Search

Average monthly air temperatures in Bosnia and Herzegovina (BiH) exhibit a notable rise during summer, ranging from 0.4 to 0.8 °C per decade, while precipitation experiences a significant decrease of up to 8 mm per decade. Climate models, across various RCP scenarios, project an increase in air temperature, that is most pronounced in the summer season. Additionally, there is a projected frequency and intensity of heavy precipitation during autumn. In BiH, agricultural production faces substantial risks, including droughts, spring and autumn frosts, hail, and floods. Recent years have witnessed extreme hydrological events, notably the 2012 drought and the 2014 floods. Strategic documents highlight the critical importance of addressing floods and droughts for agriculture, as well as their implications for the environment, households, and industry. To assess the severity of extreme hydrological events and their impact on agriculture, with a specific emphasis on autumn and summer in Bosnia and Herzegovina, average and peak values of the Standardized precipitation evapotranspiration index (SPEI) were calculated separately for the periods 1961-1990 and 1991-2020, focusing on October and August. Compared to the reference climatic period the current climate is characterized by shifts between intense wet and dry periods, with very few years exhibiting stable and expected weather conditions. Identified as extremely wet and flood-prone years, SPEI2 October values for 1974 (2.42), 1996 (2.13), 2001 (2.24), and 2014 (2.05) stand out, with only one extremely dry year in 1985 (-2.21). SPEI2 August indicates extremely dry years, notably 2012 (-2.35) and 2017 (-2.25). [ABSTRACT FROM AUTHOR]

Global climate change has affected vegetation cover in alpine areas. In this paper, we analyzed the correlation between Leaf Area Index (LAI) and climate factors of the Yarlung Tsangpo River basin, and identified their contributions using the quantitative analysis method. The results show that the vegetation cover in the study area generally exhibited an increasing trend. Grassland in the middle- and high-altitude areas was the main contributing area. Temperature is the dominant climatic factor affecting the change, the effect of which increases with the rise in elevation. The influences of precipitation and radiation had obvious seasonality and regionality. The vegetation illustrated a lag response to climate drivers. With the change in the elevation band, the response time to precipitation was significantly less than that to air temperature in the low-elevation area, while the opposite trend was observed in the high-elevation area. In the future, the LAI of the watershed will show different characteristics at different time points, with the increases in the LAI in autumn and winter becoming the main factors for the future increase in the LAI. This provides a crucial basis upon which to explore hydrological and ecological processes as important components of the Third Pole region. [ABSTRACT FROM AUTHOR]

In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies. [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]

The climate change–built environment nexus is complex and intertwined. Recognizing the rising air temperatures and solar radiations owing to climate-induced global warming, it is critical to manage the increased building energy and cooling loads in the Middle East Gulf states' hot desert climates (Bwh). One of the top climate priorities is to promote climate resilience by reducing risks and enhancing adaptation options. This study aims to systematically review the existing literature to document building energy performances in and the associated adaptation measures of the Middle East Gulf states, regarding the implications of climate change. It is accomplished by answering the following questions: 'How well do we understand the effects of climate change on building energy use in hot urban deserts?' and 'What are the most appropriate adaptation strategies to reduce energy use in hot urban deserts?'. Using the Preferred Reporting Items for Systematic review and Meta-Analysis protocols (PRISMA), 17 studies on the influence of present and future weather scenarios on building performance are examined, considering variations in typology, methods, and input variables. Finally, the paper identifies the preferred methods and input variables for modelling building energy performance under predicted climatic changes. Passive design considerations are considered highly effective in mitigating and adapting to climate change implications. Thermal insulation and efficient window glazing are identified as the best-performing strategies, while the use of solar Photovoltaic (PV) is considered efficient in meeting the primary energy demands. The study's findings can assist planners and designers in projecting future climatic influences on the energy usage of existing buildings. [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]

This paper presents an analysis of the relationships between soil moisture, cloud cover, solar radiation, air temperature and humidity, and precipitation during the warm half of the year in East‐Central Europe over the years 1971–2020. The temporal and spatial variability of these meteorological elements is presented in association with the occurrence of anticyclonic blocking events over the study area. It demonstrates that changes in soil moisture in East‐Central Europe point to the combined influence of many meteorological factors resulting from the atmospheric circulation, and are an indicator of the comprehensive relationships among those factors. The main factors affecting soil water content are precipitation and evapotranspiration, which in turn depend on air humidity, cloudiness, intensity of solar radiation and air temperature. The increase in the frequency and duration of sequences of days with blocking events in East‐Central Europe has contributed to an increased probability of longer periods with soil moisture negative anomalies. [ABSTRACT FROM AUTHOR]

Separating existing historical precipitation data into solid and liquid precipitation remains a challenge in the study of climate change, extreme precipitation, and hydrological modelling. Based on historical daily air temperature and precipitation data, as well as visual observations of precipitation phase (weather phenomena records) in China mainland, this study proposed a snow‐day direct definition method (SDDM) to determine the threshold air temperature (TAT) of rainfall and snowfall, and analysed the spatial pattern and its influential factors. The main findings include: (1) the TAT based on the SDDM varied from −1.2 to 6.3°C, with a mean value of 2.8°C for the entire study region; (2) TAT was generally higher and more variable in the low‐latitude areas, and the Qinghai‐Tibet Plateau was characterized by an abnormally high average TAT of 5.2°C, almost twice as large as that of the eastern monsoon region; (3) TAT exhibited a significant positive correlation with altitude and negative correlation with precipitation and relative humidity. The results presented in this paper have potential application for studies of large‐scale snowfall climatology and climate change, weather forecasting techniques, and hydrological model parameterization in areas with complex and diverse geographical and climatic conditions. [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]

LST (Land Surface Temperature) is a significant parameter that represents the ground energy balance and plays a crucial role in understanding climate change. The LST of the Tibetan Plateau (TP) has a direct influence on the climate and environmental changes of the TP, and it also has a significant impact on global climate and atmospheric circulation. Although there are various factors that drive the spatial and temporal distribution of LST on the TP, the primary driving forces and its seasonal variations of LST are not yet well understood. The research focuses specifically on the TP region, selecting three types of LST data, using geodetector model, to analyze the driving factors affecting the spatial pattern of LST in different seasons. The results indicate that the three factors, Air Temperature (AT), Elevation (Ele), and Permafrost Thermal Stability (PTS), have a significant influence on LST throughout all seasons, whereas other variables demonstrate varying contributions to LST depending on the season. This study contributes to the understanding of the spatial variability of surface thermal conditions and the intricate relationships between their driving factors. It also emphasizes the potential changes in these relationships throughout the year. [ABSTRACT FROM AUTHOR]

İstanbul is the largest city located in the Mediterranean Basin and has a medium to high risk of climate change and future climate risks. Changes in temperature and other weather variables have had significant impacts on İstanbul. In this context, there is a need for studies on the issues of climate monitoring and climate change vulnerability to reduce the adverse impacts. The aim of this study is to investigate the temperature trends of synoptic weather station in İstanbul Atatürk Airport between 1973 and 2023 to have a general idea about how the temperature has changed over the last half-century and to establish statistically whether a trend is significant or not. The values of minimum (Tmin), maximum (Tmax) and mean (Tmean) temperature related parameters were estimated. Annual, monthly and seasonal temperature trends are also analyzed. The findings of this study indicate a significant (p < 0.001) rise in the mean air temperature (Tmean) of İstanbul over the past 51 years (1973–2023), with an annual warming trend of 0.06 °C. The strongest increasing trend in seasonal mean air temperatures has been observed in the summer season, with an increase of 0.08 °C per year. The trend analysis also shows a statistically non-significant increase in yearly average minimum temperature (Tmin) between 1973 and 2023, with a rate of 0.04 °C per year. However, the annual maximum temperature (Tmax) has shown no changes. [ABSTRACT FROM AUTHOR]

