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Europe and the Mediterranean are considered climate change hot spots. This is the reason why this paper focuses on the analysis of the trends of essential climate variables in a Mediterranean country, Greece. The analyzed period is 1991–2020, and the dataset used is ERA5-Land (produced by the European Center for Medium-Range Weather Forecasts), which has global coverage and an improved resolution of ~9 × 9 km compared to other datasets. Significant climatic changes across Greece have been put in evidence during the analyzed period. More specifically, the country averaged a 30-year trend of temperature of +1.5 °C, locally exceeding +2 °C, and this increasing trend is positively correlated with the distance of the areas from the coasts. Accordingly, the number of frost days has decreased throughout the country. In terms of rainfall, a major part of Greece has experienced increasing annual rainfall amounts, while 86% of the Greek area has experienced a positive trend of days with heavy rainfall (>20 mm). Finally, a multiple signal of the trend of consecutive dry days was found (statistically non-significant in the major part of Greece). [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]

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]

This paper compares the ideas contained in the main papers published on climate change since World War II to arrive at a suggested consensus of our present knowledge regarding climatic changes and their causes. Atmospheric carbon dioxide is only suggested as a cause in one theory, which, despite its wide acceptance by Politicians, the media, and the Public, ignores the findings in other studies, including the ideas found in the Milankovitch Cycles. It also does not explain the well-known NASA map of the changes between the global 1951–1978 and the 2010–2019 mean annual temperatures. The other theories by Oceanographers, Earth scientists, and Geographers fit together to indicate that the variations in climate are the result of differential solar heating of the Earth, resulting in a series of processes redistributing the heat to produce a more uniform range of climates around the surface of the Earth. Key factors are the shape of the Earth and the Milankovitch Cycles, the distribution of land and water bodies, the differences between heating land and water, ocean currents and gateways, air masses, and hurricanes. Low atmospheric carbon dioxide levels during cold events could result in too little of this gas to support photosynthesis in plants, resulting in the extermination of most life on Earth as we know it. The 23 ka Milankovitch cycle has begun to reduce the winter insolation received at the surface of the atmosphere in the mid-latitudes of the Northern Hemisphere starting in 2020. This results in extreme weather as the winter insolation reaching the surface of the atmosphere in the higher latitudes of the Northern Hemisphere decreases while the summer air temperatures increase. It heralds the start of the next glaciation. A brief outline is given of some of the climatic changes and consequences that may be expected in western Canada during the next 11.5 ka. [ABSTRACT FROM AUTHOR]

The subject of this paper is the analysis of possible influence of climate change on the energy performance of building and indoor temperatures. The model is based on the Maison Air et Lumière house, which concept was developed as part of the Model Homo 2020 project. It was a low-energy, single family, detached house. The model was divided into three thermal zones and developed by using SketchUp software. The analysis of the climate change was made on the example of the city in Poland - Kielce and described in the first part of the paper. Dynamic calculations of the building model were performed by using the TRNSYS software. The calculations were made for three different scenarios relating to existing technical systems: ventilation, ventilation + heating, ventilation + heating + cooling. Annual energy consumption and rooms air temperature changes were estimated for each variant. The results showed higher risk of summer discomfort and change in energy balance of building what indicates the need to use the cooling system in the future during the summer to reduce the discomfort of overheating. In the variant without the cooling system, the percentage of time with an indoor temperature above 27°C increased from 23.7% to 44.2% in zone 2. The energy demand for heating was reduced by 23.4% compared to the current climate, and the energy consumption for cooling (with the cooling option) increased significantly by 232% compared to the current demand. Summarizing, research indicates that with global warming, the energy demand for heating will decrease and the cooling demand will increase significantly in order to maintain the required user comfort. [ABSTRACT FROM AUTHOR]

The paper purpose was to assess the impact of climate change on wheat, maize and sunflower yield in the period 2017-2021, using statistical data from National Institute of Statistics (NIS) and National Administration of Meteorology (NAM) and other sources. Comparison method was used to evaluate the deviations between the registered air temperatures and precipitations and the 1981-2010 climatological norm. Graphic method reflected the dynamics of monthly air temperatures and rainfalls in each year. Descriptive statistics for mean, standard deviation and coefficient of variation reflected an more comprehensive image upon air temperature, precipitations and yield. Correlations and regression equations were used to establish the intensity of the kinks between climate factors and yield. The highest average air temperature In Romania was 12.130C in 2019. In the period 2017-2020, the average annual temperatures exceeded the climatological norm 1981-2010 accounting for 9.10C. The lowest rainfalls, 614.2 mm, were recorded in 2019, being below of 633.1 mm the norm for the period 1981-2010. The high temperatures associated with drought and low precipitations have deeply affected yield of many agricultural crops, including maize, wheat and sunflower. The highest wheat yield 4,888 kg/ha was achieved in 2017, and the lowest one, 2,966 kg/ha in 2020. Maize registered the highest performance of 7,644 kg/ha in 2018, and the lowest one, 3,977 kg/ha in 2020. Sunflower carried out the high performance 3,041 kg/ha in 2018, and the lowest one, 1,858 kg/ha in 2020. The worst agricultural years for these three crops was 2020, but 2017 favored wheat, while 2018 favored maize and sunflower. The correlation coefficient had in general small values between average temperature and yield, but a higher link with precipitations level. The multiple correlation between yield, air temperatures and precipitations was: r= 0.817 for wheat, r = 0.116 for maize and r = 0.504 for sunflower. In the South Eastern Dobrogea, the driest area in Romania, the rainfalls declined by 65% in the period 2018-2020 having a deep negative impact on sunflower seeds yield, which decreased from 4,282 kg/ha in 2018, to 1,503 kg/ha in 2020. The correlation between precipitations and sunflower yield positive and very strong (r = 0.737). As a conclusion, the climate conditions should be analyzed in each farm and farmers have to take measure to adapt the technologies for sustaining production. [ABSTRACT FROM AUTHOR]

