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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]

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]

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]

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]

Some of the major dimensions of climate change include increase in surface temperature, longer spells of droughts in significant portions of the world, associated higher evapotranspiration rates, and so on. It is therefore essential to comprehend the future possible scenario of climate change in terms of global warming. A high resolution limited area Regional Climate Model (RCM) can produce reasonably appropriate projections to be used for climate-scenario generation in country-scale. This paper features the development of future surface temperature projections for Bangladesh on monthly resolution for each year from 2011 to 2100 applying Providing Regional Climates for Impacts Studies (PRECIS), and it explains in detail the modeling processes including the model features, domain size selection, bias identification as well as construction of change field for the concerned climatic variable, in this case, surface temperature. PRECIS was run on a 50 km horizontal grid-spacing under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario and it was found to perform reasonably well in simulating future surface temperature of Bangladesh. The linear regression between observed and model simulated results of monthly average temperatures, within the 30-year period from 1971 to 2000, gives a high correlation of 0.93. The applied change field in average annual temperature shows only 0.5 °C-1 °C deviation from the observed values over the period from 2005 to 2008. Eventually, from the projected average temperature change during the years 1971--2000, it is apparent that warming in Bangladesh prevails invariably every month, which might eventually result in an average annual increase of 4 °C by the year 2100. Calculated anomalies in country-average annual temperature mostly remain on the positive side throughout the period of 2071--2100 indicating an overall up-shift. Apart from these quantitative analyses of temporal changes of temperature, this paper also illustrates their spatial distribution with a view to identify the most vulnerable zones under consequent warming through future times. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP), which is well known as "The Third Pole", is of great importance to climate change in East Asia, and even the whole world. In this paper, we selected the monthly temperature (including the monthly mean and the maximum and minimum temperature) during 1971-2015 from 88 meteorological stations on the TP. The data were tested and corrected by using Penalized Maximal F Test (PMFT) based on RHtest. Afterwards, based on the Mann-Kendall test, we analyzed the seasonal and time-interval characteristics on each station in detail. The results show that the TP has experienced significant warming during 1971-2015. When comparing the selected elements, the warming rate of minimum temperature (Tmin) is the largest, the mean temperature (Tmean) comes second, and the maximum temperature (Tmax) is the smallest. The warming trends in four seasons are significant, and the highest warming rate occurs in winter. The warming trend on the TP has a prominent spatial difference, with a large warming rate on the eastern parts and a small one on the central regions. In different seasons, the warming trends on the TP have different characteristics in the time interval. Since 1998, the warming rate in spring increased markedly, spring has displaced winter as the season with the highest warming rate recently. [ABSTRACT FROM AUTHOR]

This work describes a mountain meteorological network that was in operation from 1999 to 2014 in a mountain range with elevations ranging from 1104 to 2428 m in Central Spain. Additionally, some technical details of the network are described, as well as variables measured and some meta information presented, which is expected to be useful for future users of the observational database. A strong emphasis is made on showing the observational methods and protocols evolution, as it will help researchers to understand the sources of errors, data gaps and the final stage of the network. This paper summarizes mostly the common sources of errors when designing and operating a small network of this kind, so it can be useful for individual researchers and small size groups that undertake a similar task on their own. Strengths and weaknesses of some of the variables measured are discussed and some basic calculations are made in order to show the potential of the database and to anticipate future deeper climatological analyses over the area. Finally, the configuration of an automatic mountain meteorology station is suggested as a result of the lessons learned and the the common state of the art automatic measuring techniques. [ABSTRACT FROM AUTHOR]

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen's slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson's correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions. [ABSTRACT FROM AUTHOR]

Global warming may increase potential evapotranspiration (ETp), reducing the water resources in Yangzi River Delta. Therefore, it is important to investigate the trend of ETp there under the background of climate change. To this purpose, the systematic biases in temperature outputs of 24 global climate models (GCMs) under 3 shared socioeconomic pathways—representative concentration pathways (SSPs) emission scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5)—are first corrected by using 8 bias correction methods. Then, the trend of ETp in Yangtze River Delta is projected by using 4 ETp calculation formulas (Blaney–Criddle, Hargreaves–Samani, Makkink, and Priestley–Taylor). The uncertainty of the projections is estimated and decomposed by using multi-way analysis of variance frameworks. The influence of uncertainty on the projected change signal is quantified by using the signal-to-noise ratio. The results show that all emission scenarios indicate robust increments of ETp. Specifically, relative to 1971~2000, ETp will increase by 0.14~0.17 mm d−1 (5.7~6.8%) during 2021~2050 and by 0.21~0.41 mm d−1 (8.5~16.7%) during 2061~2090, respectively. During 2021~2050, the uncertainty of ETp projections is dominantly contributed by the main effects of GCM (63%) and the ETp calculation formula (24%). During 2061~2090, it is mainly contributed by the main effect of GCM (36%), followed by the main effects of the emission scenario (34%) and the ETp calculation formula (18%). The ETp projections are generally reliable and robust during the two projection periods. [ABSTRACT FROM AUTHOR]

This paper summarizes the results from microclimatic monitoring of the impacts related to the construction and exploration phase of a hydroelectric powerplant in the upper Douro River (Portugal). Reference climatic elements for both periods were obtained and the impacts of the reservoir water mass on the region's microclimate were evaluated. For this purpose, Sen's slope estimate non-parametric test was used to detect the meteorological variables' trends over 10 years, considering the division into the construction (2011–2015) and exploration (2016–2020) phases. A network of meteorological stations located close to the dam, in addition to a control station relatively distant from the dam, was used to collect the meteorological data. The control station is still integrated into the same regional climatic context but not exposed to the direct influence of the resulting reservoirs. As a result, temporal differences were determined for temperature and relative humidity. The results show a statistically significant increase in the minimum relative humidity, accompanied by a statistically significant decrease in the daily and seasonal temperature amplitudes between the construction and the exploration phase periods. These outcomes thereby suggest that large reservoirs affect the local climate and may create new microclimates, in the surrounding area, with both positive and negative potential effects. [ABSTRACT FROM AUTHOR]