Accurately assessing cyclone intensity changes due to global warming is crucial for predicting and mitigating sequential hazards. This study develops a high-resolution, fully coupled air–sea model to investigate the impact of global warming on Supertyphoon Mangkhut (2018). A numerical sensitivity analysis is conducted using the pseudo–global warming (PGW) technique based on multiple global climate models (GCMs) from phase 6 of Coupled Model Intercomparison Project (CMIP6). Under ocean warming scenarios, the increasing average sea surface temperature (SST) by 2.26°, 2.44°, 3.45°, and 4.53°C results in reductions in the minimum sea level pressure by 9.2, 10.6, 15.7, and 19.4 hPa, respectively, compared to the original state of Typhoon Mangkhut. Rising SST increases the turbulent heat flux; to be specific, an average SST increase of 2.26°–4.53°C changes the turbulent heat flux into 177%–272% of the original value. Besides, stronger winds enhance SST cooling, including upwelling and entrainment, leading to an increase in the mixed layer depth (MLD). Tropical cyclone heat potential (TCHP) tends to be enhanced under the combined influences as the SST rises. An average increase in the SST of 2.26°, 2.44°, 3.45°, and 4.53°C leads to an increase in the TCHP of 9.94%, 9.85%, 14.67%, and 15.30%, respectively. However, future changes in atmospheric temperature and humidity will moderate typhoon intensification induced by ocean warming. Considering atmospheric conditions, the maximum wind speed decreases by approximately 10% compared to only considering ocean warming. Nevertheless, typhoon intensity is projected to strengthen under future climate change. Significance Statement: This study examines the role of global warming in typhoon intensity and the response of typhoon events to changes in the oceanic thermal structure. Sensitivity experiments considering future warming climates are conducted using a fully coupled air–sea numerical model. An average increase in sea surface temperature (SST) by 4.53°C can lead to a reduction in the minimum sea level pressure by 19.4 hPa. Ocean warming enhances oceanic mixing, potentially increasing the availability of heat energy for typhoon's development (i.e., an average increase in SST by 4.53°C leads to a 15.30% increase in heat energy). However, future changes in atmospheric temperature and humidity will moderate the intensification of typhoons induced by ocean warming. These results are expected to provide information for assessing the future changes in typhoon intensity under a warming climate, which is important for predicting and reducing sequential risks. [ABSTRACT FROM AUTHOR]

The complex meso- and microclimatic heterogeneity inherent to mountainous regions, driven by both topographic and biotic factors, and the lack of observations, poses significant challenges to using climate models to predict and understand impacts at various scales. We present here a six-year dataset (2017–2022) of continuous climatic measurements collected at five elevations from 983 m to 2705 m above sea level in the Val Mazia - Matschertal valley in the Italian Alps. The measurements include the air temperature, relative humidity, wind speed and direction, solar radiation, soil properties, precipitation, and snow height. Collected within the European Long-Term Ecological Research program (LTER), this dataset is freely available in an open access repository. The time series may be valuable for the validation of regional climate models, atmospheric exchange modelling, and providing support for hydrological models and remote sensing products in mountain environments. Additionally, our data may be useful for research on the influence of elevation on ecological processes such as vegetation growth, plant composition, and soil biology. Beyond its utility in advancing such fundamental research, meteorological monitoring data contribute to informed socio-political decisions on climate adaptation strategies, land management, and water resource planning, enhancing the safety and resilience of mountain communities and biodiversity. [ABSTRACT FROM AUTHOR]

The focus and goal of this effort are to evaluate how the regime of climatic factors has changed and how it has affected the regime of river flow. The evaluation technique is based on the utilization of long-term and intraannual observational data on air temperature, precipitation, and water discharge. In order to analyze observational data, long-term series of observed parameters were plotted and statistical analysis was used. The study's principal findings include an examination of the dynamics of average annual values of air temperature, precipitation, and water flow from 1960 to 2019. According to the evaluation, there has been a 2.0-2.5°C increase in air temperature in recent years. The analysis of a long-term series of data revealed that the trend line of average precipitation values remained virtually constant over the whole observed time. An assessment of the fluctuations in the average annual water flows of the rivers of the Surkhandarya basin over a long period of time revealed no change in the average values of water discharges, either decreasing or increasing. However, assessments of the intra-annual distribution of atmospheric precipitation and water flow have revealed that there has been a shift in maximum precipitation values from winter to spring in recent years, as well as a shift in water flow from July-August to June-July. Simultaneously, a study of river feeding types revealed that in recent years, the indicator of feeding type began to fall from 0.30, corresponding to snow-glacial feeding, to 0.10, corresponding to snow-rain feeding. The main conclusion of this work is to establish the impact of climate change on the intra-annual regime of precipitation and water flow in rivers, as well as on changes in the type of river feeding. The main factor behind these changes is an increase in air temperature. [ABSTRACT FROM AUTHOR]

Cold extremes have large impacts on human society. Understanding the physical processes dominating the changes in cold extremes is crucial for a reliable projection of future climate change. The observed cold extremes have decreased during the last several decades, and this trend will continue under future global warming. Here, we quantitatively identify the contributions of dynamic (changes in large-scale atmospheric circulation) and thermodynamic (rising temperatures resulting from global warming) effects to East Asian cold extremes in the past several decades and in a future warm climate by using two sets of large-ensemble simulations of climate models. We show that the dynamic component accounts for over 80 % of the cold-month (coldest 5 % boreal winter months) surface air temperature (SAT) anomaly over the past 5 decades. However, in a future warm climate, the thermodynamic change is the main contributor to the decreases in the intensity and occurrence probability of East Asian cold extremes, while the dynamic change is also contributive. The intensity of East Asian cold extremes will decrease by around 5 °C at the end of the 21st century, in which the thermodynamic (dynamic) change contributes approximately 75 % (25 %). The present-day (1986–2005) East Asian cold extremes will almost never occur after around 2035, and this will happen 10 years later due solely to thermodynamic change. The upward trend of a positive Arctic Oscillation-like sea level pressure pattern dominates the changes in the dynamic component. The finding provides a useful reference for policymakers in climate change adaptation activities. [ABSTRACT FROM AUTHOR]

Here, we introduce the concept of "outdoor days" to describe how climate change can affect quality of life for different communities and individuals. An outdoor day is characterized by moderate temperature, neither too cold nor too hot, allowing most people to enjoy outdoor activities. The number of "outdoor days" is a nonlinear function of the daily surface air temperature. If the latter falls within a specific range describing assumed thermal comfort conditions, then we assign that day as an "outdoor day." Using this function, we describe climate change impacts on temperature differently, compared to other studies which often describe these impacts in terms of the linear averaging of daily surface air temperature. The introduction of this new concept offers another way for communicating how climate change may impact the quality of life for individuals who usually plan their outdoor activities based on how local weather conditions compare to their preferred levels of thermal comfort. Based on our analysis of regional variations in "outdoor days," we present observational and modeling evidence of a north–south disparity in climate change impacts. Under high-emission scenarios, CMIP5 and CMIP6 models project fewer "outdoor days" for people living in developing countries, primarily located in low-latitude regions. Meanwhile, developed countries in mid- and high-latitude regions could gain more "outdoor days," redistributed across seasons. Significance Statement: We introduce a novel concept: outdoor days, characterizing surface air temperature conditions that allow for outdoor activities, such as walking, jogging, and cycling, by most people. We project that under high-emission scenarios of anthropogenic greenhouse gases, a north–south disparity of climate change risk will be enhanced considerably toward the end of this century due to more frequent outdoor days in the wealthy Global North and less frequent outdoor days in the deprived Global South. [ABSTRACT FROM AUTHOR]

Several developing countries in Asia are relying on agricultural practices in which climate change is a challenging concern. The trends change in atmospheric parameters and vegetation indices are questioned and vague. Consequently, the trend variations of the environmental characteristics were introduced in the first decade of 21 century to better understand the trend changes and envisage the relationship between the atmospheric parameters and the vegetation cover. The Moderate Resolution Imaging Spectroradiometer and the Atmospheric Infrared Sounder provide several atmospheric parameters, e.g., Air Temperature, Aerosol Optical Depth (AOD), and Carbon Dioxide (CO2). In addition, NDVI was estimated and aimed at the role of the interactions among the atmospheric parameters based on statistical analysis. The results showed that AOD and NDVI were air temperature dependent; meanwhile, AOD, NDVI, and air temperature were exchanging and influencing one another. Furthermore, the average minimum air temperature of the region increased during this period and carbon dioxide was a time-dependant parameter that was rising at a steep slope, which may lead to environmental crises. The trend analysis outlines what policies, programs, and procedures should be used to balance the ecosystem and mitigate the climatic negative effects. The Current research strengthens on the social awareness and the international cooperation to reduce socio-economic and political harm and loss in the face of climate change. [ABSTRACT FROM AUTHOR]

