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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]

Pakistan is among the countries that are highly vulnerable to climate change. The country has experienced severe floods and droughts during recent decades. The agricultural sector in Pakistan is adversely affected by climate change. This systematic review paper set out to analyze the existing literature on adaptation measures at the farm level toward climate change in Pakistan. Adopting a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, a total of 62 articles were identified from the Web of Science and Scopus databases. The review paper indicates that the main adaptation strategies adopted by farmers are as follows: changing cropping practices, changing farm management techniques, advanced land use management practices, and nonagriculture livelihood options. Further, this review shows the factors influencing the farmer's adaptation measures to climate change. Influencing factors were examined and classified into three groups: demographic, socioeconomic, and resources and institutional. Barriers hindering farmers' adaptive capacity were identified as lack of access to information and knowledge, lack of access to extension services, lack of access to credit facility, and lack of farm resources. [ABSTRACT FROM AUTHOR]

In the context of anomalous global climate change and the frequent occurrence of droughts and floods, studying trends in the conversion rate between precipitable water vapor (PWV) and actual precipitation in a certain region can help in analyzing the causes of these natural disasters. This paper examines the variation trend in the conversion rate between PWV and actual precipitation on a monthly scale in Hubei from 1960 to 2020. To estimate historical PWV data, we propose a new method for estimating PWV using water vapor pressure based on the RF algorithm. The new method was evaluated by radiosonde data and improved the accuracy by 1 mm over the traditional method in Hubei. Based on this method, we extrapolate the monthly average PWV in Hubei from 1960 to 2020 and analyze the conversion rate between PWV and precipitation during this period. Our results showed that there was no obvious cyclical pattern in the conversion rate in either the longitude or latitude directions. In Hubei, where the topography varies significantly in the longitude direction, the conversion rate is influenced by topography, with the smallest conversion rate being in the transition zone between the mountainous region of western Hubei and the Jianghan Plain. In the latitudinal direction, the conversion rate decreases with increasing latitude. [ABSTRACT FROM AUTHOR]

Damage from climate change is widespread throughout the world. This change has brought about calamities, the most prevalent of which is the emergence of numerous droughts which are increasingly threatening human lives. In this paper, we studied the spatial and temporal variations of drought under the effect of climate change in the Huaibei Plain, which is a very important agricultural zone in China. Drought has attracted increasing attention in research due to its heavy impact on agriculture, the environment, livelihood, and food security. The SPEI (Standardized Precipitation Evapotranspiration Index) has been used in this study to express and identify drought events in the Huaibei Plain due to climate change. A general circulation model (GCM), HadGEM2-AO, which was the most appropriate for the study area's precipitation simulation, and three Representative Concentration Pathways (RCP), RCP 2.6, RCP 4.5, and RCP 8.5, were used to analyze and compare the drought effect for the baseline (1985–2017) and the future climate scenarios (2025–2090). At 3 and 6 months, the SPEI successfully detects agricultural drought in temporal and spatial variation. However, according to the analysis, more severe agricultural drought events are foreseen in the future than in the baseline because of climate change. SPEI performed better than SPI in detecting drought in the baseline and simulated data due to increased evapotranspiration. Between the SPEI-3 and SPEI-6, the Pearson coefficient correlation reveals a positive association. The Mann-Kendall test was used to cover the two studied periods in order to establish the drought trend. Both decreasing and increasing trends, in different timescales, were detected by Sen's Slope in the baseline and future periods with all RCPs. [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]

In recent years, the frequent occurrence of extreme climate disasters has seriously affected agriculture in Northeast China. Based on precipitation data derived from 83 geographical stations in the study area for 60 years (1960–2019), we chose the reliable statistical methods of the Mann–Kendall test, Sen's slope, and the Standardized Precipitation Index, and regarded drought and flood as a whole in this paper, to identify the temporal and spatial variation characteristics of precipitation and extreme climate events in Northeast China. The results show that an increasing trend of disasters was detected at the 95% confidence level (Z = 2.3). According to the timescale analysis, abrupt climate changes started in 2006. Temporal and spatial distribution of extreme climate disasters, mainly drought and flood disasters, showed a significant upward trend from 2006 to 2019. According to the spatial analysis, the precipitation in Northeast China decreased from south to north and fluctuated less from east to west. Moreover, stations with extreme climate trends (trend of climatic anomaly with confidence level > 90%) followed the same spatial pattern as those with a high frequency of extreme climate disasters (more than 17.87 times/decade). The severity and frequency of extreme climate have increasingly threatened Northeast China in the past decade. In particular, the Northeast Plain experienced the most severe and extreme climate events that seriously threatened the study area in 2007, 2009, 2010, and 2019. Our results highlight the urgent need for the development of monitoring and early warning of droughts and flood disasters to reduce economic losses. [ABSTRACT FROM AUTHOR]

Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area. [ABSTRACT FROM AUTHOR]