Climate change and climate-sensitive disasters caused by climatic hazards have a significant and increasing direct and indirect impact on human health. Due to its vast area, complex geographical environment and various climatic conditions, Russia is one of the countries that suffers significantly from frequent climate hazards. This paper provides information about temperature extremes in Russia in the beginning of the 21st century, and their impact on human health. A literature search was conducted using the electronic databases Web of Science, Science Direct, Scopus, and e-Library, focusing on peer-reviewed journal articles published in English and in Russian from 2000 to 2021. The results are summarized in 16 studies, which are divided into location-based groups, including Moscow, Saint Petersburg and other large cities located in various climatic zones: in the Arctic, in Siberia and in the southern regions, in ultra-continental and monsoon climate. Heat waves in cities with a temperate continental climate lead to a significant increase in all-cause mortality than cold waves, compared with cities in other climatic zones. At the same time, in northern cities, in contrast to the southern regions and central Siberia, the influence of cold waves is more pronounced on mortality than heat waves. To adequately protect the population from the effects of temperature waves and to carry out preventive measures, it is necessary to know specific threshold values of air temperature in each city. [ABSTRACT FROM AUTHOR]

Background: Heatwaves have become a public health emergency raising great public health concerns. Correspondingly, due to climate change, the increase in extreme weather events, such as heatwaves, floods and hurricanes, is predicted through state-of-the-art models and robust statistical analyses. Since the Mediterranean basin is recognized as the most prominent global climate change hot spot, further scientific research on the future impacts of heatwaves on human mortality, as well as human health and well-being, in the Mediterranean region is critical. Methods: The aim of the present study is to compare the relationship between three different causes of mortality (i.e., cardiological, respiratory and cardiorespiratory) and temperature between two countries (Spain and Greece) and five cities (i.e., Madrid, Barcelona, Valencia, Attica and Thessaloniki). To compare the five cities under examination, a robust statistical methodological framework (i.e., Threshold Regression Analysis (TRA)) was applied so as to examine the critical value above which the mean temperature affects cardiological, respiratory and cardiorespiratory mortality. Results: Our results prove that the relationship between mortality and temperature is a nonlinear relationship shaping a U- or J-shaped curve, meaning that mortality is affected by temperature in a non-constant way, indicating that mortality increases during both low and high temperatures. Conclusions: By calculating different temperature thresholds for the five cities under examination, we show that different temperature thresholds are more accurate for different climatic conditions. Hence, climatic conditions should be taken into account when examining the impacts of temperature on human health. [ABSTRACT FROM AUTHOR]

We apply extreme value theory (EVT) to study the daily precipitation and temperature extremes in the Calabria region (southern Italy) mainly considering a long-term observational dataset (1990–2020) and also investigating the possible use of the ERA5 (ECMWF Reanalysis v5) fields. The efficiency of the EVT applied on the available observational dataset is first assessed—both through a punctual statistical analysis and return-level maps. Two different EVT methods are adopted, namely the peak-over-threshold (POT) approach for the precipitation and the block-maxima (BM) approach for the temperature. The proposed methodologies appear to be suitable for describing daily extremes both in quantitative terms, considering the punctual analysis in specific points, and in terms of the most affected areas by extreme values, considering the return-level maps. Conversely, the analysis conducted using the reanalysis fields for the same time period highlights the limitations of using these fields for a correct quantitative reconstruction of the extremes while showing a certain consistency regarding the areas most affected by extreme events. By applying the methodology on the observed dataset but focusing on return periods of 50 and 100 years, an increasing trend of daily extreme rainfall and temperature over the whole region emerges, with specific areas more affected by these events; in particular, rainfall values up to 500 mm/day are predicted in the southeastern part of Calabria for the 50-year-return period, and maximum daily temperatures up to 40 °C are expected in the next 100 years, mainly in the western and southern parts of the region. These results offer a useful perspective for evaluating the exacerbation of future extreme weather events possibly linked to climate change effects. [ABSTRACT FROM AUTHOR]

Climate extreme events have been observed more frequently since the 1970s throughout Ethiopia, which adversely affects the socio-economic development of the country, as its economy depends on agriculture, which, in turn, relies heavily on annual and seasonal rainfall. Climate extremes studies conducted in Ethiopia are mainly limited to a specific location or watershed, making it difficult to have insights at the national level. The present study thus aims to examine the observed climate extreme events in Ethiopia at both station and agro-ecological zone (AEZ) levels. Daily rainfall and temperature data for 47 and 37 stations, respectively (1986 up to 2020), were obtained from the National Meteorology Agency (NMA). The Modified Mann–Kendall (MMK) trend test and the Theil–Sen slope estimator were employed to estimate the trends in rainfall and temperature extremes. This study examines trends of 13 temperature and 10 rainfall extreme indices using RClimDex in R software. The results revealed that most of the extreme rainfall indices showed a positive trend in the majority of the climate stations. For example, an increase in consecutive dry days (CDD), very heavy rainfall days (R20), number of heavy rainfall days (R10) and consecutive wet days (CWD) were exhibited in most climate stations. In relation to AEZs, the greater number of extreme rainfall indices illustrated an upward trend in cool and sub-humid, cool and humid, and cool and moist AEZs, a declining trend in hot arid AEZ, and equal proportions of increasing and decreasing trends in warm semi-arid AEZs. Concerning extreme temperature indices, the result indicated an increasing trend of warm temperature extreme indices and a downward trend of cold temperature extreme indices in most of the climate stations, indicating the overall warming and dryness trends in the country. With reference to AEZs, an overall warming was exhibited in all AEZs, except in the hot arid AEZ. The observed trends in the rainfall and temperature extremes will have tremendous direct and indirect impacts on agriculture, water resources, health, and other sectors in the country. Therefore, the findings suggest the need for identifying and developing climate change adaptation strategies to minimize the ill effects of these extreme climate events on the social, economic, and developmental sectors. [ABSTRACT FROM AUTHOR]

A region in the tropical western Pacific is selected to study the notable change in temperature between the recent warming hiatus period and the post-hiatus period. In total, three probable factors, namely sea-surface temperature (SST), cloud vertical structure (CVS) and wind speed, which may account for the temperature change are found to exhibit noticeable differences between these two periods. A one-dimensional atmospheric radiative transfer model, incorporating convective adjustment and energy exchange with the ocean, is developed to simulate the diurnal pattern of temperature profile under the influence of the three probable factors in the two concerned periods. Virtual profiles of sea-surface temperature, cloud vertical structure and wind speed in both periods are developed from data available in the literature. Diurnal patterns of temperatures near the air–sea interface are computed with the proposed model over a sufficient number of days. The simulated temperatures under different combinations of factors, in either the hiatus or post-hiatus period, are statistically analyzed to gain insights about the separate and combined effects of these three factors on causing climate change. [ABSTRACT FROM AUTHOR]