During the early 21st century, the Carpathian Basin was recognised as one of the world's most important migratory area for the Common Crane, but it is not completely clear, what was its status during the late 19th and early 20th centuries. Between 1897 and 1916, a total of 1487 field observation data were published in the journal Aquila from the Carpathian Basin. Our work analysed the timing of the spring migration, how it differed between years and geographical regions, and how the temperature and geographical variables reported above influenced the timing of the migration. The results show that the migration routes of the species have changed significantly over the last century. During the study period, the migration concentrated in the eastern part of the Carpathian Basin, and was particularly rare in the Great Hungarian Plain. There was on average a two-week difference in the timing of migration between the western and eastern parts and between different years. The start and peak of migration were weeks later than today, and this change is mainly due to the effects of climate change. Geographical factors did not influence the migration of the species, whereas higher air temperatures advanced the timing of the migration. [ABSTRACT FROM AUTHOR]

East Asia is a region that is highly vulnerable to drought disasters during the spring season, as this period is critical for planting, germinating, and growing staple crops such as wheat, maize, and rice. The climate in East Asia is significantly influenced by three large-scale climate variations: the Pacific Decadal Oscillation (PDO), the El Niño–Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD) in the Pacific and Indian Oceans. In this study, the spring meteorological drought was quantified using the standardized precipitation evapotranspiration index (SPEI) for March, April, and May. Initially, coupled climate networks were established for two climate variables: sea surface temperature (SST) and SPEI. The directed links from SST to SPEI were determined based on the Granger causality test. These coupled climate networks revealed the associations between climate variations and meteorological droughts, indicating that semi-arid areas are more sensitive to these climate variations. In the spring, PDO and ENSO do not cause extreme wetness or dryness in East Asia, whereas IOD does. The remote impacts of these climate variations on SPEI can be partially explained by atmospheric circulations, where the combined effects of air temperatures, winds, and air pressure fields determine the wet/dry conditions in East Asia. [ABSTRACT FROM AUTHOR]

Soil water and soil temperature are important ecological factors and driving forces for ecosystem restoration and sustainable development, possessing great significance for climate modeling and prediction. The Hengduan Mountains in southeastern Tibet, China, are located in a climate-change-sensitive area, and the study of soil hydrothermal dynamics in this area is of great significance for local and global climatic change and water resource utilization. This study, based on the soil hydrothermal and meteorological data of the Hengduan Mountain area in Southeast Tibet, analyzes the dynamic change patterns of soil hydrothermal and meteorological factors and explores their influencing relationships. It was found that the dynamic change in soil water content affected by precipitation was "bimodal" type. Among the meteorological factors, soil water content has the strongest correlation with relative humidity. The intra-annual variation curve of soil temperature is similar to that of the atmospheric temperature, showing a "unimodal" type, and has the highest correlation with atmospheric temperature. Specifically, it takes 70 mm and 170 mm of precipitation to change the soil water content and soil temperature at the 150 cm depth. For every 20 °C change in atmospheric temperature, soil temperature above 150 cm changes by an average of 7.2 °C. [ABSTRACT FROM AUTHOR]

Macroclimate drives vegetation distributions, but fine‐scale topographic variation can generate microclimate refugia for plant persistence in unsuitable areas. However, we lack quantitative descriptions of topography‐driven microclimatic variation and how it shapes forest structure, diversity, and composition. We hypothesized that topographic variation and the presence of the forest overstory cause spatiotemporal microclimate variation affecting tree performance, causing forest structure, diversity, and composition to vary with topography and microclimate, and topography and the overstory to buffer microclimate. In a 20.2‐ha inventory plot in the North American Great Plains, we censused woody stems ≥1 cm in diameter and collected detailed topographic and microclimatic data. Across 59‐m of elevation, microclimate covaried with topography to create a sharp desiccation gradient, and topography and the overstory buffered understory microclimate. The magnitude of microclimatic variation mirrored that of regional‐scale variation: with increasing elevation, there was a decrease in soil moisture corresponding to the difference across ~2.1° of longitude along the east‐to‐west aridity gradient and an increase in air temperature corresponding to the difference across ~2.7° of latitude along the north‐to‐south gradient. More complex forest structure and higher diversity occurred in moister, less‐exposed habitats, and species occupied distinct topographic niches. Our study demonstrates how topographic and microclimatic gradients structure forests in putative climate‐change refugia, by revealing ecological processes enabling populations to be maintained during periods of unfavorable macroclimate. [ABSTRACT FROM AUTHOR]

Predictive estimates of changes in the climatological boundary of the permafrost zone as a function of the average annual air temperature in the Bolshezemelskaya tundra under various global economy scenarios until the middle of the XXI century have been obtained. The permafrost climatological boundary shift in the northeasterly direction observed in the period from 1950 to 2010 was determined from the threshold average annual air temperature. According to the adjusted scenario forecasts obtained using the climate model, it will continue in the coming decades under any global economy scenario and is an inevitable consequence of the anthropogenic influence on the climate. The study results are important for assessing the prospects and development of a long-term observation network created to monitor the permafrost state and greenhouse gas fluxes in the Russian Federation. [ABSTRACT FROM AUTHOR]

Urban heat island (UHI) mitigation and adaptation are urgent needs in a built environment, which requires us to search for sustainable solutions to limit the urban heat island effect and improve the energy efficiency of building envelopes. Among these solutions, vertical green structures (VGSs) have recently attracted significant attention for their potential to mitigate adverse effects, especially in densely built areas. This study presents a comprehensive data analysis of the microclimate of a living wall in Milan, Italy. Our aim was to evaluate this VGS's performance in mitigating temperature increases caused by the UHI effect. In the literature, similar studies are limited to shorter monitoring periods (mostly in cooling seasons) and specific orientations (mostly facing south). However, the VGS presented in this case study here faces northwest and was continuously monitored for one calendar year. During this continuous in situ monitoring campaign, air temperature data from sensors either embedded in vegetation or exposed on a bare wall were collected and analysed over a whole calendar year, which is a novelty compared to the existing literature focused on VGSs due to the long duration. The findings indicate that the studied VGS has the ability to influence the outdoor microclimate depending on the season, the precipitation events, the wall exposure, the type of vegetation, and the vegetation's phenological attributes. The analysis showed that the VGS consistently maintained cooler temperatures than the bare wall, with mean temperature differences ranging from 2.8 °C in autumn to 0.8 °C in spring through the winter. The vegetation acted as a natural insulator by reducing the air temperature during the hot summer and in early autumn, corresponding to the growing period of the vegetation. Thus, VGSs show potential to mitigate the global warming effect. These findings provide valuable insights on vegetation's capability to act as a thermal regulator for sustainable urban planning and energy-efficient building design and retrofitting. [ABSTRACT FROM AUTHOR]

Using quarterly temperature and employment data between 1990 and 2021, this paper uncovers nuanced evidence on the impact of seasonal temperature within US counties: higher winter temperature increases private sector employment growth while higher summer temperature decreases it. The impacts of higher temperature in milder seasons, fall and spring, are statistically insignificant. Moreover, the negative impact of higher summer temperature persists while the positive impact of higher temperature in the winter is more short-lived. The negative effects of a hotter summer are pervasive and persistent in many sectors: most significantly in "Construction" and "Leisure and Hospitality" but also in "Trade, Transport, and Utilities" and "Financial Activities". In contrast, the positive effects of a warmer winter are less pervasive. The employment effect of a hotter summer has been more severe in recent decades. [ABSTRACT FROM AUTHOR]