Future climate change and its impact on drought is critical for Uzbekistan, located in Central Asia, the world's largest arid zone. This study examines the evolving intensity of climate change and drought events using multi-model ensembles (MMEs) derived from the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5 and CMIP6) simulated under the Representative Concentration Pathway and Shared Socioeconomic Pathway (RCP and SSP) scenarios. The projections show different rates of increase in temperature and precipitation under the RCPs and SSPs. Projected temperature increases are expected to reach up to 2–2.5 °C under SSP1-2.6, SSP2-4.5, and SSP3-7.0, by mid-century. By 2080–2099, an increase is projected of 2–3 °C in monthly mean temperatures throughout the year (SSP1-2.6), and a more pronounced increase in summer up to 3–4 °C (SSP2-4.5) and 4–6 °C (SSP3-7.0), with a marked contrast in conditions between the mountainous and desert regions of Uzbekistan. Regional changes in precipitation over the study periods show relatively little variability, except for FD, where notable trends are found. Under SSP1-2.6 and SSP2-4.5, the increase in precipitation is relatively modest, whereas the changes in SSP3-7.0 are more substantial, with some regions experiencing variations of up to 10–20 mm per period. The Standardized Precipitation Evapotranspiration Index (SPEI), calculated based on the projected temperature and precipitation, provides an estimate of future drought trends. Our results show increasing aridity under all scenarios by mid-century, with longer-term projections indicating stabilization around different SPEI values by 2100: RCP2.6 and SSP1-1.9 stabilize around −1.0; RCP4.5, RCP6.0, SSP2-4.5, and SSP3-7.0 stabilize around −1.5; while RCP8.5 and SSP5-8.5 scenarios project values of −2 or less by 2100. Notable differences in the SPEI index are found between lowland and foothill regions. In view of Uzbekistan's heavy reliance on agriculture and irrigation, which are the sectors that are expected to be mostly affected by climate change, our study provides a scientific basis for informed policy decision-making. This includes various aspects such as planning and management water resources, as well as the broader socioeconomic development of the country. [ABSTRACT FROM AUTHOR]

Flash droughts (FDs) pose significant challenges for accurate detection due to their short duration. Conventional drought monitoring methods have difficultly capturing this rapidly intensifying phenomenon accurately. Machine learning models are increasingly useful for detecting droughts after training the models with data. Northeastern Brazil (NEB) has been a hot spot for FD events with significant ecological damage in recent years. This research introduces a novel 2D convolutional neural network (CNN) designed to identify spatial FDs in historical simulations based on multiple environmental factors and thresholds as inputs. Our model, trained with hydro-climatic data, provides a probabilistic drought detection map across northeastern Brazil (NEB) in 2012 as its output. Additionally, we examine future changes in FDs using the Coupled Model Intercomparison Project Phase 6 (CMIP6) driven by outputs from Shared Socioeconomic Pathways (SSPs) under the SSP5-8.5 scenario of 2024–2050. Our results demonstrate that the proposed spatial FD-detecting model based on 2D CNN architecture and the methodology for robust learning show promise for regional comprehensive FD monitoring. Finally, considerable spatial variability of FDs across NEB was observed during 2012 and 2024–2050, which was particularly evident in the São Francisco River Basin. This research significantly contributes to advancing our understanding of flash droughts, offering critical insights for informed water resource management and bolstering resilience against the impacts of flash droughts. [ABSTRACT FROM AUTHOR]

This paper presents the results of research on possible climate change in Bosnia and Herzegovina according to the climate scenario RCP8.5 and its potential impact on fruit production. Climate change analyses are based on expected fluctuations in air temperature, precipitation and climate indices. The results indicate pronounced climate change, which refers to an increase in annual temperature to 5 °C, and a decrease in annual precipitation of up to 30% and in the summer season (June, July, and August) and up to 40% by the end of the XXI century. In addition, an increase in the number of summer days and a decrease in the number of days with the appearance of snow can be expected. Reducing the number of days with snow and snow cover can cause a decrease in underground aquifers with water during the winter and spring seasons. These changes can have a serious impact on the problem of drought and water deficit, which can have direct consequences for the agricultural sector in Bosnia and Herzegovina, especially for fruit production. These findings show that fundamental changes in agriculture and an approach to land treatment and water resources management, as well as fruit production planning in changed climatic conditions, are needed. [ABSTRACT FROM AUTHOR]

Rural communities in West Africa have long adopted a variety of coping and adaptation strategies to periods of climate variability and risks. These strategies have mostly been shaped by prevailing indigenous knowledge systems and shared understandings of the underlying causes of climate events. Despite the increasing scientific and policy attention to climate perceptions and integration of indigenous knowledge in climate governance, there is still a lag in going further to probe and consider the socio-cultural and cognitive systems that shape local appreciation of climate change risks and responses. Based largely on qualitative interviews, and complementary household surveys, the paper draws on the concepts of 'mental' and 'cognised' models to examine drought and climate change risk perceptions and responses in the rural savannah of North-eastern Ghana. Local farmers generally allude to changes in rainfall patterns and prolonged intra-seasonal dry spells. Based on subscriptions to local models of blame in explaining climate risks and impacts, it is also seen that prevailing socio-cultural beliefs and understandings of environmental events tend to inform the responses of farmers in addressing these perceived risks and impacts. The paper advocates for ongoing climate action and policy processes to consider the complexity of different actors and context (socio-cultural, institutional, power structures) in enhancing sustainable adaptation and mitigation measures in vulnerable rural communities. [ABSTRACT FROM AUTHOR]

