2-ES model under two emission scenarios, RCP2.6, and RCP8.5, of the IPCC Fifth Assessment Report. The LARS-WG model was used to downscale the climatic data, while land use mapping was performed using Landsat satellite images of 1990, 2005, and 2020 in ENVI 5.3 software. Then, the Markov chain method implemented in TerrSet software was used to model land use change for 2050. The effect of climate change and land use on the decrease of groundwater level was then simulated using the MODFLOW model for the period 2020–2050. In order to manage the water allocation in the area, the information obtained from MODFLOW was transferred to the WEAP model using Link Kitchen interface software. The effects of various management scenarios such as increasing irrigation efficiency, reducing the loss of drinking water distribution networks, and allocating water from the transmission line were evaluated on the adaptation to climate change and land use for a 30-year period. The results showed that with the simultaneous consideration of climate change and land use in the most critical state, the average drop in groundwater level would reach 58 m during the study period, and aquifer reserves will be reduced by more than 50%. The evaluation of management scenarios showed that their implementation not only will protect aquifer reserves but, in addition to meeting 100% of the water needs, will result in sustainable exploitation of groundwater resources. [ABSTRACT FROM AUTHOR]

This study analyzes the spatial and temporal distribution of trends on monthly, seasonal, and annual mean temperatures (1967–2017) at 22 stations in the Euphrates Basin of Turkey. The recently proposed innovative trend analysis (ITA) and the nonparametric Mann–Kendall (MK) and Spearman's rho (SR) test at 5% and 1% significance levels were applied to examine the temporal trends of temperatures. Before using the nonparametric trend analysis, the serial correlation of the temperature data was removed with the pre-whitening (PW) method. Then, MK-Z values were mapped in ArcGIS environment using the Empirical Bayesian Kriging (EBK) method to reveal the spatial variation of temperature trends. As a result, according to the ITA method, increasing temperature trends at 1% significance level dominate almost all periods. Based on the MK and SR tests, it was identified that increase trends were dominant at 1% and 5% significance levels in February, March, April, July, August, Spring, Summer, and Annual periods. According to the spatial temperature trend maps, significant increase trends occupy an important place in most of the basin in February, March, April, June, July, August, Spring, Summer, Winter, and Annual periods. The study results provide important information to water resources managers and decision-makers about the regions at significant risk in climate change in the Euphrates Basin. [ABSTRACT FROM AUTHOR]

We describe an algorithm for rapidly computing the surface displacements induced by a general polygonal load on a layered, isotropic, elastic half-space. The arbitrary surface pressure field is discretized using a large number, n, of equally-sized circular loading elements. The problem is to compute the displacement at a large number, m, of points (or stations) distributed over the surface. The essence of our technique is to reorganize all but a computationally insignificant part of this calculation into an equivalent problem: compute the displacements due to a single circular loading element at a total of m n stations (where m n is the product m × n). We solve this 'parallel' problem at high computational speed by utilizing the sparse evaluation and massive interpolation (SEMI) method. Because the product m n that arises in our parallel problem is normally very large, we take maximum possible advantage of the acceleration achieved by the SEMI algorithm [ABSTRACT FROM AUTHOR]

Changes in thermal extremes of the climate of Poland in 1951-2010 are examined. Warm extremes have become more frequent, while cold extremes have become less frequent. In the warming climate of Poland, the increase in the number of extremely warm days in a year and the decrease in the number of extremely cold days in a year have been observed. Also the increase of the maximum number of consecutive hot days in a year and the decrease of the maximum number of consecutive very cold and extremely cold days in a year have been observed. However, the trends are not of ubiquitous statistic significance, as the natural variability is strong. [ABSTRACT FROM AUTHOR]