Despite efforts to mitigate climate change, annual greenhouse gas emissions continue to rise, which may lead to the global warming of our planet. Buildings' thermal energy needs are inherently linked to climate conditions. Consequently, it is crucial to evaluate how climate change affects these energy demands. Despite extensive analysis, a comprehensive assessment involving a diverse range of building types has not been consistently conducted. The primary objective of this research is to perform a coherent evaluation of the influence of climate changes, construction element properties, and the Heating, Ventilation, and Air Conditioning (HVAC) system type of control on the energy requirements of six buildings (residential, services, and commercial). The buildings are considered to be located in a temperate Mediterranean climate. Our focus is on the year 2070, considering three distinct climatic scenarios: (i) maintaining the current climate without further changes, (ii) moderate climate changes, and (iii) extreme climate changes. The buildings are distributed across three different locations, each characterized by unique climatic conditions. Buildings' envelope features a traditional External Thermal Insulation Composite System (ETICS) and expanded polystyrene (EPS) serves as thermal insulation material. Two critical design factors are explored: EPS thickness ranging from 0 (no insulation) to 12 cm; and horizontal external fixed shading elements varying lengths from 0 (absence) to 150 cm. Six alternative setpoint ranges are assessed for the HVAC system control: three based on the Predicted Mean Vote (PMV) and three based on indoor air temperature (Tair). Results were obtained with a validated in-home software tool. They show that, even under extreme climate conditions, the application of thermal insulation remains energetically favorable; however, its relative importance diminishes as climate severity increases. Then, proper insulation design remains important for energy efficiency. The use of external shading elements for glazing (e.g., overhangs, louvers) proves beneficial in specific cases. As climate changes intensify, the significance of shading elements grows. Thus, strategic placement and design are necessary for good results. The HVAC system's energy consumption depends on the level of thermal comfort requirements, on the climate characteristics, and on the building's type of use. As climate change severity intensifies, energy demands for cooling increase, whereas energy needs for heating decrease. However, it is essential to recognize that the impact of climate changes on HVAC system energy consumption significantly depends on the type of building. [ABSTRACT FROM AUTHOR]

Introduction: Root hairs increase the surface area of a plant's root system that is in contact with the soil, thus facilitating plant water and nutrient uptake. However, little is known about the characteristics of the root hairs of herbaceous and woody plants and their specific response patterns to biotic and abiotic variables from the perspective of resource acquisition strategies in the context of global change. Methods: Here, we analyzed 74 published case studies with 1074 observations of root hair traits to identify patterns of root hair length, density and diameter in relation to soil (e.g., soil pH, nutrient levels), growing environments (e.g., greenhouse, field) and climatic factors (e.g., air temperature), as well as genome size and plant age. Results: Root hairs were longer, denser and thicker in woody plants compared with herbaceous plants, and the length and diameter of root hairs in herbaceous plants increased with genome size. With increasing plant age, woody plants had significantly longer and thicker root hairs, while root hair density and diameter declined significantly for herbaceous plants. Soil-cultured plants had longer root hairs than solution-cultured plants. The length and density of root hairs were greater in greenhouse-cultured plants than in field-grown plants, and the latter had thicker root hairs than the former. As soil pH increased, root hair length increased but diameter decreased in woody plants, while root hair density increased in herbaceous plants. Increased soil total nitrogen (N) and potassium (K) significantly increased root hair length, density and diameter in herbaceous plants, while soil total N significantly decreased root hair density in woody plants. Root hair length increased significantly, while root hair density decreased significantly, with higher mean annual temperature and greater precipitation seasonality, while the opposite pattern was true for a wider annual temperature range. Discussion: Our findings emphasize the life-form-specific responses of root hairs to soil and climatic variables. These findings will help deepen our understanding of resource acquisition strategies and their mechanisms in different plant forms under global climate change. [ABSTRACT FROM AUTHOR]

An accurate simulation and projection of future warming are needed for a proper policy response to expected climate change. We examine the simulations of the mean global and Arctic surface air temperatures by the CMIP6 (Climate Models Intercomparison Project phase 6) climate models. Most models overestimate the observed mean global warming. Only seven out of 19 models considered simulate global warming that is within ±15% of the observed warming between the average of the 2014–2023 and 1961–1990 reference period. Ten models overestimate global warming by more than 15% and only one of the models underestimates it by more than 15%. Arctic warming is simulated by the CMIP6 climate models much better than the mean global warming. The reason is an equal spread of over and underestimates of Arctic warming by the models, while most of the models overestimate the mean global warming. Eight models are within ±15% of the observed Arctic warming. Only three models are accurate within ±15% for both mean global and Arctic temperature simulations. [ABSTRACT FROM AUTHOR]

The research on the trends of mountainous aridity and the issue of elevation‐dependent aridity (EDA) has long been hindered by limitations in data validity. In this study, we present global monthly merged data sets of Vapor Pressure Deficit and Aridity Index (AI) from 1960 to 2020, aiming to detect and attribute elevation‐dependent patterns of atmospheric and soil aridity in six representative high mountainous areas worldwide. Our findings reveal that most of the mountainous regions experienced significant aridification after the 1970s (p < 0.05). The Rocky Mountains and Ethiopian Highlands are identified as the most vulnerable areas, with both atmospheric and soil aridity increasing by 13% across all elevation gradients. Significant humidification has been observed only in High Asian Regions at 4,000 m above sea level with an approximate decrease of 11% in soil AI. In both temporal and spatial patterns, soil aridity exhibits stronger heterogeneity compared to atmospheric aridity, with certain regions and seasons showing humidification, despite the overall aridification trend. Elevation‐dependent aridity is observed in two‐thirds of the mountains, but whether high altitude alleviates or amplifies aridity depends on the pattern of precipitation changes at different elevations. The rise in air temperature is the primary driving factor for soil and atmospheric aridification, contributing to over 50% of each. In two‐thirds of the regions, changes in precipitation exacerbate soil aridity. Simulations show that human activities are closely related to the ongoing prolonged atmospheric aridification. This study contributes to a comprehensive understanding of global mountainous aridity evolution projected under climate change. Plain Language Summary: Due to limitations in data validity, the conclusions regarding mountainous aridity changes and related elevation‐dependent aridity issues have often been contradictory. To address this issue, we generated a comprehensive data set of drought indices by integrating observed and simulated data, covering the period from 1960 to 2020. Our analysis revealed that the 1970s marked a significant turning point for aridity patterns in mountainous regions globally. Since then, except for the High Asian Regions, both soil and atmospheric aridity have exhibited a rapid increase in mountainous areas worldwide, with the most severe aridification observed in the Rocky Mountains and Ethiopian Highlands. We also identified a certain relationship between the severity of aridification and elevation gradients, although it is not a straightforward relationship where higher elevations necessarily experience more severe aridification. Importantly, our attribution analysis suggests that human activities may impact the observed atmospheric aridification in mountainous regions on a global scale. Key Points: The period from 1970 to 1980 witnessed a significant shift from humidification to aridification in most mountainous regions worldwideThe relationship between changes in precipitation and elevation gradients shapes the distinct patterns of elevation‐dependent aridityProlonged atmospheric aridification in mountainous regions may not be solely attributed to natural variability [ABSTRACT FROM AUTHOR]