Recent studies on China's arid and semi-arid regions, particularly the Tarim River Basin (TRB), have shown an increase in the intensity and frequency of extreme weather events. This research examines the link between meteorological droughts, as measured by the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts, as indicated by the Standardized Runoff Index (SRI) and the Standardized Terrestrial Water Storage Index (STI), over various time scales. Historical data indicate that SPEI drought frequency (DF) was 14.3–21.9%, with prevalent events in the northern oases. SRI DF ranged from 9.0% to 35.8%, concentrated around the Taklamakan and Kumtag Deserts, while STI DF varied between 4.4% and 32.7%, averaging 15% basin-wide. Future projections show an increased DF of SPEI in deserts and a decrease in oases; SRI DF decreased in deserts but increased in oases. STI changes were more moderate. The study also found a higher risk of drought progression from SPEI to SRI in the southwestern and northeastern oases, exceeding 50% probability, while central and eastern TRB had lower risks. The western TRB and inner Taklamakan Desert faced higher risks of SPEI to STI progression, with probabilities over 45%, in contrast to the lower risks in the eastern and central oases. The concurrence of SRI/STI with moderate to extreme SPEI droughts led to a higher probability and area of SRI/STI droughts, whereas consistent SPEI types showed a reduced induced probability and extent of SRI/STI droughts. This study enhances the understanding of drought propagation from meteorological to hydrological droughts in the TRB and contributes to the prevention of hydrological drought to a certain extent. [ABSTRACT FROM AUTHOR]

The primary innovation of this study lies in the development of an integrated modeling framework that combines downscaled climate projections, land-use-change simulations, and copula-based risk analysis. This framework allows for the assessment of localized sub-seasonal and seasonal drought hazards under future scenarios. The BCC-CSM1-1 climate model projections from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset are utilized to represent the future climate for 2025–2060 under RCP 4.5 and 8.5 scenarios. The CA-Markov model is employed to predict future land-use-change distributions. The climate–land use–drought modeling nexus enables the generation of refined spatio-temporal projections of meteorological and hydrological drought risks in the Yellow River Basin (YRB) in the future period of 2025–2060. The results highlight the increased vulnerability of the upper YRB to sub-seasonal meteorological droughts, as well as the heightened sub-seasonal hydrological drought risks in the Loess Plateau. Furthermore, downstream areas experience escalated seasonal hydrological drought exposure due to urbanization. By providing actionable insights into localized future drought patterns, this integrated assessment approach advances preparedness and climate adaptation strategies. The findings of the study enhance our understanding of potential changes in this integral system under the combined pressures of global climate change and land use shifts. [ABSTRACT FROM AUTHOR]

This study analyzes the potential response of the seasonal cycle of heatwaves (HWDI) and dry (CDD) and wet (CWD) spell indices over West Africa for the near- (2031–2060) and the far-future periods (2071–2100) under RCP4.5 and RCP8.5 scenarios using Coordinated Regional Climate Downscaling Experiment (CORDEX) simulations. Despite the fact that some relative biases (an underestimation of 30% for CDD, an overestimation of about 60% for CWD, and an overestimation of about 50% for HWDI) exist, during the historical period (1976–2005) in general, the CORDEX simulations and their ensemble mean outperform the seasonal variability in the above-mentioned indices over three defined subregions of West Africa (i.e., the Gulf of Guinea and Western and Eastern Sahel). They show high correlation coefficients (0.9 in general) and less RMSE. They project an increase (about 10 and 20 days) in heatwave days for both the near- and far-future periods over the whole West African region under both RCP scenarios. In addition, projections indicate that the Sahel regions will experience a decrease (about 5 days) in wet spell days from March to November, while in the Gulf of Guinea, a decrease (about 3 days) is projected throughout the year, except in the CCCLM simulation, which indicates an increase (about 5 days) during the retreat phase of the monsoon (October to December). Our results also highlight an increase (about 80%) in dry spells over the Sahel regions that are more pronounced during the March–November period, while over the Gulf of Guinea, an increase (about 40%) is projected over the entire year. Moreover, the months of increasing dry spells and decreasing wet spells coincide, suggesting that countries in these regions could be simultaneously exposed to dry seasons associated with a high risk of drought and heatwaves under future climate conditions. [ABSTRACT FROM AUTHOR]

Drought is the main meteorological disaster that affects the yield and quality of spring maize on the Loess Plateau. This study used data of the spring maize growth period, relative soil humidity, and yield at 18 agricultural meteorological observation stations on the Loess Plateau from 1997 to 2013 to determine the drought category based on the yield reduction rate. Through the drought index according to the conformity rate of category standard and individual case verification, a refined suitability drought index of spring maize on the Loess Plateau was constructed, and the spatial distribution characteristics of drought in different growth stages of spring maize were analyzed. The results showed the following: (1) The number of days in the whole growth period of spring maize in all regions of the Loess Plateau has been extended. The average sowing date of spring maize in the northwest region of the Loess Plateau was 9 April, and that in the east and central regions was 26 April. In terms of spatial distribution, each growth period was gradually delayed from west to east. (2) The correlation between relative soil humidity and yield of spring maize at the jointing stage and heading stage was the best, followed by the milky stage and mature stage, and the relative soil humidity at the sowing stage and emergence stage had little effect on the yield. (3) According to the national drought category standard "Drought Category of Spring Maize in the North", based on the data of yield reduction rate, the drought index of spring maize on the Loess Plateau was refined by region and growth stage. The drought category index values of spring maize in different growth stages and regions changed according to the revised drought category standard, with 71.4% of the sites in the sowing seedling stage and 85.7% of the sites in the seedling jointing stage, and the revised drought category was more severe than the national drought category standard, while at 57.1% of the sites in the jointing and tasseling stages and 71.4% in the tasseling and milking stages, the revised drought category was less severe than the national drought category standard. (4) Based on the revised refined drought index for spring maize on the Loess Plateau, the spatial distribution of drought occurrence frequency across different growth stages of spring maize on the Loess Plateau was analyzed. The frequency of drought occurrence during the seeding and emergence stages was 25–75%. With the change in growth stages, the high-value area of drought occurrence frequency gradually moved northward, and the overall frequency of drought occurrence decreased. For the milky mature stage, the frequency of drought occurrence in a few regions was around 42%, and the drought frequency in most regions was between 8% and 33%. [ABSTRACT FROM AUTHOR]