Decisions that are based on the future climate data, and its consequences are significantly important for many sectors such as water, agriculture, built environment, however, the performance of model outputs have direct influence on the accuracy of these decisions. This study has focused on the performance of three bias correction methods, Delta, Quantile Mapping (QM) and Empirical Quantile Mapping (EQM) with two reference data sets (ERA and station-based observations) of precipitation for 5 single CMIP6 GCM models (ACCESS-CM2, CNRM-CM6-1-HR, GFDL-ESM4, MIROC6, MRI-ESM2-0) and ensemble mean approach over Turkey. Performance of model-bias correction method-reference data set combinations was assessed on monthly basis for every single station and regionally. It was shown that performance of GCM models mostly affected by the region and the reference data set. Bias correction methods were not detected as effective as the reference data set over the performance. Moreover, Delta method outperformed among the other bias correction techniques for the computation that used observation as reference data while the difference between bias correction methods was not significant for the ERA-based computations. Besides ensemble approach, MIROC6 and MRI-ESM2-0 models were selected as the best performing models over the region. In addition, selection of the reference data sets also found to be a dominant factor for the prediction accuracy, 65% of the consistent performance at the stations achieved by the ERA reference used bias correction approaches. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to investigate the effects of land cover changes and vegetation loss under conditions of change in climatic parameters (temperature and precipitation) and determining their impacts on different ecological functions in the eastern watershed of Lake Urmia and its four sub-watersheds in northwestern Iran. The method used has been a quantitative assessment of selected ecosystem functions using a self-parameterizing, physically based model called Water World Policy Support System as well as applying satellite images to detect land-use/cover changes. Modeling of important ecological and hydrological parameters including vegetation density, water balance, surface runoff, and soil erosion was performed and for each of them, the quantity of changes was calculated and mapped. Then, by standardizing the maps for each parameter and overlapping them, cumulative impact levels across the watershed were classified. The result showed that with decrease in rainfall and increase in temperature, the average vegetation density decreased by 32% in the watershed and from 79 to 47%. Decreased vegetation, followed by increased runoff by about 2.5% and equivalent to 19,656.95 cubic meters per year. Consequently, the average net soil erosion has been changed from − 0.012 to 0.20 mm per year per square meter. Hence, the average soil erosion in the watershed has increased by more than 3 tons per hectare. Based on the final results, more than 40% of the watershed area is under severe and very severe ecological impact. [ABSTRACT FROM AUTHOR]

Understanding the role of ecosystem services (ESs) within environmental management has become a critical issue of the twenty-first century. This is because scientific study of ES interactions can aid effective planning and management of ESs, thus curtailing degradation and enhancing restoration. In this study, ES interactions of the climate-sensitive West African Sokoto-Rima basin were quantified using land cover and a series of GIS-derived data as inputs into the InVEST model. Crop production (CP), seasonal water yield (SWY), habitat quality (HQ), and nutrient retention ratio (NRR) between 1992 and 2015 were assessed. Climate change assessment was based Mann–Kendall trend of precipitation and temperature for both past (1951–2017) and future (2018–2050) climates. The climate dynamics present a drying-warming trend with localised cooling–warming spells in some locations and a general future wetting–warming trend. Areas dominated by cropland and CP exert significant influence on the spatiotemporal dynamics of ES interactions contributing to the manifestation of substantial trade-offs and synergies across the past (2015) and the future (2050) climates. This also regulates the overbearing pattern of multiple ES interactions such that the relationship CP > SWY > HQ > EVI > NRR was observed over the study area. The persistence of these diverse relationships will stimulate the possible degradation of natural regulating ESs. Improvement of existing crop cultivation clusters, cultivation of flood-resistant crop varieties, and agroforestry expansion were proposed as climate and ESs interaction-based restoration measures. When adopted, these measures will douse the increasing ES pressures within this semi-arid zone. [ABSTRACT FROM AUTHOR]