While previous studies have largely focused on anthropogenic warming characterized by surface air temperature, little is known about the behaviors of human‐perceived temperature (HPT), which describe the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity and/or wind speed. Here we adopted an optimal fingerprinting method to compare seasonal mean HPTs in China with those from simulations conducted with multiple climate models participating in the Coupled Model Intercomparison Project Phase 6. We found clear anthropogenic signals in the observational records of changes in both summer and winter HPTs over the period 1971–2020. Moreover, the anthropogenic greenhouse gas influence was robustly detected, with clear separation from natural and anthropogenic aerosol forcings. The anthropogenic greenhouse gas forcing plays the dominant role (>90%) of human‐perceived warming. Urbanization effects contribute slightly and moderately to the estimated trends in summer and winter HPTs, respectively, in addition to the effects of external forcing. Plain Language Summary: Human influences have been identified in the observed warming quantified by surface air temperature (SAT), but SAT alone is inadequate as a metric for human thermal comfort. Here we focus on human‐perceived temperature (HPT), which describes the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity, and/or wind speed. We isolate anthropogenic impacts on the observed increase in summer and winter HPTs in China during 1971–2020 by comparing observations with state‐of‐the‐art climate models. Results show that the influence of anthropogenic greenhouse gas is detected, with clear separation from other external forcings such as solar and volcanic activities and anthropogenic aerosols. The human‐induced greenhouse gas increases are also found to explain most (>90%) of the observed human‐perceived warming. Along with the effects of large‐scale anthropogenic forcing, urbanization effects also have a slight to moderate influence on the estimated trends in summer and winter HPTs. Our work is an early attempt to provide quantitative evidence for the physiological impacts of anthropogenic global warming and local urbanization on human beings. Key Points: The warming is quantified by human‐perceived temperature that considers the joint effects of temperature, humidity and/or wind speedHuman influence could be robustly detected in both summer and winter human‐perceived warmingThe observed increase in human‐perceived temperature is mostly attributed to anthropogenic greenhouse gas increases [ABSTRACT FROM AUTHOR]

Climate change (CC) threatens Mediterranean viticulture. Rhizospheric microorganisms may be crucial for the adaptation of plants to CC. Our objective was to assess whether the association of two grapevine varieties with arbuscular mycorrhizal fungi (AMF) increases grapevine's resilience to environmental conditions that combine elevated atmospheric CO2, increased air temperatures, and water deficit. Tempranillo (T) and Cabernet Sauvignon (CS) plants, grafted onto R110 rootstocks, either inoculated (+M) or not (−M) with AMF, were grown in temperature-gradient greenhouses under two environmental conditions: (i) current conditions (ca. 400 ppm air CO2 concentration plus ambient air temperature, CATA) and (ii) climate change conditions predicted by the year 2100 (700 ppm of CO2 plus ambient air temperature +4 °C, CETE). From veraison to maturity, for plants of each variety, inoculation treatment and environmental conditions were also subjected to two levels of water availability: full irrigation (WW) or drought cycles (D). Therefore, the number of treatments applied to each grapevine variety was eight, resulting from the combination of two inoculation treatments (+M and −M), two environmental conditions (CATA and CETE), and two water availabilities (WW and D). In both grapevine varieties, early drought decreased leaf conductance and transpiration under both CATA and CETE conditions and more markedly in +M plants. Photosynthesis did not decrease very much, so the instantaneous water use efficiency (WUE) increased, especially in drought +M plants under CETE conditions. The increase in WUE coincided with a lower intercellular-to-atmospheric CO2 concentration ratio and reduced plant hydraulic conductance. In the long term, mycorrhization induced changes in the stomatal anatomy under water deficit and CETE conditions: density increased in T and decreased in CS, with smaller stomata in the latter. Although some responses were genotype-dependent, the interaction of the rootstock with AMF appeared to be a key factor in the acclimation of the grapevine to water deficit under both current and future CO2 and temperature conditions. [ABSTRACT FROM AUTHOR]

Climate change inevitably affects vegetation growth in the Tibetan Plateau (TP). Understanding the dynamics of vegetation phenology and the responses of vegetation phenology to climate change are crucial for evaluating the impacts of climate change on terrestrial ecosystems. Despite many relevant studies conducted in the past, there still remain research gaps concerning the dominant factors that induce changes in the start date of the vegetation growing season (SOS). In this study, the spatial and temporal variations of the SOS were investigated by using a long-term series of the Normalized Difference Vegetation Index (NDVI) spanning from 2001 to 2020, and the response of the SOS to climate change and the predominant climatic factors (air temperature, LST or precipitation) affecting the SOS were explored. The main findings were as follows: the annual mean SOS concentrated on 100 DOY–170 DOY (day of a year), with a delay from east to west. Although the SOS across the entire region exhibited an advancing trend at a rate of 0.261 days/year, there were notable differences in the advancement trends of SOS among different vegetation types. In contrast to the current advancing SOS, the trend of future SOS changes shows a delayed trend. For the impacts of climate change on the SOS, winter Tmax (maximum temperature) played the dominant role in the temporal shifting of spring phenology across the TP, and its effect on SOS was negative, meaning that an increase in winter Tmax led to an earlier SOS. Considering the different conditions required for the growth of various types of vegetation, the leading factor was different for the four vegetation types. This study contributes to the understanding of the mechanism of SOS variation in the TP. [ABSTRACT FROM AUTHOR]

The Barents Sea is experiencing large trends in sea ice decline and increasing surface temperatures while at the same time, it is a key region of weather variability in the Arctic and therefore predestined for the occurrence of surface weather extremes. In this study, we identify extreme winter seasons in the Barents Sea, based on a multivariate method, as winters with large seasonal-mean anomalies in one or several surface parameters encompassing surface temperature, precipitation, surface heat fluxes and surface net radiation. Using large-ensemble climate model data for historical (S2000) and end-of-century (S2100) projections following a RCP8.5 emission scenario, we find distinct clusters of extreme winters that are characterized by similar combinations of anomalies in these key surface weather parameters. In particular, we find that, during extreme winters, seasonal-mean anomalies in surface temperature are usually spatially extended with a maximum over sea ice in S2000 simulations, which shifts towards the continental land masses in a warmer climate, as the formation of a warm or cold air reservoir is being hampered by the increasing area of open ocean. Several extreme winters are selected for a detailed investigation of their substructure focusing on the relative importance of anomalies in the occurrence of synoptic-scale weather systems and anomalous surface boundary conditions for the formation of such seasons. Large combined anomalies in the key surface parameters result mainly from the accumulation of recurrent short-term events that are linked to distinct patterns of anomalous frequencies in cyclones, anticyclones and cold air outbreaks. While large seasonal-mean anomalies in surface air temperature can be linked to large-scale patterns facilitating the horizontal advection of relatively warmer (colder) air, which coincides with a lack (surplus) of cold air outbreaks, precipitation anomalies are characterized by local anomalies in cyclone and anticyclone frequency. Additionally, anomalous surface boundary conditions – that is sea ice concentration and sea surface temperatures – facilitate the formation of persistent anomalous surface conditions or further enhance atmospherically driven anomalies due to anomalous surface heat fluxes. In a warmer climate, we find extreme winters with similar substructures as in S2000. However, the increasing distance of the Barents Sea to the sea ice edge causes a decreasing magnitude in seasonal-mean anomalies of surface air temperatures and the atmospheric components of the surface energy balance. A decrease in the variability of both sea ice and sea surface temperatures indicates a decreasing importance in anomalous surface boundary conditions for the formation of future extreme winters in the Barents Sea, while the robust link shown for surface weather systems persists in a warmer climate. [ABSTRACT FROM AUTHOR]

A detailed understanding of snow cover and its possible feedback on climate change on the Tibetan Plateau (TP) is of great importance. However, spatiotemporal variability in snow phenology (SP) and its influencing factors on the TP remain unclear. Based on the daily gap-free snow cover product (HMRFS-TP) with 500 m resolution, this study investigated the spatiotemporal variability in snow cover days (SCDs), snow onset date (SOD), and snow end date (SED) on the TP from 2002 to 2022. A structural equation model was used to quantify the direct and indirect effects of meteorological factors, geographical location, topography, and vegetation greenness on SP. The results indicate that the spatial distribution of SP on the TP was extremely uneven and exhibited temporal heterogeneity. SP showed vertical zonality influenced by elevation (longer SCD, earlier SOD, and later SED at higher elevations). A total of 4.62 % of the TP area had a significant decrease in SCDs, at a rate of -1.74 d yr -1. The SOD of 2.34 % of the TP area showed a significant delayed trend, at a rate of 2.90 d yr -1 , while the SED of 1.52 % of the TP area had a significant advanced trend, at a rate of at -2.49 d yr -1. We also found a strong elevation dependence for the trend in SCDs (R=-0.73). Air temperature, precipitation, wind speed, and shortwave radiation can directly affect SP as well as indirectly affect it by influencing the growth of vegetation, whereas the direct effect was much greater than the indirect effect. Geographical location (latitude and longitude) and topographic conditions (elevation and slope) indirectly affected SP by modulating meteorological conditions and the growth of vegetation. Vegetation primarily influences SP by intercepting the snow and regulating the balance of the solar radiation budget. Regarding the total effect, air temperature was found to be the dominant factor. This study contributes to the understanding of snow variation in response to global warming over the past 2 decades by providing a basis for predicting future environmental and climate changes and their impacts on the TP. [ABSTRACT FROM AUTHOR]