Vegetation, especially forest ecosystems, plays an important role in the global energy flow and material cycle. The vegetation index (VI) is an important index reflecting the dynamic change in vegetation and directly reflects the response of ecosystem to global climate change. The Greater Khingan Mountains Forest region is located in the northeast of China. It is the largest primeval forest region in China, which is well preserved and less affected by human activities. It is of great significance to study the driving mechanism of forest vegetation change for future ecological prediction and management. In this study, GIMMS NDVI data were used to explore the characteristics of nonlinear temporal and spatial variation of NDVI in the Greater Khingan Mountains and its relationship with climatic factors. Firstly, the EEMD method was used to analyze the characteristics of vegetation change in the study area from 1982 to 2015. Secondly, the relationship between vegetation change and climate was discussed by using precipitation and temperature data. The results showed that the following: (1) from 1982 to 2015, the interannual change in vegetation in the Greater Khingan Mountains presented a trend of slow fluctuation and gradual decrease (SLOPE = −0.1645/10,000, p < 0.01). (2) The spatial distribution of vegetation change had obvious geographical differences, and in the central region, the overall distribution characteristics had an obvious browning trend, and in the northwest and southeast, the distribution characteristics had a green trend. (3) The correlation analysis results of vegetation change and climate factors showed that NDVI change was significantly positively correlated with temperature and precipitation; additionally, NDVI change was more correlated with temperature with a range of 0.8–1 than precipitation. (4) The results of vegetation attribution analysis in four typical areas of the study area showed that the following: the coniferous forest area has good cold tolerance and drought tolerance, the correlation between vegetation change and climate factors (temperature, precipitation) was not the strongest, which was 0.537 and 0.828, respectively. The ecological transition area and the broad-leaved forest area, which was located at the edge of the study area, have relatively fragile ecosystems, showed a strong correlation with precipitation, and the correlation coefficients reached 0.670 and 0.632, respectively. The surface water resources provide favorable conditions for the growth of vegetation, it showed a weak correlation with precipitation, and the correlation coefficient was 0.5349. [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]

The objectives of the work were to understand the potential future climate changes in the Mediterranean region, assess the drought tolerance of the black calla lily (Arum palaestinum Boiss.), and investigate the mechanisms associated with its ability to withstand drought conditions. The Shared Socioeconomic Pathways (SSPs) of the Intergovernmental Panel on Climate Change (IPCC) were used to predict future temperature and precipitation changes. Both the SSP2-4.5 and SSP5-8.5 scenarios predicted a general increase in minimum and maximum temperatures and a decrease in precipitation. The projected increase in minimum temperature ranged from 2.95 °C under SSP2-4.5 to 5.67 °C under SSP5-8.5. The projected increase in maximum temperature ranged from 0.69 °C under SSP2-4.5 to 3.34 °C under SSP5-8.5. The projected decrease in precipitation ranged from −1.04 mm/day under SSP2-4.5 to −1.11 mm/day under SSP5-8.5. Results indicated that drought significantly impacted the physiological responses of the black calla lily. As drought increased, the black calla lily showed a reduction in leaf characteristics and non-structural carbohydrates, while proline content and reducing sugar content were increased, enhancing drought tolerance through osmoregulation. The black calla lily tolerates drought at a total ET of up to 50%. It has the potential to adapt to expected climate change through osmoregulation or by building a carbon and nitrogen sink for stress recovery. [ABSTRACT FROM AUTHOR]

Germany's increasing temperatures and droughts are significantly impacting the hydrological realm. This study examines the implications of climate change on future droughts in a representative catchment within Germany's low mountain range. Findings of this research shed light on potential impacts on future seasonal water availability, aiding decision makers and stakeholders in managing regional climate change risks. Climate and drought indices, as well as the climatic water balance, are computed and analyzed until 2100, relative to a reference period. A high emission scenario (RCP8.5) and a climate protection scenario (RCP2.6) are considered to address uncertainties. Results reveal above-average warming in the study area compared to the national average. Under the RCP8.5 scenario, the far future exhibits an average of 44 annual heat days. Despite wetter winters, extended droughts persist. Water stress intensifies in summer and autumn, with a projected 68% increase in dry period duration. The findings emphasize the necessity of adaptation strategies, as even ambitious global warming mitigation efforts require regional adaptation. The study represents the first application of a Germany-wide, bias-adjusted, and regionalized dataset at catchment level. It contributes novel insights for regional water resources management and advances understanding of climate change impacts in German low mountain range regions. [ABSTRACT FROM AUTHOR]

