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Drought monitoring and early detection have improved greatly in recent decades through the development and refinement of numerous indices and indicators. However, a lack of guidance, based on user experience, exists as to which drought-monitoring tools are most appropriate in a given location. This review paper summarizes the results of targeted user engagement and the published literature to improve the understanding of drought across North America and to enhance the utility of drought-monitoring tools. Workshops and surveys were used to assess and make general conclusions about the perceived performance of drought indicators, indices and impact information used for monitoring drought in the five main Köppen climate types (Tropical, Temperate, Continental, Polar Tundra, Dry) found across Canada, Mexico, and the United States. In Tropical, humid Temperate, and southerly Continental climates, droughts are perceived to be more short-term (less than 6 months) in duration rather than long-term (more than 6 months). In Polar Tundra climates, Dry climates, Temperate climates with dry warm seasons, and northerly Continental climates, droughts are perceived to be more long-term than short-term. In general, agricultural and hydrological droughts were considered to be the most important drought types. Drought impacts related to agriculture, water supply, ecosystem, and human health were rated to be of greatest importance. Users identified the most effective indices and indicators for monitoring drought across North America to be the U.S. Drought Monitor (USDM) and Standardized Precipitation Index (SPI) (or another measure of precipitation anomaly), followed by the Normalized Difference Vegetation Index (NDVI) (or another satellite-observed vegetation index), temperature anomalies, crop status, soil moisture, streamflow, reservoir storage, water use (demand), and reported drought impacts. Users also noted the importance of indices that measure evapotranspiration, evaporative demand, and snow water content. Drought indices and indicators were generally thought to perform equally well across seasons in Tropical and colder Continental climates, but their performance was perceived to vary seasonally in Dry, Temperate, Polar Tundra, and warmer Continental climates, with improved performance during warm and wet times of the year. The drought indices and indicators, in general, were not perceived to perform equally well across geographies. This review paper provides guidance on when (time of year) and where (climate zone) the more popular drought indices and indicators should be used. The paper concludes by noting the importance of understanding how drought, its impacts, and its indicators are changing over time as the climate warms and by recommending ways to strengthen the use of indices and indicators in drought decision making. [ABSTRACT FROM AUTHOR]

As the second most predominant greenhouse gas, methane-targeted emission mitigation holds the potential to decelerate the pace of global warming. Satellite remote sensing is an important monitoring tool, and we review developments in the satellite detection of methane. This paper provides an overview of the various types of satellites, including the various instrument parameters, and describes the different types of satellite retrieval algorithms. In addition, the currently popular methane point source quantification method is presented. Based on existing research, we delineate the classification of methane remote sensing satellites into two overarching categories: area flux mappers and point source imagers. Area flux mappers primarily concentrate on the assessment of global or large-scale methane concentrations, with a further subclassification into active remote sensing satellites (e.g., MERLIN) and passive remote sensing satellites (e.g., TROPOMI, GOSAT), contingent upon the remote sensing methodology employed. Such satellites are mainly based on physical models and the carbon dioxide proxy method for the retrieval of methane. Point source imagers, in contrast, can detect methane point source plumes using their ultra-high spatial resolution. Subcategories within this classification include multispectral imagers (e.g., Sentinel-2, Landsat-8) and hyperspectral imagers (e.g., PRISMA, GF-5), contingent upon their spectral resolution disparities. Area flux mappers are mostly distinguished by their use of physical algorithms, while point source imagers are dominated by data-driven methods. Furthermore, methane plume emissions can be accurately quantified through the utilization of an integrated mass enhancement model. Finally, a prediction of the future trajectory of methane remote sensing satellites is presented, in consideration of the current landscape. This paper aims to provide basic theoretical support for subsequent scientific research. [ABSTRACT FROM AUTHOR]

The rainfall distribution in southwest China is uneven, and the rainstorm threshold cannot use in a unified standard. This paper synthesizes a calculation method for the extremely heavy precipitation threshold and the provision of the rainstorm threshold in meteorological operation. It calculates the daily precipitation rainstorm threshold at 400 national ground stations in southwest China. The rainstorm events from 1961 to 2021 were statistically analyzed using the rainstorm threshold and analyzing the spatial-temporal variation characteristics. The results show that the number of single-station rainstorm events and the average precipitation of single-station rainstorm events in southwest China decreased from east to west. The number and frequency of single-station rainstorm events in Guizhou, Sichuan, Tibet, and Chongqing are increasing, while the number of single-station rainstorm events in Yunnan is decreasing. There is no apparent spatial distribution pattern for the continuous rainstorm events in the southwest region. From 1961 to 2021, the number and frequency of rainstorm events at a single station in southwest China followed an upward trend. The number of rainstorm events at a single station increased by 16.7 times · (10a)−1, and the frequency of rainstorms increased by 9.9% · (10a)−1. The continuous rainstorm events show an increasing trend, with an increase of 0.1 times · (10a)−1. Using the rainstorm threshold in southwest China, the early warning threshold for rainstorm disasters can be adjusted. The temporal and spatial characteristics of rainstorm events since 1961 can analyze the changes occurring in rainstorm events under global warming and provide data to support the response of southwest China to climate change. [ABSTRACT FROM AUTHOR]

Climate change indices (CCI) profoundly contribute to understanding the climate and its change. They are used to present climate change in an easy-to-understand and tangible way, thus, facilitating climate communication. Most of these indices are calculated by daily data but there are also many valuable data sets that consist solely of a monthly temporal frequency. In this paper, we present a method that enables the estimation of specific CCIs from monthly instead of daily data, allowing the expression and examination of data sets consisting solely of monthly parameters through climate change indices. Therefore, we used the ERA5 Land data supplemented by a CMIP6 ssp5-8.5 climate projection to train multiple regression models with different regression functions and selected the best fitting for every grid point. Using a climate projection as a supplement in training the regression functions accounts for climate change and empowers the method's application in future climate periods. The method includes a simple bias adjustment (delta change). Its output is regridded to ERA5 Land's 0. 1 ∘ grid, adapting it to the local environment and offering better application in areas with complex terrain using coarse data. Furthermore, the presented method and its regression coefficients can be created from any data set, allowing an even higher spatial resolution than ERA5 Land's. While the method performs best for the temperature-related indices in warm temperate climates, it works uniformly well for the precipitation-related index maximum consecutive dry days on a global scale. [ABSTRACT FROM AUTHOR]

Under global warming, the climate in semi-arid inland Eurasia (SAIE) has changed in an opposite manner, thereby seriously impacting the local ecological environment. However, the key influencing factors and physical mechanism remain inconclusive. In this paper, we remodel the precipitation recycling ratio (PRR) model to assess the contributions of moisture from different water vapor sources to local precipitation, analyze the characteristics of the PRR and precipitation in SAIE, and provide possible physical reasons based on the Clausius–Clapeyron equation. It is found that the PRR increased from 1970 to 2017 as the result of linear trend analysis, with obvious seasonality. Moreover, the component of precipitation contributed by locally evaporated moisture (Pl), and that contributed by advected moisture (Pa) as well as the total precipitation (P), increased during the past 48 years. In particular, the Pa, Pl, and P in autumn and winter all increased obviously during the past 20 years from the interdecadal change trend, as well as the PRR (Pl/P), which was opposite to the decrease in the total water vapor input I(Ω) in the horizontal direction. According to the Clausius–Clapeyron equation, one of the causes might be that global warming has accelerated the local water cycle and driven the increase in Pa, and the increase in atmospheric water holding capacity caused by global warming provides the power source. We suggest that the climate's transformation from dry to wet in SAIE can only be temporary since SAIE is an inland area and the adjustment of atmospheric circulation did not lead to the increase in external water vapor. [ABSTRACT FROM AUTHOR]