This paper analyzed the variations of two air temperature indices, diurnal temperature range (DTR) and annual temperature range (ATR), calculated based on observations at the Zagreb Grič Observatory over a period of 133 years (1887–2019). In intense climate changes strongly manifested by the increased air temperature, these two climate indices were determined to significantly impact human health and the environment. This effect is especially evident in urban areas. The Zagreb Grič Observatory is located in the center of Zagreb and has not changed its location during the observed period. It has a long homogeneous series of climatological observations, enabling a detailed study of climate variation in the city, which is strongly influenced by various urbanization processes. In 133 years, both of the analyzed indicators showed a statistically insignificant downward trend. The Rescaled Adjusted Partial Sums (RAPS) method revealed statistically significant differences in DTR's time series between three sub-periods: 1887–1953, 1954–1989, and 1990–2019. The time series of ATR during 133 years behaved statistically differently in four sub-periods: 1887–1905; 1906–1926; 1927–1964; and 1965–2019. The analysis of monthly values of DTR showed that the DTR values are the highest in the warm part of the year, from May to August, when they are twice as high as those during the cold period from November to December. With an increase in precipitation, the DTR values decrease, while they increase as the mean annual temperature increases. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) plays a crucial role in the climate change of China as well as global climate change. It is therefore of great practical significance to study vegetation and its dynamic changes for regional ecological protection. The combination of a dry climate and notable temperature disparities can lead to intricate effects on the region's vegetation. However, there are few studies exploring the complex effects of diurnal temperature variations on vegetation growth that differ from the effects of mean temperature on the TP, especially under different frozen ground types. Based on the long-time series maximum temperature (Tmax), minimum temperature (Tmin), and Normalized Difference Vegetation Index (NDVI) of the TP, we conducted a comparative study of the warming effects on plant growth under different frozen types. The results exhibit that it warms up faster at night (0.223 °C de−1; p < 0.01) than during the day (0.06 °C de−1; p < 0.01), resulting in a significant decrease in the temperature difference between day and night (−0.078 °C de−1; p < 0.01) in the past few decades. The principal finding of this paper is that Tmin is the dominant temperature indicator for vegetation growth on the TP, which dominates 63.3% of the area for NDVI and 61.4% of the area for GPP, respectively. The results further identify a stronger correlation between air temperature and vegetation growth in seasonal frozen grounds (R = 0.68, p < 0.01) and permafrost regions (R = 0.7, p < 0.01) compared to unfrozen grounds (R = 0.58, p < 0.01). Moreover, the physiological mechanism underlying the asymmetric influence of Tmin and Tmax on vegetation growth is further elucidated in this study. Given that future climate changes are expected to exacerbate these changes, it is imperative to explore additional avenues in pursuit of potential mechanisms that can offer adaptive strategies for safeguarding the ecology of the TP. [ABSTRACT FROM AUTHOR]

The influences of human activity on regional climate over China have been widely reported and drawn great attention from both the scientific community and governments. This paper reviews the evidence of the anthropogenic influence on regional climate over China from the perspectives of surface air temperature (SAT), precipitation, droughts, and surface wind speed, based on studies published since 2018. The reviewed evidence indicates that human activities, including greenhouse gas and anthropogenic aerosol emissions, land use and cover change, urbanization, and anthropogenic heat release, have contributed to changes in the SAT trend and the likelihood of regional record-breaking extreme high/low temperature events over China. The anthropogenically forced SAT signal can be detected back to the 1870s in the southeastern Tibetan Plateau region. Although the anthropogenic signal of summer precipitation over China is detectable and anthropogenic forcing has contributed to an increased likelihood of regional record-breaking heavy/low precipitation events, the anthropogenic precipitation signal over China is relatively obscure. Moreover, human activities have also contributed to a decline in surface wind speed, weakening of monsoon precipitation, and an increase in the frequency of droughts and compound extreme climate/weather events over China in recent decades. This review can serve as a reference both for further understanding the causes of regional climate changes over China and for sound decision-making on regional climate mitigation and adaptation. Additionally, a few key or challenging scientific issues associated with the human influence on regional climate changes are discussed in the context of future research. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) vegetation plays an important role in the local ecosystem, which responds significantly to climate change and can affect local and large-scale weather and climate anomalies. However, little attention has been paid to its year-to-year variation. In this paper, using two NDVI datasets (GIMMS and MODIS) originated from satellite remote sensing, the variability characteristics of NDVI over the TP on the interannual time scale and associated local climatic factors were investigated. The results show that two primary patterns of NDVI governed TP during the main growing season (June–September, JJAS) for the period 1982–2020. The first one is a uniform pattern, with a consistent spatial variation over the entire TP, and the second is a dipole pattern, with an out-of-phase spatial variation of NDVI between the northern and southern TP. Interannual variations of the different climatic factors regulate the NDVI variability over the different regions of the TP. The interannual variability of the uniform NDVI pattern is mainly affected by the two local climatic factors, the preceding May–August precipitation and simultaneous JJAS sunshine duration. Specifically, NDVIs over the southern and eastern TP have a more significant response to the preceding precipitation and simultaneous sunshine duration, respectively. The variability of the dipole NDVI pattern is primarily modulated by the preceding May–August precipitation and simultaneous surface air temperature, ground surface temperature, and sunshine duration. However, NDVIs over the northern and southern TP have different degrees of response to the four climatic factors, with the most significant response being to preceding precipitation. The combined effect of these factors contributes to the formation of the interannual variability in the uniform and dipole patterns. This paper may shed light on deeply understanding the reasons for the inconsistency in variations of vegetation over the different regions of the TP under climate change. In addition to the effect of local climatic factors that this study focuses on, the influence of external climatic factors on the variability of the TP NDVI deserves further research in the future. [ABSTRACT FROM AUTHOR]

