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Atmospheric extreme events cause severe damage to human societies and ecosystems. The frequency and intensity of extremes and other associated events are continuously increasing due to climate change and global warming. The accurate prediction, characterization, and attribution of atmospheric extreme events is, therefore, a key research field in which many groups are currently working by applying different methodologies and computational tools. Machine learning and deep learning methods have arisen in the last years as powerful techniques to tackle many of the problems related to atmospheric extreme events. This paper reviews machine learning and deep learning approaches applied to the analysis, characterization, prediction, and attribution of the most important atmospheric extremes. A summary of the most used machine learning and deep learning techniques in this area, and a comprehensive critical review of literature related to ML in EEs, are provided. The critical literature review has been extended to extreme events related to rainfall and floods, heatwaves and extreme temperatures, droughts, severe weather events and fog, and low-visibility episodes. A case study focused on the analysis of extreme atmospheric temperature prediction with ML and DL techniques is also presented in the paper. Conclusions, perspectives, and outlooks on the field are finally drawn. [ABSTRACT FROM AUTHOR]

de Freitas et al. (2015) (henceforth dFDB) report a trend of 0.28 °C per century over the period 1909-2009 for New Zealand land surface temperatures, from their reanalysis of a composite of seven long-term records. This is much lower than the warming trend of about 0.9 °C per century reported previously by other researchers and much smaller than trends estimated from independent sea surface temperature data from the surrounding region. We show these differences result primarily from the way inhomogeneities in temperature time series at individual stations due to site or instrument changes are identified and adjusted for in the dFDB paper. The adjustments reported in that paper are based on a method designed by one of us (Salinger), but use only a short (1-2-year) overlap period with comparison stations and consider only inhomogeneities in monthly mean (rather than monthly maximum and minimum) temperatures. This leads to underestimates of the statistical significance of individual temperature discontinuities and hence rejection of many valid adjustments. Since there was a systematic tendency for the seven-station sites to be relocated to colder locations as the early half of the twentieth century progressed, this rejection of valid adjustments produces an artificially low rate of warming. We therefore disagree with the trend calculations in the dFDB paper and consider there is no reason to reject the previous estimates of around 0.9 °C warming per century. [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 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]

Space observations (1979–2020) have shown that, over the past 40 years, years with a decrease in the area of summer ice and their thickness prevailed. Over 10 years, negative trends of anomalies in the area and thickness of the ice are –13 and –15%, respectively. A rapid reduction in the area of old ice (>4-year-old) is also noted, because in 1985 it was estimated at 2.7 million km2, while in March 2010 it was 0.34 million km2. The paper analyses paleo sea ice extent during the Holocene (the last 12 000 years) based on empirical IP25 biomarkers (a sea ice proxy with 25 carbon atoms synthesized by the specific Arctic sea ice diatoms Hasleaspp, which have been proven to be a suitable proxy for paleo-sea ice reconstructions) obtained from deep-sea cores from the North Atlantic. The data showed that, during the warm periods of the Early and Middle Holocene, the area of summer sea ice was reduced to a minimum. This confirms the conclusion made earlier in (Kinnard et al., 2011) that the current trend of reducing the area and thickness of ice is unprecedented over the past 1500 years. There is no complete analogue of the climate in the past corresponding to the current level of the CO2 concentration in the atmosphere. The period with CO2 concentrations in the atmosphere similar to the current level was the warm part of the Middle Pliocene between 3 and 4 million years ago with level of the CO2 concentration 450–500 ppm against approximately 420 ppm at present. Paleo-climate reconstructions for this period estimate the global temperature to be 3.0–3.5 ± 0.5°C higher than at the end of the 19th century. Summer air temperatures in the high latitudes of the Northern Hemisphere exceeded the current ones by 8–10°C, and the sea ice in the Arctic shelf seas was completely absent in the summer. Empirical data and model simulations have shown that presently the main driver of the reduction of the Arctic sea ice area is the increase in concentration of CO2 in the atmosphere. At the present time, old sea ice tends to be replaced by seasonal ice, demonstrating a natural shift from the predominance of permanent ice to an ice-free Arctic. In the case of a continuous increase in CO2 concentration in the atmosphere despite emission control measures, one of the scenarios that happened in the past may occur again. [ABSTRACT FROM AUTHOR]

The paper reveals the causes and consequences of unfavorable conditions for overwintering of winter grain crops on the example of the Moscow region. Unstable winter periods in the recent decades resulting from climate change have often led to the damage or loss of winter grain crops (winter wheat, winter rye, and triticale). Using the difference integral curve of average annual temperatures for the entire year, the growing season (May–September), and the period from September to April, including the winter season, it is shown that warm years and warm seasons have been generally observed since 1987. The sum of negative temperatures, snow depth, frost depth, the number of days with snow cover, the duration of cold periods with air temperatures below 0, –5, –10°C, etc. are analyzed for assessment of the changes in overwintering conditions. [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]

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]

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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]

A significant fraction of multidecadal fluctuations in the reanalysis-based gridded estimates of the observed climate variability over the past century and a half lie outside of the envelope generated by ensembles of climate-model historical simulations. Several pattern-recognition methods have been previously used to map out a truly global reach of the observed vs. simulated climate-data differences; in our own work we dubbed these global discrepancies the stadium wave to highlight their most striking spatiotemporal characteristic. Here we used a novel combination of such methods in conjunction with a large multi-model ensemble and two popular twentieth-century reanalysis products to: (i) succinctly describe the geographical evolution of the observed stadium wave in the annually sampled near-surface atmospheric temperature and mean sea-level pressure fields in terms of three basic patterns; (ii) show the robustness of this identification with respect to methodological details, including the demonstration of the truly global character of the stadium wave; and (iii) provide essential clues to its dynamical origin. Part I of this study decomposed all input time series into the forced signal and the residual internal variability; multi-model forced-signal estimates were also decomposed into their common-evolution part and the individual-model residuals. Analysis of the latter residuals suggests a contribution to the stadium-wave dynamics from a delayed climate response to variable external forcing despite the observed stadium-wave patterns' exhibiting the magnitudes and the level of global teleconnectivity unmatched by the forced-signal residuals. Part III of this paper will compare the observed stadium wave with the model simulated internal patterns. [ABSTRACT FROM AUTHOR]