Nature has been adversely affected by increasing industrialization, especially during the latter part of the last century, as a result of accelerating technological development, unplanned urbanization, incorrect agricultural policies and deforestation, which have contributed to the elevated concentration of the greenhouse gases (GHGs) in the environment. GHG accumulation has an adverse impact on meteorological and hydro-meteorological parameters, particularly temperature. Temperature plays a prominent and well-known role in evaporation, transpiration and changes in water demand, and thus significantly affects both water availability and food security. Therefore, a systematic understanding of temperature is important for fighting food insecurity and household poverty. Variations in temperature are often assessed and characterized through trend analysis. Hence, the objective of this paper is to determine long-term trends in mean monthly maximum and minimum air temperatures for the Maloti-Drakensberg region. The Mann–Kendall test, a non-parametric test, was applied on mean air temperature for the 1960–2016 period. A significant rising trend (p < 0.001) was detected with a yearly change in the long term annual mean maximum and mean minimum temperature by 0.03 °C/annum and 0.01 °C/annum, respectively. This knowledge has important implications for both the state of the environment and livelihoods in the region, since its use can be useful in planning and policymaking in water resource management, biodiversity conservation, agriculture, tourism and other sectors of the economy within the region. [ABSTRACT FROM AUTHOR]

In this study, we consider the historical climatological time series available in the meteorological yearbooks of the Royal Hungarian Central Institute of Meteorology and Earth Magnetism, first published in 1871. Data quality improvement of historical data includes the homogenization process with outlier checks and data gap filling by applying the MASH software. We investigated 13 stations from the Carpathian Region having the most complete monthly temperature and precipitation time series for the period of 1871–1918 and 8 stations with fog observations (1886–1916). First, statistical tests were conducted to compare the main statistics of the historical datasets (1871–1918) with current data (1971–2020). The sources of the current data are the National Meteorological Administration of Romania and the European Climate Assessment & Dataset. The results show significant changes between the two periods. In the whole region, the mean temperature in the last five decades (1971–2020) was 0.77 °C higher than in 1871–1918. Changes in the frequency of foggy situations were also detected. On an annual scale, in the last 31-year period (1990–2020), the number of foggy days increased by 16.2 compared with 1886–1916. Even if some local trends can be detected in the historical periods (e.g., Cluj-Napoca), significant changes are much more characteristic in the recent period. [ABSTRACT FROM AUTHOR]

Recent work attributing decadal regime changes in temperature to radiative forcing is extended to atmospheric moisture. Temperature, and specific and relative humidity (T, q, RH) from the HadISDH data set were analyzed for regime shifts using the bivariate test. Most shifts in q and T for global and northern hemisphere (NH), and tropical land occurred within a year of each other. Only one shift of q was recorded in the southern hemisphere (SH). RH increased in the NH in 1990–91 and decreased in a series of shifts from the late 1990s, while in the SH decreased from 2001. The tropics have remained neutral, shifting negative over land and positive over the ocean. The global decreases in 2001 and 2011 was −0.56%. Global RH from 32 climate models from the CMIP5 RCP4.5 archive all contained regime shifts but only 4 reached or exceeded the observed decreases by 2100, the earliest in 2056. Regime shifts in RH and fire danger over Australia are consistent with the SH decreases in RH, shifting within one year of global fire season length in 2002, showing that impacts are also being underestimated by current analyses. Methods for nonlinear attribution and the contributing processes for nonlinear change are discussed. These results show that developing a better understanding of nonlinear change in moisture-related climate risk is an urgent task. [ABSTRACT FROM AUTHOR]

The present study investigates the response of natural gas consumption to temperature on the basis of observations during heating season (middle November–middle March) for the period 2002–2021 in Beijing, China, and then estimates temperature-related changes in the gas consumption under future scenarios by using climate model simulations from the Coupled Model Intercomparison Project Phase 6. Observational evidence suggests that the daily natural gas consumption normalized by gross domestic product is linearly correlated with the daily average temperature during heating season in the past two decades in Beijing. Hence, a linear regression model is built to estimate temperature-related changes in the natural gas consumption under future scenarios. Corresponding to a rising trend in the temperature, the natural gas consumption shows a decrease trend during 2015–2100 under both the SSP245 and the SSP585 scenarios. In particular, the temperature would increase rapidly from early 2040s to the end of 21st century under the SSP585 scenario, leading to an obvious reduction in the natural gas consumption for heating in Beijing. Relative to that in the present day (1995–2014), the natural gas consumption would show a reduction of approximately 9% (±4%) at the end of 21st century (2091–2100) under the SSP245 scenario and approximately 22% (±7%) under the SSP585 scenario. [ABSTRACT FROM AUTHOR]

Climate change continues to increase the intensity, frequency and impacts of weather and climate extremes. This work uses bias-adjusted Coupled Model Intercomparison Project Phase six (CMIP6) model datasets to investigate the future changes in temperature extremes over Mediterranean (MED) and Sahara (SAH) regions. The mid- (2041–2070) and far-future (2071–2100) are studied under two Shared Socioeconomic Pathways: SSP2-4.5 and SSP5-8.5 scenarios. Quantile mapping function greatly improved the performance of CMIP6 by reducing the notable biases to match the distribution of observation data, the Climate Prediction Center (CPC). Results show persistent significant warming throughout the 21st century, increasing with the increase in radiative forcing. The MED will record a higher increase in temperature extremes as compared to SAH. The warming is supported by the projected reduction in cold days (TX10p) and cold nights (TN10p), with the reduction in the number of cold nights exceeding cold days. Notably, warm spell duration index (WSDI) and summer days (SU) have a positive trend in both timelines over the entire study area. There is a need to simulate how climate sensitive sectors, such as water and agriculture, are likely to be affected by projected changes under different scenarios for informed decision making in the choice and implementation of adaptation and mitigation effective measures. [ABSTRACT FROM AUTHOR]