Agricultural production and advancement is significantly affected by climate change (CC), especially in drought-prone regions where farmers depend primarily on rainfall for their livelihoods. One of the main threats to the agricultural sector for decades has been global warming, and the sector is particularly susceptible to climatic circumstances. CC has become a crucial concern impeding sustainable development due to rapid changes in urbanization, industry, and agricultural systems. Food security, which is a worldwide concern, is another essential component connected to a country's economy and people's livelihoods. In view of these adverse consequences, the main objective of this study was to examine the impact of CC and food security on sustainable agricultural development in Pakistan. The study area was selected from twenty-four districts in two provinces of Pakistan (Khyber Pakhtunkhwa and Balochistan). Collectively, the current research offers possible solutions to the dilemmas described above, which could have a significant impact on improving efficiency and technological progress. To address these issues, we introduced a slack-based approach to quantify inefficiencies in overall agricultural production. In addition, this study further scrutinized the decomposition of specific variables. The results show that Pakistan has an agricultural inefficiency of 0.62 under CC and food security constraints, of which 0.29 is primarily attributable to food security limitations. In the end, this study will help policymakers to make appropriate decisions to minimize the impact of CC on sustainable agriculture growth and improve human living standards and food security. [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]

Along with tree ring width, carbon isotopes are also good proxies for climate change. Water use efficiency (WUE) can be calculated more quickly and accurately based on carbon isotopes. In this study, according to the principle of dendroclimatology, the sequence of δ13C and WUE of tree rings of Picea meyeri are built. Pearson correlation analysis and multiple regression analysis are used to explore the response of carbon stable isotopes of Picea meyeri to climate change, which revealed the relationship between δ13C of Picea meyeri and climatic factors. Based on δ13C, we calculated the WUE of Picea meyeri and analyzed its response to climate change. The main conclusions are as follows: (1) The δ13C of Picea meyeri decreases year-by-year from 1957 to 2020, in the range from −23.89‰~−21.67‰, and the average value is −22.67‰. The water use efficiency of Picea meyeri increases in the range from 17.26~61.31, with an average of 39.45. (2) The δ13C of Picea meyeri is negatively correlated with temperature, which has the highest correlation with the temperature of the growing season (c5–c9), and its coefficient is higher than that of the mean temperature of each month. (3) There is a significant positive correlation between WUE sequence and temperature. Meanwhile, due to the effect of precipitation and temperature, the Picea meyeri is subject to drought stress to some extent. Above all, temperature is the main climatic factor affecting the δ13C and WUE of Picea meyeri on Luya mountain. [ABSTRACT FROM AUTHOR]

Kabul River Basin is one of the most significant river basins in Afghanistan from a socio-economic perspective. Since the country is located in an arid climate zone with drastically varying climatic behavior, an effective assessment of meteorological drought is very essential to managing the limited availability of water resources. For this endeavor, the outputs of three general circulation models under two representative concentration pathways (RCP 4.5 and RCP 8.5) were used against the baseline period of 1961–1980. Different bias correction methods were applied, and the results show that the delta change method, quantile mapping method, and empirical quantile mapping all performed better for the precipitation, maximum temperature, and minimum temperature datasets, respectively. The ERA5-Land datasets and WorldClim Version 2 are used to validate the bias-corrected precipitation and temperature datasets, respectively, to determine their dependability, and the results were found to be promising. Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Deciles Index (DI), and New Drought Index (NDI) were used to assess the drought condition in the past and forecast for the future periods of the 2020s, 2050s, and 2080s. The spatial distribution of assessed drought indices was mapped using the inverse distance weighting (IDW) method. Our results revealed that moderate to extreme droughts are consistent across the entire basin. This might be because the projected annual precipitation in the river basin shows a decline of 53–65% up to the end of this century (2100), and the average annual temperature is projected to increase by 1.8 °C, 3.5 °C, and 4.8 °C, respectively, for the three future periods of the 2020s, 2050s, and 2080s. Furthermore, the results show that the drought estimated by SPI and RDI for future climate scenarios is almost the same, whereas NDI estimates frequent drought events after the 2050s. However, for moderate drought, RDI, which includes the effects of evapotranspiration, was found to be far greater than SPI under both scenarios, and NDI considering temperature and precipitation also estimates a larger number of drought years, strengthening the possibility of its occurrence in the basin. A regional comparison of drought also indicates a decrease in precipitation in future periods, predominantly in high altitudes. [ABSTRACT FROM AUTHOR]