Climate change is the meteorological alterations that occurred in the past by natural causes, which is occurring today and being intensified by the human behavior. Some of the main consequences of these alterations are: increase in the air temperature, changes in the hydrological cycle and occurrence of extreme weather events with greater intensity and frequency. This work was performed in Alto Camaquã in the Pampa Biome, which is considered as a region of stability and of great importance for biodiversity conservation. The main economical and sociocultural activity in the region is livestock run by different families, which is also considered fundamental for the maintenance of this biome. The objective of this work was to infer information on hydric deficit in Alto Camaquã watershed related to the increase in the air temperature and its impacts on family livestock. For this purpose, we estimated the climatic water balance (CWB) derived from pluviometric and meteorological data. We also estimated the maximum capacity of available water for the period between 1990 and 2016 and also for the predictive scenarios when an increase as well as no change in the air temperature occur. It has been observed that there will be hydric deficit during the summer, except for Rainy Year, independent on whether a change in the air temperature occurs or not. The results demonstrated that the effects of climate change are already occurring and that, even if the ongoing climate change stops before the predictions come true, the hydric deficit has already been experienced by the society. [ABSTRACT FROM AUTHOR]

This study assesses the spatial and temporal characteristics (e.g., frequency, intensity, spatial extent) of meteorological drought in Syria. Specifically, drought was characterized using the observed rainfall data from 36 rain gauges spanning the period between 1990 and 2010 and covering the main climatic regions in Syria (i.e., Mediterranean, arid, semiarid and mountainous). Meteorological drought was assessed using the standardized precipitation index (SPI) at 12-month timescale, allowing for detecting the impacts of climate variability on agricultural droughts. The dominant modes of drought were defined using an S-mode of the principal component analysis. To assess the links between meteorological drought evolution and vegetation greening in Syria, the time series of SPI were correlated with the normalized difference vegetation index (NDVI). Time series of NDVI were retrieved from the remotely sensed National Oceanic and Atmospheric Administration Advanced Very High-Resolution Radiometer (NOAA/AVHRR) sensor at a spatial resolution of 25 km for the common period 1990–2010. Trend analysis suggests a statistically significant increase in the frequency and intensity of drought at 12-month timescale. The observed intensification of meteorological drought is mostly associated with the increase in mild and moderate droughts, relative to extremes and very extreme droughts. Results also suggest a statistically significant decrease (p < 0.05) in vegetation greening over Syria during the study period, especially in the eastern parts of the country. Our results demonstrate that the decrease in vegetation cover can directly be linked to the anomalous drought events, with Pearson' r coefficients generally above 0.6. This dependency was more highlighted during wintertime for the Mediterranean vegetation and in northeastern portions of the country. Overall, the increase in the frequency and intensity of meteorological drought, combined with a series of unrest and political instability, have drastic impacts on the agricultural sector in Syria, with serious implications for crop yield. [ABSTRACT FROM AUTHOR]

Climate change is a challenging global issue for the sustainable production of various crops around the world as change in climatic patterns can create a stressful environment for plant growth. This study assesses the impact of climate change on future water demand and sugarcane yield in Pakistan for the baseline (1981–2005) and future timescales (2020s, 2050s and 2080s). For evaluating the crop water requirement and yield under future climate, CROPWAT 8.0 and AquaCrop models were used, respectively. For the estimation of future climate, three different Regional Climatic Models were applied under two projection scenarios i.e. RCP 4.5 and RCP 8.5. Maximum temperature, precipitation and minimum temperature displayed an increasing trend under the projected future climatic conditions. The results revealed a growth in the crop water requirement with a subsequent escalating irrigation demand caused due to rise in projected temperature; this is because the projected increase in precipitation under forecasted weather conditions cannot compensate for the increased evaporative demand. Moreover, the results showed a general increasing trend of sugarcane yield under projected climate. By delaying the crop calendar, an overall decrease in crop water requirement in the range of 10.7–12.6% and increase in the yield in the range of 0.37–6.48 tha−1 can be observed under both climate change scenarios. Moreover, 90% of control irrigation level proved beneficial in terms of saving around 10% irrigation water with acceptable yield reduction. The outcomes of the study are supportive for growers to gain more yield using less amount of water and to adapt to changing climate. The results are also helpful for policy makers to develop adaptation strategies to improve sugarcane productivity and to address water stress in Pakistan. [ABSTRACT FROM AUTHOR]

