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Climate change represents one of the most pressing societal and scientific challenges of our time. While much of the current research on climate change focuses on future prediction, some of the strongest signals of warming can already be seen in Arctic and alpine areas, where temperatures are rising faster than the global average, and in the oceans, where the combination of rising temperatures and acidification due to increased CO2 concentrations has had catastrophic consequences for sensitive marine organisms inhabiting coral reefs. The scientific papers highlighted as part of this anniversary issue represent some of the most impactful advances in our understanding of the consequences of anthropogenic climate change. Here, we reflect on the legacy of these papers from the biotic perspective. [ABSTRACT FROM AUTHOR]

Tick-borne diseases are a public health issue. To predict vector tick abundance and activity, it is necessary to understand the driving factors for these variables. In this study, the activity of Ixodes ricinus was investigated in forest and meadow habitats in Germany with a focus on abiotic factors. Ixodes ricinus adults, nymphs and larvae were caught by flagging over a period of 2 years. Microclimatic and weather conditions were recorded at the collection sites. Statistical models were applied to describe correlations between abiotic factors and tick activity in univariable and multivariable analyses. Tick activity was observed in a broad range of air temperature between 3 and 28 °C, and air humidity varied between 35 and 95%. In general, tick activity of nymphs and larvae was higher in forest habitats than that in meadows. With the exception of a single specimen of Dermacentor reticulatus, all ticks were Ixodes ricinus, most of them nymphs (63.2% in 2009 and 75.2% in 2010). For the latter, a negative binomial mixed-effects model fitted best to the observed parameters. The modelling results showed an activity optimum between 20 and 23 °C for air temperature and between 13 and 15 °C for ground temperature. In univariable analyses, the collection site, month, season, ground and air temperature were significant factors for the number of ticks caught and for all life stages. In the multivariable analysis, temperature, season and habitat turned out to be key drivers. Ixodes ricinus positive for RNA of tick-borne encephalitis virus was only found at a single sampling site. The results of this study can be used in risk assessments and to parameterise predictive models. [ABSTRACT FROM AUTHOR]

This study aimed to explore the published research on the relationship between climate change and skin cancer and the implications for prevention, management and further research. Scoping review. This scoping review following JBI methodology reviewed English articles identified in searches of MEDLINE, Embase, CINAHL, Web of Science and Scopus on 14 April 2023. The screening of articles was completed by two independent reviewers. Data were extracted by a single reviewer and checked by another. A causal pathway diagram was iteratively developed throughout the review and was used to categorise the findings. The search identified 1376 papers, of which 45 were included in the final review. Nine papers reported primary research, and 36 papers were reviews, perspectives, commentaries, editorials, or essays. The papers examined climate change influencing behaviours related to ultraviolet exposure (30 papers), ambient temperature (21 papers) and air pollution (five papers) as possible risk factors; occupational, rural, and contextual factors affecting skin cancer (11 papers); and prevention and access to health care in the context of climate change (seven papers). Most papers were published in journals in subject areas other than health. This review identified ultraviolet radiation, occupation, rising temperature, individual behaviour and air pollution as possible influences on skin cancer rates. Furthermore, it highlights the complexity and uncertainties in the relationship between climate change and skin cancer and the need for further research on this relationship, including primary epidemiological research and reviews that follow recognised review guidelines and include assessment of health services and social determinants in the causal pathways of this relationship. [ABSTRACT FROM AUTHOR]

The spread of infectious diseases was further promoted due to busy cities, increased travel, and climate change, which led to outbreaks, epidemics, and even pandemics. The world experienced the severity of the 125 nm virus called the coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization (WHO) in 2019. Many investigations revealed a strong correlation between humidity and temperature relative to the kinetics of the virus's spread into the hosts. This study aimed to solve the riddle of the correlation between environmental factors and COVID-19 by applying RepOrting standards for Systematic Evidence Syntheses (ROSES) with the designed research question. Five temperature and humidity-related themes were deduced via the review processes, namely 1) The link between solar activity and pandemic outbreaks, 2) Regional area, 3) Climate and weather, 4) Relationship between temperature and humidity, and 5) the Governmental disinfection actions and guidelines. A significant relationship between solar activities and pandemic outbreaks was reported throughout the review of past studies. The grand solar minima (1450-1830) and solar minima (1975-2020) coincided with the global pandemic. Meanwhile, the cooler, lower humidity, and low wind movement environment reported higher severity of cases. Moreover, COVID-19 confirmed cases and death cases were higher in countries located within the Northern Hemisphere. The Blackbox of COVID-19 was revealed through the work conducted in this paper that the virus thrives in cooler and low-humidity environments, with emphasis on potential treatments and government measures relative to temperature and humidity. Highlights: • The coronavirus disease 2019 (COIVD-19) is spreading faster in low temperatures and humid area. • Weather and climate serve as environmental drivers in propagating COVID-19. • Solar radiation influences the spreading of COVID-19. • The correlation between weather and population as the factor in spreading of COVID-19. [ABSTRACT FROM AUTHOR]

Water bodies can offer local microclimates that have the potential to attenuate the effects of urban heat islands by reducing local temperature. This capability is shaded when the river is channelized. In such cases, the river temperature rises during hot periods, leading to negative impacts on the water quality. The main aim of this paper is to develop a local simple model to predict the temperature of the Dâmbovița River at its exit from Bucharest City, the capital of Romania. The location is chosen based on the historical critical impacts, in terms of extreme heatwaves that took place during hot summers, as well as future possible risks due to climate change. The water temperature prediction model is based on an artificial neural network that uses the Levenberg–Marquardt algorithm, due to its stability and rapid convergence capabilities. The model forecasts, with an accuracy of ±1 °C, the water temperature in an ungauged, downstream location, as a function of measured air and upstream water temperatures. The proposed model represents a first attempt to provide water managers in Bucharest City with a useful tool that will allow them to take timely measures to counteract the unwanted effects that can be generated by high water temperatures. [ABSTRACT FROM AUTHOR]

Using data from 32 European countries for nearly 244 million live births between 1969 and 2021, this paper examines the effects of temperatures on birth rates. The results show that exposure to hot days slightly reduces birth rates five to eight months later, while much stronger negative effects are observed nine to ten months after exposure to hot temperatures. Thereafter, a partial recovery is observed, with slightly increased birth rates. This study also shows that the effect of high-humidity hot days is much stronger than that of hot days with low humidity. Besides, the effect of heatwave days has been found to be more severe than that of hot days that are not preceded by other hot days. This study finds that some adaptation to heat might be expected only in the long run. [ABSTRACT FROM AUTHOR]