As an essential part of the hydrological cycle, precipitation is usually associated with floods and droughts and is increasingly being paid attention to in the context of global warming. Analyzing the change trends and correlation of temperature and extreme precipitation indicators can effectively identify natural disasters. This study aimed to detect the correlation and change trends of temperature and extreme precipitation indicators in Inner Mongolia from 1960 to 2019. Panel vector autoregression (PVAR) models based on Stata software were used to detect the correlation between temperature and extreme precipitation indicators at 35 climatological stations throughout Inner Mongolia. The temperature and extreme precipitation indicator trends were analyzed using the Mann–Kendall test and Sen's slope method. The spatial distribution characteristics of the annual precipitation and rainfall intensity were more significant in the southeast and more minor in the northwest, while an increase in the annual wet days was noticeable to the northeast. The Granger cause tests of the temperature and the extreme precipitation indicators showed a correlation between each indicator and temperature at the significance level of 1%. The temperature positively correlated with only the rainfall intensity while negatively correlating with the remaining indicators. There is no doubt that trend analysis showed significant increasing trends in rainfall intensity at all stations, which means increased risk in extreme precipitation events. By contrast, the annual precipitation and annual wet days showed significant decreasing trends, which means that the precipitation is concentrated, and it is easier to form extreme precipitation events. The study can provide a basis for decision-making in water resources and drought/flood risk management in Inner Mongolia, China. [ABSTRACT FROM AUTHOR]

Alaska observes very large differences in precipitation throughout the state; southeast Alaska experiences consistently wet conditions, while northern Arctic Alaska observes very dry conditions. The maximum mean annual precipitation of 5727 mm is observed in the southeastern panhandle at Little Port Arthur, while the minimum of 92 mm occurs on the North Slope at Kuparuk. Besides explaining these large differences due to geographic and orographic location, we discuss the changes in precipitation with time. Analyzing the 18 first-order National Weather Service stations, we found that the total average precipitation in the state increased by 17% over the last 67 years. The observed changes in precipitation are furthermore discussed as a function of the observed temperature increase of 2.1 °C, the mean temperature change of the 18 stations over the same period. This observed warming of Alaska is about three times the magnitude of the mean global warming and allows the air to hold more water vapor. Furthermore, we discuss the effect of the Pacific Decadal Oscillation (PDO), which has a strong influence on both the temperature and precipitation in Alaska. [ABSTRACT FROM AUTHOR]

Increases in numbers and lengths of heat waves have previously been identified in global temperature records, including locations within Europe. However, studies of changes in UK heat wave characteristics are limited. Historic daily maximum temperatures from 29 weather stations with records exceeding 85 years in length across the country were examined. Heat waves were defined as periods with unusually high temperatures for each station, even if the temperatures would not be considered warm in an absolute sense. Positive trends in numbers and lengths of heat waves were identified at some stations. However, for some stations in the south east of England, lengths of very long heat waves (over 10 days) had declined since the 1970s, whereas the lengths of shorter heat waves had increased slightly. Considerable multidecadal variability in heat wave numbers and lengths was apparent at all stations. Logistic regression, using a subset of eight stations with records beginning in the nineteenth century, suggested an association between the Atlantic Multidecadal Oscillation and the variability in heat wave numbers and lengths, with the summertime North Atlantic Oscillation playing a smaller role. The results were robust against different temperature thresholds. [ABSTRACT FROM AUTHOR]

The widely used Global Historical Climatology Network (GHCN) monthly temperature dataset is available in two formats—non-homogenized and homogenized. Since 2011, this homogenized dataset has been updated almost daily by applying the "Pairwise Homogenization Algorithm" (PHA) to the non-homogenized datasets. Previous studies found that the PHA can perform well at correcting synthetic time series when certain artificial biases are introduced. However, its performance with real world data has been less well studied. Therefore, the homogenized GHCN datasets (Version 3 and 4) were downloaded almost daily over a 10-year period (2011–2021) yielding 3689 different updates to the datasets. The different breakpoints identified were analyzed for a set of stations from 24 European countries for which station history metadata were available. A remarkable inconsistency in the identified breakpoints (and hence adjustments applied) was revealed. Of the adjustments applied for GHCN Version 4, 64% (61% for Version 3) were identified on less than 25% of runs, while only 16% of the adjustments (21% for Version 3) were identified consistently for more than 75% of the runs. The consistency of PHA adjustments improved when the breakpoints corresponded to documented station history metadata events. However, only 19% of the breakpoints (18% for Version 3) were associated with a documented event within 1 year, and 67% (69% for Version 3) were not associated with any documented event. Therefore, while the PHA remains a useful tool in the community's homogenization toolbox, many of the PHA adjustments applied to the homogenized GHCN dataset may have been spurious. Using station metadata to assess the reliability of PHA adjustments might potentially help to identify some of these spurious adjustments. [ABSTRACT FROM AUTHOR]

Thirty-year periods are treated in climatology as spans with relatively representative and stable climatic patterns, which can be used for calculating climate normals. Annual and seasonal series of circulation types were used to compare two 30-year sub-periods, 1961–1990 and 1991–2020, the second one being strongly influenced by recent global warming. This analysis was conducted according to the objective classification of circulation types and the climatic characteristics of sunshine duration, temperature, humidity, precipitation, and wind speed as calculated for the territory of the Czech Republic during the 1961–2020 period. For both sub-periods, their statistical characteristics were calculated, and the statistical significance of differences between them was evaluated. There was a statistically significant increase in the annual frequencies of anticyclonic circulation types and a significant decrease in cyclonic circulation types during 1991–2020 compared with 1961–1990. Generally, in both 30-year periods, significant differences in means, variability, characteristics of distribution, density functions, and linear trends appear for all climatic variables analysed except precipitation. This indicates that the recent 30-year "normal" period of 1991–2020, known to be influenced more by recent climate change, is by its climatic characteristics unrepresentative of the stable climatic patterns of previous 30-year periods. [ABSTRACT FROM AUTHOR]

To date, due to climate change, heatwaves are more frequent, with greater intensity and duration resulting in deleterious impacts on human health. To be able to manage heatwaves and quantify the impacts on human health, it is crucial to define them and implement policy preventive measures. However, heatwaves are relative to the climate of a location: The same meteorological conditions can constitute a heatwave in one place but not in another. Due to different climatic conditions, social characteristics, and adaptation, heatwaves should be defined on a local scale, which poses difficulties when it comes to comparison of different definitions. The aim of the present study is to define heatwaves, implementing robust statistical analysis for three different indicators (temperature, physiological equivalent temperature (PET), and universal thermal climate index (UTCI)) for three causes of mortality (i.e., cardiological and respiratory mortality and cardiorespiratory mortality) using Attica (Greece) as a case study. Our results define a heatwave for Attica as a period of at least 3 days when the mean temperature is higher than the 97.5th percentile. Afterwards, we encapsulate the harvesting effect by implementing robust statistical analysis, using the Superposed Epoch analysis. Consequently, quantifying heatwaves is crucial so as to create early warning systems and prevent avoidable mortality. [ABSTRACT FROM AUTHOR]