Due to global warming and other climate changes, it is increasingly important to study the response of regional environmental changes and dynamic changes in vegetation to climate change. Based on meteorological data from the last 60 years, this paper calculates the humidity index of western China under a wide range of long time series in different regions and explores the cross-correlation effect between series by offering a comparison with NDVI data, to analyze the cross-correlation between wet and dry changes and changes in vegetation in western China on a spatial scale. The results show that the spatial distribution of the interdecadal humidity index is different between different regions in western China. For example, the semi-arid and the semi-humid zones of the Weihe River region exhibit significant changes, while the Xinjiang and Qinghai–Tibet regions show a trend of constant wetness, on the whole, and the Sichuan and Yunnan–Guizhou regions are relatively humid and the distribution of wetness and dryness is relatively stable. The distribution of high and low values of the humidity index is very obvious and consistent with that of the distribution of desert bare land and precipitation in western China. In common with the distribution in the humidity index, the maximum correlation number between the NDVI and the humidity index in the whole western region is also significantly different in spatial distribution. There is a positive correlation between the NDVI and the humidity index in 99% of the study area. However, the delay in response time of the NDVI to changes in the humidity index in each region is inconsistent. For example, changes in the NDVI lag changes in the humidity index in the Menggan region by generally either 2 months or 5 months, while in the Sichuan region the delay in response time is generally 3 months. The variation and trend in dry and wet areas are closely related to the geographical location, climate zone, and topographic terrain, which may be the reason for the differences in the distribution of vegetation types and the response time to dry and wet changes. There is significant interaction between the humidity index and the vegetation type or precipitation distribution in western China. The positive correlation between the NDVI and the humidity index means that the positive effect is more sensitive, and the response of grassland is the most sensitive in the ecosystem. [ABSTRACT FROM AUTHOR]

Global warming has increased the occurrence of extreme weather events, causing significant economic losses and casualties from rainfall-induced landslides. China, being highly prone to landslides, requires comprehensive predictions of future rainfall-induced landslide risks. By developing a landslide-prediction model integrated with the CMIP6 GCMs ensemble, we predict the spatiotemporal distribution of future rainfall-induced landslides in China, incorporating antecedent soil-wetness factors. In this study, antecedent soil wetness is represented by the antecedent effective rainfall index (ARI), which accounts for cumulative rainfall, evaporation, and runoff losses. Firstly, we calculated landslide susceptibility using seven geographic factors, such as slope and geology. Then, we constructed landslide threshold models with two antecedent soil-wetness indicators. Compared to the traditional recent cumulative rainfall thresholds, the landslide threshold model based on ARI demonstrated higher hit rates and lower false alarm rates. Ensemble predictions indicate that in the early 21st century, the risk of landslides decreases in the Qinghai–Tibet Plateau, Southwest, and Southeast regions but increases in other regions. Mid-century projections show a 10% to 40% increase in landslide risk across most regions. By the end of the century, the risk is expected to rise by more than 15% nationwide, displaying a spatial distribution pattern that intensifies from east to west. [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]

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

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]

Temperature extremes can cause disastrous impacts on ecological and social economic systems. China is very sensitive to climate change, as its warming rate exceeds that of the global mean level. This paper focused on the spatial and temporal changes of the temperature extremes characterized by the 95th percentile of maximum temperature (TX95), the 5th percentile of the minimum temperature (TN5), high-temperature days (HTD) and low-temperature days (LTD). The daily maximum and minimum temperatures generated by PRECIS under different Representative Concentration Pathways (RCPs) are used in the research. The results show that: (1) Model simulation data can reproduce the spatial distribution features of the maximum temperature (Tmax) and minimum temperature (Tmin) as well as that of the extreme temperature indices; (2) By the end of the 21st century (2070-2099), both the Tmax and Tmin are warmer than the baseline level (1961-1990) in China and the eight sub-regions. However, there are regional differences in the asymmetrical warming features, as the Tmin warms more than the Tmax in the northern part of China and the Tibetan Plateau, while the Tmax warms more than the Tmin in the southern part of China; (3) The frequency of the warm extremes would become more usual, as the HTD characterized by the present-day threshold would increase by 106%, 196% and 346%, under RCP2.6, RCP4.5 and RCP8.5, respectively, while the cold extremes characterized by the LTD would become less frequent by the end of the 21st century, decreasing by 75%, 90% and 98% under RCP2.6, RCP4.5 and RCP8.5, respectively. The southern and eastern parts of the Tibetan Plateau respond sensitively to changes in both the hot and cold extremes, suggesting its higher likelihood to suffer from climate warming; (4) The intensity of the warm (cold) extremes would increase (decrease) significantly, characterized by the changes in the TX95 (TN5) by the end of the 21st century, and the magnitude of the increase in the TN5 is larger than that of the TX95 in the national mean value. The changes in both the TX95 and TN5 are larger under the higher versus weaker emission scenario, indicating that it is essential to reduce the GHG emissions and take adaptation measures in the future. [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]

In recent years, there has been a notable surge in lightning events within the Arctic region. This is possibly due to the ongoing trend of global warming that is particularly pronounced in the Arctic. This study focuses on instances of rare lightning activity in the proximity to the North Pole in the last decade. We hypothesize that these occurrences are linked to augmented land heating in Eurasia rather than solely due to the increasing temperatures in the Arctic region. This assertion is substantiated by model simulations using the Weather Research and Forecasting model. [ABSTRACT FROM AUTHOR]

Emissions of fluorinated greenhouse gases (F-gases), which are used as replacements for ozone-depleting substances, have risen sharply since 1995. The rapid increase in F-gas emissions coupled with their global warming potential (GWP) has led to increased worldwide attention to monitoring emission levels and subsequently regulating the use of F-gases. These restrictions apply in particular to applications for which alternative technologies are available that are more economically efficient and have minor or no impact on the Earth's climate system. This paper brings new information about changes in composition of consumed F-gases in the Czech Republic. Since no F-gases are produced in the country, data about F-gas consumption are obtained from three resources which give information about import and export. The paper also describes implementation of newly used F-gases, which are used as replacements for specific F-gases, into emission calculation models. Emissions are estimated according to the methodology developed by the Intergovernmental Panel on Climate Change (IPCC). Although consumption of F-gases with high GWP has already started decreasing, it will have no effect on F-gas emissions for several years. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (PET) is a crucial variable for implementing adaptation measures to mitigate the potential impacts of climate change on water resources. In the context of global warming, PET is essential for predicting water resource supply and demand, guiding irrigation and water management decisions. However, there is limited understanding of the spatiotemporal changes in PET and its driving factors in the hyper-arid regions of Northwest China. In this study, the Hargreaves model was employed to estimate PET in the Hami region from 1991 to 2020. By combining relevant climate data and partial correlation analysis, we investigated the spatiotemporal distribution patterns of PET within the study area and analyzed the factors influencing these patterns. The results showed the following: (1) From 1991 to 2020, the overall PET in the Hami region demonstrated a tendency to rise. The interannual trend rates of PET for the full year, spring, summer, autumn, and winter were 0.933, 2.744, 0.906, 0.488, and −0.406 mm·a-1, respectively. Despite a decreasing trend in winter PET, the other seasonal PET values and the annual PET values exhibited an increasing trend. (2) The spatial distribution of both annual and seasonal PET showed significant regional heterogeneity, following a consistent pattern marked by lower values in the central part and higher values in the surrounding areas. The southern region tended to have relatively high PET, while the northwestern region experienced comparatively low PET. (3) Partial correlation analysis indicated significant differences in the impact of various climatic factors on PET. The maximum temperature emerged as the dominant factor influencing annual PET variation, while precipitation played a leading role in influencing autumn PET variation. This study underscores the influence of climate change on PET in the Hami region, contributing to an enhanced comprehension of PET variations. [ABSTRACT FROM AUTHOR]