Drought is a natural phenomenon that occurred in Central Europe in the past, but it is becoming a more serious problem due to the changes in its occurrence and intensity related to climate change. The main aim of this paper was to determine changes in air temperature and precipitation amounts in Slovakia from 1931 to 2020 and to identify changes in drought occurrence and intensity using the Standardised Precipitation and Evapotranspiration Index (SPEI). Cluster analysis was used to determine regions with similar drought occurrences. For each of the identified five clusters, drought characteristics were determined and compared between two reference periods 1961–1990 and 1991–2020. While a decrease in the number of months with SPEI-1 below − 1 was observed in autumn, spring and summer months showed a drying tendency. Overall, we can say that we observed a shift in drought occurrence from autumn and winter months to spring and summer months. This is an important finding for the agriculture or forestry because it affects work management and planning. The clearest tendency in drought events was observed in the western part of Slovakia covering areas with agriculturally intensive land use. Besides prolonging drought events, there was also a higher accumulated deficit for each event. The increase in drought intensity was not spatially consistent over the cluster area, mostly reaching a slight decline of about − 0.1 to − 0.3, which means slight intensification of drought periods in 1991–2020. [ABSTRACT FROM AUTHOR]

In the context of the ongoing United Nations Framework Convention on Climate Change (UNFCCC) process, it seems important to focus attention not only on global mean surface air temperature (GSMT) but also on the climate of specific regions in order to gain insights into the dynamics of the changes, the timescales of the periodic components, the local trends and the relationships between climatic variables in the region of interest. This is important for scientists as well as for policymakers. This paper provides an analysis of the changes in local air temperature and precipitation depth in exceptionally long observational records and examines the relationships between these two variables. The focus is on monthly values. Temperature maximum, minimum, range, and cumulative precipitation depth are considered. The wavelet analysis shows that the scale of variation is different for temperature and precipitation and that the behavior of the temperature range values diverges from the behavior of the minimum and maximum values. The timescale of important changes in the long-term trend is, however, similar. Results also suggest that the main mode of variability is persistent through time in the series of temperature maximum, minimum, and range but not in precipitation depth. This is a clear evidence of climate change. All series show variances that change over time and are, as expected, nonstationary. The analysis of the wavelet coherence shows that the relationship between precipitation and temperature evolves through time, and its intensity varies considering different time scales. The association between these climatic variables is particularly strong in the last decade. Is it noteworthy that the analysis of the coherence suggests that temperature is leading to rain and not the other way around. This highlights the impact of global warming on the hydrologic cycle and on related human activities. [ABSTRACT FROM AUTHOR]

This paper is devoted to studying the response of different types of vegetation cover in the West Siberian Plain to temperature changes observed in recent decades. The paper analyzes trends in the series of the normalized difference vegetation index (NDVI) and air temperature in the vicinities of meteorological stations of the West Siberian Plain, which are characterized by different types of vegetation. Phases of growth (1982–1997) and stabilization (1997–2015) of NDVI values have been revealed against the background of the observed effects of global-warming slowdown, decrease of solar activity, and transition from the positive phase of the ocean-surface temperature to the negative phase in the El Niño region (ONI). It is shown that the spring months make the main contribution to variations in the seasonal NDVI value. A correlation analysis of spring NDVI and air-temperature values during the periods of NDVI growth and stabilization has been carried out. It is shown that the pattern of response of vegetation to the observed increase in temperature depends on its type and location. Thus, the relationship between the NDVI and air temperature increases in the tundra zone, decreases in very swampy areas of forest tundra and northern taiga, generally decreases in the Ob–Yenisei interfluve from forest tundra to subtaiga, and increases on the left bank of the Ob River. [ABSTRACT FROM AUTHOR]

This paper examines meteorological and vegetation-monitoring data collected in the Northern Caspian semidesert over a 70-year period. It is established that the average air temperature of the hydrological year has gradually increased over the monitoring period by 2.73°C (0.039°C/years). Prior to 2000, this increase in temperature was caused by warming of the cold season; after 2000, by warming of the warm season. The precipitation amount in the spring–summer period increased, mainly in 1978–1995, due to rainfalls in April–June. The humidity factor dynamics makes it possible to distinguish three periods. The first period (1951–1977) features insignificant fluctuations around the average humidity factor value (0.30). The second period (1978–1994) is characterized by abundant wetting. By contrast, the third period (1995–2020) is distinguished by severe aridity. These climatic changes have significantly transformed mechanisms responsible for the formation of snow cover, surface runoff of spring melt water, and groundwater level. Despite such fluctuations in natural conditions, the annual vegetation productivity on virgin lands remains in dynamic equilibrium changing over time in a wave-like manner; no invasions of alien species occur. By 2000, the ongoing warming of the winter months made the sustainable development of forest crops impossible. The absence of snow accumulation and surface inflow of spring melt waters deprived planted forest stands of additional wetting sources. Recurrent summer atmospheric droughts intensified their withering. The production of agricultural crops was discontinued since the mid-1990s due to annual harvest failures and the aridity of growing seasons. The climate warming observed in the last two decades contributes to the restoration of the original appearance of plain semidesert Northern Caspian landscapes (without agricultural fields and planted forest stands). Out of necessity, local communities are returning to the extensive cattle breeding traditionally practiced there since ancient times. [ABSTRACT FROM AUTHOR]

At present, air conditioning (AC) is the most effective means for the cooling of indoor space. However, its increased global use is problematic for various reasons. This paper explores the challenges linked to increased AC use and discusses more sustainable alternatives. A literature review was conducted applying a transdisciplinary approach. It was further complemented by examples from cities in hot climates. To analyse the findings, an analytical framework was developed which considers four societal levels—individual, community, city, and national. The main challenges identified from the literature review are as follows: environmental, organisational, socio-economical, biophysical and behavioural. The paper also identifies several measures that could be taken to reduce the fast growth of AC use. However, due to the complex nature of the problem, there is no single solution to provide sustainable cooling. Alternative solutions were categorised in three broad categories: climate-sensitive urban planning and building design, alternative cooling technologies, and climate-sensitive attitudes and behaviour. The main findings concern the problems arising from leaving the responsibility to come up with cooling solutions entirely to the individual, and how different societal levels can work towards more sustainable cooling options. It is concluded that there is a need for a more holistic view both when it comes to combining various solutions as well as involving various levels in society. [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]

This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007–2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov–Smirnov test, the corrected Akaike criterion AICc, the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28–32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes. [ABSTRACT FROM AUTHOR]