There are few studies on the climate and glacial scale in the mountains east of the Qinghai–Tibet Plateau. So, we used glacial features to determine the range of the area's paleoglaciers and the equilibrium line altitude (ELA) of theGlA modern and paleoglaciers in the Tianchi area of the Changbai Mountains. Then, the GlaRe toolbox 2015 () was used to reconstruct the surface of the paleoglaciers. The probable air temperature during the glacial advances of the LGM was calculated by applying the P-T and LR models. The results showed the following: (1) the change in ELA is 950 m in the Tianchi area of the Changbai Mountains; (2) glacial coverage in the Tianchi area of the Changbai Mountains during the LGM period was ~27.05 km2 and the glacial volume was ~9.94 km3; and (3) the mean temperature in the Tianchi area of the Changbai Mountains during the LGM was 6.6–9.0 °C lower than today's, and was the principal factor controlling the growth of glaciers. There is a difference in the climate change in monsoon-influenced mountains during the LGM, and this difference may be related to the precipitation in the mountains. [ABSTRACT FROM AUTHOR]

The changing global climate, characterized by rising surface air temperatures, shifting precipitation patterns, and heightened occurrences of extreme weather events, is anticipated to profoundly impact the environment, economy, and society worldwide. This impact is particularly acute in African nations like Angola, where crucial sectors, such as agriculture, rely heavily on climate variability and exhibit limited adaptive capacity. Given that the majority of Angola's agriculture is rain-fed and serves as a vital source of livelihood for the populace, the country is especially vulnerable to climate change, particularly in its southern region. Climate change has caused severe damage in Angola, especially in the southern part of the country, where the worst droughts in decades have affected over 3.81 million people, resulting in food and water shortages. Between 2005 and 2017, climate-related disasters cost the country about 1.2 billion US dollars, further exacerbating the economic and social challenges faced by the population. This study presents a systematic review of the effects of climate change on agriculture in Angola, with a focus on the southern region. Employing the PRISMA2020 methodology, the review examined 431 documents from databases such as Scopus and Web Science, spanning from 1996 to 2023, with 63 meeting inclusion criteria. The review reveals a paucity of research on the short and long-term impacts of climate change on Angolan agriculture. Projections indicate a rise in temperatures and a general decrease in precipitation, with the southern region experiencing a more pronounced decline. Agricultural productivity may suffer significantly, with models suggesting a potential 7% reduction by 2050. [ABSTRACT FROM AUTHOR]

A main source of regional climate change uncertainty is the large disparity across models in simulating the atmospheric circulation response to global warming. Using the latest suite of global climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), a storyline approach is adopted to derive physically plausible scenarios of Antarctic climate change for 2070–99, according to Shared Socioeconomic Pathway SSP5-8.5. These storylines correspond to differences in the simulated amount of seasonal sea ice loss and either (i) the delay in the summertime stratospheric polar vortex (SPV) breakdown or (ii) wintertime SPV strengthening, which together constitute robust drivers of the response pattern to future climate change. Such changes combined are known to exert a strong control over the Southern Hemisphere midlatitude jet stream, which we quantify as collectively explaining up to 70% of the variance in jet response in summer and 35% in winter. For summer, the expected strengthening and displacement of the tropospheric jet stream varies between a ∼1 and 2 m s−1 increase and ∼2°–4° poleward shift, respectively, across storylines. In both seasons, a larger strengthening of the jet is correlated with less Antarctic warming. By contrast, the response in precipitation is more consistent but still strongly attenuated by large-scale dynamics. We find that an increase in high-latitude precipitation around Antarctica is more pronounced for storylines characterized by a greater poleward jet shift, particularly in summer. Our results highlight the usefulness of the storyline approach in illustrating model uncertainty and understanding the processes that determine the spread in projected Antarctic regional climate response. Significance Statement: Uncertainty in future climate predictions for the Antarctic is dominated by the unknown response of the large-scale (global) atmospheric circulation. In characterizing such uncertainty, plausible outcomes of climate response (storylines) are generated from the organization of model projections according to the amount of simulated seasonal sea ice loss and the delay in summertime breakdown/winter strengthening of the stratospheric westerly circulation (polar vortex). The intensity and location of the tropospheric jet stream is strongly dependent on both factors, which strongly influences the near-surface climate response over Antarctica. We find that the simulated amount that Antarctic air temperatures increase by in the future (to the end of the century) is intrinsically related to the projected intensification of the Southern Hemisphere tropospheric jet, varying by a factor of 2 or more across storylines for summer. Storylines with greater jet strengthening are associated with less Antarctic warming (reduced poleward advection of air masses from lower latitudes). Similar differences are found for changes in jet position, which we note has a much stronger control on mid- to high-latitude precipitation response. This includes both an enhanced wetting response around Antarctica and drying response farther equatorward, for storylines characterized by a greater poleward jet shift. [ABSTRACT FROM AUTHOR]

Understanding the topographic basis for microclimatic variation remains fundamental to predicting the site level effects of warming air temperatures. Quantifying diurnal fluctuation and seasonal extremes in relation to topography offers insight into the potential relationship between site level conditions and changes in regional climate. The present study investigated an annual understory temperature regime for 50 sites distributed across a topographically diverse area (>12 km2) comprised of mixed evergreen-deciduous woodland vegetation typical of California coastal ranges. We investigated the effect of topography and tree cover on site-to-site variation in near-surface temperatures using a combination of multiple linear regression and multivariate techniques. Sites in topographically depressed areas (e.g., valley bottoms) exhibited larger seasonal and diurnal variation. Elevation (at 10 m resolution) was found to be the primary driver of daily and seasonal variations, in addition to hillslope position, canopy cover and northness. The elevation effect on seasonal mean temperatures was inverted, reflecting large-scale cold-air pooling in the study region, with elevated minimum and mean temperature at higher elevations. Additionally, several of our sites showed considerable buffering (dampened diurnal and seasonal temperature fluctuations) compared to average regional conditions measured at an on-site weather station. Results from this study help inform efforts to extrapolate temperature records across large landscapes and have the potential to improve our ecological understanding of fine-scale seasonal climate variation in coastal range environments. [ABSTRACT FROM AUTHOR]

Primary production in the Sea of Okhotsk is largely supported by dissolved iron (dFe) transported by the Amur river, indicating the importance of dFe discharge from terrestrial environments. However, little is known about the mechanisms of dFe discharge into the Amur river, especially in terms of long-term change in dFe concentration. In the Amur river, extreme increase in dFe concentration was observed between 1995 and 1997, the cause of which remains unclear. As a cause of this iron anomaly, we considered the impact of permafrost degradation. To link the permafrost degradation to long-term variation in dFe concentration, we examined the changes in annual air temperature (Ta), accumulated temperature (AT), and net precipitation for three regions (northeast, south, and northwest) of the basin between 1960 and 2006. Ta and AT were relatively high in one out of every few years, and were especially high during 1988–1990 continuously. Net precipitation in late summer (July to September) has increased since 1977 and has stayed positive until 2006 throughout the basin. Most importantly, we found significant correlations between Ta and late summer dFe concentration with a 7-year lag (r = 0.54–0.69, p < 0.01), which indicate a close relationship between high Ta in year Y and increased late summer dFe concentration in year Y + 7. This correlation was the strongest in northeastern Amur basin where permafrost coverage is the highest. Similar 7-year lag correlation was also found between AT in the northeastern basin and late summer dFe concentration (r = 0.51, p < 0.01). Based on our findings, we propose the following hypothesis as a cause of iron anomaly. (1) Increased net precipitation since 1977 has increased soil moisture, which created suitable conditions for microbial dFe generation; (2) permafrost degradation during the warm years of 1988–1990 promoted iron bioavailability and led to the intensive dFe generation in the deeper part of the active layer; and (3) dFe took approximately 7 years to reach the rivers and extremely increased dFe concentration during 1995–1997. This is the first study to suggest the time-lagged impact of permafrost degradation on iron biogeochemistry in the Amur river basin. [ABSTRACT FROM AUTHOR]