Co-occurring extreme heat, drought, and moisture events are increasing under global warming and pose serious threats to ecosystem and food security. However, how to effectively link compound agrometeorological disasters (CADs) with climate change has not been well assessed. In this study, we focus on the comprehensive influence of large-scale climate factors on CADs rather than extreme meteorological elements. The results indicate that there are two main CADs of spring maize in Shenyang, Northeast China (NEC), including concurrent drought and cold damage (DC) and drought in multiple growth periods (MD). The related circulation anomalies at mid–high latitudes are identified as four patterns, namely, the Northeast Asia Low (NEAL) and Ural High (UH) patterns affecting DC, the Baikal High and Okhotsk Low (BHOL), and the Northeast Asia High (NEAH) patterns leading to MD. The vertical profile and water vapor transport anomalies further demonstrate the influence mechanism of large-scale circulation on compound heat–moisture stresses. This study highlights the role of atmospheric circulation, which can provide effective predictors for these synergistic agrometeorological disasters. [ABSTRACT FROM AUTHOR]

This review identifies a critical problem in the fundamental physics of current climate models. The large greenhouse effect of rising CO2 assumed in climate models is assessed by six key observations from ground- and satellite-based measurements. This assessment is enhanced by statistical analyses and model calculations of global or regional mean surface temperature changes by conventional climate models and by a conceptual quantum physical model of global warming due to halogen-containing greenhouse gases (halo-GHGs). The postulated large radiative forcing of CO2 in conventional climate models does not agree with satellite observations. Satellite-observed warming pattern resembles closely the atmospheric distribution of chlorofluorocarbons (CFCs). This review helps understand recent remarkable observations of reversals from cooling to warming in the lower stratosphere over most continents and in the upper stratosphere at high latitudes, surface warming cessations in the Antarctic, North America, UK, and Northern-Hemisphere (NH) extratropics, and the stabilization in NH or North America snow cover, since the turn of the century. The complementary observation of surface temperature changes in 3 representative regions (Central England, the Antarctic, and the Arctic) sheds new light on the primary mechanism of global warming. These observations agree well with not CO2-based climate models but the CFC-warming quantum physical model. The latter offers parameter-free analytical calculations of surface temperature changes, exhibiting remarkable agreement with observations. These observations overwhelmingly support an emerging picture that halo-GHGs made the dominant contribution to global warming in the late 20th century and that a gradual reversal in warming has occurred since ~2005 due to the phasing out of halo-GHGs. Advances and insights from this review may help humans make rational policies to reverse the past warming and maintain a healthy economy and ecosystem. [ABSTRACT FROM AUTHOR]

Our understanding of the time variability of intense cyclones in the Mediterranean region is still lacking despite its importance for the long-term forecast of climate anomalies. This study examines the month-to-month variability and predictability of cyclones, the intensity of which exceeded the 75th percentile (intense cyclones) and the 95th percentile (extreme cyclones), over the Western and Eastern Mediterranean. The locations of cyclones were obtained by applying the method of M. Yu. Bardin on the 6-hourly 1000 hPa geopotential height data from the NCEP/NCAR reanalysis for the period 1951–2017 (67 years). It was shown that annual frequencies of cyclones were higher in the Western Mediterranean due to the contribution of spring and autumn; monthly averages were higher in the Eastern Mediterranean in December/January–March for intense/extreme cyclones. In the context of global warming, no linear trends significant at the 90% confidence level were found in the variability of intense and extreme cyclones, except for a positive trend in autumn extreme cyclones over the Eastern Mediterranean. The time series of cyclones in both parts of the Mediterranean were characterized by a pronounced interannual variability with a noticeable decadal modulation. According to spectral analysis, these interannual periods were multiples of 2–3 years corresponding to the main global teleconnection patterns. Seasonally, the most energy was concentrated in winter spectra; spring and autumn spectra had lower comparable magnitudes. The correlation analysis between the frequency of cyclones and the indices of the main atmospheric patterns showed that the main synchronous patterns for intense and extreme Mediterranean cyclones in September–April were the Mediterranean Oscillation (with the opposite signs for the Western and Eastern Mediterranean), Scandinavia pattern (positive correlation), and East Atlantic Oscillation (negative correlation). Additional important synchronous teleconnection patterns for some months were the Arctic Oscillation and East Atlantic/West Russia pattern for the Western Mediterranean, and the Polar/Eurasia pattern and Tropical Northern Hemisphere pattern for the Eastern Mediterranean. The outcome of this paper was the use of an artificial neural network model with inputs of global teleconnection indices both in the atmosphere and ocean to describe the temporal variability of the frequency of intense cyclones in the Western and Eastern Mediterranean. The predictability of intense cyclones was shown with the possibility of forecasts with a lead time of 0, 2, 4, and 6 months for the Western Mediterranean in October, January, February, April, and May, and for the Eastern Mediterranean in January, February, March, April, and May. One of the applications of this model may be in forecasting the evolution of the monthly frequency of cyclones with a lead time of 2 to 6 months. [ABSTRACT FROM AUTHOR]