Many regions around the world are facing climate changes, with substantial increase in air temperature over the past decades, which is mainly related to continental and global warming forced by the higher greenhouse gas (GHG) emissions. The objectives of this study were to use the Köppen climate classification to detect local climate change based on a historical series of 100 years and to assess if such change is related to those that are occurring in other spatial scales as a likely consequence of increasing GHG. This paper brings a content full of innovative results. The study area presented an average annual air temperature increase by 0.9 °C between 1917 and 2016, rising from 21.4 °C for the first climatological normal (1917–1946) to 22.3 °C for the last one (1987–2016). Furthermore, in the summer months, the temperature rose from 24.5 to 25.3 °C, and in the winter months, such increase was from 17.1 (1917–1946) to 18.3 °C (1987–2016). Our findings showed the subtropical conditions (Cfa in Köppen's classification) in the study area persisted from the beginning of the analysis (1917–1946) until the climatological normal of 1979–2008, with a clear tendency of tropicalization after that with a change in the climate type of Piracicaba from subtropical to tropical, which can now be classified as tropical with dry winter (Aw climate type). The local average air temperature showed concordances with the long-term air temperature anomalies from regional, continental, and global scales, indicating that all of them may be linked with increasing GHG emissions, since well-defined long-term linear relationships (r2 = 0.99) were observed between continental and global average air temperature anomalies and atmospheric CO2 concentration observed at the NOAA Lab in Mauna Loa in the last 59 years. While the local and regional forcing effects remain to be fully unraveled, our study provided a valid and strong scientific sound evidence that climate change occurred in Piracicaba, southeastern Brazil, in the last 100 years. [ABSTRACT FROM AUTHOR]

Land cover change (LCC) significantly changed the local/regional temperature. This paper attempts to reveal the effects of cropland expansion in different ways on temperature change from the 1900s to 2010s in Heilongjiang Province. To reach this goal, we conducted four simulation research schemes with the coupled Weather Research and Forecast (WRF)-Noah model to investigate the warming/cooling effect of cropland expansion. The results show that cropland expansion exerted different effects with different land-use type conversions. In the last century, the areas with grassland-to-cropland and wetland-to-cropland transition show the warming effect, and the average surface temperature in Heilongjiang Province increased by 0.023 ℃ and 0.024 ℃, respectively. The areas with forest-to-cropland transition show the cooling effect, in which the average temperature decreased by 0.103 ℃. The variation of air temperature is mainly caused by the variation of surface reflectance and surface net radiation flux. The results provide evidence that cropland expansion changes to biophysical landscape characteristics, warming/cooling the land surface and thus enhancing/reducing the temperature, and lead to regional climate change eventually. [ABSTRACT FROM AUTHOR]

The paper contributes to the growing literature highlighting the significance of assessing risk and vulnerability, micro-level perceptions and adaptation decision-making in building resilience of farm communities to climate change in dryland region of India. To select a region for grassroots enquiry, spatial differential in risk to climate change was assessed in Rajasthan, using IPCC AR5 framework. Among the highly vulnerable and risky districts, Bikaner district was selected for elicitation of micro-level imperatives. Rising atmospheric temperature, inter-seasonal displacements of rainfall and recurrence of extreme events were perceived by the farmers resulting in resource degradation, production risks and erosion of households' socio-economic dynamics. As risk preventive measures, suitable adjustment in agricultural practices, natural resource management, shift to off-farm activities and other relief measures were adopted by the farmers. Farmer's choice of adaptation was influenced by several climatic, socio-economic and infrastructural & institutional factors in varying degree. Moreover, several financial, economic, infrastructural and informational bottlenecks to adaptations were reported during household survey and FGDs. The results suggest that capturing grassroots evidence is crucial for directing locally tailored adaptation strategies, along with the improving deficiencies in the developmental pathways for climate-resilient agriculture. [ABSTRACT FROM AUTHOR]

In this paper, we have analyzed the time series of daily values for three meteorological elements, two continuous and a discontinuous one, i.e., the maximum and minimum air temperature and the precipitation. The analysis was done based on the observations from seven stations in Serbia from the period 1951-2010. The main aim of this paper was to quantify the complexity of the annual values for the mentioned time series and to calculate the rate of its change. For that purpose, we have used the sample entropy and the Kolmogorov complexity as the measures which can indicate the variability and irregularity of a given time series. Results obtained show that the maximum temperature has increasing trends in the given period which points out a warming, ranged in the interval 1-2 °C. The increasing temperature indicates the higher internal energy of the atmosphere, changing the weather patterns, manifested in the time series. The Kolmogorov complexity of the maximum temperature time series has statistically significant increasing trends, while the sample entropy has increasing but statistically insignificant trend. The trends of complexity measures for the minimum temperature depend on the location. Both complexity measures for the precipitation time series have decreasing trends. [ABSTRACT FROM AUTHOR]

This paper examines drought trends in Turkey due to climate change. Therefore, forecasting of periods of drought, which is one of the major negative side effects of climate change, is urgent. The authors use data on drought indicators according to the SPEI (Standardized Precipitation and Evapotranspiration Index) for the period from 1901 to 2015 obtained at intervals of 1, 3, 6, and 12 months. The data have been processed by several statistical tests: the Mann–Kendall test to determine the direction and significance of the trend, the Theil–Sen estimator to assess the trend slope coefficient, and the Pettitt test to determine the most probable year of change. The period under study is divided into two intervals (1901–1981 and 1982–2015), which are compared. The GIS program is used to isolate spatial characteristics from the results we obtained. It is concluded that Turkey is divided into two main zones of drought trends. The largest one allocated to the northern regions is characterized by an increase in moisture, and a decrease in moisture is observed in the southern regions. The trend towards dry periods was more significant until 1981, but the situation has changed since 1981 due to the trend towards excess moisture, except for southeastern Turkey, where a trend towards droughts persists. [ABSTRACT FROM AUTHOR]

Global warming is the average temperature of the earth's surface which has increased over the past century by about 0.6 °C. This rising temperature may vary precipitation patterns, more frequent droughts, rise in sea level and intense storms and can be termed as climate change. To understand uneven precipitation pattern for monsoon dominated region like India, there is a need to study cloud processes at high resolution with the help of cloud microphysical properties. Ocean is the major and primary source of cloud whereas local water bodies and re-evaporated water over land could be secondary source. Paper focuses over ocean (Arabian Sea) as well as over land (central India) to know the effect of global warming on cloud microphysical properties such as cloud effective radius and cloud liquid water content. Warming signal in terms of rise in sea surface temperature (0.1 °C/decade) as well as rise in surface air temperature (0.05 °C/decade) are observed over Arabian Sea and central India respectively. Satellite data show an increasing (0.5 µm/decade) trend in cloud effective radius over Arabian Sea, whereas it decreases (− 0.1 µm/decade) over central India. Increasing trend in temperature and cloud properties is may be due to warming signal. Aerosol concentration over ocean and land further helped to understand cloud processes with cloud microphysical properties. Paper will focus on the effect of warming signal in cloud properties over Arabian Sea and central India. This type of high resolution study may help to understand cloud processes which in turn may help to understand precipitation patterns. [ABSTRACT FROM AUTHOR]