The aim of the study was to establish the strength and direction of the relationship between daily temperature of river water and air with the use of selected estimation methods. The relationship was assessed for the River Noteć and its tributaries (Western Poland), using the cross-correlation function and Granger causality. The study established cause-and-effect relations for "water–air" and "air–water" directions of influence. It was confirmed that forecasting the pattern of flowing water temperature from changes in air temperature yields better results when done based on data from the previous day. Results of modelling the relationship between data series with the use of the linear and natural cubic splines models confirmed the presence of a nonlinear relation. It was also established that there is a statistically significant correlation of random fluctuations for both temperature series on the same days. This made it possible to confirm the occurrence of short-term connections between water and air temperature. The results can be used to determine the qualities of thermal regimes and to predict temperature of river waters in the conditions of climate change. [ABSTRACT FROM AUTHOR]

There is an exceptional opportunity of achieving simultaneous and complementary data from a multitude of geoscience and environmental near-earth orbiting artificial satellites to study phenomena related to the climate change. These satellite missions provide the information about the various phenomena, such as sea level change, ice melting, soil moisture variation, temperature changes and earth surface deformations. In this study, we focus on permafrost thawing and its associated gravity change (in terms of the groundwater storage), and organic material changes using the gravity recovery and climate experiment (GRACE) data and other satellite- and ground-based observations. The estimation of permafrost changes requires combining information from various sources, particularly using the gravity field change, surface temperature change, and glacial isostatic adjustment. The most significant factor for a careful monitoring of the permafrost thawing is the fact that this process could be responsible for releasing an additional enormous amount of greenhouse gases emitted to the atmosphere, most importantly to mention carbon dioxide (CO2) and methane that are currently stored in the frozen ground. The results of a preliminary numerical analysis reveal a possible existence of a high correlation between the secular trends of greenhouse gases (CO2), temperature and equivalent water thickness (in permafrost active layer) in the selected regions. Furthermore, according to our estimates based on processing the GRACE data, the groundwater storage attributed due to permafrost thawing increased at the annual rates of 3.4, 3.8, 4.4 and 4.0 cm, respectively, in Siberia, North Alaska and Canada (Yukon and Hudson Bay). Despite a rather preliminary character of our results, these findings indicate that the methodology developed and applied in this study should be further improved by incorporating the in situ permafrost measurements. [ABSTRACT FROM AUTHOR]

Lake waters are a significant source of drinking water and contribute to the local economy (e.g. enabling irrigation, offering opportunities for tourism, waterways for transport, and meeting utility water demands); therefore, the ability to accurately forecast lake water levels is important. However, given the significant lack of research with respect to forecasting water levels in small lakes (i.e. 0.05 km2 < area < 10 km2), the present study sought to address this knowledge gap by testing a pair of hypotheses: (1) it is possible to forecast water levels in small surface lakes using artificial neural networks (ANN), and (2) better water-level forecasts will be obtained when the wavelet transform (WT) is used as an input data pre-processing tool. Based on an analysis of a case study in Lake Biskupinskie (1.16 km2) in Poland and based on a range of model performance statistics (e.g. mean absolute error, root mean square error, mean squared error, coefficient of determination, mean absolute percentage error), both hypotheses were confirmed for monthly forecasting of lake water levels. ANNs provided good forecasting results, and WT pre-processing of input data led to even better forecasts. Additionally, it was found that meteorological variables did not have a significant impact in forecasting water-level fluctuations. In light of the results and the limited scope of the present study, proposed future research directions and problems to be resolved are discussed. [ABSTRACT FROM AUTHOR]