The existence of global warming is common knowledge. However, it can be predicted that there may be cooling zones worldwide based on the mechanism of terrestrial biophysical processes. Here, the Theil–Sen median trend, the Mann–Kendall trend test method, continuous wavelet transformation, and the Hurst exponent were used to study the cooling trends, abrupt change times, periodicity, and future sustainability of temperature changes in different cooling zones since the 1900s based on the CRU dataset. We found an amazing result; 8,305,500 km2 of land surface had been cooling since the 1900s, covering five continents and 32 countries, accounting for 86% of land area in China, and distributed over 16 zones. The average cooling rate of the cooling zones was −0.24 °C/century. The maximum cooling rate was −1.40 °C/century, and it was 1.43 times the average rate of global land warming (0.98 °C/century). The cooling zones near the sea were greatly influenced by ocean currents and were mainly affected by a small time scale periodicity of less than 30 years, whereas the cold zones located relatively far from the sea and less affected by ocean currents were mainly affected by medium time scales of more than 30 years. Moreover, 32.33% of the cooling zones, involving 2,684,900 km2, will be continuously cooling in the future, and the rest will probably warm up in 2114, 2041, 2096, 2099, 2119, 2073, 2048, and 2101, respectively. The study will help us to further understand the essential characteristics of global climate change, and to find more theoretical bases for mitigating global warming and exploring surface cooling mechanisms. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change (ACC) has evolved into a set of crises due to society's deep economic dependency on fossil fuels. These multiple crises have been well documented and span diverse ecological, human health and economic settings. Given the scale and breadth of CC impacts, expert labeling of the issues has gradually changed from the somewhat benign sounding "global warming" to the more frightening description of a "climate emergency". Notwithstanding calls for transformative societal change, serious attempts to confront ACC have been hampered by decades of government policy inaction, various scientific debates, political conservatism and denial and public ignorance or apathy. Meanwhile, atmospheric greenhouse gas concentrations have increased inexorably and show no sign of plateauing. The impacts of ACC are becoming evident sooner than expected, and projections for the future of the planet's ecosystems and the human population which depends on them are dire. Proposals to geoengineer the climate are currently being hotly debated within the scientific community but may prove to be a last resort if the impacts of unmitigated warming become even more severe. [ABSTRACT FROM AUTHOR]

Frequent droughts may have negative influences on the ecosystem (i.e., terrestrial vegetation) under a warming climate condition. In this study, the linear regression method was first used to analyze trends in vegetation change (normalized difference vegetation index (NDVI)) and drought indices (Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI)). The Pearson Correlation analysis was then used to quantify drought impacts on terrestrial vegetation in the Weihe River Basin (WRB); in particular, the response time of vegetation to multiple time scales of drought (RTVD) in the WRB was also investigated. The trend analysis results indicated that 89.77% of the area of the basin showed a significant increasing trend in NDVI from 2000 to 2019. There were also significant variations in NDVI during the year, with the highest rate in June (0.01) and the lowest rate in January (0.002). From 2000 to 2019, SPI and SPEI at different time scales in the WRB showed an overall increasing trend, which indicated that the drought was alleviated. The results of correlation analysis showed that the response time of vegetation to drought in the WRB from 2000 to 2019 was significantly spatially heterogeneous. For NDVI to SPEI, the response time of 12 months was widely distributed in the north; however, the response time of 24 months was mainly distributed in the middle basin. The response time of NDVI to SPI was short and was mainly concentrated at 3 and 6 months; in detail, the response time of 3 months was mainly distributed in the east, while a response time of 6 months was widely distributed in the west. In autumn and winter, the response time of NDVI to SPEI was longer (12 and 24 months), while the response time of NDVI to SPI was shorter (3 months). From the maximum correlation coefficient, the response of grassland to drought (SPEI and SPI) at different time scales (i.e., 6, 12, and 24 months) was higher than that of cultivated land, forestland, and artificial surface. The results may help improve our understanding of the impacts of climatic changes on vegetation cover. [ABSTRACT FROM AUTHOR]

Atmospheric ducting is an anomalous atmospheric structure that affects electromagnetic wave propagation. In the context of global warming, the navigation capacity of the Arctic is increased, and the atmospheric duct can affect communication and navigation in the Arctic. In this study, based on the European Centre for Medium-Range Weather Forecasts reanalysis data (ERA-interim), the climate characteristics and their variations of atmospheric ducts over the Arctic polar region (north of 60° N) from 1989 to 2018 were analyzed, including the occurrence frequency, spatial distribution, thickness and intensity of the atmospheric ducts. The results show that the overall frequency of atmospheric ducts in the Arctic is low, with the average frequency of all types of ducts being less than 10% throughout the year. The frequency of surface ducts is 2~3 times that of elevated ducts. More than 90% of the atmospheric ducts in the Arctic have a trapped layer with a thickness of less than 100 m, and the average thickness of surface ducts is higher than that of the elevated ducts. The intensity of the Arctic surface ducts is stronger than that of the elevated ducts, with an average intensity of 2.1 M (±2.3 M) to 4.5 M (±4.5 M) for the surface ducts and 1.7 M (±2 M) to 2.5 M (±2.9 M) for the elevated ducts. There is a positive correlation between the ducts' trapped layer thickness and duct intensity. The variation in atmospheric ducts is responsive to the changes in atmospheric circulation and the sea ice extent. This anomalous circulation changes surface wind in the Arctic, which affects the formation and maintenance of the ducts. The trends of ducts in the Arctic Ocean are consistent with those of the Arctic Sea ice extent, while the Arctic continental and coastal ducts show the opposite trend. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is an existential threat whose influences continue to increase in severity. It is pivotal to understand the implications of climate change and their effects on mental health. This integrative review aims to summarize the relevant evidence examining the harm climate change may have on mental health, suggest potential mechanisms and discuss implications. Empirical evidence has begun to indicate that negative mental health outcomes are a relevant and notable consequence of climate change. Specifically, these negative outcomes range from increased rates of psychiatric diagnoses such as depression, anxiety and post-traumatic stress disorder to higher measures of suicide, aggression and crime. Potential mechanisms are thought to include neuroinflammatory responses to stress, maladaptive serotonergic receptors and detrimental effects on one's own physical health, as well as the community wellbeing. While climate change and mental health are salient areas of research, the evidence examining an association is limited. Therefore, further work should be conducted to delineate exact pathways of action to explain the mediators and mechanisms of the interaction between climate change and mental health. [ABSTRACT FROM AUTHOR]

Data from historical observatories and future simulations were analyzed using the representative concentration pathway (RCP) 8.5 scenario, which covered the period from 1951 to 2100. In order to characterize the drought, three widely used drought indicators were used: the standardized precipitation index (SPI), the reconnaissance drought index (RDI), and the standardized precipitation and evapotranspiration index (SPEI). The ensemble of the seven (7) GCMs that used RCA-4 was able to capture several useful characteristics of Nigeria's historical climatology. Future climates were forecasted to be wetter than previous periods during the study period based on the output of drought characteristics as determined by SPI. SPEI and RDI predicted drier weather, in contrast. SPEI and RDI's predictions must have been based on the effect of rising temperatures brought on by global warming as depicted by RCP 8.5, which would then have an impact on the rate of evapotranspiration. According to drought studies using the RCP 8.5 scenario, rising temperatures will probably cause more severe/extreme droughts to occur more frequently. SPEI drought frequency changes in Nigeria often range from 0.75 (2031–2060) to 1.80 (2071–2100) month/year, whereas RDI changes typically range from 0.30 (2031–2060) to 0.60 (2071–2100) month/year. The frequency of drought incidence has recently increased and is now harder to forecast. Since the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) and the Sustainable Development Goals (SDGs) have few more years left to be completed, drastic efforts must be made to create climate-resilient systems that can tackle the effects that climate change may have on the water resources and agricultural sectors. [ABSTRACT FROM AUTHOR]