This paper deals with the analysis of the temperatures in a group of 36 African countries. By looking at the maximum, minimum and the range (the difference between the maximum and the minimum) and using a long memory model based on fractional integration and cointegration, we first show that all series display a long memory pattern, with a significant positive time trend in 29 countries for the maximum temperatures and in 33 for the minimum ones. Looking at the range, the estimated value for the order of integration is smaller than the one based on maximum or minimum temperatures in 17 countries. Performing fractional cointegration tests between the maximum and minimum temperatures, our results indicate that the two series cointegrate in the classical sense (i.e., with a short memory equilibrium relationship) in a group of 11 countries, and there is another group of eight countries displaying cointegration in the fractional sense. The remaining 17 countries with no evidence of cointegration are therefore at a very high risk of climate change due to the absence of long-term co-movement in their maximum and minimum temperatures. Findings in this paper are of tremendous interpretations and relevance for the analysis and climate projections in Africa. [ABSTRACT FROM AUTHOR]

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

The distribution of stations network is not uniform in Iran. The number of stations is more in densely populated areas and less around a large part of the central areas of Iran. Also, these stations have been operating for various periods. Therefore, in situ observation cannot lead to robust results and conclusions for the climate model evaluation and climate change studies. In recent years, reanalysis products have been considered as pseudo-observations, especially for climate studies and weather forecasting. The evaluation of reanalysis products is fundamental and critical because of the uncertainty due to the interpolation and to the data assimilation and forecasting models. In this paper, the reanalysis data of CFS-v2, MERRA-2, and ERA-5 climate databases are evaluated, using the data of 143 meteorological stations over the period 1991-2020. Reanalysis data are compared using Pearson's correlation coefficient (R), root mean square error (RMSE), normalized mean square error (NRMSE), Nash-Sutcliffe efficiency coefficient (NSC), bias index (BIAS), mean absolute error (MAE) and Kling-Gupta efficient (KGE), in the 6 regions representative of climate diversity in Iran. Also, the seasonal accuracy, annual trend, and probability distribution of the reanalyzed data were analyzed in comparison with the observations. The results show that CFS-v2, MERRA-2, and ERA-5 have high accuracy for estimating the temperature in Iran. In general, based on all statistical indicators and in all regions, ERA-5 is the most accurate; MERRA-2 and CFS-v2 were ranked second and third, with MAE values of 1.39, 1.71, and 2.077, respectively. In the spring, for the hot cluster (southwest), CFS-v2 data; in the summer, for the hot (southwest) and very cold (northwest) clusters, MERAA-2 data; and in autumn and winter, for the warm coastal cluster (coasts of Oman Sea and Persian Gulf), MERAA-2 data; are most accurate. In terms of annual trends, in the very cold cluster (northwest), CFS-v2 data; in the hot cluster (southwest), MERRA-2 data; and in other places, the data of ERA-5 have the closest trend to the trend of observations. [ABSTRACT FROM AUTHOR]

Results of calculations of temperature trends in the free atmosphere (troposphere and lower stratosphere) using the quantile regression apparatus are considered and analyzed. In traditional techniques used in climatology, trends are estimated by use of regression based on the least squares method. Quantile regression, in contrast to these techniques, makes it possible to estimate regression parameters for each quantile of predictand values in the quantile range from zero to one. Using quantile regression to estimate climate changes results in a detailed picture of the dependence of the climate trend on the variation range of meteorological parameters in the quantile range of these parameters from zero to one. In particular, climate trends can be estimated for meteorological parameter values close to extreme. This paper uses the global radiosonde data array from which the stations are selected if the completeness of their data meets the requirements stated. Using the radiosonde data from the selected stations, the dependences of climatic trends of temperature on isobaric surfaces on values of quantiles (so-called process diagrams), as well as vertical quantile cross sections of climate trend values, are calculated, plotted, and analyzed. For thirteen high-latitude stations in the Northern Hemisphere among the selected ones, temperature trends are estimated both using radiosonde data and based on the ERA 5/ERA 5.1 reanalyses. An analysis of the results allows one to note the nonuniform character of tropospheric warming trends in the range of quantile variation, which is more apparent in the winter season. The nonuniform (for the range of quantile variation) character of tropospheric temperature trends is due to the fact that the tropospheric warming rate in the "cold" part of the quantile range is higher than that in its "warm" part. This agrees with the results obtained previously by analysis of surface temperature trends using the quantile regression method (QRM). The nonuniform character of cooling trends in the lower stratosphere is noted for the range of quantile variations. In winter and, to a lesser extent, in spring, the rate of stratospheric cooling decreases in absolute magnitude with an increase in quantile values at some stations in northern latitudes. Moreover, for the quantiles close to 1.0, negative trends can change sign. This can be both due to incomplete data on lower stratospheric temperature, which is particularly inherent in the high-latitude regions of the Northern Hemisphere, and due to the influence of more frequently occurring sudden stratospheric warmings (SSWs) on the temperature trend structure that is detailed within the range of quantile values. In is noted that the detailed structures of climate temperature trends that are obtained on the basis of radiosonde data proved to be very similar to those obtained based on arrays of ERA 5/ERA 5.1 reanalysis. [ABSTRACT FROM AUTHOR]

Changing climate has altered the trends and variability of precipitation and temperature globally and thereby increasing the risk of natural and social disasters, especially in coastal climatic transitional zones such as the Huaihe river basin (HRB). This paper applies the Empirical Quantile Mapping (EQM) method for bias correction and systematically evaluates the performance of the 30 Global climate models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating precipitation and temperature over the Huaihe river basin (HRB) for 1979–2014. A suitable multi-model ensemble subset (BMME) is selected based on the Euclidean Distance (ED) synthetic metric. Results show that in comparison to the baseline period 1995–2014, precipitation (temperature) over HRB is projected to increase at the rate of around 15 mm/decade (0.1 °C/decade), 16 mm/decade (0.3 °C/decade), 20 mm/decade (0.5 °C/decade), and 15 mm/decade (0.6 °C/decade) for the period 2015–2100, under Shared Socioeconomic Pathways SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. In the long-term (2081–2100), the annual precipitation is projected to increase by 32%, 27%, 35%, and 26%, under the four scenarios, respectively. The temperature is projected to remain stable or slightly decrease under SSP1-2.6 (2 °C) and SSP2-4.5 (3 °C), while will keep rising and increasing by 6 °C under SSP5-8.5 and by 4 °C under SSP3-7.0 by 2100. The isotherm and isohyet are projected to shift northwest from southeastern coastal China to inland in the future, which is likely associated with the northwestward shift of the western Pacific anticyclone in summer. [ABSTRACT FROM AUTHOR]