The phase shift between changes in the global surface temperature Tg and atmospheric CO2 content has been shown earlier not to characterize causal relationships in the Earth system in the general case. Specifically, the sign of this phase shift under nongreenhouse radiative forcing changes depends on the time scale of this forcing. This paper analyzes the phase shift between changes in the global surface temperature Tg and the atmospheric CO2 content under synchronous external emissions of carbon dioxide and methane into the atmosphere on the basis of numerical experiments with the IAP RAS climatic model and a conceptual climate model with carbon cycle. For a sufficiently large time scale of external forcing, the changes in lag relative to the corresponding changes in Tg. [ABSTRACT FROM AUTHOR]

A global problem facing humanity today is the changing planetary climate. The Earth's northern regions play an important role in processes that affect the environment on a global scale and serve as indicators of global natural changes, especially climate change. The currently observed climate changes in the Arctic, such as rising air temperature, shrinking ice cover, increased river runoff, and permafrost degradation, have already shown that the Arctic is experiencing the greatest changes in comparison with other regions of the Earth. The response of the Arctic to all climatic change occurring on the planet is the strongest. The strong and rapid changes in the Arctic climate in recent years require comprehensive studies of their causes with assessment of the role of natural and anthropogenic factors. This paper analyzes the temporal changes in a number of Arctic climate indicators based on its main components (air temperature and oscillations in the atmospheric circulation, ocean waters, and ice cover extent) at time intervals of the 20th century, the period of anthropogenic impact on the climate, the last 2000 years, and the Holocene period, as well as the role of solar activity (cyclical changes and insolation) in climate change on the Earth. Trends in the variation in natural climate indicators are traced. Problems of prime importance for an understanding of the nature of current climate change and the main physical processes responsible for these changes are discussed. The goal of the study is to summarize the current understanding of Arctic climate change. [ABSTRACT FROM AUTHOR]

Significant changes in climate variables in the last decades resulted in changes of perceived climate conditions. However, there are only few studies discussing long-lasting changes in bioclimatic conditions. Thus, the purpose of this paper is to present the temporal and spatial distribution of hazardous heat and cold stress conditions in different regions of Poland. Its focus is on long-lasting changes in such conditions in the period 1951–2018. To assess changes in hazardous thermal stress conditions, the Universal Thermal Climate Index (UTCI) was used. UTCI values at 12 UTC hour (respectively 1 pm winter time, 2 pm summer time) were calculated daily based on air temperature, relative humidity, total cloud cover and wind speed at 24 stations representing the whole area of Poland. We found that the greatest changes were observed in minimum (1.33 °C/10 years) and average (0.52 °C/10 years) UTCI values as well as in cold stress frequency (− 4.00 days per 10 years). The changes vary seasonally and regionally. The greatest increase in UTCImin and decrease in cold stress days were noted from November to March and had the highest values in north-east and east Poland, and also in the foothills of the Carpathian Mountains. The trends in maximum UTCI are much smaller and not always positive. The spatially averaged trend in UTCImax for Poland as a whole was 0.35 °C/10 years and the increase in heat stress days was 0.80 days/10 years. The highest increases in UTCImax and heat stress days were noted in eastern and south-eastern Poland. [ABSTRACT FROM AUTHOR]

The paper analyses the temporal and spatial variability of the Universal Thermal Climate Index (UTCI) in Poland in summer. Summer is the season with the highest intensity of tourism traffic that is why it is important to determine biometeorological conditions, especially in popular tourist destinations such as coastal, mountain and urban areas, in the times of climate changes. The analysis was based on data from 18 stations of IMGW-PIB (Institute of Meteorology and Water Management—National Research Institute), distributed evenly in the territory of the country, and representing all eight bioclimatic regions. The data include air temperature, relative humidity, wind velocity and cloudiness at 12 UTC from summer months: June, July and August from the years 2001–2018. Thermoneutral zone was the most frequently occurring UTCI class in Poland. It was recorded during 56–75% of summer days (with the exception of mountain stations, where it occurred on 30–35% of days). Moderate heat stress is the second most frequently occurring category with a frequency from 18 to 29% with the exception of mountain and coastal areas. Extreme and very strong cold stress occurred particularly in high mountain stations, and was sporadically observed at the coast of the Baltic Sea; however, the occurrence of such conditions decreases, which if favourable for beach tourism. No cases of extreme heat stress were recorded in any of the stations. The most unfavourable bioclimatic conditions were characteristic of the Upland Region (IV), represented by Kraków and Sandomierz, where very strong heat stress occurred with a 10% frequency. This is a limitation for urban tourism in those regions. The highest UTCI values were recorded in Kraków on 17 July 2007 and 29 July 2005. The highest number of cases with strong and very strong heat stress was recorded in 2015 as a consequence of the heat wave observed in Poland in the first half of August. In the majority of the analysed stations, in the second half of the analysed period (2010–2018), an increase in the number of days with strong and very strong heat stress was observed in comparison with the first half of period (2001–2009). The highest frequency of such days was observed in July. Based on the data, there are 4 potential periods of occurrence of such days, with two most intense being 26. July–13 August and 14–22 July. [ABSTRACT FROM AUTHOR]

Canopy phenology is sensitive to variability in local environmental settings. In temperate climates, urban phenological processes and their determinants are relatively well understood. Equivalent understanding of processes in tropical urban settings is, however, less resolved. In this paper, we explore the influence of local urban environmental characteristics (that is, degree of urbanization, land cover and urban climate) on canopy phenology of two deciduous tree species (Jacaranda mimosifolia, n = 48, and Tabebuia rosea, n = 24) in a tropical city (Kampala, Uganda). Our study design involved ground monitoring and field sampling in 2017, with a focus on the dry season. We found that both species experienced significantly higher rates of canopy cover decline in heavily built-up neighborhoods (p < 0.05 for both species). Moreover, Jacaranda was more sensitive to differences in the degree of urbanization than Tabebuia, both in terms of total percentage tree canopy cover (p < 0.01) and net leaf loss (p < 0.05). Total percentage tree canopy cover for Jacaranda declined with increasing proportion of impervious cover (that is, roads and paved cover) and was positively related to relative humidity (p < 0.01), a variable correlated with soil moisture. Net leaf loss in Jacaranda increased with the decreasing proportion of pervious land cover and as nighttime air temperature increased (p < 0.01). In contrast, land cover and urban climate had no significant influence on either measure of phenological traits for Tabebuia. These results provide new evidence of the effect of urbanization on canopy phenology of different tree species in the tropics. Such knowledge offers new insights into the spatial and temporal differences in the physiological functional traits of trees and also serves as a proxy for possible species responses under future climate change. [ABSTRACT FROM AUTHOR]