The glaciers in Arctic Archipelago of Svalbard, located in the hotspot of global warming, are sensitive to climate change. The assessment of glacier mass balance in Svalbard is one of the hotspots in Arctic research. In this study, we use the laser altimetry ICESat-2 data to investigate the elevation and mass change of Svalbard from 2019 to 2021 by a hypsometric approach. It is shown that the Svalbard-wide elevation change rate is −0.775 ± 0.225 m yr−1 in 2019–2021, corresponding to the mass change of −14.843 ± 4.024 Gt yr−1. All regions exhibit a negative mass balance, and the highest mass loss rates are observed at Northwestern Spitsbergen. Compared with ICESat/ICESat-2 (2003–2008 to 2019) and Cryosat-2 (2011–2017) periods, the elevation change from 2019 to 2021 has accelerated, with an increase by 158.3% and 31.5%, respectively, leading to equilibrium line altitude increasing to 750 m. Among the seven subregions, four are accelerated. It is shown that the overall accelerated glacier mass loss in Svalbard is expected to be caused by increasing surge events and temperature rise. [ABSTRACT FROM AUTHOR]

The Earth has seen El Niño-Southern Oscillation (ENSO)—the leading mode of interannual climate variability—for at least millennia and likely over millions of years. This paper reviews previous studies from perspectives of both paleoclimate proxy data (from traditional sediment records to the latest high-resolution oxygen isotope records) and model simulations (including earlier intermediate models to the latest isotope-enabled coupled models). It summarizes current understanding of ENSO’s past evolution during both interglacial and glacial periods and its response to external climatic forcings such as volcanic, orbital, ice-sheet and greenhouse gas forcings. Due to the intrinsic irregularity of ENSO and its complicated relationship with other climate phenomena, reconstructions and model simulations of ENSO variability are subject to inherent difficulties in interpretations and biases. Resolving these challenges through new data syntheses, new statistical methods, more complex climate model simulations as well as direct model-data comparisons can potentially better constrain uncertainty regarding ENSO’s response to future global warming. [ABSTRACT FROM AUTHOR]

Under global warming, the climate in semi-arid inland Eurasia (SAIE) has changed in an opposite manner, thereby seriously impacting the local ecological environment. However, the key influencing factors and physical mechanism remain inconclusive. In this paper, we remodel the precipitation recycling ratio (PRR) model to assess the contributions of moisture from different water vapor sources to local precipitation, analyze the characteristics of the PRR and precipitation in SAIE, and provide possible physical reasons based on the Clausius–Clapeyron equation. It is found that the PRR increased from 1970 to 2017 as the result of linear trend analysis, with obvious seasonality. Moreover, the component of precipitation contributed by locally evaporated moisture (Pl), and that contributed by advected moisture (Pa) as well as the total precipitation (P), increased during the past 48 years. In particular, the Pa, Pl, and P in autumn and winter all increased obviously during the past 20 years from the interdecadal change trend, as well as the PRR (Pl/P), which was opposite to the decrease in the total water vapor input I(Ω) in the horizontal direction. According to the Clausius–Clapeyron equation, one of the causes might be that global warming has accelerated the local water cycle and driven the increase in Pa, and the increase in atmospheric water holding capacity caused by global warming provides the power source. We suggest that the climate’s transformation from dry to wet in SAIE can only be temporary since SAIE is an inland area and the adjustment of atmospheric circulation did not lead to the increase in external water vapor.

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]

Manifestations of global warming in the Arctic include amplifications of temperature increases and a general increase in precipitation. Although topography complicates the pattern of these changes in regions such as Alaska, the amplified warming and general increase in precipitation are already apparent in observational data. Changes in snow cover are complicated by the opposing effects of warming and increased precipitation. In this study, high-resolution (0.25°) outputs from simulations by the Community Atmosphere Model, version 5, were analyzed for changes in snow under stabilized global warming scenarios of 1.5 °C, 2.0 °C and 3.0 °C. Future changes in snowfall are characterized by a north–south gradient over Alaska and an east–west gradient over Eurasia. Increased snowfall is projected for northern Alaska, northern Canada and Siberia, while milder regions such as southern Alaska and Europe receive less snow in a warmer climate. Overall, the results indicate that the majority of the land area poleward of 55°N will experience a reduction in snow. The approximate threshold of global warming for a statistically significant increase in temperature over 50% of the pan-Arctic land area is 1.5 °C. The corresponding threshold for precipitation is approximately 2.0 °C. The global warming threshold for the loss of high-elevation snow in Alaska is approximately 2.0 °C. The results imply that limiting global warming to the Paris Agreement target is necessary to prevent significant changes in winter climates in Alaska and the Arctic. [ABSTRACT FROM AUTHOR]

The warming observed over the past summers since 2000 is unprecedented in climate records in Europe and especially in France. Extreme temperatures and heat spells were often analyzed in the literature by applying extreme value theory but rarely in a non-stationary (NS) framework and duration modeling is often excluded. For a modern risk-based approach, it is important to have knowledge of the duration, magnitude, and frequency of occurrence of heat spells in a climate variability and change context. Yet, despite their obvious importance, teleconnections and associated climate indices (CIs) have often been excluded from heat spell modelling. The notion of duration is also not easily interpretable in a frequency analysis and can even be subtle, especially in a NS context. In this study, we used time-varying statistical distributions with parameters conditional on covariates representing the time and CIs. The daily maximum temperatures (DMTs) observed at the Orange and Dijon stations in France were used as a case study. This paper highlights a possible relationship between some large-scale climate patterns and the heat spells in France. Overall, the results suggest that considering the combined effect of global warming and these patterns in NS models is useful for a more appropriate characterization of the hazard heat spells in France. [ABSTRACT FROM AUTHOR]

Estimating temperature extremes (TEs) and associated uncertainties under the non-stationary (NS) assumption is a key research question in several domains, including the nuclear safety field. Methods for estimating TEs and associated confidence intervals (CIs) have often been used in the literature but in a stationary context, separately and without detailed comparison. The extreme value theory is often used to assess risks in a context of climate change. It provides an accurate indication of distributions describing the frequency of occurrence of TEs. However, in an NS context, the notion of the return period is not easily interpretable. For instance, to predict a high return level (RL) in a future year, time-varying distributions must be used and compared. This study examines the performance of a new concept to predict RLs in an NS context and compares three methods for constructing the associated CIs (delta, profile likelihood, and parametric bootstrap). The present work takes up the concept of integrated return periods that define the T-year RL as the level for which the expected number of events in a T-year period is one and proposes a new method based on conditional predictions that is useful for predicting high RLs of extreme events in the near future (the 100-year RL in the year 2030, for instance). The daily maximum temperature (DMT) observed at the Orange Station in France was used as a case study. Several trend models were compared and a new likelihood-based method to detect breaks in TEs is proposed. The analyses were conducted assuming the time-varying Generalized Extreme Value (GEV) distribution. The concepts have been implemented in a software package (Non-Stationary Generalized Extreme Value (NSGEV)). The application demonstrates that the RL estimates for NS situations can be quite different from those corresponding to stationary conditions. Overall, the results suggest that the NS analysis can be helpful in making a more appropriate assessment of the risk for periodic safety reviews during the life of a nuclear power plant (NPP). [ABSTRACT FROM AUTHOR]