Having an extreme topography and heterogeneous climate, the Upper Indus Basin (UIB) is more likely to be affected by climate change and it is a crucial area for climatological studies. Based on the monthly minimum temperature (Tmin), maximum temperature (Tmax) and precipitation from nine meteorological stations, the spatiotemporal variability of temperature and precipitation were analyzed on monthly, seasonal, and annual scales. Results show a widespread significant increasing trend of 0.14 °C/decade for Tmax, but a significant decreasing trend of −0.08 °C/decade for Tmin annually, during 1955–2016 for the UIB. Seasonally, warming in Tmax is stronger in winter and spring, while the cooling in Tmin is greater in summer and autumn. Results of seasonal Tmax indicate increasing trends in winter, spring and autumn at rates of 0.38, 0.35 and 0.05 °C/decade, respectively, while decreasing in summer with −0.14 °C/decade. Moreover, seasonal Tmin results indicate increasing trends in winter and spring at rates of 0.09 and 0.08 °C/decade, respectively, while decreasing significantly in summer and autumn at rates of −0.21 and −0.22 °C/decade respectively for the whole the UIB. Precipitation exhibits an increasing trend of 2.74 mm/decade annually, while, increasing in winter, summer and autumn at rates of 1.18, 2.06 and 0.62 mm/decade respectively. The warming in Tmax and an increase in precipitation have been more distinct since the mid-1990s, while the cooling in Tmin is observed in the UIB since the mid-1980s. Warming in the middle and higher altitude (1500–2800 m and >2800 m) are much stronger, and the increase is more obvious in regions with elevation >2800 m. The wavelet analysis illustrated sporadic inter-annual covariance of seasonal Tmax, Tmin and precipitation with ENSO, NAO, IOD and PDO in the UIB. The periodicities were usually constant over short timescales and discontinuous over longer timescales. This study offers a better understanding of the local climate characteristics and provides a scientific basis for government policymakers. [ABSTRACT FROM AUTHOR]

Despite having contributed the least to global warming and having the lowest emissions, the African region is the most vulnerable continent to climate change impacts. To reduce the levels of risk arising from climate change, it is mandatory to combine both mitigation and adaptation. While mitigation can reduce global warming, not all impacts can be avoided. Therefore, adaptation is essential to advance strategic interventions and reduce the impacts. As part of the international effort to cope with changing climate, a set of Coordinated Regional Downscaling Experiment (CORDEX) domains have been established worldwide. The CORDEX-Africa initiative has been developed to analyze downscaled regional climate data over the African domain for climate data analysis techniques and engage users of climate information in both sector-specific and region/space-based applications. This study takes outputs of high-resolution climate multi-models from the CORDEX-Africa initiative constructed at a spatial resolution of 50 km to assess climate change projections over Mozambique. Projected spatial and temporal changes (three 30-year time periods, the present (2011–2040), mid (2041–2070), and the end (2071–2100)) in temperature and precipitation under the Representative Concentration Pathways RCP2.6, RCP4.5, and RCP8.5 are analyzed and compared relative to the baseline period (1961–1990). Results show that there is a tendency toward an increase in annual temperature as we move toward the middle and end of the century, mainly for RCP4.5 and RCP8.5 scenarios. This is evident for the Gaza Province, north of the Tete Province, and parts of Niassa Province, where variations will be Tmax (0.92 to 4.73 °C), Tmin (1.12 to 4.85 °C), and Tmean (0.99 to 4.7 °C). In contrast, the coastal region will experience less variation (values < 0.5 °C to 3 °C). At the seasonal scale, the pattern of temperature change does not differ from that of the annual scale. The JJA and SON seasons present the largest variations in temperature compared with DJF and MAM seasons. The increase in temperature may reach 4.47 °C in DJF, 4.59 °C in MAM, 5.04 °C in JJA, and 5.25 °C in SON. Precipitation shows substantial spatial and temporal variations, both in annual and seasonal scales. The northern coastal zone region shows a reduction in precipitation, while the entire southern region, with the exception of the coastal part, shows an increase up to 40% and up to 50% in some parts of the central and northern regions, in future climates for all periods under the three reference scenarios. At the seasonal scale (DJF and MAM), the precipitation in much of Mozambique shows above average precipitation with an increase up to more than 40% under the three scenarios. In contrast, during the JJA season, the three scenarios show a decrease in precipitation. Notably, the interior part will have the largest decrease, reaching a variation of −60% over most of the Gaza, Tete, and Niassa Provinces. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) is one of the greatest global public health challenges. Acute exacerbations of COPD lead to the accelerated deterioration of lung function, reduced quality of life, a higher number of hospitalizations, and increased mortality. The factor causing the exacerbation is usually an infectious agent, but the impact of environmental factors is being studied more thoroughly. Among them, meteorological factors are the least examined. Multiple studies have shown that lower temperatures during the cold season, as well as sudden temperature changes regardless of the season, have the most significant negative effect on patients with COPD. However, higher temperatures, especially during summer heatwaves, can also cause COPD exacerbation and it is expected that this will be an even more important health problem in the future considering climate changes. The effects of other meteorological factors on acute exacerbation of COPD, such as atmospheric pressure, solar radiation, rainfall, wind speed, and humidity are far less investigated and opposing results have been obtained in different studies. Thus, there is a need for further research in this area that would result in clinical recommendations and public health interventions that could decrease the global burden of COPD. [ABSTRACT FROM AUTHOR]

The diurnal temperature range (DTR) is considered a signature of observed climate change, which is defined as the difference between the maximum (Tmax) and minimum temperatures (Tmin). It is well known that the warming rate of mean temperature is larger at high elevations than at low elevations in northeast China. However, it is still uncertain whether DTR trend is greater at high elevations. This study examined the spatiotemporal variation in DTR and its relationship with elevation in northeast China based on data from 68 meteorological stations from 1961 to 2015. The results show that there was a significant declining trend (0.252 °C/decade) in DTR from 1961 to 2015 due to the fact that Tmin increased at a faster rate than Tmax. Seasonally, DTR in northeast China showed a decreasing trend with the largest decrease rate in spring (−0.3167 °C/decade) and the smallest decrease rate in summer (−0.1725 °C/decade). The results of correlation analysis show that there was a significant positive correlation between the annual DTR trend and elevation in northeast China. This is due to the fact that increasing elevation has a significant warming effect on Tmax. Seasonally, there were significant positive correlations between the DTR trend and elevation in all seasons. The elevation gradient of DTR trend was the greatest in winter (0.392 °C/decade/km) and the lowest in autumn (0.209 °C/decade/km). In spring, summer, and autumn, increasing elevation has a significant warming effect on Tmax, leading to a significant increase of the DTR trend with increasing elevation. However, in winter, increasing elevation has a significant cooling effect on Tmin, resulting in a significant increase of the DTR trend with increasing elevation. [ABSTRACT FROM AUTHOR]