Long Xuyen Quadrangle is one of the important agricultural areas of the Mekong Delta of Vietnam accounting for 25% of rice production. In recent years, the area faces drought and salinization problems, as part of climate change impact and sea level rise. These are the main causes that led to the crop water deficits for agricultural production. Therefore, this work was conducted to predict crop water requirement (CWR) based on consideration of other related meteorological factors and further redefine the crop planting calendar (CPC) for three main cropping seasons including winter-spring (WS), summer-autumn (SA) and autumn-spring (AS) using the Cropwat crop model based on the current climate conditions and future climate change scenarios. Meteorological data for the baseline period (2006-2016) and future corresponding to timescales 2020s, 2055s and 2090s of Representative Concentration Pathways (RCP)4.5 and RCP8.5 scenarios are used to predict CWR and CPC for the study area. The results showed that WS and SA crops needed more irrigation water than AS crop and the highest irrigation water requirement of the WS and SA crops occurred on developmental stage, while the AW crop appeared on growth, developmental and late stage for the baseline and timescales of RCP4.5 and RCP8.5 scenarios. Calculation results of the shift of CPC indicated that the CWR of the AW crop decreased lowest approximately 6.6-20.6% for timescales of RCP4.5 scenario and 20.6-25.5% for RCP8.5 scenario compared with the baseline. [ABSTRACT FROM AUTHOR]

As well as in other natural processes, it has been frequently observed that the phenomenon arising from the rainfall generation process presents fractal self-similarity of statistical type, and thus, rainfall series generally show scaling properties. Based on this fact, there is a methodology, simple scaling, which is used quite broadly to find or reproduce the intensity-duration-frequency curves of a place. In the present work, the relationship of the simple scaling parameter with the characteristic rainfall pattern of the area of study has been investigated. The calculation of this scaling parameter has been performed from 147 daily rainfall selected series covering the temporal period between 1883 and 2016 over the Catalonian territory (Spain) and its nearby surroundings, and a discussion about the relationship between the scaling parameter spatial distribution and rainfall pattern, as well as about trends of this scaling parameter over the past decades possibly due to climate change, has been presented. [ABSTRACT FROM AUTHOR]

A number of recent studies suggest that atmospheric changes that precede an earthquake might offer the hope of providing early warning. This study attempts to examine seismo-atmospheric anomalies around the time and the location of some of the major earthquakes in Greece in the period 2001-2015. Daily values of aerosol optical depth (AOD) and total ozone column (TOZ) obtained from satellite observations are used, in the time window between 25 days before and 14 days after each of these events, in a 1° × 1° area centred on the epicentre of each earthquake. For some of these earthquake events, abnormal increases in time series of AOD and TOZ data were detected before and after the occurrence of the earthquake. Nevertheless, in other cases, no clear anomalies were observed around the earthquake date. In addition, examining the statistics of AOD and TOZ daily values, there were many cases of prominent abnormal variations, without, however, being associated with an earthquake event. Therefore, no clear association was found between AOD and TOZ fluctuations and recent earthquakes in Greece. [ABSTRACT FROM AUTHOR]

This study aims to investigate trends and regime changes in streamflow and basic factors driving these changes. The investigated area is located in central Poland and is influenced by temperate transitional climate. New insight is provided into the phenomenon of past climate-driven changes to streamflow patterns over a 65-year period (1951-2015). The Mann-Kendall test for monotonic trends and the CUSUM test are used to determine the presence or absence of changes in climatic variables, shallow groundwater level, and streamflow. Time series are explored to detect the direction of trends and the period when the significant change occurred. Differences in climatic conditions and streamflow patterns are discussed for two sub-periods, before and after the change. Overall, the results suggest stability in precipitation, with limited evidence for change in the annual amount, but reveal a significant change in streamflow regime in the 1980s, attributed to higher temperature driving evapotranspiration and reducing shallow groundwater recharge. It is concluded that the catchment is prone to increased evapotranspiration and in effect to greatly reduced runoff. [ABSTRACT FROM AUTHOR]