Air temperature is the main climatic variable for climate change and global warming assessment. In different regions, different climatic features and forcing factors affect air temperature behaviour and development differently. In this paper, time series of monthly and annual absolute minimum, mean and absolute maximum air temperatures measured in the period Jan. 1949–Dec. 2018 at two meteorological stations, Zagreb Grič and Lastovo, were analysed. The stations are situated in distinct climatological areas in geographically and climatologically completely opposite parts of Croatia. The climate of Zagreb Grič station is mild continental. Station Lastovo is located on the small isolated Adriatic Sea island, which has a hot Mediterranean climate. The distance by air between the two analysed meteorological stations is 340 km. In time series of the absolute annual minimum air temperatures measured at both analysed stations, an increasing trend is not statistically significant, while in the time series of mean annual and absolute annual maximum air temperatures, the trends are statistically significant at the level p<0.01. The statistically significant trend of air temperature increase at both stations appeared in the warm season of the year generally from May to August. The day-to-day (DTD) method established a decrease in night-time to night-time air temperature variability, and an increase in the day-time to day-time temperature variability at Lastovo. In Zagreb Grič, the situation is the opposite but the process is very slow. [ABSTRACT FROM AUTHOR]

This paper studies the long-term variability of frequency of atmospheric blockings over Western Siberia in 1948-2015 based on the data of three reanalysis projects. We revealed a decreasing blocking frequency for eight of twelve months. However, since the estimated trends of blocking frequency are small comparing to the significant amplitude of interannual variations, we proposed to divide the entire studied period into several quasi-decadal intervals that differ both in the amplitude of interannual fluctuations of blocking frequency and in trends. The effect of Western Siberian blockings imposed on synoptic and climatic variability of meteorological parameters in Asia was studied. The study demonstrated that in summer teleconnection patterns in temperature and precipitation fields are of the close sign-alternating structure; this indirectly indicates that in Western Siberia the blocking is a part of a large-scale wave mechanism. Like the Ural blockings, the blockings occurring over Western Siberia affect meteorological characteristics within the East Asian monsoon area. In winter time they contribute to lower surface temperature and decreased precipitation in Southeast Asia. In summer during blocking events over Western Siberia, precipitation increases in the East Asian monsoon area. [ABSTRACT FROM AUTHOR]

Europe and in particular its southern part are expected to undergo serious climate changes during summer in response to anthropogenic forcing, with large surface warming and decrease in precipitation. Yet, serious uncertainties remain, especially over central and western Europe. Several mechanisms have been suggested to be important in that context but their relative importance and possible interplays are still not well understood. In this paper, the role of soil-atmosphere interactions, cloud-temperature interactions and land-sea warming contrast in summer European climate change and how they interact are analyzed. Models for which evapotranspiration is strongly limited by soil moisture in the present climate are found to tend to simulate larger future decrease in evapotranspiration. Models characterized by stronger present-day anti-correlation between cloud cover and temperature over land tend to simulate larger future decrease in cloud cover. Large model-to-model differences regarding land-sea warming contrast and its impacts are also found. Warming over land is expected to be larger than warming over sea, leading to a decrease in continental relative humidity and precipitation because of the discrepancy between the change in atmospheric moisture capacity over land and the change in specific humidity. Yet, it is not true for all the models over our domain of interest. Models in which evapotranspiration is not limited by soil moisture and with a weak present-day anti-correlation between cloud cover and temperature tend to simulate smaller land surface warming. In these models, change in specific humidity over land is therefore able to match the continental increase in moisture capacity, which leads to virtually no change in continental relative humidity and smaller precipitation change. Because of the physical links that exist between the response to anthropogenic forcing of important impact-related climate variables and the way some mechanisms are simulated in the context of present-day variability, this study suggests some potentially useful metrics to reduce summer European climate change uncertainties. [ABSTRACT FROM AUTHOR]

Although climate change impacts on the agricultural sector were investigated intensively, however, vulnerability assessments and adaptation planning at the community level are still limited. This study aimed at providing a comprehensive climate change vulnerability assessment of four agriculture responses of barley production, wheat production, olive trees production, and goats' mortality at the Yarmouk River Basin in northern Jordan using a qualitative-quantitative scoring method based on actual estimations of exposure, sensitivity, and adaptive capacity with an emphasis on community engagement. Thirty-year temporal variability (1982–2012) analysis using Kendall test and Pearson correlation test for three climatic variables (maximum and minimum air temperature, and annual rainfall) indicates high significant exposure level of increasing air temperature trends by rates of 0.07 °C/year and 0.06 °C/year for maximum and minimum temperature, respectively, and insignificant annual rainfall reductions ranging spatially from 2.1 mm/year at Irbid governorate to 2.9 mm/year at Mafraq Governorate. Agriculture responses sensitivity assessment indicates goats' mortality followed by olive production are moderately correlated with climate variables (r ranges from 0.32 to 0.57). The adaptive capacity assessment highlights the presence of low to moderate financial, institutional, political enforcement, technology implementation, and awareness of the farmers to climate change impacts and potential adaptation measures that subjected the study area to be ranked as moderately to highly vulnerable to climate change impacts. Multi-criteria decision analysis suggests that irrigation water-related adaptation measures are listed within top priorities. This paper addresses the qualitative-quantitative vulnerability assessment approach at the local rural level and through participatory engagements to be effective for improving the vulnerable adaptive capacities and suggesting further recommendations to be mainstreamed urgently with governmental strategies and action plans. [ABSTRACT FROM AUTHOR]