Qinghai Province is situated deep in inland China, on the Qinghai-Tibet plateau, and it has unique climate change characteristics. Therefore, understanding the temporal and spatial distributions of water vapor in this region can be of great significance. The present study applied global navigation satellite system (GNSS) technology to retrieve precipitable water vapor (PWV) in Qinghai and analyzed its relationship with rainfall and drought. Firstly, radiosonde (RS) data is used to verify the precision of the surface pressure (P) and temperature (T) from the fifth-generation atmosphere reanalysis data set (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF), as well as the zenith troposphere delay (ZTD), calculated based on the data from continuously operating reference stations (CORS) in Qinghai. Secondly, a regional atmospheric weighted mean temperature (Tm) (QH-Tm) model was developed for Qinghai based on P, T, and relative humidity, as well as the consideration of the influence of seasonal changes in Tm. Finally, the PWV of each CORS in Qinghai was calculated using the GNSS-derived ZTD and ERA5-derived meteorological data, and its relationship with rainfall and drought was evaluated. The results show that the ERA5-derived P and T have high precision, and their average root mean square (RMS), mean absolute error (MAE) and bias were 1.06/0.85/0.01 hPa and 2.98/2.42/0.03 K, respectively. The RMS, MAE and bias of GNSS-derived ZTD were 13.2 mm, 10.3 mm and −1.8 mm, respectively. The theoretical error for PWV was 1.98 mm; compared with that of RS- and ERA5-derived PWV, the actual error was 2.69 mm and 2.16 mm, respectively. In addition, the changing trend of GNSS-derived PWV was consistent with that of rainfall events, and it closely and negatively correlated with the standardized precipitation evapotranspiration index. Therefore, the PWV retrieved from GNSS data in this study offers high precision and good feasibility for practical applications; thus, it can serve as a crucial tool for investigating water vapor distribution and climate change in Qinghai. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? The HRB most frequently suffers from continued dryness followed by transition from dry-ness to wetness. Dryness–wetness combinations generally occur more frequent under climate change. Frequency of prolonged dryness/wetness escalates more rapidly than abrupt transition events. What is the implication of the main finding? The spatial and temporal preference of inter-seasonal dryness–wetness combinations are elucidated. Bivariate hazard assessment of dryness–wetness combinations enriches water-related hazard atlas and facilitates more integrated mitigation planning. Accumulated evidence reminds one that abrupt transitions between dry and wet spells, though attracting less attention, have harmful influences upon global continents as extensively investigated droughts and floods. This study attempts to incorporate dryness–wetness transitions into the current hazard assessment framework through bivariate frequency analysis and causal attribution from a teleconnection perspective. In the study, regional dry and wet conditions are monitored using the multivariate standardized drought index (MSDI) which facilitates the integrated evaluation of water deficits/surplus from a combined viewpoint of precipitation (largely denoting the received atmospheric water) and runoff (representing an important source of surface water). On such a basis, a copula-based method is subsequently utilized to calculate joint return periods of dryness–wetness combinations in three (i.e., moderate, severe and extreme) severity scenarios. The changing frequency of diverse dryness–wetness combinations is also estimated under a changing climate using a 25-year time window. Furthermore, the cross-wavelet transform is applied to attribute variations in dry and wet conditions to large-scale climate indices, which benefits the early warning of dryness–wetness combinations by providing predictive information. A case study conducted during 1952–2010 in the Huai River basin (HRB)—a typical climatic transition zone in China—shows that the HRB is subject to prolonged dryness with the highest frequency, followed by the abrupt transition from dryness to wetness. Spatially, abrupt dryness–wetness transitions are more likely to occur in the southern and central parts of the HRB than in the rest of the proportion. The past half-century has witnessed the dominantly higher frequency of occurrence of dryness–wetness combinations under three severity scenarios. In particular, the occurrence of the continued dry/wetness escalates more rapidly than transition events under climate change. Moreover, a preliminary attribution analysis discloses the link of the dry and wet conditions in the HRB with climate indices, such as the El Niño southern oscillation, the Pacific decadal oscillation and the Arctic oscillation, as well as sunspot activities. The results of the study enrich the current atlas of water-related hazards, which may benefit more effective hazard mitigation and adaptation. [ABSTRACT FROM AUTHOR]