Cellular signaling generates calcium (Ca2+) ions, which are ubiquitous secondary messengers decoded by calcium-dependent protein kinases, calcineurins, calreticulin, calmodulins (CAMs), and CAM-binding proteins. Previous studies in the model plant Arabidopsis thaliana have shown the critical roles of the CAM-BINDING PROTEIN 60 (CBP60) protein family in plant growth, stress responses, and immunity. Certain CBP60 factors can regulate plant immune responses, like pattern-triggered immunity, effector-triggered immunity, and synthesis of major plant immune-activating metabolites salicylic acid (SA) and N-hydroxypipecolic acid (NHP). Although homologous CBP60 sequences have been identified in the plant kingdom, their function and regulation in most species remain unclear. In this paper, we specifically characterized 11 members of the CBP60 family in the agriculturally important crop tomato (Solanum lycopersicum). Protein sequence analyses revealed that three CBP60 homologs have the closest amino acid identity to Arabidopsis CBP60g and SARD1, master transcription factors involved in plant immunity. Strikingly, AlphaFold deep learning–assisted prediction of protein structures highlighted close structural similarity between these tomato and Arabidopsis CBP60 homologs. Conserved domain analyses revealed that they possess CAM-binding domains and DNA-binding domains, reflecting their potential involvement in linking Ca2+ signaling and transcriptional regulation in tomato plants. In terms of their gene expression profiles under biotic (Pseudomonas syringae pv. tomato DC3000 pathogen infection) and/or abiotic stress (warming temperatures), five tomato CBP60 genes were pathogen-responsive and temperature-sensitive, reminiscent of Arabidopsis CBP60g and SARD1. Overall, we present a genome-wide identification of the CBP60 gene/protein family in tomato plants, and we provide evidence on their regulation and potential function as Ca2+-sensing transcriptional regulators. [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]

Combating global warming-related climate change demands prompt actions to reduce greenhouse gas emissions, particularly carbon dioxide. Biomass-based biofuels represent a promising alternative fossil energy source. To convert biomass into energy, numerous conversion processes are performed at high pressure and temperature conditions, and the design and dimensioning of such processes requires thermophysical property data, particularly thermal conductivity, which are not always available in the literature. In this paper, we proposed the application of Chemoinformatics methodologies to investigate the prediction of thermal conductivity for hydrocarbons and oxygenated compounds. A compilation of experimental data followed by a careful data curation were performed to establish a database. The support vector machine algorithm has been applied to the database leading to models with good predictive abilities. The support vector regression (SVR) model has then been applied to an external set of compounds, i.e. not considered during the training of models. It showed that our SVR model can be used for the prediction of thermal conductivity values for temperatures and/or compounds that are not covered experimentally in the literature. [ABSTRACT FROM AUTHOR]

Instrumental data from the pre–Industrial Revolution period are important to -understand climate change. In this paper, the observations made by the French missionary J. Amiot in present-day central Beijing during 1757–62 were processed and analyzed. The observations represent the earliest continuous dataset of meteorological records found in China that have been digitized recently. Comparisons between the Amiot annual temperature range and extreme values with modern observations showed that the observations were read at approximately 0800 and 1500 local solar time (LST) in a well-ventilated outdoor site. The daily maximum, minimum, and mean temperatures (T-max, T-min, and T-mean, respectively) during 1757–62 were determined by examining the relationship between temperature at 0800 and 1500 LST and T-max, T-min, and T-mean in modern reference series. Nearly 260 years ago, Beijing's climate was typical of an inland temperate monsoon zone with annual T-mean, annual mean T-max, and annual mean T-min being 11.5°, 17.8°, and 6.1°C, respectively; further, the temperatures did not vary considerably from the 1951–1980 temperatures, but differed evidently compared to relatively recent decades (1981–2020). The difference was larger than the magnitudes of global and regional temperature changes. Thus, climate warming since the pre–Industrial Revolution period in the urban areas of Beijing has dominantly occurred over the last four decades. Uncertainties related to the thermometer and observational conditions 260 years ago and the interpolation method used have also been discussed in this paper. [ABSTRACT FROM AUTHOR]

The Australian Institute for the Conservation of Cultural Material has published a range of resources that promote environmentally aware collection care and management practices including climate-specific Environmental Guidelines, the Sustainable Collections wiki and the Climate Adaptation resource. The Climate Adaptation resource provides access to 180 maps illustrating potential future climate scenarios for Australia in 2030 and 2090, using the two Representative Concentration Pathways RCP4.5 and RCP8.5. These maps were produced as part of research undertaken in 2019–2020 by Pagliarino and Meredith and supplement those published in volume 41 (issue 1) of the AICCM Bulletin. The release of updated climate change projections in the Sixth Assessment Report from the Intergovernmental Panel on Climate Change (IPCC) – Climate Change 2021: The Physical Science Basis – precipitated a review of the Climate Adaptation resource to confirm the continued veracity of the maps. This paper provides the results of that assessment, which confirmed the resource's ongoing accuracy and currency. In addition, the paper includes discussion of the new IPCC future climate scenarios of Shared Socioeconomic Pathways, which supersede RCP, and a summary of the state of the climate in Australia with warming, humidity, fire, weather and sea level rise investigated in more detail. [ABSTRACT FROM AUTHOR]

This paper deals with the study of stationarity and mean reversion in the temperature anomalies series in the southwestern American cone. In particular, monthly temperatures in 12 Chilean meteorological stations were studied (from the 1960's to nowadays), examining if temperature shocks are expected to remain in the long term or if they are reversible. The results clearly show a significant relationship between the latitude, climate, and the order of integration of the temperatures. The orders of integration tend to be smaller in colder southern parts, therefore impacts of climate change are expected to be more reversible. However, in northern desert areas the orders of integration are larger than 0.5, thus impacts are expected to be maintained for a longer time. [ABSTRACT FROM AUTHOR]