As global temperatures continue to rise unabated, episodes of heat-related catastrophes across the world have intensified. In Kenya, heatwave phenomena and their associated impacts are ignored and neglected due to several reasons, including unreliable and inconsistent weather datasets and heatwave detection metrics. Based on CHIRTS satellite infrared estimates and station blended temperature, this study investigated the spatiotemporal distribution of the heatwave events over Kenya during 1987–2016 using the Heatwave Magnitude Index daily (HWMId). The results showed that contrary to the absence of heatwave records in official national and international disaster database about Kenya, the country experienced heatwaves ranging from less severe (normal) to deadly (super-extreme) between 1987 and 2016. The most affected areas were located in the eastern parts of the country, especially in Garissa and Tana River, and in the west-northern side around the upper side of Turkana county. It was also found that the recent years' heatwaves were more severe in magnitude, duration, and spatial extent. The highest magnitude of the heatwaves was recorded in 2015 (HWMId = 22.64) while the average over the reference period is around 6. CHIRTS and HWMId were able to reveal and capture most critical heatwave events over the study period. Therefore, they could be used respectively as data source and detection metrics, for heatwaves disaster emergency warning over short period as well as for long-term projection to provide insight for adaptation strategies. [ABSTRACT FROM AUTHOR]

The evaluation of intraseasonal, seasonal, and annual variability of rainfall and temperature extremes, while using climate change scenarios data, is extremely important for socio-economic activities, such as water resources management. Costa Rica, a climate change hotspot, is largely dependent on rainfall for socioeconomic activities; hence, the relevance of this study. Based on the NEX-GDDP, rainfall and temperature range were analyzed for Costa Rica at the end of the century (2070–2099), while using 1970–1999 as a baseline for six available meteorological stations. Differences between the multimodel ensembles of two prospective scenarios (RCP 4.5 and 8.5) and the historical information were computed. This study highlights Costa Rica as an inflexion region for climate change impacts in Central America, for which projected scenarios suggest an early onset of the rainy season, and a decline in the mid-summer drought (MSD) minimum. The assessment of model data in some regions of Costa Rica, for which historical data were available, suggests that the latter does not capture a well-known regional climate feature, the MSD, in both precipitation and temperature range well. The availability of observed past data sources is a major limitation of this research; however, with the station data used, it is still possible to draw some conclusions regarding future climate in some regions of Costa Rica, especially in the northwest side of the country, where past data are consistent with model information, providing a more reliable picture of changes in climate there that has potential implications for socioeconomic sectors. [ABSTRACT FROM AUTHOR]

Fortunately, extreme temperatures reaching 50 °C are not common on our planet. The capability of the consortium for small-scale modelling regional climate model (COSMO-CLM), with 0.44° resolution, to project future trends of an extremely hot environment with direct model output (DMO) is questioned. The temperature distribution of COSMO-CLM output driven by reanalysis and RCP4.5 scenario in southern Iraq was remarkably good, with a slight temperature overestimation, compared to the overlapping observations from Basra airport. An attempt to enhance the DMO with a statistical downscaling method did not improve the results. The COSMO-CLM projection indicates that a very sharp increase in the number of consecutive hours and days with the temperature reaching 50 °C or higher will occur. During 1951–1980, consecutive hours and days reaching 50 °C were rare events. By the end of the century, the projected climate in southern Iraq contains up to 13 consecutive hours and 21 consecutive days reaching 50 °C or higher. As the average projected temperature will increase by ~2 °C compared to the recent climate, new records may be expected. However, the major climate change feature is the increase in consecutive hours and days of very high temperatures. These findings require adaptation measures to support future habitation of the region. [ABSTRACT FROM AUTHOR]

The ongoing global warming and changing patterns of precipitation have significant implications for crop yields. Process-based models are the most commonly used method to assess the impacts of projected climate changes on crop yields. In this study, the crop-environment resource synthesis (CERES)-Maize 4.6.7 model was used to project the maize crop yield in the Shaanxi Province of China over future periods. In this context, the downscaled ensemble projections of 17 general circulation models (GCMs) under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) were used as input for the calibrated CERES-Maize model. Results showed a negative correlation between temperature and maize yield in the study area. It is expected that each 1.0 °C rise in seasonal temperature will cause up to a 9% decrease in the yield. However, the influence of CO2 fertilization showed a positive response, as witnessed by the increase in the crop yield. With CO2 fertilization, the average increase in the maize crop yield compared to without CO2 fertilization per three decades was 10.5%, 11.6%, TA7.8%, and 6.5% under the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios, respectively. An elevated CO2 concentration showed a pronounced positive impact on the rain-fed maize yield compared to the irrigated maize yield. The average water use efficiency (WUE) was better at elevated CO2 concentrations and improved by 7–21% relative to the without CO2 fertilization of the WUE. Therefore, future climate changes with elevated CO2 are expected to be favorable for maize yields in the Shaanxi Province of China, and farmers can expect further benefits in the future from growing maize. [ABSTRACT FROM AUTHOR]

This is the first study to look at future temporal urban heath island (UHI) trends of Athens (Greece) under different UHI intensity regimes. Historical changes in the Athens UHI, spanning 1971–2016, were assessed by contrasting two air temperature records from stable meteorological stations in contrasting urban and rural settings. Subsequently, we used a five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11° (~12 × 12 km) to simulate air temperature data, spanning the period 1976–2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5, and RCP8.5) were implanted in the simulations after 2005 covering the period 2006–2100. Two 20-year historical reference periods (1976–1995 and 1996–2015) were selected with contrasting UHI regimes; the second period had a stronger intensity. The daily maximum and minimum air temperature data (Tmax and Tmin) for the two reference periods were perturbed to two future periods, 2046–2065 and 2076–2095, under the three RCPs, by applying the empirical quantile mapping (eqm) bias-adjusting method. This novel approach allows us to assess future temperature developments in Athens under two UHI intensity regimes that are mainly forced by differences in air pollution and heat input. We found that the future frequency of days with Tmax > 37 °C in Athens was only different from rural background values under the intense UHI regime. Thus, the impact of heatwaves on the urban environment of Athens is dependent on UHI intensity. There is a large increase in the future frequency of nights with Tmin > 26 °C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site. This large urban amplification of the frequency of extremely hot nights is likely caused by air pollution. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be highly effective in reducing urban temperatures and extreme heat events in Athens under future climate change scenarios. Such policies directly have multiple benefits, including reduced electricity (energy) needs, improved living quality and strong health advantages (heat- and pollution-related illness/deaths). [ABSTRACT FROM AUTHOR]