Southwest Florida is one of the most rapidly growing regions of the United States and has been impacted over the past decade with water-quality issues and some associated health problems. The ionic ratios of the dust measured in southwest Florida vary significantly from those on the Florida east coast and in the Caribbean. The metals concentrations reported herein are enriched in potassium and calcium from local sources. Atmospheric deposition of metals and nutrients appears to have potential impacts on both indirect health problems and environmental issues of concern, particularly harmful algal blooms. However, no significant past research has been performed on measurement of the concentration of either metals including the micronutrient iron or nutrient concentrations occurring in atmospheric dry and wet fallout in southwest Florida. Measurements of the composition of key metals and nutrients were made over a one-year period. Concentrations of total phosphorus in the dust ranged from 0–80.5 mg/kg with an average of 4 mg/kg and in rainfall from 1–15.8 чg/L with an average of 4 mg/kg. Nitrate ranged from 0–746 чg/L with an average of 114.4 чg/L in rainfall in a soluble form, and from 1.3 to 718 mg/kg with an average of 209.9 mg/kg in an insoluble form. Ammonia was measured to range from 1.4 to 658 mg/kg with an average of 101.4 mg/kg in rainfall. Iron was found in the dust at concentrations ranging from 0–81 mg/kg with an average of 3.8 mg/kg and in rainfall from 0–125.7 mg/kg with an average of 3.0 mg/kg. While the measured nutrient and iron concentrations are not likely to initiate a harmful algal bloom, they are likely to sustain an existing bloom. Global climate change may exacerbate the atmospheric aerosol issue by increased wind speeds over Africa associated with longer term drought conditions caused by atmospheric temperature increases. [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 El Niño Southe58rn Oscillation (ENSO) is a typical oscillation affecting climate change, and its stable periodicity, long-lasting effect, and predictable characteristics have become important indicators for regional climate prediction. In this study, we analyze the Standardized Precipitation Evapotranspiration Index (SPEI), the Niño3.4 index, the Southern Oscillation Index (SOI), and the Multivariate ENSO Index (MEI). Additionally, we explore the spatial and temporal distribution of the correlation coefficients between ENSO and SPEI and the time lag between ENSO events of varying intensities and droughts. The results reveal that the use of Nino3.4, MEI, and SOI produces differences in the occurrence time, end time, and intensity of ENSO events. Nino3.4 and MEI produce similar results for identifying ENSO events, and the Nino3.4 index accurately identifies and describes ENSO events with higher reliability. In China, the drought-sensitive areas vulnerable to ENSO events include southern China, the Jiangnan region, the middle and lower reaches of the Yangtze River, and the arid and semi-arid areas of northwestern China. Droughts in these areas correlate significantly with meteorological drought, and time-series correlations between ENSO events and droughts are significantly stronger in regions close to the ocean. Drought occurrence lags ENSO events: when using the Niño3.4 index to identify ENSO, droughts lag the strongest and weakest El Niño events by 0–12 months. However, when using the MEI as a criterion for ENSO, droughts lag the strongest and weakest El Niño events by 0–7 months. The time lag between the strongest ENSO event and drought is shorter than that for the weakest ENSO event, and droughts have a wider impact. The results of this study can provide a climate-change-compatible basis for drought monitoring and prediction. [ABSTRACT FROM AUTHOR]

The Integrated Agrometeorological Prediction System (IAPS) was a two-year project for the development of the long term forecast (LRF) for agricultural producers. Using LRF in decision-making, to reduce the risks and seize the opportunities, represents short-term adaptation to climate change. High-resolution ensemble forecasts (51 forecasts) were made for a period of 7 months and were initiated on the first day of each month. For the initial testing of the capacity of LRF to provide useful information for producers, 2017 was chosen as the test year as it had a very hot summer and severe drought, which caused significant impacts on agricultural production. LRF was very useful in predicting the variables which bear the memory of the longer period, such are growing degree days for the prediction of dates of the phenophases' occurrences and the soil moisture of deeper soil layers as an indicator for the drought. Other project activities included field observations, communication with producers, web portal development, etc. Our results showed that the selected priority forecasting products were also identified by the producers as being the highest weather-related risks, the operational forecast implementation with the products designed for the use in agricultural production is proven to be urgent and necessary for decision-making, and required investments are affordable. The total cost of the full upgrade of agrometeorological climate services to meet current needs (including monitoring, seamless forecasting system development and the development of tools for information dissemination) was found to be about three orders of magnitude lower than the assessed losses in agricultural production in the two extreme years over the past decade. [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]

This study assesses changes in meteorological droughts in West Africa under a high greenhouse gas scenario, i.e., a representative concentration pathway 8.5 (RCP8.5), and under a scenario of stratospheric aerosol geoengineering (SAG) deployment. Using simulations from the Geoengineering Large Ensemble (GLENS) project that employed stratospheric sulfate aerosols injection to keep global mean surface temperature, as well as the interhemispheric and equator-to-pole temperature gradients at the 2020 level (present-day climate), we investigated the impact of SAG on meteorological droughts in West Africa. Analysis of the meteorological drought characteristics (number of drought events, drought duration, maximum length of drought events, severity of the greatest drought events and intensity of the greatest drought event) revealed that over the period from 2030–2049 and under GLENS simulations, these drought characteristics decrease in most regions in comparison to the RCP8.5 scenarios. On the contrary, over the period from 2070–2089 and under GLENS simulations, these drought characteristics increase in most regions compared to the results from the RCP8.5 scenarios. Under GLENS, the increase in drought characteristics is due to a decrease in precipitation. The decrease in precipitation is largely driven by weakened monsoon circulation due to the reduce of land–sea thermal contrast in the lower troposphere. [ABSTRACT FROM AUTHOR]

In spite of the obvious climate changes effects on the Carpathian Basin hydrographic nets fish fauna, studies on their potential refuge habitats in drought periods are scarce. Multiannual (2016–2021) research of fish in some streams located in the Saxon Villages area during hydrological drought periods identified, mapped, and revealed the refuge aquatic habitats presence, management needs, and importance for fish diversity and abundance for small rivers. The impact of increasing global temperature and other human activities induced hydrologic net and habitats alteration, decreased the refuge habitats needed by freshwater fish, diminished the fish abundance, and influenced the spatial and temporal variation in fish assemblage structure in the studied area. The sites more than one meter in depth in the studied lotic system were inventoried and all 500 m of these lotic systems were also checked to see what species and how many individuals were present, and if there is was difference in their abundance between refuge and non-refuge 500 m sectors. The scarce number of these refuges due to relatively high soil erosion and clogging in those basins and the cumulative effects of other human types of impact induced a high degree of pressure on the fish fauna. Overall, it reduced the role of these lotic systems as a refuge and for reproduction for the fish of downstream Târnava Mare River, into which all of them flow. Management elements were proposed to maintain and improve these refuges' ecological support capacity. [ABSTRACT FROM AUTHOR]