This paper examines the long-term changes in temperature and precipitation in the karst region of Imotski, Croatia, which is of particular interest due to its abundance of karst phenomena. This study analyses temperatures and precipitation on monthly and annual scales at two climatological stations in the region, Imotski and Ričice. Linear regression, the Theil–Sen estimator (β), and the Mann–Kendall test were used to determine the trends and statistical significance. The homogeneity of the data was checked using the Standard Normal Homogeneity Test (SNHT), and the F-test and t-test were used to test the significance of the mean shift between the two subseries. Additionally, the coefficient of variability, standardized rainfall anomaly, and precipitation concentration index were employed to analyze the precipitation variability. The study found a statistically significant (p < 0.05) upward trend in the mean (β = 0.0437) and maximum (β = 0.0590) annual air temperature at the Imotski station and the mean (β = 0.0387) annual temperature at the Ričice station. The SNHT test showed a statistically significant (p < 0.05) shift in the mean annual temperatures after 2007 and maximum annual temperatures after 1998 at the Imotski station. Similarly, a statistically significant (p < 0.05) shift in the mean annual temperatures after 2011 and the maximum annual temperatures after 1998 was found at the Ričice station. A seasonal distribution of precipitation is observed at both the Ričice and Imotski stations, with a downward trend (β = −2.7693) at Ričice and an upward trend (β = 6.0575) at Imotski; however, neither trend is statistically significant (p > 0.05). An increase in the intensity of dry periods and the occurrence of extreme events was also noted. The climatological analysis, conducted for the first time in this area, is a crucial step toward understanding local climate patterns and making informed decisions toward sustainable development and adaptation strategies. [ABSTRACT FROM AUTHOR]

Since the mid-1990s, there has been a marked decrease in the sea ice extent (SIE) in the Arctic Ocean. After reaching an absolute minimum in September 2012, the seasonal variations in the SIE have settled at a new level, which is almost one-quarter lower than the average climatic norm of 1979–2022. Increased melting and accelerated ice export from marginal seas ensure an increase in the open water area, which affects the lower atmosphere and the surface layer of the ocean. Scientists are cautiously predicting a transition to a seasonally ice-free Arctic Ocean as early as the middle of this century, which is about 50 years earlier than was predicted just a few years ago. Such predictions are based on the fact that the decrease in sea ice extent and ice thinning that occurred at the beginning of this century, initially caused by an increase in air temperature, triggered an increase in the thermal and dynamic contribution of the ocean to the further reduction in the ice cover. This paper reviews published evidence of such changes and discusses possible mechanisms behind the observed regional anomalies of the Arctic Sea ice cover parameters in the last decade. [ABSTRACT FROM AUTHOR]

Meteorological drought (MDr) causes considerable economic losses in many countries, including in relation to agriculture. To examine the diversity of seasonal meteorological drought in Poland, the study uses monthly precipitation sums in the period from March to November, collected from 74 ground-based meteorological stations in 1951–2020. The paper defines meteorological drought on the basis of the standardized precipitation index in three seasons (SPI-3) and differentiates three degrees of drought intensity: extreme, severe and moderate. The study also calculates the size of Poland's area affected by meteorological drought (AAMDr) and determines the relationship between AAMDr and SPI-3. MDr in Poland occurred more frequently in spring and autumn (every 4–5 years) than in summer (every 7 years). In the areas affected by extreme drought, precipitation was below the average, mainly ≤50% of the climatic norm, and air temperature values were below or above the average of the climatic norm, mainly ranging from −1.0 to 1.0 °C. A significant negative correlation between AAMDr and SPI-3 indices was found. The obtained results could be useful for managing climatic risk and developing regional and local agriculture adaptation plans aimed at mitigating the effects of climate change. [ABSTRACT FROM AUTHOR]

As an important part of the Earth's environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way. [ABSTRACT FROM AUTHOR]

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

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]