Air temperatures (Ta) are rising in a changing climate, increasing extreme temperature events. Examining how Ta increases are influencing extreme temperatures at the soil surface and belowground in the soil profile can refine our understanding of the ecological consequences of rising temperatures. In this paper, we validate surface and soil temperature (Ts: 0–100-cm depth) simulations in the SOILWAT2 model for 29 locations comprising 5 ecosystem types in the central and western USA. We determine the temperature characteristics of these locations from 1980 to 2015, and explore simulations of Ta and Ts change over 2030–2065 and 2065–2100 time periods using General Circulation Model (GCM) projections and the RCP 8.5 emissions scenario. We define temperature extremes using a nonstationary peak over threshold method, quantified from standard deviations above the mean (0-σ: an event > ∼ 51% of extreme events; 2- σ : > ∼ 98 % ). Our primary objective is to contrast the magnitude (∘C) and frequency of occurrence of extreme temperature events between the twentieth and twenty-first century. We project that temperatures will increase substantially in the twenty-first century. Extreme Ta events will experience the largest increases by magnitude, and extreme Ts events will experience the largest increases by proportion. On average, 2-σ extreme Ts events will increase by 3.4 ∘C in 2030–2065 and by 5.3 ∘C in 2065–2100. Increases in extreme Ts events will often exceed + 10 ∘C at 0–20 cm by 2065–2100, and at 0–100 cm will often exceed 5.0 standard deviations above 1980–2015 values. 2-σ extreme Ts events will increase from 0.9 events per decade in 1980–2015 to 23 events in 2030–2065 and 38 events in 2065–2100. By 2065–2100, the majority of months will experience extreme events that co-occur at 0–100 cm, which did not occur in 1980–2015. These projections illustrate the non-analog temperature increases that ecosystems will experience in the twenty-first century as a result of climate change. [ABSTRACT FROM AUTHOR]

This paper presents the results of a trend and correlation analysis of the air temperature and the normalized difference vegetation index (NDVI) performed for the warm season in the taiga and tundra zones of West Siberia over the period of 1982–2015. Both in the taiga and tundra zones, a significant increase in NDVI values is observed in certain months of the spring–summer period amid significant (α = 0.05) positive air temperature trends. The air temperature and NDVI trends have been computed for the taiga and tundra zones from April to October over the period of 1982–2015; the irregularity of their spatial distribution in the study area is demonstrated. It is established that the vegetation development during the warm season is significantly determined by its development in the first month of the warm season (May for taiga and June for tundra). In the taiga zone, the NDVI value in May is formed under the influence of April and May temperatures; in the tundra zone, it is formed in June under the influence of June temperatures. However, the input of May temperatures into the formation of the tundra vegetation cover has increased in recent years due to climate warming. Significant correlation coefficients between the NDVI and averaged temperatures in April–May and May–June are typical for most of the study area, except for coastal northern regions in the first case and southwestern regions in the second case. [ABSTRACT FROM AUTHOR]

Analyses of the variation characteristics for aridity index (AI) can further enhance the understanding of climate change and have effect on hydrology and agriculture. In this paper, based on the data of 283 standard meteorological stations, the temporal-spatial variations and the influences of climate factors on AI were investigated and the relationship between AI and two climate indices (the Arctic Oscillation (AO); El Nino-Southern Oscillation (ENSO)) were also assessed in northern China (NC) during the period from 1961 to 2012. The results revealed that the annual mean AI decreased at the rate of −0.031 per decade in the past 52 years and the trend was statistically significant at the 0.01 level. The Mann-Kendall (M-K) test presented that the percentages of stations with positive trends and negative trends for AI were 10 and 81.9 % (22.6 % statistically significant), respectively. Spatially, in the western part of 100° E, the extremely dry area declined and the climate tended to become wet obviously. In the eastern part of 100° E, dry area moved toward the east and the south, which resulted in the enhancement of semiarid area and the shrinkage of subhumid area. The contributions of sunshine duration and precipitation to the decline of AI are more than those of other meteorological variables in NC. Moreover, the average temperature has risen significantly and AI decreased in NC, which indicated the existence of 'paradox.' Relationship between climate indices (AO and ENSO) and AI demonstrated that the influence of ENSO on AI overweight the AO on AI in NC. [ABSTRACT FROM AUTHOR]

Studies of the anticipated consequences of climate change suggest that among all economic sectors, agriculture would be the most affected. In Brazil, this issue is particularly relevant, since the agricultural sector and its related activities account for a significant share of the country's GDP and employment. Using a fixed effects panel model and data from 1990 through 2012, this paper empirically analyzes the vulnerability of agriculture to climate variables in Brazil's ten main agricultural states and the possible resulting loss of agricultural value in the face of future climate change. Our work is differentiated from prior studies in that it employs state level annual data series, which allows the aggregation of a great deal of relevant current information to the analysis. The results indicate that climate variables have a significant impact on most of these states' agricultural production, especially air temperature, whose effects showed higher estimated magnitude than those from rainfall. Considering the estimated elasticities and climatic projections, the most severe damage to agriculture is expected in Espírito Santo, Minas Gerais, and Rio Grande do Sul. [ABSTRACT FROM AUTHOR]

This paper describes changes of near-surface air temperature in southern South America from the Last Glacial Maximum (~ 21,000 years before present) to the end of the twenty-first century based on PMIP3-CMIP5 model simulations. The study shows modeled time evolution of temperature highlighting how different the projected future warming will be with respect to paleoclimatic changes documented in the region. In this context, model simulations suggest that the projected twenty-first century warming will be markedly higher than the change of temperature registered between the mid-Holocene (~ 6000 years before present) and the present. Even more, the regional warming projected by the following 60–80 years might be almost similar to or even higher than the pronounced increment of temperature developed between the Last Glacial Maximum and the present. This past/future comparison provides a new picture of the unusual warming expected for the following decades in southern South America in the context of climate changes developed through the last ca. 21,000 years. [ABSTRACT FROM AUTHOR]

This paper studies the changes in winter air temperatures in the Siberian sector of the northern hemisphere (60–120° E) over a long-term period of 1947–2017. A positive trend in air temperature (0.3°C/10 years) was revealed. An analysis of the magnitude and frequency of temperature anomalies also confirms an increase in surface temperature. The distribution of large positive and negative temperature anomalies was investigated. Centers of the largest recurrence of large negative anomalies were located in the south and south-west of the study area. A maximum number of negative anomalies were observed in December. Large positive anomalies (the highest frequency in January) were observed throughout the territory under consideration, and extremely large anomalies were found only at 20% of the stations. The largest number of anomalies in the period of 1947–2017 was observed at the Irkutsk station. Based on the analysis of elementary circulation mechanisms (classification by B.L. Dzerdzeevskii), a relationship was established between the atmospheric circulation and the distribution of air temperature anomalies. It was concluded that the temperature regime in the winter months was formed under the influence of 26 elementary circulation mechanisms, combined into seven groups. The meridional circulation prevailed (75% of cases). The elementary circulation mechanisms of the meridional northern circulation group were all characterized by the presence of blockings and intrusions of southern cyclones into the study area. In general, over the past two decades, an increase in duration of macrocirculation processes resulting in the inter-latitudinal air mass exchange has been revealed. [ABSTRACT FROM AUTHOR]