Studies based on the 10th (90th) percentiles as thresholds have been presented to assess moderate extremes in China and globally. However, there has been notably little research on the occurrences of high extremes of warm days and hot days (TX95p and TX99p) and cold nights and very cold nights (TN05p and TN01p), based on the 95th and 99th (5th and 1st) percentiles of the daily maximum (minimum) temperature data at a certain station in the period 1971-2000, which have more direct impacts on society and the ecosystem. The trends analyses of cool nights or warm days are based upon the hypothesis that expects a linear trend and no abrupt change. However, abrupt changes in the climate, especially in extreme temperatures, have been pointed to as a major threat to ecosystem services. This study demonstrates that (1) the mean frequencies of TX95p and TX99p increased by 1.80 day/10 year and 0.62 day/10 year, respectively, and that those of TN05p and TN01p decreased by 3.18 day/10 year and 1.01 day/10 year, respectively, in mainland China. Additionally, the TX95p and TX99p increased significantly by 50.42% and 58.21%, respectively, while the TN05p and TN01p of all of the stations decreased significantly by 83.76% and 76.48%, respectively. Finally, (2) the TX95p and TX99p trends underwent abrupt changes in the 1990s or 2000s, but the trends of TN05p and TN01p experienced abrupt changes in the late 1970s and early 1980s. After the abrupt change points, the trend of warm and hot days increased more rapidly than before in most regions, but the trend of cold days and very cold days decreased more slowly than before in most regions, which indicates a greater risk of heat waves in the future. [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]

As one of the largest arid and semi-arid regions in the world, central Asia (CA) is very sensitive to changes in regional climate. However, because of the poor continuity of daily observational precipitation records in CA, the spatial and temporal variations of extreme precipitation in recent decades remain unclear. Considering their good spatial and temporal continuity, gridded data, such as Climate Prediction Center (CPC) global precipitation, and reanalysis data, such as ERA-Interim (ERA), are helpful for exploring the spatial–temporal variations of extreme precipitation. This study evaluates how well CPC and ERA can represent observed precipitation extremes by comparing the differences in eight extreme precipitation indices and observation data at 84 meteorological stations. The results indicate that the CPC (except for 1979–1981) is more suitable for depicting changes in precipitation extremes. Based on the CPC data for the period 1982–2020, we found that seven indices of precipitation extremes, including consecutive wet days (CWD), max1-day precipitation amount (Rx1day), max5-day precipitation amount (Rx5day), number of heavy precipitation days (R10), very wet days (R95p), annual total precipitation in wet days (PRCPTOT), and simple precipitation intensity index (SDII) have increased by 0.2 d/10a, 0.9 mm/10a, 1.8 mm/10a, 0.3 d/10, 8.4 mm/10a, 14.3 mm/10a and 0.1 mm/d/10a, respectively, and the consecutive dry days (CDDs) have decreased by −3.10 d/10a. It is notable that CDDs decreased significantly in the north of Xinjiang (XJ) but increased in Kyrgyzstan (KG), Tajikistan (TI), and eastern Turkmenistan (TX). The other indices increased clearly in the west of XJ, north of Kazakhstan (KZ), and east of KG but decreased in the south of KG, TI, and parts of XJ. For most indices, the largest change occurred in spring, the main season of precipitation in CA. Therefore, the large-scale atmospheric circulation in April is analyzed to contrast between the most and least precipitation years for the region. A typical circulation pattern in April for those extremely wet years includes an abnormal low-pressure center at 850 hpa to the east of the Caspian Sea, which enhances the southerly winds from the Indian Ocean and hence the transportation of water vapor required for precipitation into CA. This abnormal circulation pattern occurred more frequently after 2001 than before, thus partly explaining the recent increasing trends of precipitation extremes in CA. [ABSTRACT FROM AUTHOR]

The Earth's ionosphere presents long-term trends that have been of interest since a pioneering study in 1989 suggesting that greenhouse gases increasing due to anthropogenic activity will produce not only a troposphere global warming, but a cooling in the upper atmosphere as well. Since then, long-term changes in the upper atmosphere, and particularly in the ionosphere, have become a significant topic in global change studies with many results already published. There are also other ionospheric long-term change forcings of natural origin, such as the Earth's magnetic field secular variation with very special characteristics at equatorial and low latitudes. The ionosphere, as a part of the space weather environment, plays a crucial role to the point that it could certainly be said that space weather cannot be understood without reference to it. In this work, theoretical and experimental results on equatorial and low-latitude ionospheric trends linked to the geomagnetic field secular variation are reviewed and analyzed. Controversies and gaps in existing knowledge are identified together with important areas for future study. These trends, although weak when compared to other ionospheric variations, are steady and may become significant in the future and important even now for long-term space weather forecasts. [ABSTRACT FROM AUTHOR]

Climate change implications are a severe risk to food security and the economy. Global warming could disturb the production of both rainfed and irrigated agriculture thru the amplify of yield water requests in many areas. In this study, the fast-track projections available through the Inter-Sectors Impact Model Intercomparison Project (ISI-MIP) were presented and analyzed to assess the effects of two global warming (GW) levels (1.5 and 2.0 °C) on the maize and wheat yields in Egypt. Outcomes proposed spatial variations in the effects of temperature change on crop yield. Compared with the referenced situation, an observed national average change in wheat yield about 5.0% (0.0% to 9.0%) and 5.0% (−3.0% to 14.0%) under GW1.5 and GW2.0 respectively. While for maize yield, the change in national average about −1.0% (−5.0% to 3.0%) and −4.0% (−8.0% to 2.0%) under GW1.5 and GW2.0 respectively. GW1.5 could be helpful for wheat yield, but the positive effect decayed when the warming level reached 2.0 °C overhead the pre-industrial level. Nevertheless, the possible deviations to Egypt's maize production under the GW1.5 and GW2.0 scenarios are unclear where the models do not agree with the sign of change. Adjusting the temperature rise within 1.5 °C would diminish the yield reduction, as it is an extraordinary priority to safeguard crop production. To achieve Progress of innovative agronomic managing plans and swapping to additional drought-resistant crops may be valuable for coping with climate change in regions vulnerable to yield decline. [ABSTRACT FROM AUTHOR]

Simple Summary: Polar regions are more sensitive to the increase in atmospheric CO2 concentration than the rest of the world. This phenomenon is known as the Polar Amplification and is related to many nonlinear, complex coupled ocean-atmosphere processes with effects beyond high latitudes. Aiming to account for the Polar Amplification, this study used global climate simulations to investigate the effects of three different global warming thresholds (1.5, 2 and 3 °C) in the warming and sea ice conditions of both poles. Our results shown high climate sensitivity in the Arctic and Antarctica as a response to the increase in atmospheric CO2 concentration. The warming signal is not symmetric in the two poles: the Arctic warms faster than Antarctica in all climate scenarios. Global warming crosses the minimum (maximum) future scenarios thresholds of +1.5 °C (+3 °C) around 2024 (2063). The equivalent Arctic (Antarctic) warming for these years is 3.6 (1.5) °C and (3.2) 6.6 °C, respectively. Although limited, Global Climate models used here are important tools to help on better understand the projected effects of climate change in high latitudes. One of the most visible signs of global warming is the fast change in the polar regions. The increase in Arctic temperatures, for instance, is almost twice as large as the global average in recent decades. This phenomenon is known as the Arctic Amplification and reflects several mutually supporting processes. An equivalent albeit less studied phenomenon occurs in Antarctica. Here, we used numerical climate simulations obtained from CMIP5 and CMIP6 to investigate the effects of +1.5, 2 and 3 °C warming thresholds for sea ice changes and polar amplification. Our results show robust patterns of near-surface air-temperature response to global warming at high latitudes. The year in which the average air temperatures brought from CMIP5 and CMIP6 models rises by 1.5 °C is 2024. An average rise of 2 °C (3 °C) global warming occurs in 2042 (2063). The equivalent warming at northern (southern) high latitudes under scenarios of 1.5 °C global warming is about 3 °C (1.8 °C). In scenarios of 3 °C global warming, the equivalent warming in the Arctic (Antarctica) is close to 7 °C (3.5 °C). Ice-free conditions are found in all warming thresholds for both the Arctic and Antarctica, especially from the year 2030 onwards. [ABSTRACT FROM AUTHOR]