Canada's climate is warming at a rate about double the global average, leading to potential negative impacts on public infrastructures such as jointed plain concrete pavement (JPCP). In light of this reality of changing climate, the work contained in this paper is aimed at evaluating JPCP's early-age behaviour in response to environmental conditions. HIPERPAV® software and the associated models developed by the U.S. Federal Highway Administration (FHWA) were used to identify cracking potential. A sensitivity analysis was performed to assess the effect of different levels of air temperature, mix temperature, base layer temperature, wind speed, and relative humidity. Additionally, projected extreme temperatures predicted by the Canadian Regional Climate Model (CanRCM) were used to determine the relative impact of climate change on cracking risk. The results demonstrated the increased cracking risk under changing climate in several Canadian cities by mid-century and highlighted the importance of developing a pathway forward for climate adaptation. [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 deals with peculiar features of development of the species Veronica L. in the conditions of the steppe zone of Ukraine (central part of the country). Under the action of climatic changes occurring for the last 20 years, the species began to grow 6–14 days earlier and increased the vegetation period by 15–25 days. Under the effect of extreme growing conditions (hot weather and drought) decrease in the area of the leaf blade by almost 2 times was recorded in V. prostrata and V. incana. Length and width of the leaf in V. prostrata and V. incana decreased by 20–30%, but in V. austriaca ssp. teucrium a decrease was observed for the leaf width only while its length increased by 17%. Analysis of correlation of climatic factors (air temperature, precipitation amount) to the morphometric parameters of the leaf during seasonal development showed greater dependence of their value on the air temperature, which was confirmed by the inverse correlation coefficients (r = -0.55–-0.66). In the unfavorable growing conditions, the features of formation of the underground part of species are manifested in the inhibited development of underground shoots (by 80–85%) and stimulation of branching and increase in the length of thin sucking roots (1.5 times). Studied species of the genus Veronica in the climatic conditions of the steppe zone of Ukraine go through all stages of phenological development and are marked by rather wide range of phenotypic changes in the vegetative sphere. [ABSTRACT FROM AUTHOR]

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

Due to a changing climate, likely changes to a hydrological regime are one of the primary sources of uncertainty to consider in managing water resources. In Slovakia, a decline in the country's water resources, combined with a change in the seasonality of runoff and an increase in the extremeness of floods and droughts, represents a potential threat. The objective of the paper was to explore trends in the components of the long-term hydrological balance of various river basins to detect the impacts of changing climate conditions along the Western Carpathians. The proposed method is a comparative exploratory analysis of the hydrological balance of the selected river basins. Temporal changes in the catchments' average air temperatures, precipitation, runoff, and their differences (considered as an index of the actual evapotranspiration), were estimated for 49 years of data; two non-overlapping sub-periods (25 and 24 years) in the seven river basins were also compared. This work also aims at evaluating the applicability of gridded inputs from the CarpatClim database for modelling the hydrological balance over an extended period. The results document the impact of the rising air temperature and, in part, local physiographic factors on the changes in runoff and actual catchment evapotranspiration. [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]

The main atmospheric climate parameters are important for the daily and seasonal variation of the parameters of the Comana Puddle aquariums. The anomalous variation of temperatures, precipitation and evaporation induces a fluctuation in the volume of water from the pond and the river Neajlov. Atmospheric temperature and precipitation directly affect winter phenomena and breakdown processes during the summer period, with significant effects on the agriculture, the most vulnerable domain on climate changes. In the hilly or hill area, the amount of rainfall decreases, thus influencing the water intake in these aquariums. The high warming time of the heat season leads to an increase in evaporation values, so that a water deficit is recorded in the hillside, hillside and plain areas, which also entails a loss in the volume of water in the lagoons. These seasonal fluctuations directly affect the limbic or aquatic fauna, but also the agriculture. In the cold season winter phenomena (ice bridge, ice on the shore, slopes, snowballs) and blocking water as snow, creates a deficiency in the water supply of lakes, ponds, puddles and swamps. This paper analysed the impact of climatic changes but also the possibilities of the recovery a part of the gloss of water, a gloss that existed years ago and which was greatly diminished after the work done downstream changed the hydrological balance of the area. This effect adds to the fact that climate change has made it possible for the volume of evaporation to be increased and sometimes to exceed the volume of precipitation. [ABSTRACT FROM AUTHOR]

Climate change has acquired a status of a global issue in the second half of the 20th century, nowadays becoming more and more prominent. The negative effects of climate change as manifested through natural disasters are noticeable the most in forest stands and forest ecosystems. This study covers the period from 2008 to 2017, and the data included was collected from official statistical reports. The data on the following categories was collected: average annual air temperature, average annual precipitation, average annual relative air humidity, the number of disaster events, such as insect activity, plant diseases, wildfires, or climate and geological disasters, causing damage in state forests, and the scope of such damage. The aim of this paper is to analyze the said data and to use the results to determine the influence of observed climatic elements on the incidence of damage, the scope of damage, and the damage per one disaster event in Serbian state forests. This paper is significant because it represents a pioneering attempt to synthesize the influence of temperature, precipitation, and humidity on the incidence and scope of damage in state forests resulting from insect activity, plant diseases, geophysical events, and wildfires in Serbia (excluding the Autonomous Province of Kosovo and Metohija). A non-linear dependence of the influence of climate factors on damage incidence and scope has been determined. [ABSTRACT FROM AUTHOR]