Climate change leads to an increase in the frequency, duration and intensity of climate risks. Rising temperatures and heat waves constitute the climatic risk that causes the most deaths in Europe. More and more economic and natural implications are also being identified. Municipalities must guarantee a fair and equitable socio-ecological transition in urban centers through adaptation. Nature-based Solutions (NbS) can facilitate this and several European cities are already applying them. However, smaller municipalities may be left behind. The literature identifies different incentives and barriers during the phases of adaptation policy making. The research objective of this paper is to determine the perception that technical and political managers have of this climate risk, the level of adaptation through NbS of the municipalities and the incentives and barriers that may arise in the Costa Brava Region. To do this this, seven public officials from different municipalities of Cap de Creus (Alt Empordà, Catalonia) have been interviewed. The analysis has been carried out with a mixed triangulation methodology. The main results indicate that the risk studied is not perceived as being of great concern. NbS are adaptation measures that are little known by municipalities but relevant measures in the adaption process. New incentives and barriers not identified in the literature have also emerged. [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]

Context: Documenting trends in the health impacts of ambient temperature is key to supporting adaptation strategies to climate change. This paper explores changes in the temperature-related mortality in 18 French urban centers between 1970 and 2015. Method: A multicentric time-series design with time-varying distributed lag nonlinear models was adopted to model the shape of the relationship and assess temporal changes in risks and impacts. Results: The general shape of the temperature-mortality relationship did not change over time, except for an increasing risk at very low percentiles and a decreasing risk at very high percentiles. The relative risk at the 99.9th percentile compared to the 50th percentile of the 1970–2015 temperature distribution decreased from 2.33 [95% confidence interval (CI): 1.95:2.79] in 1975 to 1.33 [95% CI: 1.14:1.55] in 2015. Between 1970 and 2015, 302,456 [95% CI: 292,723:311,392] deaths were attributable to non-optimal temperatures, corresponding to 5.5% [95% CI: 5.3:5.6] of total mortality. This burden decreased progressively, representing 7.2% [95% CI: 6.7:7.7] of total mortality in the 1970s to 3.4% [95% CI: 3.2:3.6] in the 2000s. However, the contribution of hot temperatures to this burden (higher than the 90th percentile) increased. Discussion: Despite the decreasing relative risk, the fraction of mortality attributable to extreme heat increased between 1970 and 2015, thus highlighting the need for proactive adaptation. [ABSTRACT FROM AUTHOR]

Heterosigma akashiwo is a golden-brown unicellular phytoflagellate with a high potential to create harmful algal blooms (HABs) and kill fish in many coastal regions worldwide, resulting in significant economic losses. Climate change and global warming have been introduced as triggers that impact the frequency and severity of H. akashiwo and other bloom-forming species in the past decades. In this review paper, the author tried to briefly discuss the morphology and taxonomy of H. akashiwo and show how environmental parameters can influence the physiology and toxicity of this species. Although the toxin production and mechanisms are still a conundrum, the proposed fish-killing mechanisms will be reviewed in the next step. [ABSTRACT FROM AUTHOR]

The use of green roof is a great choice in case of climate change mitigation and reduction of urban heat islands. Positive aspects of green roofs during winter or the whole year round balance are often overlooked. The surface of highly insulated flat roof is overcooled during the night by the long wave sky radiation. This radiative cooling increases the thermal losses that are reduced by the existence of additional layers. The green roof composition layers also have their thermal resistance, which is not usually included within the calculation of thermal resistance using the EN ISO 6946. The presence of snow on the roof can also increase the resistance. This paper analyzes the measurement results of various experimental green roof fragments in Central Europe. [ABSTRACT FROM AUTHOR]

This paper summarises an updated climate change trends analysis—developed for the period from 1 October 1864 to 30 September 2021 within the scope of a Horizon 2020-funded project to increase climate resilience in European coastal cities—for a representative site of the Lisbon Metropolitan Area (Portugal). By using long ground-based daily records of rainfall and surface temperature at the Lisboa-Geofísico climatological station, the analysis aimed to identify (i) long-term and recent climate trends in rainfall and temperature, (ii) changes in extreme rainfalls, heatwaves, and droughts, and (iii) possible effects of the coupled changes of minimum and maximum daily temperatures (Tmin and Tmax, respectively) on drought development based on the diurnal temperature range (DTR) indicator. To detect these trends and quantify their magnitude, the Mann−Kendall and Sen's slope estimator tests were implemented. The analysis of the mean annual temperatures indicated that the study area has warmed ∼1.91 °C through the 157 analysed years. Results evidenced statistically significant upward trends in both Tmin and Tmax, and in the number of Tmax heatwave days. In what concerns the extreme hydrological events, the analysis of annual maximum rainfall series and peaks-over-threshold (POT) techniques showed more frequent and intense events in recent years, reaching up to ∼120.0 mm in a single day. With regard to drought, the study proved that the characterisation based on the commonly used standardised precipitation index (SPI) might differ from that based on the standardised precipitation evapotranspiration index (SPEI), as the latter can take into account not only rainfall but also temperature, an important trigger for the development of drought. According to the SPEI index, severe and extreme drought conditions have been more frequent in the last 60 years than in any other recorded period. Finally, a decreasing DTR trend towards the present was found to influence evapotranspiration rates and thus drought characteristics. [ABSTRACT FROM AUTHOR]

Increased heat stress and sea-level rise, associated with climate change could threaten the viability of some cities by the latter part of this century. This paper reviews urban development patterns in Dubai and Abu Dhabi, in the United Arab Emirates, and concludes these cities are highly vulnerable to elevated wet-bulb temperatures and sea level rise. This is predominantly due to the focus of development along the Gulf coastline, where these issues are concentrated. In response, this paper ventures regional planning responses to adapt to these threats through decentralising populations to inland areas. [ABSTRACT FROM AUTHOR]

Due to the current situation when we observe numerous climate changes, manifested by rising air and seawater temperatures, there have been observed also, changes in recent years regarding the biology aspects of some fish species from the Romanian Black Sea coast. Trachurus mediterraneus (Steindachner, 1868) - horse mackerel, having economic importance it is necessary to observe its biology in order to develop an appropriate management required by the changes observed at the population level. This paper presents results on temporal variations of total length and weight, age composition, growth parameters and sex ratio of the Mediterranean horse mackerel from the Romanian Black Sea coast. Data were collected from commercial trap net catch and from pelagic trawl expeditions in the period 2018-2020. Significant differences were observed between the length distribution and the stations, with the specification that in 2020 individuals from classes of smaller lengths predominated compared to previous years. [ABSTRACT FROM AUTHOR]

In this paper, we examine the relationship between temperature and human conception rates and project the impacts of climate change by the mid-twenty-first century. Using complete administrative data on 6.8 million pregnancies between 1980 and 2015 in Hungary, we show that exposure to hot temperatures reduces the conception rate in the first few weeks following exposure, but a partial rebound is observed after that. We project that with absent adaptation, climate change will increase seasonal differences in conception rates and annual conception rates will decline. A change in the number of induced abortions and spontaneous fetal losses drives the decline in conception rates. The number of live births is unaffected. However, some newborns will experience a shift in the timing of conception that leads to changes in in utero temperature exposure and therefore might have further consequences. [ABSTRACT FROM AUTHOR]