Due to climate change, the Iberian Peninsula is suffering an increasing trend of extreme temperature events. The main objective of this study is to analyse this trends in frequency, duration and intensity of warm events and heat waves. The datasets used are 14 different regionalized dynamic climate projections. We choose the projections that present a spatial dependence similar to that of observed data. The spatial dependence is calculated by adjusting the data to max-stable processes. The observed data belong to the SPAIN02 grid for the period 1961–2000. We apply the Mann-Kendall test and the Theil-Sen estimator to calculate model trends in the future period (2011–2099). We have studied future extreme temperature events using two different definitions. One varying the threshold for each period and the other keeping it constant. The results show that the variability of maximum temperatures is decreasing for the western region of the Peninsula, while the Mediterranean area will see an increase in this variability. There will be an increase in the frequency of warm events for the southwestern corner of the Peninsula. Also, maximum temperatures will be higher in this area at the end of the century. However, in the Mediterranean region the warm events will last longer. Heat waves will be more frequent throughout the territory and more lasting in the Mediterranean area. We also found that studying extreme events using a varying threshold allows these events to be studied from the point of view of the variability of maximum temperatures, while if the study is carried out maintaining the threshold constant the results will be more direct. [ABSTRACT FROM AUTHOR]

Record-breaking precipitation events have been frequent in Japan in recent years. To investigate the statistical characteristics of the frequency of record-breaking events, observations can be compared with the values derived from sampling theory with a stationary state. This study counted the number of record-breaking daily and 3-day total precipitation events at 58 rain-gauge stations in Japan between 1901 and 2018. The average number of record-breaking events over the 118-year period was 5.9 for daily total precipitation, which is larger than the theoretical value of 5.4 derived using the assumption that the climate system over the same period was stationary. Sampling theory was used to incorporate the influence of the long-term temperature trend from the Clausius–Clapeyron relation associated with the saturation vapor pressure. In theory, the long-term temperature trend gives a similar number of observed record-breaking events when the long-term temperature trend is approximately 0.5 Kelvin/100 years. [ABSTRACT FROM AUTHOR]

An in-depth understanding of the impact of vulnerability on livelihoods and food security is important in deploying effective adaptation actions. The Nigerian agricultural sector is dominated by rainfed and non-homogenous smallholder farming systems. A number of climate change risk studies have emerged in the last decade. However, little attention has been given to vulnerability assessments and the operationalization of vulnerability. To highlight this shortcoming, this study systematically reviewed climate-change-focused vulnerability assessments in the agricultural sector by evaluating (1) variation in climate variables in Nigeria over time; (2) the state of climate change vulnerability assessment in Nigerian agriculture; (3) the theoretical foundations, operationalization approaches, and frameworks of vulnerability assessments in Nigeria; (4) the methods currently used in vulnerability assessments; and (5) lessons learned from the vulnerability studies. We used a linear trend of climatic data spanning over a period of 56 years (1961–2016) obtained from the Nigerian Meteorological Agency and the Climate Research Unit of the University of East Anglia, United Kingdom, along with a systematic review of literature to achieve the objectives. The analysis indicates a significant and positive correlation between temperature and time in all major agro-ecological zones. For precipitation, we found a non-significant correlation between precipitation in the Sahel, Sudan, and Guinea Savanna zones with time, while the other zones recorded positive but significant associations between precipitation and time. The systematic review findings indicate no clear progress in publications focused specifically on vulnerability assessments in the Nigerian agricultural sector. There has been progress recently in applying frameworks and methods. However, there are important issues that require addressing in vulnerability assessments, including low consideration for indigenous knowledge and experience, unclear operationalization of vulnerability, non-standardization of vulnerability measures, and inadequacy of current assessments supporting decision making. [ABSTRACT FROM AUTHOR]

Climate models are important tools to assess current and future climate. While they have been extensively used for studying temperature and precipitation, only recently regional climate models (RCMs) arrived at horizontal resolutions that allow studies of snow in complex mountain terrain. Here, we present an evaluation of the snow variables in the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) RCMs with gridded observations of snow cover (from MODIS remote sensing) and temperature and precipitation (E-OBS), as well as with point (station) observations of snow depth and temperature for the European Alps. Large scale snow cover dynamics were reproduced well with some over- and under-estimations depending on month and RCM. The orography, temperature, and precipitation mismatches could on average explain 31% of the variability in snow cover bias across grid-cells, and even more than 50% in the winter period November–April. Biases in average monthly snow depth were remarkably low for reanalysis driven RCMs (

Occupational exposure to heat and solar ultraviolet radiation (UVR) threatens the health and wellbeing of outdoor workers. These threats are likely to increase as a result of climate change. This study examined the perceptions of occupational heat and sun exposure and health risk prevention among forestry workers removing alien invasive vegetation in the Western Cape, South Africa. The linkages between workers' perceptions of heat, solar UVR, and herbicide exposure and impacts under the current climate were investigated to better understand potential adaptation needs under a changing climate. Using focus group discussions and participatory risk mapping, heat stresses identified by workers were either environmental (e.g., lack of shade) or work-related (e.g., wearing required personal protective equipment). Several heat and solar UVR health impacts were reportedly experienced by workers; local indigenous knowledge and coping mechanisms, such as wearing ochre for sun protection, were used to prevent these impacts. Despite workers' current efforts to protect their health, existing gaps and opportunities to improve working conditions were identified. Institutional structures for improved reporting of adverse events are imperative, together with awareness and education campaigns about the risks associated with working in hot and sunny environments. [ABSTRACT FROM AUTHOR]