The paper presents a discussion on an opinion about the stability margin towards an emergency in local climate dynamics from the bifurcation analysis viewpoint. With this purpose we propose to attract the practice-oriented bifurcation analysis, where the conflict-of-units between notions used to understand natural evolution processes and notions used to describe desirable artificial regimes is resolved by integrating analytics on the basis of modified bifurcation diagrams. The discussion focuses on the phenomenon of interannual temperature variability, where local annual maximums and minimums are analyzed with daily details in both time and temperature coordinates. This phenomenon is considered via the probable, periodical and regulator conceptions. Advantages of the regulator conception are verified by results of processing the data of temperature meteorological observations on daily means over the last 135 years. This conception is based on the HDS-hypothesis, in accordance to which local climate dynamics is determined by the natural competition between the amplitude quantization (restricted by the temperature Hysteresis) and time quantization (caused by the Double Synchronization). Thus an alternation between three elementary processes with the same period (year) and different patterns of annual warming–cooling cycles is supposed as a typical behavior for local climate systems, and the idea on high-dynamic local climate ensembles is developed instead of the conventional opinion on quasi-static local climate norms. Mechanisms of temperature changes due to abrupt shifts (so-called change-points) of the HDS-regulator parameters are distinguished from mechanisms of temperature changes due to bifurcations. The notion of a stability margin is used as a distance to an emergency and is visualized in the parametrical space. So, in spite of the mechanisms of temperature changes with/without bifurcations are different, their conflict-free sewing becomes conceptually possible in the context of the stability margin towards emergencies determined relatively bifurcation boundaries in the parametrical space. Since the discussed dynamics is not supposed to exist in terms of the traditional estimations concerning the observed local climate changes, then we believe that the paper would be interesting for scientists in the field of bifurcation analysis as well as for scientists and specialists, activity areas of which relate to the contemporary challenges connected with climate changes. [ABSTRACT FROM AUTHOR]

The article reports on the climate impacts of anthropogenic carbon dioxide emissions. In its Fourth Assessment Report, the Intergovernmental Panel on Climate Change (IPCC) suggests that about 50 percent of a carbon dioxide increase will be removed from the atmosphere within 30 years. It is reported that the logarithmic relationship between carbon dioxide and its radiative forcing implies that the time scale at which atmospheric temperature declines will be longer.

The energy crisis caused by climate change is the most significant challenge of the 21st century. Single-objective and multi-objective optimization studies for buildings often only consider the building itself, without considering the impacts of climate change. However, in the future, energy-efficient design and appropriate operating parameters will be crucial considerations in the face of global climate change. This paper aims to discuss the impact of climate change in the humid-hot region over the past 60 years on the energy consumption of office buildings and propose countermeasures. Firstly, the meteorological data of Guangzhou from 1960 to 2020 is statistically analyzed, and four typical meteorological years and corresponding air conditioning design days are established. Secondly, Energyplus is used to simulate the building's energy consumption, and the energy consumption factors are analyzed for sensitivity using jEplus. Finally, a multi-objective optimization is performed using jEPlus + EA with the Non-dominated Sorting Genetic Algorithm (NSGA-II). The results found that climate change led to a significant increase in the duration of high outdoor temperatures during summer. Specifically, the daily dry-bulb temperature for air conditioning design increased by 0.4–0.7 °C, and due to climate change, the energy consumption of the office building increased by about 4.6 %. The main factor affecting the cooling energy consumption in summer was the indoor cooling set point (8.29%–30%), infiltration air volume (1.0%–8.6%), fresh air volume (3.2%–16.06%), the glazing solar transmission rate (1.25%–9.0%), building orientation (0%–1.43%), and relatively small influence of envelope insulation performance. The operation scheme determined by multi-objective optimization can reduce the cooling energy consumption of the building by 10.6%–16.8%, which can mitigate the rise in energy consumption resulting from climate change to a greater extent. [Display omitted] • Discuss the impact of climate change over the past 60 years on the energy consumption of office buildings. • There was a significant increase in the duration of high outdoor temperatures during the summer. • Multi-objective optimization is performed using jEPlus + EA. • Climate change caused energy consumption to increase by about 4.6 %. • Optimal solutions can reduce the cooling energy consumption of the building by 10.6%–16.8%. [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]

A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a "training" phase. Then, in an "implementation" phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the "training" phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more computationally efficient than running multiple GCM or RCM simulations. Such a large ensemble of projections permits a description of a probability density function (PDF) of future climate states rather than a small number of individual story lines within that PDF, which may not be representative of the PDF as a whole; the EPIC method largely corrects for such potential sampling biases. The method is useful for providing projections of changes in climate to users wishing to investigate the impacts and implications of climate change in a probabilistic way. A web-based tool, using the EPIC method to provide probabilistic projections of changes in daily maximum and minimum temperatures for New Zealand, has been developed and is described in this paper. [ABSTRACT FROM AUTHOR]

Climate change is widely recognized as one of the most challenging, urgent and complex problem facing humanity. There are rising interests in understanding and quantifying climate changing. We analyze the climate trend in Canada using Canadian monthly surface air temperature, which is longitudinal data in nature with long time span. Analysis of such data is challenging due to the complexity of modeling and associated computation burdens. In this paper, we divide this type of longitudinal data into time blocks, conduct multivariate regression and utilize a vine copula model to account for the dependence among the multivariate error terms. This vine copula model allows separate specification of within-block and between-block dependence structure and has great flexibility of modeling complex association structures. To release the computational burden and concentrate on the structure of interest, we construct composite likelihood functions, which leave the connecting structure between time blocks unspecified. We discuss different estimation procedures and issues regarding model selection and prediction. We explore the prediction performance of our vine copula model by extensive simulation studies. An analysis of the Canada climate dataset is provided. [ABSTRACT FROM AUTHOR]