The Grain for Green Project (GGP) has considerably improved the vegetation cover of the Loess Plateau, as well as changed the carbon and water coupling process of local vegetation to a certain extent. Water use efficiency (WUE) is a crucial measure for evaluating ecosystem responses to global climate change and is a key indicator of the carbon–water coupling between terrestrial ecosystems and the environment. A comprehensive understanding of the impact of vegetation reconstruction on WUE on the Loess Plateau is of great significance to the vegetation growth and contribution to sustainable of the Loess Plateau. In recent years, scholars have gained a more comprehensive understanding of the distribution and drivers of WUE on the Loess Plateau. However, through the study of carbon and water coupling in the Loess Plateau, it is found that the effects of different vegetation restoration levels on WUE are still to be studied in depth in terms of spatial and temporal heterogeneity and long timeseries. In this paper, we analyzed the trends of Normalized Difference vegetation cover (NDVI) and WUE from 2001 to 2010 and 2011 to 2020, respectively, to research at the WUE of the vegetation in this area in relation to vegetation restoration. It was found that the Loess Plateau's vegetation WUE rose from 2001 to 2020 at a rate of 0.023 g C kg−1 H2O per year, and that the increase from 2011 to 2020 was more significant than the growth from 2000 to 2010. The Loess Plateau's area with a growing trend in vegetation water use rate increased from 77.12% in 2001–2010 to 88.63% in 2011–2020, with the majority of the increased area occurring in the northeastern Inner Mongolia region. After 20 years of the reforestation project, the area where NDVI and WUE increased simultaneously accounted for 71.54% of the Loess Plateau, the area where NDVI increased but WUE decreased accounted for 10.95% of the Loess Plateau, and the area where NDVI increased but WUE decreased accounted for 7.15% of the Loess Plateau. The correlation between temperature precipitation and WUE was not significant for the whole Loess Plateau, further indicating that the increase in vegetation cover was the main reason for the increase in vegetation water efficiency. Therefore, the effect of vegetation cover on WUE should be fully considered when vegetation restoration is carried out on the Loess Plateau. [ABSTRACT FROM AUTHOR]

BACKGROUND: This paper represents, to our knowledge, the first national-level (United States) estimate of the economic impacts of vibriosis cases as exacerbated by climate change. Vibriosis is an illness contracted through food- and waterborne exposures to various Vibrio species (e.g., nonV. cholerae O1 and O139 serotypes) found in estuarine and marine environments, including within aquatic life, such as shellfish and finfish. OBJECTIVES: The objective of this study was to project climate-induced changes in vibriosis and associated economic impacts in the United States related to changes in sea surface temperatures (SSTs). METHODS: For our analysis to identify climate links to vibriosis incidence, we constructed three logistic regression models by Vibrio species, using vibriosis data sourced from the Cholera and Other Vibrio Illness Surveillance system and historical SSTs. We relied on previous estimates of the cost-per-case of vibriosis to estimate future total annual medical costs, lost income from productivity loss, and mortality-related indirect costs throughout the United States. We separately reported results for V. parahaemolyticus, V. vulnificus, V. alginolyticus, and “V. spp.,” given the different associated health burden of each. RESULTS: By 2090, increases in SST are estimated to result in a 51% increase in cases annually relative to the baseline era (centered on 1995) under Representative Concentration Pathway (RCP) 4.5, and a 108% increase under RCP8.5. The cost of these illnesses is projected to reach $5:2 billion annually under RCP4.5, and $7:3 billion annually under RCP8.5, relative to $2:2 billion in the baseline (2018 U.S. dollars), equivalent to 140% and 234% increases respectively. DISCUSSION: Vibriosis incidence is likely to increase in the United States under moderate and unmitigated climate change scenarios through increases in SST, resulting in a substantial burden of morbidity and mortality, and costing billions of dollars. These costs are mostly attributable to deaths, primarily from exposure to V. vulnificus. Evidence suggests that other factors, including sea surface salinity, may contribute to further increases in vibriosis cases in some regions of the United States and should also be investigated. [ABSTRACT FROM AUTHOR]

Converging global evidence highlights the dire consequences of climate change for human mental health and wellbeing. This paper summarises literature across relevant disciplines to provide a comprehensive narrative review of the multiple pathways through which climate change interacts with mental health and wellbeing. Climate change acts as a risk amplifier by disrupting the conditions known to support good mental health, including socioeconomic, cultural and environmental conditions, and living and working conditions. The disruptive influence of rising global temperatures and extreme weather events, such as experiencing a heatwave or water insecurity, compounds existing stressors experienced by individuals and communities. This has deleterious effects on people's mental health and is particularly acute for those groups already disadvantaged within and across countries. Awareness and experiences of escalating climate threats and climate inaction can generate understandable psychological distress; though strong emotional responses can also motivate climate action. We highlight opportunities to support individuals and communities to cope with and act on climate change. Consideration of the multiple and interconnected pathways of climate impacts and their influence on mental health determinants must inform evidence-based interventions. Appropriate action that centres climate justice can reduce the current and future mental health burden, while simultaneously improving the conditions that nurture wellbeing and equality. The presented evidence adds further weight to the need for decisive climate action by decision makers across all scales. [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]

Climate change has become a serious environmental matter of global concern. This paper attempts to verify if there is climatic change in Sub-Saharan Africa with the help of monthly station data from January 1901 to December 2020 on the mean temperatures of 48 countries of Sub-Saharan Africa. To do this, we employ fractional integration to account for the data's probable long memory feature. However, because other statistical features such as linear trends and seasonality might also be present in the data, we propose a broad framework that treats these three characteristics (long-range dependence, time trends, and seasonality) in a unified treatment. We first note that long memory is an observed feature in the data and using the original data, the time trends are found to be significant in Southern and Eastern countries, with higher coefficients being observed when the post-War II data are employed. When looking at the anomalies with respect to selected periods, long memory is found in all cases, and a higher number of trends are detected. Thus, 41 countries show significant time trends, with the values being higher again in the post WW2 sample, suggesting that industrialization might have contributed to global warming. The results also indicate some degree of heterogeneity across the African countries. • Examined mean temperatures in 48 countries through a monthly sample spanning January 1901 to December 2020. • Long memory is an observed feature in the data. • Time trends are found to be significantly positive in Southern and Eastern countries. • Higher coefficients are observed when the post-War II data are employed. • The results also indicate some degree of heterogeneity across the African countries. [ABSTRACT FROM AUTHOR]