Within the United States, the Southwest USA deserts show the largest temperature changes (1901–2010) besides Alaska, according to the most recent USA National Climate Assessment report. The report does not discuss urban effects vs. regional effects that might be evident in trends. Twenty-five temperature stations with ca. 68-year records (1950 to 2018) have been accessed from US Global Historical Climate Network archives. Land cover data are accessed from a National Land Cover Database. June results considering both urban and rural sites show an astounding rate per year change among sites ranging from −0.01 to 0.05 °C for maximum temperatures and 0.01 to 0.11 °C for minimum temperatures (−0.8 to 3.2 °C, and 0.8 to 8.0 °C for the entire period). For maximum temperatures, almost half of the sites showed no significant trends at a stringent 0.01 level of statistical significance, but 20 of 25 were significant at the 0.05 level. For minimum temperatures, over 75% of sites were significant at the 0.01 level (92% at 0.05 level of significance). The urban-dominated stations in Las Vegas, Phoenix, Tucson, and Yuma show large minimum temperature trends, indicating emerging heat island effects. Rural sites, by comparison, show much smaller trends. Addressing heat in our urban areas by local actions, through collaborations with stakeholders and political resolve, will aid in meeting future urban challenges in this era of projected global climate change and continued warming. [ABSTRACT FROM AUTHOR]

Confounding factors like urbanization and land-use change could introduce uncertainty to the estimation of global temperature trends related to climate change. In this work, we introduce a new way to investigate the nexus between temporal trends of temperature and urbanization data at the global scale in the period from 1992 to 2013. We analyze air temperature data recorded from more than 5000 weather stations worldwide and nightlight satellite measurements as a proxy for urbanization. By means of a range of statistical methods, our results quantify and outline that the temporal evolution of urbanization affects temperature trends at multiple spatial scales with significant differences at regional and continental scales. A statistically significant agreement in temperature and nightlight trends is detected, especially in low and middle-income regions, where urbanization is rapidly growing. Conversely, in continents such as Europe and North America, increases in temperature trends are typically detected along with non-significant nightlight trends. [ABSTRACT FROM AUTHOR]

Projected increase in frequency and severity of extreme events are important threat brought by climate change. Thus, there is a need to understand the dynamics and magnitude of climate extreme at local and regional level. This study examines the patterns of annual trends and changes of extreme daily temperature and precipitation in Myanmar for the period of 1981 to 2015 using the RClimDex 1.1 software. The trends of maximum and minimum temperature show significant warming trends (p < 0.001) across Myanmar. From 2009 to 2015, the maximum temperature anomaly has continuously increased by 0.5 °C for all years except 2011. The larger rise in both maximum and minimum temperature observed after 2000 suggests that, overall, days and nights are becoming hotter for the entirety of Myanmar over this recent period. Furthermore, our works also show that the temperature extreme indices of warm days and warm nights have increased, whereas the frequency of cool days and cool nights have decreased. Our analysis also reveals that increasing trends in precipitation anomaly were not significant during 1981–2015. On the contrary, slight increasing trends towards wetter conditions were observed with a rate of 76.52 mm/decade during the study period. The other precipitation extreme indicators—namely, annual total precipitation (PRCPTOT), heavy precipitation days (R20mm), extreme wet days precipitation (R99p), and consecutive wet days (CWD)—are consistent with warming trends. Additionally, the relationship between inter-annual variability in the climate extremes indices and Oceanic Niño Index (ONI) patterns was also examined with a focus on the influence of the El Niño-Southern Oscillation (ENSO) phenomenon. [ABSTRACT FROM AUTHOR]

Understanding long-term changes in precipitation and temperature patterns is important in the detection and characterization of climate change, as is understanding the implications of climate change when performing impact assessments. This study uses a statistically robust methodology to quantify long-, medium- and short-term changes for evaluating the degree to which climate change and urbanization have caused temporal changes in precipitation and temperature in South Korea. We sought to identify a fingerprint of changes in precipitation and temperature based on statistically significant differences at multiple-timescales. This study evaluates historical weather data during a 40-year period (1973–2012) and from 54 weather stations. Our results demonstrate that between 1993–2012, minimum and maximum temperature trends in the vicinity of urban and agricultural areas are significantly different from the two previous decades (1973–1992). The results for precipitation amounts show significant differences in urban areas. These results indicate that the climate in urbanized areas has been affected by both the heat island effect and global warming-caused climate change. The increase in the number of rainfall events in agricultural areas is highly significant, although the temporal trends for precipitation amounts showed no significant differences. Overall, the impacts of climate change and urbanization in South Korea have not been continuous over time and have been expressed locally and regionally in terms of precipitation and temperature changes. [ABSTRACT FROM AUTHOR]

The need to restrict global mean temperature to avoid irreversible climate change is supported by scientific evidence. The need became political practice at the Conference of the Parties in 2015, where the participants decided to limit global warming to not more than +2.0 °C compared to pre-industrial times and to rather aim for a limit of +1.5 °C global warming. Nevertheless, a clear picture of what European climate would look like under +1.5 °C, +2.0 °C and +3.0 °C global warming level (GWL) is still missing. In this study, we will fill this gap by assessing selected climate indices related to temperature and precipitation extremes, based on state of the art regional climate information for Europe taken from the European branch of the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) ensemble. To assess the impact of these indices under climate change, we investigate the spatial extent of the area of the climate change signal in relation to the affected population. This allows us to demonstrate which climate extremes could be avoided when global warming is kept well below +2.0 °C or even +1.5 °C compared to higher GWLs. The European north–south gradient of tropical nights and hot days is projected to be intensified with an increasing global warming level. For precipitation-related indices, an overall increase in precipitation extremes is simulated, especially under +3.0 °C GWL, for mid- and northern Europe, whereas an increase in dry days is projected for many regions in southern Europe. The benefit of staying below +1.5 °C GWL compared to +2.0 °C GWL is the avoidance of an additional increase in tropical nights and hot days parallel to an increase in dry days in parts of southern Europe as well as an increase in heavy precipitation in parts of Scandinavia. Compared to +3.0 °C GWL, the benefit of staying at +1.5 °C GWL is to avoid a substantial increase (i.e., an increase of more than five dry days and ten tropical nights) in dry days and tropical nights in southern European regions, while, in several European regions and especially in northern Europe, a substantial increase (i.e., more than two heavy precipitation days) in heavy precipitation days could be avoided. This study shows that a statistically significant change in the investigated climate indices can be avoided under +1.5 °C GWL compared to the investigated higher GWLs +2.0 °C and +3.0 °C for the majority of the population in almost all regions. Future studies will investigate compound events where the severity of single extreme events is intensified. [ABSTRACT FROM AUTHOR]