In climate change research, accurate temperature data are often demanded. However, affected by many factors, especially solar radiation, the accuracy of environmental air temperature measurement can be greatly reduced, since there is a difference in temperature between the environmental air and the related temperature measured by the sensor accommodated inside the radiation shield. In the paper, the term “temperature error” refers to the temperature difference described above. To improve the accuracy of the temperature data, a temperature errorcorrection method is proposed. First, a computational fluid dynamics (CFD) method is adopted to quantify the temperature errors accurately. A neural network algorithm is then applied to form a universal correction equation by fitting temperature errors calculated using the CFD method. Finally, to validate the correction equation, field observation experiments are performed. The root mean square error (RMSE) and the mean absolute error (MAE) between the temperature errors obtained experimentally using a sensor inside the DTR503A shield and the corresponding temperature errors determined by using the proposed correction method are 0.043 and 0.038°C, respectively. The RMSE and MAE for the DTR13 radiation shield are 0.049 and 0.044°C, respectively. This method may reduce the error of the temperature data to 0.05°C. If the environmental factors corresponding to the temperature data can be quantified accurately, the factors influencing the temperature error can be added to the correction method continuously. The accuracy of this correction method may be furtherly improved. [ABSTRACT FROM AUTHOR]

A new data set of Night Marine Air Temperature (NMAT) is presented that builds on the HadNMAT2 data set, which was released in 2013. In a similar manner to HadNMAT2, the new data set (CLASSnmat) provides uninterpolated, monthly global values at a 5° resolution back to 1880. In addition to being extended to the end of 2019, four main developments are made in CLASSnmat: (1) the NMAT values are extracted from the most recent version of the International Comprehensive Ocean‐Atmosphere Data Set (ICOADS Release 3) and a revised method of eliminating duplicated observations is used; (2) values of NMAT are adjusted to 2m and 20m heights in addition to the 10 m height used in HadNMAT2; (3) a refinement is made to the corrections necessary during World War 2, which uses more of the NMAT observations and hence results in a more extensive spatial coverage for this period than was possible in HadNMAT2; (4) an updated gridding method is used that allows for an improved propagation of uncertainty from the individual NMAT values through to the gridded estimates. In this paper, the method used to construct CLASSnmat (version 1.0.0.0) is described. [ABSTRACT FROM AUTHOR]

Temperature observations of the upper-air atmosphere are now available for more than 40 years from both ground- and satellite-based observing systems. Recent years have seen substantial improvements in reducing long-standing discrepancies among datasets throughmajor reprocessing efforts. The advent of radio occultation (RO) observations in 2001 has led to further improvements in vertically resolved temperature measurements, enabling a detailed analysis of upper-troposphere/lower-stratosphere trends. This paper presents the current state of atmospheric temperature trends from the latest available observational records. We analyze observations from merged operational satellite measurements, radiosondes, lidars, and RO, spanning a vertical range fromthe lower troposphere to the upper stratosphere. The focus is on assessing climate trends and on identifying the degree of consistency among the observational systems. The results showa robust cooling of the stratosphere of about 1-3 K, and a robust warming of the troposphere of about 0.6-0.8K over the last four decades (1979- 2018). Consistent results are found between the satellite-based layer-average temperatures and vertically resolved radiosonde records. The overall latitude-altitude trend patterns are consistent between RO and radiosonde records. Significant warming of the troposphere is evident in the RO measurements available after 2001, with trends of 0.25-0.35K per decade. Amplified warming in the tropical upper-troposphere compared to surface trends for 2002-18 is found based on ROand radiosonde records, in approximate agreement withmoist adiabatic lapse rate theory. The consistency of trend results from the latest upper-air datasets will help to improve understanding of climate changes and their drivers. [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]

An analysis of a hydrological time-series data offers the possibility of detecting changes that have arisen due to climate change or change in land use. This paper deals with the detection of changes in the hydrological time data series. The trend analysis was applied at 58 stage-discharge gauging stations that are located throughout Slovakia, with the measurement period from 1962 to 2017. The Mann-Kendall test show a declining trends in the summer and a few rising trends in the winter in discharges. In the town of Banská Bystrica at a station on the Hron River, decades of discharges, air temperatures, and precipitation totals were analyzed. The five decades from the 1960s to the 2000s were used. The hydrological time data series were also analyzed by the Pettitt's test, which is used to detect change points. The decadal analysis at the Banská Bystrica station shows an increase in the air temperature but insignificant changes in discharges and precipitation. Pettitt's test identified many change points in the 1990s in the air temperature. [ABSTRACT FROM AUTHOR]

Individual glacier changes are still poorly documented in the Georgian Caucasus. In this paper, the change of Chalaati and Zopkhito glaciers in Georgian Caucasus has been studied between 1960 and 2014. Glacier geometries are reconstructed from archival topographic maps, Corona and Landsat images, along with modern field surveys. For the first time in the Georgian Caucasus aerial photogrammetric survey of both glacier termini was performed (2014) using a drone or Unmanned Aerial Vehicle, where high-resolution orthomosaics and digital elevation models were produced. We show that both glaciers have experienced area loss since 1960: 16.2±4.9 per cent for Chalaati Glacier and 14.6±5.1 per cent for Zopkhito Glacier with corresponding respective terminus retreat by ~675 m and ~720 m. These were accompanied by a rise in the equilibrium line altitudes of ~35 m and ~30 m, respectively. The glacier changes are a response to regional warming in surface air temperature over the last half century. We used a long-term temperature record from the town of Mestia and short-term meteorological observations at Chalaati and Zopkhito glaciers to estimate a longer-term air temperature record for both glaciers. This analysis suggests an increase in the duration of the melt season over the 54-year period, indicating the importance of summertime air temperature trends in controlling glacier loss in the Georgian Caucasus. We also observed supra-glacial debris cover increase for both glaciers over the last half century: from 6.16±6.9 per cent to 8.01±6.8 per cent for Chalaati Glacier and from 2.80±6.3 per cent to 8.53±5.7 per cent for Zopkhito Glacier. [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]