Climatic warming may increase temperature variability, especially in winter months, leading to increased risk of early loss of cold hardiness and therefore freezing damage. In this study, changes in cold hardiness (measured based on electrolyte leakage), budbreak, and survival were used to indicate the responses of seedlings of 3 boreal broadleaf species trembling aspen ( Populus tremuloides Michx.), balsam poplar ( P. balsamifera L.), and white birch ( Betula papyrifera Marsh.) to experimental warming. Seedling responses were greater in winter (January) and spring (March) than fall (November), and were greater in trembling aspen and balsam poplar than white birch. Warming for 5 or 10 days at 16 °C day/-2 °C night with a 10-h photoperiod in winter and spring generally reduced cold hardiness. Combined with freezing temperatures in the postwarming ambient environment, this reduction increased seedling mortality and stem dieback and extended time to budbreak. Cold hardiness increased somewhat 10 days after seedlings were returned to the outdoor environment following warming in spring, when ambient temperatures were less damaging. The resistance of white birch to warming, likely because of its greater thermal requirement for budbreak and slower natural dehardening, suggests that this species is better suited to withstand increasing winter temperature variability that might occur under climate change. To improve the accuracy of phenological modelling, the effects of winter freezing on budbreak should be factored in. [ABSTRACT FROM AUTHOR]

This paper focuses on climate change in Turkey caused by energy consumption using an Autoregressive Distributed Lag and Toda-Yamamoto causality analysis. The motivation and aim are: Finding evidence of causality for the relationship between energy consumption, growing economies and climate change depending on parameters that vary over time, which are observed and argued through political implications. Temperature and precipitation are the dependent variables for climate change; energy types and Gross Domestic Product per capita are the independent variables for economic determiners. Data was collected annually from various institutions between 1980 and 2019. According to the Toda-Yamamoto test, a negative relationship is determined between renewable energy consumption and temperature in both the short and long term. The results reveal that a 1% increase in renewable energy reduces the temperature by 0.031%. The increase of renewable energy may help in decreasing temperature. Precipitation and non-renewable energy consumption have a positive relationship in both the short and long term, with a 1% increase in non-renewable energy consumption causing a 0.175% increase in precipitation, indicating a negative effect on climate change. Encouraging renewable energy consumption through government incentives can be a powerful solution to decrease the negative effects of climate change in Turkey. • This study examines the relationships between climate change and energy consumption. • It conducts an ARDL analysis and Toda-Yamamoto causality tests in a growing economy. • Renewable energy consumption has a positive effect (reduces) temperature. • Non-renewable energy consumption has a negative effect (increases) precipitation. • Renewable energy consumption is critical mitigating global warming in Turkey. [ABSTRACT FROM AUTHOR]

Excessive anthropogenic emissions of greenhouse gas have led to global climate change in recently years. Methane is an important greenhouse gas after carbon dioxide. Methane emissions increase with the global temperature, which further intensifies global warming. Soil is a huge source and sink of methane, and methanotrophic bacteria play a key role in reducing methane emissions. Exploring the effect of temperature on soil methane-oxidizing ability has been a research hotspot in recent years. This paper reviewed the effects of temperature on soil methane oxidation and methanotrophic bacteria; analyzes and compares the soil methane oxidation process and methanotrophic bacteria in various ecosystems at different temperatures, and the growth temperature range of methanotrophic bacteria strains. The results showed that various ecosystems have different temperature ranges for methane oxidation; the rate of methane oxidation increases with increasing temperature in their particular temperature ranges. When the cultivation temperature is closer to the in-situ temperature, the methane oxidation response will be faster. Similar to the effect of temperature on methane oxidation, the diversity and abundance of methanotrophic bacteria also increase with increasing temperature and are closely related to the magnitude of temperature increase and the adaptation temperature of dominant bacteria. Type II methanotrophic bacteria in the soil are more sensitive to temperature. As the temperature rises, the abundance of type II methanotrophs increases. Therefore, temperature affects the abundance and community structure of methanotrophs, thereby affecting the rate of methane oxidation and methane emissions. However, whether temperature can only change the methane oxidation capacity of the soil by regulating the replacement of dominant bacteria is still unconfirmed. This review discussed the response of methane oxidation to temperature and its microbial mechanism, in order to provides a comprehensive analysis for methane oxidation capacity under the context of future climate change. [ABSTRACT FROM AUTHOR]

This paper deals with the earliest meteorological observations in Florence after the Medici Network (1654–1670), i.e., from mid-seventeenth to mid-eighteenth century, and puts them in the context of the history of meteorology in Florence. After the gap caused by the Inquisition, observations started again in the eighteenth century, made by Cipriano Antonino Targioni (1728–1748), Giovanni Targioni-Tozzetti (1737–1740), Pietro Gaetano Grifoni (1751–1766), Leonardo Ximenes (1752), and Luca Martini (1756–1772). The first two records were lost, and this paper considers those by Grifoni and Ximenes. The latter is affected by severe bias; the former is of good quality and has been recovered and analyzed. Both the observers made only one reading a day and the metadata are scarce. The paper discusses several issues: the conversion from the apparent solar time to the Central Europe Time; the transformation from a single reading to a daily average; the identification of the thermometric liquid and the scale; the test made with the snow benchmark; the comparison with the contemporary series in Bologna. The comparison of the reconstructed series with other periods, i.e., 1654–1670, 1881–1910, 1961–1990, and 1991–2017, reveals that in mid-eighteenth century the temperature reached the lowest levels, especially in summer, and showed a sudden warming in the most recent decades. [ABSTRACT FROM AUTHOR]