The Yarlung Zangbo River is the largest river on the Tibetan Plateau and a major international river in South Asia. Changes in the blue and green water resources in its basin are of great importance to the surrounding local and Asian regions in the context of global warming. This research used the Soil and Water Assessment Tool model to estimate blue and green flows (BWF and GWF) and analyze the spatial-temporal distribution characteristics under different hypothetical climate change scenarios. The results show that (1) the multi-year average BWF in the middle and upper reaches of the Yarlung Zangbo River Basin is 176.2 mm, the GWF is 213.1 mm, and the difference between precipitation and total water resources is only 5.4 mm; (2) both BWF and GWF in this basin showed a slightly increasing trend from 1980 to 2010, but the distribution of subbasins from upstream to downstream is decreasing; and (3) GWF has a positive correlation with both precipitation and temperature, but BWF only increases with precipitation and decreases with increasing temperature. Moreover, the change in blue and green water resources is more sensitive to the changes in precipitation than to changes in the temperature. [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal trends of temperature in the context of global warming is significant for public health. Although many studies have examined changes in temperature and the impacts on human health over the past few decades in many regions, they have often been carried out in data-rich regions and have rarely considered acclimatization explicitly. The most frequent temperature (MFT) indicator provides us with the ability to solve this problem. MFT is defined as the longest period of temperature throughout the year to which a human is exposed and therefore acclimates. In this study, we propose a new method to estimate the number of heat exposure days from the perspective of temperature distribution and MFT, based on the daily mean temperature readings of 2142 weather stations in eight major climate zones in China over the past 20 years. This method can be used to calculate the number of heat exposure days in terms of heat-related mortality risk without the need for mortality data. We estimated the distribution and changes of annual mean temperature (AMT), minimum mortality temperature (MMT), and the number of heat exposure days in different climate zones in China. The AMT, MMT, and number of heat exposure days vary considerably across China. They all tend to decrease gradually from low to high latitudes. Heat exposure days are closely related to the risk of heat-related mortality. In addition, we utilized multiple linear regression (MLR) to analyze the association between the risk of heat-related mortality and the city and its climatic characteristics. Results showed that the number of heat exposure days, GDP per capita, urban population ratio, proportion of elderly population, and climate zone were found to modify the estimate on heat effect, with an R2 of 0.71. These findings will be helpful for the creation of public policies protecting against high-temperature-induced mortalities. [ABSTRACT FROM AUTHOR]

We used CMIP6 GCMs to quantify climate change impacts on precipitation and potential evapotranspiration (PET) across water management zones (WMZs) in Uganda. Future changes are assessed based on four Shared Socioeconomic Pathways (SSP) scenarios including SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 over the periods 2021–2040, 2041–2060, 2061–2080, and 2081–2100. Both precipitation and PET are generally projected to increase across all the WMZs. Annual PET in the 2030s, 2050s, 2070s, 2090s will increase in the ranges 1.1–4.0%, 4.8–7.9%, 5.1–11.8%, and 5.3–17.1%, respectively. For the respective periods, annual precipitation will increase in the ranges 4.0–7.8%, 7.8–12.5%, 7.9–19.9%, and 6.9–26.3%. The lower and upper limits of these change ranges for both precipitation and PET are, respectively, derived under SSP1-2.6 and SSP5-8.5 scenarios. Climate change will impact on PET or precipitation disproportionately across the WMZs. While the eastern WMZ (Kyoga) will experience the largest projected precipitation increase especially towards the end of the century, the southern WMZ (Victoria) exhibited the largest PET increase. Our findings are relevant for understanding hydrological impacts of climate change across Uganda, in the background of global warming. Thus, the water sector should devise and implement adaptation measures to impede future socioeconomic and environmental crises in the country. [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]

Positive degree-day (PDD) indicates the accumulated positive temperature in a given time period; it directly relates to the melting of snow and ice, and it is a key parameter between global warming and cryosphere changes. In this study, we calculated the PDD based on the daily mean temperatures from 1960 to 2018 at meteorological stations, and we used measured and interpolated data to determine spatial and temporal distribution and changes in PDD in western China (WC). Results show that the mean annual, warm season, and cold season PDD values at 209 meteorological stations were 3652.2, 2832.9, and 819.3 °C, respectively. PDD spatial distribution in WC is similar to that of air temperature. In WC, PDD mainly ranged from 0 to 5000, 1000 to 4000, and 0 to 1000 °C year−1, respectively for annual, warm season, and cold season. From 1960 to 2018, the observed mean initial day of PDD moved forward by 8.3 days, and the final day was delayed by 8.2 days, with the duration expanding to 16.6 days; the trend in PDD reversed in the 1980s and the change rate in PDD for annual, warm season and cold season was 6.6, 3.8, and 2.7 °C year−1, respectively. Regionally, PDD increased in almost all areas; the high PDD advanced from south to north, east to west, desert to mountain, and low to high altitudes. The results also showed that the warming rate of PDD was lower in the cold season and in high-altitude areas, which was opposite to the observed temperature patterns, however, the non-linear relationship between PDD and mean temperature over a period of time is the main reason for this phenomenon. This study adds more details for the understanding of climate change in WC, and suggests that more attention should be paid to PDD in the study of cryosphere changes. [ABSTRACT FROM AUTHOR]

The accelerated global warming and heterogeneous change in precipitation have been resulting in climate system shifts, which plays a key role in the stability of ecosystem and social economic development. Central Asia is account 80% of the temperate desert, characterized by fragile ecosystem; however, it has experienced the fastest warming in recent decades and projected warming in future. The Köppen-Geiger climate classification is a useful tool to assess the potential impacts of climate change on regional ecosystem. The spatial shift and temporal evolution of each climatic zone based on Köppen-Geiger climate classification are analyzed in historical and future period under different scenarios (RCP2.6, RCP4.5 and RCP8.5), high risk regions that might experience more frequent climatic zone shifts are delimited in this study, which could provide the useful information for developing mitigate strategies in coping with the warming threat. The hotter and dryer subtypes of arid climatic zone and warmer subtypes of temperate climatic zone expanded their coverage in Central Asia, corresponding to the tundra climatic, cooler subtype of arid and temperate climatic zone contracted. Based on a method defining the climate-sensitivity, high risk regions are mainly distributed in northern Kazakhstan and Tianshan Mountains region. [ABSTRACT FROM AUTHOR]