Temperature sounding microwave radiometers flown on polar-orbiting weather satellites provide a long-term, global-scale record of upper-atmosphere temperatures, beginning in late 1978 and continuing to the present. The focus of this paper is a lower-tropospheric temperature product constructed using measurements made by the Microwave Sounding Unit channel 2 and the Advanced Microwave Sounding Unit channel 5. The temperature weighting functions for these channels peak in the middle to upper troposphere. By using a weighted average of measurements made at different Earth incidence angles, the effective weighting function can be lowered so that it peaks in the lower troposphere. Previous versions of this dataset used general circulation model output to remove the effects of drifting local measurement time on the measured temperatures. This paper presents a method to optimize these adjustments using information from the satellite measurements themselves. The new method finds a global-mean land diurnal cycle that peaks later in the afternoon, leading to improved agreement between measurements made by co-orbiting satellites. The changes result in global-scale warming [global trend (70°S-80°N, 1979-2016) = 0.174°C decade−1], ~30% larger than our previous version of the dataset [global trend (70°S-80°N, 1979-2016) = 0.134°C decade−1]. This change is primarily due to the changes in the adjustment for drifting local measurement time. The new dataset shows more warming than most similar datasets constructed from satellites or radiosonde data. However, comparisons with total column water vapor over the oceans suggest that the new dataset may not show enough warming in the tropics. [ABSTRACT FROM AUTHOR]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

Urban heat island has significant impacts on buildings' energy consumption. The phenomenon is associated with increased urban air temperatures compared to the air temperature of the surrounding rural or suburban areas. The ambient air temperature growth due to climate changes and the urban heat island phenomenon are dramatically increasing the cooling demand in buildings. This is worsened by irradiation conditions, construction technologies, and subjective comfort expectations. This paper examines the impact of the urban environment on the energy demand of buildings, considering the case of two districts of the city of Rome, Italy: one is representative of a central zone, the other of a rural zone. Weather data were then used to calculate the thermal demand of a typical Italian building, ideally located in the monitored areas of the city. Standalone building with modified weather file was modeled in TRNSYS. Results show that urban heat island intensity causes an increase in cooling demand up to +33% for the urban area (+20% for the rural area) compared to the demand calculated using weather data from airportual areas. On the other hand, urban heat island intensity has a positive effect on heating demand which turns out to decrease up to -32% for the urban area (-14% for the rural area). [ABSTRACT FROM AUTHOR]

The paper presents the results of time-related changes in maximum temperatures in lakes. The analysis was carried out on the basis of 9 lakes located in the northern part of Poland. The analysis was based on daily water and air temperatures in the period 1971–2015. Mann–Kendall's and Sen's tests were applied to determine the directions and rates of change of maximum air and water temperatures. The average increase of maximum water temperature in analysed lakes was found to be 0.39 °C dec–1, while the warming trend of the maximum air temperature was 0.48 °C dec–1. Cluster analysis (CA) was used to group lakes characterised by similar changes of maximum water temperature. The first group included five lakes in which the values of the maximum temperature trends were 0.41 °C dec–1. In the second cluster the average value of maximum water temperature increase was smaller than in the first cluster (0.36 °C dec–1). Comparing the results of cluster analysis with morphometric data show that in the first cluster lakes are having a greater average depth, maximum depth and water transparency in comparison to the lakes of the second cluster. The study showed significant changes in the maximum annual water temperatures in post-glacial lakes located in Poland in the years 1971-2015. The highest rate of increase in monthly maximum water temperature was recorded in April and the lowest in January and February. The value of maximum water temperature trends was lower than annual air temperature trends. [ABSTRACT FROM AUTHOR]

Freshwater resources are of high societal relevance and understanding their past variability is vital to water management in the context of current and future climatic change. This study introduces a global gridded monthly reconstruction of runoff covering the period from 1902 to 2014. In-situ streamflow observations are used to train a machine learning algorithm that predicts monthly runoff rates based on antecedent precipitation and temperature from an atmospheric reanalysis. The accuracy of this reconstruction is assessed with cross-validation and compared with an independent set of discharge observations for large river basins. The presented dataset agrees on average better with the streamflow observations than an ensemble of 13 state-of-the art global hydrological model runoff simulations. We estimate a global long-term mean runoff of 37 419 km3 yr−1 in agreement with previous assessments. The temporal coverage of the reconstruction offers an unprecedented view on large-scale features of runoff variability also in regions with limited data coverage, making it an ideal candidate for large-scale hydro-climatic process studies, water resources assessments and for evaluating and refining existing hydrological models. The paper closes with example applications fostering the understanding of global freshwater dynamics, interannual variability, drought propagation and the response of runoff to atmospheric teleconnections. The GRUN dataset is available from the ETHZ Research Collection at https://doi.org/10.3929/ethz-b-000324386 (Ghiggi et al., 2019). [ABSTRACT FROM AUTHOR]