A review of many studies published since the late 1920s reveals that the main driving mechanisms responsible for the early-twentieth-century Arctic warming (ETCAW) are not fully recognized. The main obstacle seems to be our limited knowledge about the climate of this period and some forcings. A deeper knowledge based on greater spatial and temporal resolution data is needed. The article provides new (or improved) knowledge about surface air temperature (SAT) conditions (including their extreme states) in the Arctic during the ETCAW. Daily and subdaily data have been used (mean daily air temperature, maximum and minimum daily temperature, and diurnal temperature range). These were taken from 10 individual years (selected from the period 1934–50) for six meteorological stations representing parts of five Arctic climatic regions. Standard SAT characteristics were analyzed (monthly, seasonal, and yearly means), as were rarely investigated aspects of SAT characteristics (e.g., number of characteristic days, day-to-day temperature variability, and the onset, end, and duration of thermal seasons). The results were compared with analogical calculations done for data taken from the contemporary Arctic warming (CAW) period (2007–16). The Arctic experienced warming between the ETCAW and the CAW. The magnitude of warming was greatest in the Pacific (2.7°C) and Canadian Arctic (1.9°C) regions. A shortening of winter and lengthening of summer were noted. Furthermore, the climate was also a little more continental (except the Russian Arctic) and less stable (greater day-to-day variability and diurnal temperature range) during the ETCAW than during the CAW. Significance Statement: It is well established that human activity (particularly increased greenhouse gas emissions) is the primary driving mechanism of the recent dramatic warming in the Arctic. However, the causes of a similar warming here in the first half of the twentieth century remain uncertain. The limited knowledge about the climate of that period—which mainly results from the low resolution of data—is a significant obstacle to a definitive determination of the forcing mechanisms. Therefore, the main aim of our paper is to improve our understanding of specific aspects of weather and climate (including extremes) using long-term series of daily and subdaily data that have rarely been applied for this purpose. This new, more comprehensive knowledge about the historical Arctic climate should allow the scientific community (particularly climate modelers) to better validate both climate models and reanalysis products and, consequently, to more precisely identify the causes of the early-twentieth-century Arctic warming. [ABSTRACT FROM AUTHOR]

Pakistan's agricultural economy is reliant on the Indus River's irrigation system, which is fed by the water coming from the great Himalayas-Karakoram Glacier Mountains. Because of hilly terrain areas, the climatic variations have an intense effect on the river flow, especially during the winter and monsoon months. Consequently, significant variations, which are observed annually, result in flooding situations in the monsoon months and reduced flows in the winter season. Thousands of people have lost their lives and massive property destruction has taken place due to disastrous floods that occurred during 2010 and 2016. Past studies have focused on proper water resources and the management of extreme events such as floods and droughts; however, modelling and forecasting based on the various climatic factors and stochastic variations are rare. This paper attempts to forecast Indus River flows using multiple linear regression (MLR), the stochastic time series, the seasonal autoregressive integrated moving average (SARIMA), and its reduced heteroscedasticity model, i.e., SARIMA-GARCH (generalized autoregressive conditional heteroscedasticity) methods at the Kalabagh station. The results show that MLR is best over the short-term; SARIMA is better over the long-term, and SARIMA-GARCH may be superior for a very long-term forecast. [ABSTRACT FROM AUTHOR]

The assessment of the impacts of climate change at different levels of global warming helps inform national and international policy discussion around mitigation targets. This paper provides consistent estimates of global and regional impacts and risks at increases in global mean temperature up to 5 °C above pre-industrial levels, for over 30 indicators representing temperature extremes and heatwaves, hydrological change, floods and droughts and proxies for impacts on crop yields. At the global scale, all the impacts that could plausibly be either adverse or beneficial are adverse, and impacts and risks increase with temperature change. For example, the global average chance of a major heatwave increases from 5% in 1981–2010 to 28% at 1.5 °C and 92% at 4 °C, of an agricultural drought increases from 9 to 24% at 1.5 °C and 61% at 4 °C, and of the 50-year return period river flood increases from 2 to 2.4% at 1.5 °C and 5.4% at 4 °C. The chance of a damaging hot spell for maize increases from 5 to 50% at 4 °C, whilst the chance for rice rises from 27 to 46%. There is considerable uncertainty around these central estimates, and impacts and risks vary between regions. Some impacts—for example heatwaves—increase rapidly as temperature increases, whilst others show more linear responses. The paper presents estimates of the risk of impacts exceeding specific targets and demonstrates that these estimates are sensitive to the thresholds used. [ABSTRACT FROM AUTHOR]

This paper studies the influence of temperature and of rainfall intensity and the effect of such variations on the treatment efficiencies and on the electrical consumptions in seven medium-large size Wastewater Treatment Plants (WWTPs) in Apulia in South Italy (Bari, Barletta, Brindisi, Lecce, Foggia, Andria and Taranto). It has been observed, in the considered WWTPs, a slight but clear increase of the incoming flow due to the increase in rainfall intensity, which results to an increase of the energy consumption per incoming volume. The impact of the climate change to the incoming flow, during the last five years (2016–2020), has been assessed indicating that an increase in rainfall intensity results to an increase of the WWTPs energy consumptions per wastewater treated volume. More specifically, for a specific WWTP (Lecce) it was found that the electrical consumption increases from 0.36 kw/m3 to 0.51 kw/m3 when the rainfall intensity was increased from 0.8 mm/min to 2.9 mm/min. Some adaption measures have been considered to upgrade the existing WWTP so to mitigate the energy increase and to limit the global effects of climate change. [Display omitted] • As Rain intensity rises, wastewater influx into WWTPs increases. • Rainfall intensity influences negatively electrical consumptions. • BOD removal is lower with increasing annual precipitations. • Temperature influences BOD, COD and SST removal efficiency. [ABSTRACT FROM AUTHOR]

Previous research has shown that we believe more in the reality of climate change when we experience warmer-than-usual temperatures. This reflects a psychological process in which easily accessible information from personal weather experiences is used as a heuristic to form climate opinions. This paper replicates and extends upon a research design and results of Egan and Mullin to provide the first systematic European study of the Local Warming Effect. Based on data from 12 European countries, the analysis shows that when objective temperatures increase by two standard deviations (5 °C) relative to normal temperatures, climate opinions are strengthened by around 0.5–1.0 percentage points – comparable to the effect of a full step to the left on a 0–10 political ideology scale. [ABSTRACT FROM AUTHOR]