Climate modelling output that was provided under the latest Coupled Model Intercomparison Project (CMIP6) shows significant changes in model-specific Equilibrium Climate Sensitivity (ECS) as compared to CMIP5. The newer versions of many Global Climate Models (GCMs) report higher ECS values that result in stronger global warming than previously estimated. At the same time, the multi-GCM spread of ECS is significantly larger than under CMIP5. Here, we analyse how the differences between CMIP5 and CMIP6 affect climate projections for Germany. We use the statistical-empirical downscaling method EPISODES in order to downscale GCM data for the scenario pairs RCP4.5/SSP2-4.5 and RCP8.5/SSP5-8.5. We use data sets of the GCMs CanESM, EC-Earth, MPI-ESM, and NorESM. The results show that the GCM-specific changes in the ECS also have an impact at the regional scale. While the temperature signal under regional climate change remains comparable for both CMIP generations in the MPI-ESM chain, the temperature signal increases by up to 3 °C for the RCP8.5/SSP5-8.5 scenario pair in the EC-Earth chain. Changes in precipitation are less pronounced and they only show notable differences at the seasonal scale. The reported changes in the climate signal will have direct consequences for society. Climate change impacts previously projected for the high-emission RCP8.5 scenario might occur equally under the new SSP2-4.5 scenario. [ABSTRACT FROM AUTHOR]

Changes in climate extremes under 1.5 °C and 2 °C global warming may impact agricultural production across Central Asia. We used the simulated daily data of average temperature, maximum temperature, minimum temperature, and precipitation provided by the Inter-Sectoral Impact Model Intercomparison Project and analyzed the current climate status and future projected changes of a set of climate extreme indices related to agricultural production under 1.5 °C and 2 °C global warming. In addition, the possible impacts of climate change on agricultural production in Central Asia were discussed. The results show that the annual mean temperature in Central Asia will increase by 1.48 °C and 2.34 °C at 1.5 °C and 2 °C warming levels, respectively, compared to the base period (1986–2005), and the increasing trends are significant at the α = 0.01 level for all grids. The number of warm days and growing season length will increase. Under the 1.5 °C scenario, the mean annual total precipitation (PRCPTOT) and heavy precipitation (R95P) will experience increases of 7.68% and 26.55%, respectively, and the consecutive dry days (CDD) will be reduced by 1.1 days. However, the standardized precipitation evapotranspiration index (SPEI) shows significant drought conditions in most of Central Asia (more than 60%). Under the 2 °C scenario, there will be a 3.89% increase in PRCPTOT and a 24.78% increase in R95P. Nevertheless, accompanying the increase in CDD (0.8 day) and the decrease in SPEI, drought conditions will be further exacerbated. These results indicate that Central Asia is likely to face more severe ecological problems in the future, which will threaten the regional agricultural production and the food security. Therefore, adaptation strategies should be implemented immediately to mitigate the negative impacts of climate change on Central Asia's agriculture. [ABSTRACT FROM AUTHOR]

In the Mediterranean region, climate change is likely to generate an increase in water demand and the deterioration of its quality. The adoption of precision viticulture and the best available techniques aiming at sustainable production, minimizing the impact on natural resources and reducing production costs, has therefore been a goal of winegrowers. In this work, the water footprint (WFP) in the wine sector was evaluated, from the vineyard to the bottle, through the implementation of a methodology based on field experiments and life cycle assessment (LCA) on two Portuguese case studies. Regarding direct water footprint, it ranged from 366 to 899 L/FU (0.75 L bottle), with green water being the most significant component, representing more than 50% of the overall water footprint. The approach used in the current study revealed that although more than 97.5% of the water footprint is associated with vineyard, the winery stage is responsible for more than 75% of the global warming potential indicator. A linear correlation between the carbon footprint and the indirect blue water footprint was also observed for both case studies. Climate change is expected to cause an earlier and prolonged water stress period, resulting in an increase of about 40% to 82% of blue WFP. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa (SSA) has been identified by the Intergovernmental Panel on Climate Change (IPCC) as being the most vulnerable region to climate change impacts. A major concern is the increase in extreme weather events (EWE) such as storms, floods, droughts, heatwaves, wildfires, and landslides in SSA and their potential to affect the health and well-being of children and adolescents. The objective of this systematic review is to examine the direct and indirect impacts of EWE on the mental health of children and adolescents living in SSA, in order to inform protective adaptation strategies and promote resilience. A meta-analysis will not be possible, since the assumption is that limited studies have been published on the EWE-associated mental health impacts on children and adolescents living in SSA and that those studies that are available are heterogenous. There is acknowledgement in the global literature of the need to highlight child and adolescent mental health more prominently in climate change health strategies and policies. It is vital that adaptation strategies are informed by research on risk prevention and promotion of resilience to ensure the mental health of children and adolescents is protected. [ABSTRACT FROM AUTHOR]

This study assesses the changes in precipitation (P) and in evapotranspiration (ET) under 1.5 °C and 2.0 °C global warming levels (GWLs) over Senegal in West Africa. A set of twenty Regional Climate Model (RCM) simulations within the Coordinated Regional Downscaling Experiment (CORDEX) following the Representative Concentration Pathways (RCP) 4.5 emission scenario is used. Annual and seasonal changes are computed between climate simulations under 1.5 °C and 2.0 °C warming, with respect to 0.5 °C warming, compared to pre-industrial levels. The results show that annual precipitation is likely to decrease under both magnitudes of warming; this decrease is also found during the main rainy season (July, August, September) only and is more pronounced under 2 °C warming. All reference evapotranspiration calculations, from Penman, Hamon, and Hargreaves formulations, show an increase in the future under the two GWLs, except annual Penman evapotranspiration under the 1.5 °C warming scenario. Furthermore, seasonal and annual water balances (P-ET) generally exhibit a water deficit. This water deficit (up to 180 mm) is more substantial with Penman and Hamon under 2 °C. In addition, analyses of changes in extreme precipitation reveal an increase in dry spells and a decrease in the number of wet days. However, Senegal may face a slight increase in very wet days (95th percentile), extremely wet days (99th), and rainfall intensity in the coming decades. Therefore, in the future, Senegal may experience a decline in precipitation, an increase of evapotranspiration, and a slight increase in heavy rainfall. Such changes could have serious consequences (e.g., drought, flood, etc.) for socioeconomic activities. Thus, strong governmental politics are needed to restrict the global mean temperature to avoid irreversible negative climate change impacts over the country. The findings of this study have contributed to a better understanding of local patterns of the Senegal hydroclimate under the two considered global warming scenarios. [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]

High temperatures have large impacts on premature mortality risks across the world, and there is concern that warming temperatures associated with climate change, and in particular larger-than-expected increases in the proportion of days with extremely high temperatures, may lead to increasing mortality risks. Comparisons of heat-related mortality exposure-response functions across different cities show that the effects of heat on mortality risk vary by latitude, with more pronounced heat effects in more northerly climates. Evidence has also emerged in recent years of trends over time in heat-related mortality, suggesting that in many locations, the risk per unit increase in temperature has been declining. Here, I review the emerging literature on these trends, and draw conclusions for studies that seek to project future impacts of heat on mortality. I also make reference to the more general heat-mortality literature, including studies comparing effects across locations. I conclude that climate change projection studies will need to take into account trends over time (and possibly space) in the exposure response function for heat-related mortality. Several potential methods are discussed. [ABSTRACT FROM AUTHOR]