The objective of the paper was the determination of the circulation conditions of occurrence of strong and very strong frost in Central Europe. A frost day was defined as a day with the minimum temperature lower than 0 °C and maximum temperature higher than 0 °C. Moreover, a division of frost was performed in terms of value of minimum temperature, resulting in the designation of mild frost (up to − 2.0 °C), moderate frost (from − 2.1 to − 4 °C), strong frost (from − 4.1 to − 6 °C) and very strong frost (< − 6 °C). The study was based on data from the years 1966–2015 from the Institute of Meteorology and Water Management—National Research Institute, Deutscher Wetterdienst and National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). The analysis of baric conditions employed values of pressure at sea level, height of isobaric surface of 500 hPa and air temperature at a level of 850 hPa, as well as their anomalies. The spatial analysis showed that the number of frost days in spring and autumn increased from the west to the east of Central Europe. A decrease in the number of frost days, however, is observed over the prevailing area. Average conditions favouring the occurrence of strong and very strong frost both in spring and autumn were related to higher than average pressure at sea level over the prevailing area of the Euro-Atlantic sector. Such baric conditions caused advections of cool air masses from the northern sector. [ABSTRACT FROM AUTHOR]

Surface air temperature is important for climate change, hydrological, and ecosystems undergoing climate warming in the permafrost regions on the Qinghai-Tibetan Plateau (QTP). We monitored daily air temperatures at five sites (alpine desert, alpine desert steppe, alpine steppe, alpine meadow, and alpine wet meadow) from 2011 to 2015 in permafrost regions on the QTP. Using this data, we evaluated the performance of five different reanalysis air temperature products (CFSR, ERA-Interim, GLDAS-NOAH, MERRA, JRA-55, and CMFD). These results demonstrated that the ERA-Interim air temperature products exhibited the best performance at the majority of sites. However, the original ERA-Interim air temperature products were found to overestimate air temperature at most sites. The calibration models were established by the observed daily air temperatures measured from 2013 to 2015 for the ERA-Interim air temperature products, which validated with observational data from 2011 to 2012. Following calibration, ERA-Interim products were found to be closer to the observations made across all sites. In addition, this paper demonstrated a warming trend present in month, seasonal, and annual mean air temperature from the calibration results collected from 1980 to 2015. These results demonstrated that the largest warming trend was observed in February, while the smallest warming trend was observed in March. We demonstrated that all air temperatures warmed fastest in the summer and winter, more slowly in autumn, and the slowest in spring at the majority of sites tested. In addition, we found that the average annual air temperature warming trends were 0.0398, 0.0394, 0.0288, 0.0259, and 0.0254 °C/year in the alpine desert steppe, alpine desert, alpine steppe, alpine meadow, and alpine wet meadow in the permafrost regions on the QTP, respectively. These findings generate a useful tool for the recognizing of the variation in permafrost under climate change in permafrost regions on the QTP. [ABSTRACT FROM AUTHOR]

Lake is an important water resources in Mongolia, which has undergone a large variation in past decades. However, it is still challenging to monitor long-term changes in lake water storage (LWS) due to the lack of lake level monitoring and long-term satellite altimetry data for Mongolian lakes. According to the Advanced Land Observing Satellite Digital Elevation Model (ALOS DEM) and the Joint Research Centre (JRC) dataset, we estimated the LWS changes of 55 Mongolian lakes (> 10 km2) from 1991 to 2020. The results showed that the LWS increased by 40.24 km3 from 1991 to 1997, especially for northwestern Mongolia with 31.47 km3. However, the LWS decreased by 32.44 km3 from 1998 to 2010, and the lakes in the northwestern and southern decreased by 20.24 km3 (62%) and 7.38 km3 (23%), respectively, and then the LWS continued to decrease by 10.22 km3 from 2011 to 2020. The precipitation was the primary cause of lake change, which could explain 45.13% of LWS change based on Generalized Linear Model, followed by temperature (26.33%) and irrigated area (16.72%). Analyzing the changing characteristic and driving mechanisms of LWS can provide a scientific basis for local water resources management and planning. [ABSTRACT FROM AUTHOR]

The paper discusses temporal changes in the configuration of vertical climatic belts in the Tatra Mountains as a result of current climate change. Meteorological stations are scarce in the Tatra Mountains; therefore, we modelled decadal air temperatures using existing data from 20 meteorological stations and the relationship between air temperature and altitude. Air temperature was modelled separately for northern and southern slopes and for convex and concave landforms. Decadal air temperatures were additionally used to delineate five climatic belts previously distinguished by Hess on the basis of threshold values of annual air temperature. The spatial extent and location of the borderline isotherms of 6, 4, 2, 0, and − 2 °C for four decades, including 1951–1960, 1981–1990, 1991–2000, and 2001–2010, were compared. Significant warming in the Tatra Mountains, uniform in the vertical profile, started at the beginning of the 1980s and led to clear changes in the extent and location of the vertical climatic belts delineated on the basis of annual air temperature. The uphill shift of the borderline isotherms was more prominent on southern than on northern slopes. The highest rate of changes in the extent of the climatic belts was found above the isotherm of 0 °C (moderately cold and cold belts). The cold belt dramatically diminished in extent over the research period. [ABSTRACT FROM AUTHOR]

A comprehensive performance assessment of the empirical-statistical downscaling (ESD) technique named EPISODES is presented. Pertaining evaluation analyses consist of multifarious validation experiments as well as various comparisons of EPISODES' projections with those of three RCMs and two ESD methods based on the same GCM scenarios driven by two distinct representative concentration pathways (RCPs). EPISODES combines the downscaling of GCM simulations with a follow-up production of synthetic local time series. EPISODES is a comparably simple, computationally rather inexpensive technique, providing multi-variable and multi-site data that are suitable for being merged in an ensemble of RCM projections. This allows (e.g. for different RCPs) the compilation of large multi member ensembles derived from various GCM simulations via both main downscaling strategies (ESD and RCMs). Evaluation experiments reveal satisfying degrees of compliance between various results generated by EPISODES and observations. The grid cell bias for yearly values, for instance, is mostly less than 0.1∘C for temperature and 10% for precipitation totals. Recorded temperature values and precipitation totals corresponding to their 1st and the 99th percentiles are well represented by EPISODES too. Comparisons of various climate change signals derived by EPISODES and other downscaling approaches, present high levels of agreement as well. Many more findings referring to evaluation experiments and climate change projections are to be found in the paper as well as throughout the "Appendix". [ABSTRACT FROM AUTHOR]