Paleoclimatological field reconstructions are valuable for understanding hydroclimatic variability. While being similarly impactful on societies as temperature variability, hydroclimatic variability has still remained less in focus. However, reconstructing globally complete fields of climate variables lacks adequate proxy data from tropical regions like South America, limiting our understanding of past hydroclimatic changes in these areas. This study addresses this gap using low resolution climate archives, including speleothems, previously omitted from reconstructions. Speleothems record climate variations on decadal to centennial time scales and provide a rich dataset for the otherwise proxy data scarce region of tropical South America. By employing a multi-time scale Paleoclimate Data Assimilation approach, we synthesize climate proxy records and climate model simulations, capable of simulating water isotopologues in the atmosphere, to reconstruct 2000 years of South American climate. This includes surface air temperature, precipitation amount, drought index, isotopic composition of precipitation amount, and the intensity of the South American Summer Monsoon. The reconstruction reveals anomalous climate periods: a wetter and colder phase during the Little Ice Age (1500–1850 CE) and a drier, warmer period corresponding to the early Medieval Climate Anomaly (600–900 CE). However, these patterns are not uniform across the continent, with exceptions in northeastern Brazil and the Southern Cone, indicating regional variability. The anomalies are more pronounced than in previous reconstructions, but align with local proxy record studies, thus highlighting the importance of including speleothem proxies. The multi-timescale approach is essential for reconstructing multi-decadal and centennial climate variability. Despite methodological uncertainties regarding climate model biases and proxy record interpretations, this study marks a crucial first step in incorporating speleothems into climate field reconstructions, potentially enhancing insights into past hydroclimatic variability and hydroclimate projections. [ABSTRACT FROM AUTHOR]

This study investigated the spatial distribution and trend of heat stress in Vietnam using data from 68 meteorological stations between 1979 and 2018. Daily maximum wet-bulb temperature (TWmax), an indicator of heat stress, was computed based on the daily maximum air temperature (Tx) and relative humidity at 13:00 LST (RH13). The results indicate a strong positive correlation (>0.72) between daily TWmax and Tx and a weak relationship between daily TWmax and RH13. Tx and TWmax generally increased across most stations over the study period, while RH13 displayed both negative and positive trends. The heat stress thresholds for each station are defined using the 95th percentile values of TWmax during the baseline period 1979-1998. We found that most parts of Vietnam experienced an increase in heat stress days, with the interquartile range across all stations spanning from 0.8 to 4.2 days per decade. Among seasons, summer contributed the most (typically 52-80%) to the annual number of heat stress days in most sub-regions, except for the Central Highlands and the South, where spring contributed the most (44% and 41%, respectively). Overall, this study provides useful benchmark values for future research on heat stress in Vietnam. [ABSTRACT FROM AUTHOR]

In this article the influence of abiotic factors on agrophytocoenoses is considered, these are: moisture supply, rising air temperature, increasing carbon dioxide concentration, and the probability of environmental risks in particular. The degree of ecological risk has been established. Environmental risks due to the influence of climate change on agrophytocoenoses have been identified and substantiated and are: the spread of adventive and invasive plant species; loss of competitiveness of agrophytocoenosis crops relative to segetal phytobiota; increase in the number of species and distribution areas of segetal phytobiota; change in the sown area, productivity and quality of the harvest of agricultural crops; acquisition of tolerance of segetal phytobiota of agrocoenoses to herbicides and deterioration of their effectiveness under agroclimatic fluctuations. All of the above-mentioned environmental risks, which are associated with aggravation of the phytosanitary condition of crops inevitably, lead to a loss of the productivity of agrocoenoses. They lead to a decrease in the quality of the obtained plant and agricultural products as well. Along with the loss of productivity of the weedy agrocoenosis, there are environmental risks caused by the increased need for the use of plant protection products to ensure the control of the phytosanitary state of the agrocoenosis. Ensuring the reduction of environmental risks and enhancing the ecological safety of agrocoenoses is timely environmental monitoring, considering appropriate agronomic, protective, and preventive measures. These measures increase the adaptive capacity of agrocoenoses. r atmospheric levels in analyzing pertinent cases. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Field Ornithology is the property of Resilience Alliance and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change due to enhanced greenhouse effect arising as a result of human activities is considered a major global environmental threat to mankind. This study experimentally investigates and determines the heat flow in and out of the earth surface, and the impact of greenhouse effect on the heat transfer. A high voltage electric bulb was placed between two bottles; an empty bottle containing only air and the other bottle containing a mixture of baking soda and vinegar, evolving CO2. We observed that the vinegar and baking soda in the filled bottle reacted and produced carbon dioxide (CO2). This CO2 absorbs and retains more heat from the high voltage bulb than the empty bottle of normal air. We also observed that visible light passes through the glass and is absorbed by darker surfaces inside. The demonstration of this study proves that greenhouse gases like CO2 is one of major greenhouse gases that are responsible for global warming by trapping heat thereby giving a rapid rise in temperature over time because of the concomitant lower heat loss to its environment. [ABSTRACT FROM AUTHOR]

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]

The surface and air temperature gradient (TS00 − Tair) drives the development of the convective boundary layer and the occurrence of clouds and precipitation. However, its variability is still poorly understood due to the lack of high-quality observations. This study fills in this gap by investigating the diurnal to decadal variability in TS00 − Tair from 2002 to 2022 based on hourly observations collected at over 100 stations of the U.S. Climate Reference Network. It is found that TS00 − Tair reaches its maximum at noon with an average of 6.85°C over the contiguous United States, which decreases to 4.28°C when the soil moisture exceeds 30%. The daily minimum of TS00 − Tair has an average of −2.08°C, which generally occurs in the early evening but is postponed as the cloud fraction decreases. Moreover, while existing studies have used the near-surface soil temperature, such as the 5-cm soil temperature (TS05), to calculate TS05 − Tair, we find that TS00 − Tair and TS05 − Tair have opposite diurnal cycles, and their amplitudes differed drastically. The daily minimum of TS00 − Tair has a significant decreasing trend (−0.50° ± 0.007°C decade−1) from 2002 to 2022 due to Tair increasing at a higher rate than TS00 during the nighttime. The occurrence frequency of near-surface stable conditions (TS00 − Tair < 0) increases significantly, and the frequency of unstable conditions (TS00 − Tair > 0) decreases notably throughout the year except for winter. When it is stable, the magnitude of TS00 − Tair tends to decrease while the TS00 − Tair tends to increase when it is unstable, which is consistent with the drying condition caused by the precipitation deficit. This study provides the first observational evidence on how TS00 − Tair responds to warming. Significance Statement: The impact of global warming on surface-air temperature gradients is a crucial scientific issue that needs to be addressed. These gradients determine changes in cloud and precipitation, affecting water resources. However, traditional surface temperature measurements from weather stations are of high uncertainty due to direct exposure to the insolation. Satellite retrieval of surface temperature is limited by the availability of clear sky conditions, with low accuracy for temperature gradient calculations. Despite their importance, high-accuracy data of land surface temperature are still lacking. To address this issue, the U.S. Climate Reference Network (USCRN) uses infrared radiometers to continuously monitor surface temperature with high accuracy and sampling frequency. This study reports on surface-air temperature gradients at more than 100 U.S. stations, providing insight into diurnal to decadal variability over the contiguous United States. The study also highlights the significant difference between the land surface temperature–air temperature gradient and soil temperature–air temperature gradient. [ABSTRACT FROM AUTHOR]