The northern edge of the East Asian monsoon region is also a transition zone of temperate continental and monsoon climate, which is a sensitive zone of global climate and ecological environment change. It is an urgent problem to find out the long-term climate change rules of this region. Using 101 tree core samples obtained from 54 trees, a 343-year tree-ring width chronology of the Platycladus orientalis (L.) Franco (1673–2016) in the Wula Mountains, Inner Mongolia, China was established. The analysis shows that the radial growth of P. orientalis is closely related to hydrothermal conditions, the average minimum temperature and relative humidity are the main factors that determine the growth of P. orientalis. Based on the strong correlation between the tree-ring indices and the annual average minimum temperature (r = −0.870, p < 0.001), we reconstructed an average annual minimum temperature series from 1673 to 2016 using a linear regression equation, and the reconstructed equation can explain 75.724% of the variance, respectively. According to the data from the past 343 years, the changes in the annual average minimum temperature series had the cycles of 58.6-, 7.7-, 3.4-, 3.1-, 2.2-, and 2.1-years; the series showed three warm periods (1824–1830, 1909–1922, and 1986–2011) and 4 cold periods (1703–1712, 1731–1738, 1754–1763, and 1937–1951). The low temperature periods recorded in the reconstructed series for the 17th and 18th centuries are consistent with the Little Ice Age that occurred in the northern hemisphere, and the heating rate significantly increased at the end of the 20th century. In addition, the cold and warm periods recorded by the reconstruction result is basically consistent with the extreme climate events recorded in the historical documents of the region and the reconstruction results in other regions. In this paper, the world's first chronology of P. orientalis tree ring width was established. A historical sequence of annual average minimum temperature of 343 years was reconstructed in a typical region of the East Asian monsoon climate. It fills in the blank of reconstruction sequence and variation characteristics of mean minimum temperature in the northern edge of East Asian monsoon and transition zone of temperate continental and monsoon climate in recent four centuries. [ABSTRACT FROM AUTHOR]

This paper examines the effects of extreme temperatures on mortality rates, using random year-to-year variation in temperature based on county-level panel data from China. The analysis finds a robust, U-shaped relationship between temperature and mortality rates, indicating that extremely cold or hot temperatures lead to excess deaths. The heat-related (cold-related) effect is 3.5 times (3.2 times) as large as previous findings that used U.S. data, and it is especially large for the elderly population, mainly due to excess deaths caused by cardiovascular diseases. Applying these results to climate change predictions from Hadley Centre Global Environmental Model shows that by 2061–2080 the annual mortality rate is likely to increase by 14.2% if global greenhouse gas emissions continue to rise throughout the 21st century, the estimated health cost of which is around 0.98 trillion Chinese Yuan per year. The paper also explores households' adaptation behaviors to extreme temperatures. It finds that although urban households adaptively increase energy consumption when they are exposed to cold temperatures and purchase more air conditioners on hot and cold days, rural households are unresponsive to temperature fluctuations. This finding implies that rural people may be more resource constrained and suffer more when extreme temperatures occur. [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]

Dynamical downscaling (DD) consists in using archives of Coupled Global Climate Models (CGCM) simulations as the atmospheric and sea-surface boundary conditions (BC) to drive nested, Regional Climate Model (RCM) simulations. Biases in the CGCM-generated driving BC, however, can have detrimental impacts on RCM performance. It is well documented for the historical period that CGCM-simulated sea-surface temperatures (SST) suffer substantial biases, especially important near coastal regions. Assuming that these SST biases are time-invariant, they could in principle be subtracted from century-long CGCM projections before being used to drive RCMs. This paper investigates the performance of a 3-step DD approach as follows. The CGCM-simulated sea-surface temperatures (SST) are first empirically corrected by subtracting their systematic biases; the corrected SST are then used as ocean surface BC for an atmosphere-only GCM (AGCM) simulation; finally this AGCM simulation provides the atmospheric lateral BC to drive an RCM simulation. This is what we refer to as the 3-step approach CGCM–AGCM–RCM of DD, which can be compared to the traditional 2-step approach CGCM–RCM consisting of driving an RCM simulation directly by CGCM-generated BC. In this paper we compare the results obtained with the two approaches, for present and future climates under RCP8.5, using the fifth-generation Canadian Regional Climate Model (CRCM5) with a grid mesh of 0.22° over the North American CORDEX domain, driven by two CMIP5 models: the Canadian Earth System Model of the Canadian Centre for Climate modelling and analysis (CanESM2) and the Earth System Model of the Max-Planck-Institut für Meteorologie (MPI-ESM-MR). The results show that, in current climate, the seasonal-mean 2-m temperature fields simulated with the 3-step DD have generally smaller biases with respect to the observations than those simulated with the 2-step DD; in fact the performance of the 3-step DD simulations often approaches that of the reanalyses-driven simulation. For the seasonal-mean precipitation field, however, the differences between the two DD methods are not conclusive. Differences between the projected climate changes with the two DD methods vary substantially depending upon the variable being considered. Differences are particularly important for temperature: over the bulk of the North American continent, the 3-step DD projects more warming in winter and less in summer. This result highlights the nonlinearities of the climate system, and constitutes an additional measure of uncertainty with DD. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to determine the correlation between the monthly average atmospheric air temperature values at different periods of the year and the evolution of the valuie morpho-productive characters of the bee families, thereby elucidating the impact of climate change on the vital activity of bee colonies Apis mellifera. The scientific researches were carried out at the experimental apiary of the Institute of Zoology of the Academy of Sciences of Moldova, located in the central part of Moldavian Codri. Research results have demonstrated that there are positive correlations between the atmospheric air temperature in October of the last year and January of this year and the wintering resistance of the bees colonies (rxy = 0.469 and 0.768). High temperatures of atmospheric air in July, August and September have a negative impact on the wintering resistance of bee families in the next year (rxy = -0.479; -0.699 and -0.494). The prolificity of queens is positively influenced by January temperatures (rxy = 0.464 ± 0.076; tr = 6.11; P <0.001). Air temperature in February, April and June correlates negatively with the prolificity of queens, estimated in June (rxy = -0.594; -0.795 and -0.461). High temperatures in July and September negatively influence the prolificity of queens in the following year (rxy = -0.531 and -0.711). Colony strength, evaluated in June, is negatively influenced by air temperatures in April and June (rxy = -0.603; -0.691), also correlated with air temperature in September of the last year (rxy = - 0.60; tr = 2.71; P <0.01), as well as positive one with October of the same year (rxy = 0.517; tr = 2.00; P <0.05). The viability of the bee brood is positively influenced by the January and February air temperatures (rxy = 0.495 and 0.511), and - negative in the May (rxy = -0.548, tr = 2.22, P <0.05). Overall, the annual average air temperature positively influence the viability of the brood (rxy = 0.833; tr = 7.71; P <0.001). Honey production, appreciated at the end of June, tends to be positively influenced by the atmospheric air temperature in January (rxy = 0.488; tr = 1.81; P <0.1) and, negatively, by the temperature in June (rxy = -0.497; tr = 1.87; P <0.1). Atmospheric air temperatures in July and September have a negative impact on honey production in the next year (rxy = -0.548 and - 0.684; tr = 2.22 and 3.64; P <0.05 and <0.001); but in October has a positive impact on this production (rxy = 0.513; tr = 2.00; P <0.05). [ABSTRACT FROM AUTHOR]