This paper evaluates the performance of a suite of state-of-art coupled atmosphere-ocean general circulation models (AOGCMs) in their representation of regional characteristics of hydrological cycle and temperature over South Asia. Based on AOGCM experiments conducted for two types of future greenhouse gas emission scenarios (RCP4.5 and RCP8.5) extending up to the end of 21st century, scenarios of temperature and hydrological cycle are presented. The AOGCMs, despite their relatively coarse resolution, have shown a reasonable skill in depicting the hydrological cycle over the South Asian region. However, considerable biases do exist with reference to the observed hydrological cycle and also inter-model differences. The regional climate change scenarios of temperature ( T), atmospheric water balance components, precipitation, moisture convergence and evaporation ( P, C and E) up to the end of the 21st century based on CMIP5 modeling experiments conducted for (RCP4.5 and RCP8.5) indicate marked increase in both rainfall and temperature into the 21st century, particularly becoming conspicuous after the 2050s. The monsoon rainfall and atmospheric water balance changes under RCP4.5 and RCP8.5 scenarios are discussed in detail in this paper. Spatial patterns of rainfall change projections indicate maximum increase over South Asia in most of the models. Model simulations under scenarios of increased greenhouse gas concentrations suggests that the intensification of the hydrological cycle is driven mainly by the increased moisture convergence due to increase in the water holding capacity of the atmosphere in a warmer environment, the intensification of the hydrological cycle is greater for RCP8.5 compared to RCP4.5, also fewer models indicate increased variance of temperature and rainfall in a warmer environment. While the scenarios presented in this study are indicative of the expected range of rainfall and water balance changes, it must be noted that the quantitative estimates still have large uncertainties associated with them. Five best model mean reveals the general consensus among the AOGCM results and gives the best estimate of the future projection over the South Asian monsoon region. [ABSTRACT FROM AUTHOR]

Motivated by growing heat-related morbidity and mortality in a warming climate, this paper assesses global heat health risk in order to understand the challenges to sustainability in the 21st century, using four Representative Concentration Pathways (RCPs) of the HadGEM2-ES climate model and five Shared Socio-Economic Pathways (SSPs). Factors influencing global heat health risk were reviewed and risks were estimated based on heat hazard and socio-economic vulnerability. Hazard, vulnerability, risk and in particular, populations at different risk levels, were analyzed quantitatively at both global and regional scales. The results show that under an RCP8.5-SSP3 scenario, the world will be subject to the highest heat health risk, with rapidly increasing hazard levels and vulnerability over the century. Less developed or developing regions, such as Africa and Southeast Asia, are at the highest risk. The heat risk under an RCP2.6-SSP1 scenario will first increase and then fall, resulting in the lowest heat-health-risk pattern. We found that heat health risk will increase during the century under all RCP-SSP scenarios, with a higher frequency, higher intensity, longer duration and expanding spatial reach. Significant differences were observed across regions. The results make clear that the increasing risk poses significant challenges to sustainable human health. To meet these challenges, more attention and effective actions are urgently needed from both policy makers and individuals. [ABSTRACT FROM AUTHOR]

In this paper we have put forward a Bayesian framework for the analysis and testing of possible non-stationarities in extreme events. We use the extreme value theory to model temperature and precipitation data in the Dar es Salaam region, Tanzania. Temporal trends are modeled writing the location parameter of the generalized extreme value distribution in terms of deterministic functions of explanatory covariates. The analyses are performed using synthetic time series derived from a Regional Climate Model. The simulations, performed in an area around the Dar es Salaam city, Tanzania, take into account two Representative Concentration Pathways scenarios from the Intergovernmental Panel on Climate Change. Our main interest is to analyze extremes with high spatial and temporal resolution and to pursue this requirement we have adopted an individual grid box analysis approach. The approach presented in this paper is composed of the following key elements: (1) an advanced Bayesian method for the estimation of model parameters, (2) a rigorous procedure for model selection, and (3) uncertainty assessment and propagation. The results of our analyses are intended to be used for quantitative hazard and risk assessment and are presented in terms of hazard curves and probabilistic hazard maps. In the case study we found that for both the temperature and precipitation data, a linear trend in the location parameter was the only model performing better than the stationary one in the areas where evidence against the stationary model exists. [ABSTRACT FROM AUTHOR]

The rareness and inhomogeneity of the data points cause difficulties in the reconstruction of past average temperature. Optimal regional averaging is a method that can overcome these difficulties and obtain the average temperature of target area by means of optimal weights using limited temperature data. In this paper, the average temperature in the Northern Hemisphere is calculated by the optimal regional averaging method using two types of data: temperature data from Climatic Research Unit from 1901 to 2000 and maximum latewood density dataset of tree from 1500 to 1949. Five, ten, fifteen data points from CRU and forty data points from MXD are used in our research. The results show that even with the relatively less data used in this reconstruction, the method allows the reconstruction of the average temperature of the Northern Hemisphere more accurately, which provides the temperature information for palaeoclimate reconstruction. [ABSTRACT FROM AUTHOR]

Extreme heat events have serious effects on human daily life. Accurately capturing the dynamic variance of extreme high-temperature distributions in a timely manner is the basis for analyzing the potential impacts of extreme heat, thereby informing risk prevention strategies. This paper demonstrates the potential application of multiple source remote sensing data in mapping and monitoring the extreme heat events that occurred on Aug. 8, 2013 in Jiangsu Province, China. In combination with MODIS products, the thermal sharpening (TsHARP) method and a binary linear model are compared to downscale the original daytime FengYun 2F (FY-2F) land surface temperature (LST) imagery, with a temporal resolution of 60 min, from 5 km to 1 km. Using the meteorological measurement data from Nanjing station as the reference, the research then estimates the instantaneous air temperature by using an iterative computation based on the Surface Energy Balance Algorithm for Land (SEBAL), which is used to analyze the spatio-temporal air temperature variance. The results show that the root mean square error (RMSE) of the LST downscaled from the binary linear model is 1.30°C compared to the synchronous MODIS LST, and on this basis the estimated air temperature has the RMSE of 1.78°C. The spatial and temporal distribution of air temperature variance at each geographical location from 06:30 to 18:30 can be accurately determined, and indicates that the high temperature gradually increases and expands from the city center. For the spatial distribution, the air temperature and the defined scorching temperature proportion index increase from northern to middle, to southern part of Jiangsu, and are slightly lower in the eastern area near the Yellow Sea. In terms of temporal characteristics, the percentage of area with air temperature above 37°C in each city increase with time after 10:30 and reach the peak value at 14:30 or 15:30. Then, they decrease gradually, and the rising and falling trends become smaller from the southern cities to the northern regions. Moreover, there is a distinct positive relationship between the percentage of area above 37°C and the population density. The above results show that the spatio-temporal distributions of heat waves and their influencing factors can be determined by combining multiple sources of remotely sensed image data. [ABSTRACT FROM AUTHOR]