The article presents the biometeorological impact of thermal and humidity conditions on the human body in the Hornsund area in the southern Spitsbergen, Svalbard. This was determined based on diurnal air temperature range, the day-to-day variation in average diurnal air temperature and the average diurnal relative humidity. The temporal variability of thermal and humidity biometeorological stimuli in Hornsund was examined for the period 01.11.1978-31.12.2017. A lessening of biometeorological impact was found in the southern Spitsbergen region, including a statistically significant negative trend in strongly- and severely-felt stimuli (according to diurnal air temperature range), and in significant and severe stimuli (according to day-to-day variation in average diurnal air temperature). A non-significant positive trend was observed in the number of days of relative humidity with humid and very humid air. To analyse the spatial variability of the stimuli around the Hornsund fjord, data were used from seven year-round measuring stations for the period 01.07.2014-31.06.2015. The most unfavourable conditions were found on the Hans Glacier, on the summit of Fugleberget and inside the fjord. The paper presents the role of atmospheric circulation on thermal and humidity stimuli. In the Hornsund region, the highest probability of unfavourable sensible temperatures for humans occurring during the year was mostly in winter and early spring. This was related to the advection of air masses from the north-east sector, regardless of baric regime type. It was found that very humid air (> 85%) flowed over Hornsund for practically the entire year from the S-SW as part of both cyclonic and anti-cyclonic systems. [ABSTRACT FROM AUTHOR]

Abstract Air temperature is a significant meteorological variable that affects social activities and economic sectors. In this paper, a non-parametric and a parametric approach are used to forecast hourly air temperature up to 24 h in advance. The former is a regression model in the Functional Data Analysis framework. The nonlinear regression operator is estimated using a kernel function. The smoothing parameter is obtained by a cross-validation procedure and used for the selection of the optimal number of closest curves. The other method applied is a Seasonal Autoregressive Moving Average (SARMA) model, the order of which is determined by the Bayesian Information Criterion. The obtained forecasts are combined using weights calculated based on the forecast errors. The results show that SARMA has a better performance for the first 6 forecasted hours, after which the Non-Parametric Functional Data Analysis (NPFDA) model provides superior results. Forecast pooling improves the accuracy of the forecasts. Highlights • Functional Data Analysis and autoregressive models were used to forecast hourly air temperature up to one day in advance. • The AR model has a better performance for the first 6 forecasted hours and FDA is superior for horizons of 7 to 24 hours. • Both models showed consistently good results from May until November and inferior performance in February and March. • Linear combination of the forecasts from the two models improves the accuracy. [ABSTRACT FROM AUTHOR]

Accurate global observations from space are critical for global climate change study. However, atmospheric temperature trend derived from spaceborne microwave instruments remains a subject of debate, due mainly to the uncertainty in characterizing the long-term drift of instrument calibration. Thus, a highly stable target with a well-known microwave radiation is required to evaluate the long-term calibration stability. This paper develops a new model to simulate the lunar emission at microwave frequencies, and the model is then used for monitoring the stability of the Advanced Technology Microwave Sounder (ATMS) onboard Suomi NPP satellite. It is shown that the ATMS cold space view of lunar radiation agrees well with the model simulation during the past five years and this instrument is capable of serving the reference instrument for atmospheric temperature trending studies, and connecting the previous generation of microwave sounders from NOAA-15 to the future Joint Polar Satellite System Microwave Sounder onboard NOAA-20 satellite. [ABSTRACT FROM AUTHOR]

To address the problems and limitations identified through a comprehensive evaluation in Part I paper, several modifications are made in model inputs, treatments, and configurations and sensitivity simulations with improved model inputs and treatments are performed in this Part II paper. The use of reinitialization of meteorological variables reduces the biases and increases the spatial correlations in simulated temperature at 2-m (T2), specific humidity at 2-m (Q2), wind speed at 10-m (WS10), and precipitation (Precip). The use of a revised surface drag parameterization further reduces the biases in simulated WS10. The adjustment of only the magnitudes of anthropogenic emissions in the surface layer does not help improve overall model performance, whereas the adjustment of both the magnitudes and vertical distributions of anthropogenic emissions shows moderate to large improvement in simulated surface concentrations and column mass abundances of species in terms of domain mean performance statistics, hourly and monthly mean concentrations, and vertical profiles of concentrations at individual sites. The revised and more advanced dust emission schemes can help improve PM predictions. Using revised upper boundary conditions for O 3 significantly improves the column O 3 abundances. Using a simple SOA formation module further improves the predictions of organic carbon and PM 2.5 . The sensitivity simulation that combines all above model improvements greatly improves the overall model performance. For example, the sensitivity simulation gives the normalized mean biases (NMBs) of −6.1% to 23.8% for T2, 2.7–13.8% for Q2, 22.5–47.6% for WS10, and −9.1% to 15.6% for Precip, comparing to −9.8% to 75.6% for T2, 0.4–23.4% for Q2, 66.5–101.0% for WS10, and 11.4%–92.7% for Precip from the original simulation without those improvements. It also gives the NMBs for surface predictions of −68.2% to −3.7% for SO 2 , −73.8% to −20.6% for NO 2 , −8.8%–128.7% for O 3 , −61.4% to −26.5% for PM 2.5 , and −64.0% to 7.2% for PM 10 , comparing to −84.2% to −44.5% for SO 2 , −88.1% to −44.0% for NO 2 , −11.0%–160.3% for O 3 , −63.9% to −25.2% for PM 2.5 , and −68.9%–33.3% for PM 10 from the original simulation. The improved WRF/Chem is applied to estimate the impact of anthropogenic aerosols on regional climate and air quality in East Asia. Anthropogenic aerosols can increase cloud condensation nuclei, aerosol optical depth, cloud droplet number concentrations, and cloud optical depth. They can decrease surface net radiation, temperature at 2-m, wind speed at 10-m, planetary boundary layer height, and precipitation through various direct and indirect effects. These changes in turn lead to changes in chemical predictions in a variety of ways. [ABSTRACT FROM AUTHOR]