When the notion of climate change emerged over 200 years ago, few speculated as to the impact of rising atmospheric temperatures on biological life. Tens of decades later, research clearly demonstrates that the impact of climate change on life on Earth is enormous, ongoing, and with foreseen effects lasting well into the next century. Responses to climate change have been widely documented. However, the breadth of phenotypic traits involved with evolutionary adaptation to climate change remains unclear. In addition, it is difficult to identify the genetic and/or epigenetic bases of phenotypes adaptive to climate change, in part because it often is not clear whether this change is plastic, genetic, or some combination of the two. Adaptive responses to climate-driven selection also interact with other processes driving genetic changes in general, including demography as well as selection driven by other factors. In this Special Issue, we explore the factors that will impact the overall outcome of climate change adaptation. Our contributions explain that traits involved in climate change adaptation include not only classic phenomena, such as range shifts and environmentally dependent sex determination, but also often overlooked phenomena such as social and sexual conflicts and the expression of stress hormones. We learn how climate-driven selection can be mediated via both natural and sexual selection, effectively influencing key fitness-related traits such as offspring growth and fertility as well as evolutionary potential. Finally, we explore the limits and opportunities for predicting adaptive responses to climate change. This contribution forms the basis of 10 actions that we believe will improve predictions of when and how organisms may adapt genetically to climate change. We anticipate that this Special Issue will inform novel investigations into how the effects of climate change unfold from phenotypes to genotypes, particularly as methodologies increasingly allow researchers to study selection in field experiments. [ABSTRACT FROM AUTHOR]

The temperature has been a highly discussed issue in climate change. Predicting it plays an essential role in human affairs and lives. It is a challenging task to provide an accurate prediction of air temperature because of its complex and chaotic nature. This issue has drawn attention to utilizing the advances in modelling capabilities. ARIMA is a popular model for describing the underlying stochastic structure of available data. Artificial Neural Networks (ANNs) can also be appropriate alternatives. In the literature, forecasting the temperature of Tehran using both techniques has not been presented so far. Therefore, this article focuses on modelling air temperatures in the Tehran metropolis and then forecasting for twelve months by comparing ANN with ARIMA. Particle Swarm Optimization (PSO) can help deal with complex problems. However, its potential for improving the performance of forecasting methods has been neglected in the literature. Thus, improving the accuracy of ANN using PSO is investigated as well. After evaluations, applying the seasonal ARIMA model is recommended. Moreover, the improved ANN by PSO outperforms the pure ANN in predicting air temperature. [ABSTRACT FROM AUTHOR]

Climate data matching the scales at which organisms experience climatic conditions are often missing. Yet, such data on microclimatic conditions are required to better understand climate change impacts on biodiversity and ecosystem functioning. Here we combine a network of microclimate temperature measurements across different habitats and vertical heights with a novel radiative transfer model to map daily temperatures during the vegetation period at 10 m spatial resolution across Switzerland. Our results reveal strong horizontal and vertical variability in microclimate temperature, particularly for maximum temperatures at 5 cm above the ground and within the topsoil. Compared to macroclimate conditions as measured by weather stations outside forests, diurnal air and topsoil temperature ranges inside forests were reduced by up to 3.0 and 7.8 ∘ C, respectively, while below trees outside forests, e.g. in hedges and below solitary trees, this buffering effect was 1.8 and 7.2 ∘ C, respectively. We also found that, in open grasslands, maximum temperatures at 5 cm above ground are, on average, 3.4 ∘ C warmer than those of the macroclimate, suggesting that, in such habitats, heat exposure close to the ground is often underestimated when using macroclimatic data. Spatial interpolation was achieved by using a hybrid approach based on linear mixed-effect models with input from detailed radiation estimates from radiative transfer models that account for topographic and vegetation shading, as well as other predictor variables related to the macroclimate, topography, and vegetation height. After accounting for macroclimate effects, microclimate patterns were primarily driven by radiation, with particularly strong effects on maximum temperatures. Results from spatial block cross-validation revealed predictive accuracies as measured by root mean squared errors ranging from 1.18 to 3.43 ∘ C, with minimum temperatures being predicted more accurately overall than maximum temperatures. The microclimate-mapping methodology presented here enables a biologically relevant perspective when analysing climate–species interactions, which is expected to lead to a better understanding of biotic and ecosystem responses to climate and land use change. [ABSTRACT FROM AUTHOR]

The Svalbard archipelago is particularly sensitive to climate change due to the relatively low altitude of its main ice fields and its geographical location in the higher North Atlantic, where the effect of Arctic amplification is more significant. The largest temperature increases have been observed during winter, but increasing summer temperatures, above the melting point, have led to increased glacier melt. Here, we evaluate the impact of this increased melt on the preservation of the oxygen isotope (δ18 O) signal in firn records. δ18 O is commonly used as a proxy for past atmospheric temperature reconstructions, and, when preserved, it is a crucial parameter to date and align ice cores. By comparing four different firn cores collected in 2012, 2015, 2017 and 2019 at the top of the Holtedahlfonna ice field (1100 m a.s.l.), we show a progressive deterioration of the isotope signal, and we link its degradation to the increased occurrence and intensity of melt events. Our findings indicate that, starting from 2015, there has been an escalation in melting and percolation resulting from changes in the overall atmospheric conditions. This has led to the deterioration of the climate signal preserved within the firn or ice. Our observations correspond with the model's calculations, demonstrating an increase in water percolation since 2014, potentially reaching deeper layers of the firn. Although the δ18 O signal still reflects the interannual temperature trend, more frequent melting events may in the future affect the interpretation of the isotopic signal, compromising the use of Svalbard ice cores. Our findings highlight the impact and the speed at which Arctic amplification is affecting Svalbard's cryosphere. [ABSTRACT FROM AUTHOR]

The process of climate warming significantly affects agroclimatic resources and agricultural production. We study the agroclimatic resources and their variability on the territory of the Republic of Bashkortostan (Russia). The Bashkortostan has a high agricultural potential and holds a leading position in the country in the production of grain crops, potatoes, milk, and honey. Currently, no detailed studies have been conducted for this area to assess the effects of global climate change on agro-climatic resources. World experience shows such research becomes strategically important for regions with powerful agricultural production. We used the sums of average daily air temperatures above 0 and 10 °C, the G.T. Selyaninov hydrothermal coefficient, and the Ped aridity (humidification) index as agroclimatic indicators. We used data of long-term meteorological observations of 30 meteorological stations for the period of 1961–2020. We revealed the long-term dynamics of the agroclimatic indicators and the spatial and temporal regularities in their distribution on the territory of Bashkortostan. There is a steady increase in the sums of average daily air temperatures above 0 and 10 °C. Against this background, aridity increases, which is especially manifested in the southern parts of the Republic of Bashkortostan. We assessed the impact of agroclimatic indicators on the main types of agricultural crops in the republic. We revealed that the greatest positive impact on the yield of oilseeds, cereals, and industrial crops is made by precipitation at the beginning (r = 0.50, r = 0.44, and r = 0.52, respectively) and in the middle of the growing season (r = 0.55, r = 0.76, and r = 0.51, respectively). Temperature and precipitation during the growing season have a complex effect on cereals. This is proven by correlations with HCS and the Ped index (r = 0.45 and r = −0.56, respectively). Aridity at the beginning of the growing season affects the yield of oilseeds and potatoes. This is confirmed by correlations with the Ped index (r = −0.49 and r = −0.52, respectively). In general, the aridity of the growing season has a significant impact on the yield of cereals (r = −0.57). Negative relationships have been found between the air temperature growing season and the yield of potatoes (r = −0.50) and cereals (r = −0.53). The results of the study were compared with data from the Copernicus Climate Change Service database. We identified climate trends under RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 scenarios. These scenarios should be taken into account when developing plans for the adaptation of agriculture in the Republic of Bashkortostan to changes in the regional climate. Maximum decrease in precipitation is established for the RCP 6.0 scenario. This can have an extremely negative impact on crop yields. This problem is especially relevant for the southern part of the Republic of Bashkortostan. The information presented in the study will allow for a more effective adaptation of the agricultural sector to current and future climate changes. [ABSTRACT FROM AUTHOR]