Extreme hot temperature is dangerous to the bioeconomy, and would worsen with time. Ambient heatwaves accompanied by unusual droughts are major threats to poverty eradication in Tanzania. Due to sparsity of observation data and proper heatwave detection metrics, there has been a paucity of knowledge about heatwave events in Tanzania. In this study, the Heatwave Magnitude Index daily (HWMId) was adopted to quantitatively analyze heatwave characteristics throughout Tanzania at mid-21st century (2041–2070) and end of 21st century (2071–2100), relative to the reference period (1983–2012) using the CHIRTS-daily quasi-global high-resolution temperature dataset and climate simulations from a multi-modal ensemble of median scenarios (RCP4.5, from CORDEX-Africa). The results showed that moderate to super-extreme heatwaves occurred in Tanzania between 1983 and 2012, particularly in 1999, when ultra-extreme heatwaves (HWMId > 32) occurred in the Lake Victoria basin. It is projected that by mid-21st century, the upper category of HWMId would be hotter and longer, and would occur routinely in Tanzania. The spatial extent of all of the HWMId categories is projected to range from 34% to 73% by the end of the 21st century with a duration of 8 to 35 days, compared to 1 to 5 days during the reference period. These findings will contribute to increasing public awareness of the need for adaptation. [ABSTRACT FROM AUTHOR]

Future drought-hazard assessments using standardized indices depend on the period used to calibrate the probability distributions. This appears to be particularly important in a changing climate with significant trends in drought-related variables. This study explores the effect of using different approaches to project droughts, with a focus on changes in drought characteristics (frequency, duration, time spent in drought, and spatial extent), estimated with a calibration period covering recent past and future conditions (self-calibrated indices), and another one that only applies recent-past records (relative indices). The analysis focused on the Iberian Peninsula (IP), a hot-spot region where climate projections indicate significant changes by the end of this century. To do this, a EURO-CORDEX multi-model ensemble under RCP8.5 was used to calculate the Standardized Precipitation-Evapotranspiration Index (SPEI) at both 3- and 12-month timescales. The results suggest that projections of drought characteristics strongly depend on the period used to calibrate the SPEI, particularly at a 12-month timescale. Overall, differences were larger for the near future when relative indices indicated more severe droughts. For the distant future, changes were more similar, although self-calibrated indices revealed more frequent and longer-lasting droughts and the relative ones a drought worsening associated with extremely prolonged drought events. [ABSTRACT FROM AUTHOR]

Drought is one of the most complex climate-related phenomena and is expected to progressively affect our lives by causing very serious environmental and socioeconomic damage by the end of the 21st century. In this study, we have extracted a dataset of exceptional meteorological drought events between 1975 and 2019 at the country and subregional scales. Each drought event was described by its start and end date, intensity, severity, duration, areal extent, peak month and peak area. To define such drought events and their characteristics, separate analyses based on three drought indices were performed at 12-month timescale: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Reconnaissance Drought Index (RDI). A multivariate combined drought index (DXI) was developed by merging the previous three indices for more understanding of droughts' features at the country and subregional levels. Principal component analysis (PCA) was used to identify five different drought subregions based on DXI-12 values for 312 Mediterranean stations and a new special score was defined to classify the multi-subregional exceptional drought events across the Mediterranean Basin (MED). The results indicated that extensive drought events occurred more frequently since the late 1990s, showing several drought hotspots in the last decades in the southeastern Mediterranean and northwest Africa. In addition, the results showed that the most severe events were more detected when more than single drought index was used. The highest percentage area under drought was also observed through combining the variations of three drought indices. Furthermore, the drought area in both dry and humid areas in the MED has also experienced a remarkable increase since the late 1990s. Based on a comparison of the drought events during the two periods—1975–1996 and 1997–2019—we find that the current dry conditions in the MED are more severe, intense, and frequent than the earlier period; moreover, the strongest dry conditions occurred in last two decades. The SPEI-12 and RDI-12 have a higher capacity in providing a more comprehensive description of the dry conditions because of the inclusion of temperature or atmospheric evaporative demand in their scheme. A complex range of atmospheric circulation patterns, particularly the Western Mediterranean Oscillation (WeMO) and East Atlantic/West Russia (EATL/WRUS), appear to play an important role in severe, intense and region-wide droughts, including the two most severe droughts, 1999–2001 and 2007–2012, with lesser influence of the NAO, ULMO and SCAND. [ABSTRACT FROM AUTHOR]

Seasonal drought is often overlooked because its impacts are less devasting than meteorological or hydrological drought. Nevertheless, short-term drought can have significant impacts on soil moisture content, agricultural crop yield, and sand and dust storms. Using data obtained from bias-corrected regional climate modelling (RCM) outputs, future seasonal drought is investigated over the water-scarce Arab domain using SPI-3. The climate modelling outputs include three downscaled mainframe GCMs downscaled using a single RCM for two climate scenarios: RCP4.5 and RCP8.5. Results across the region exhibit spatial and temporal variability. For example, Rift Valley, in the eastern sub-Sahara, projects less frequent and less severe drought, particularly during the winter (DJF) months. Conversely, the Morocco Highlands and adjacent Mediterranean coast signals a dramatic increase in drought by end-century during winter (DJF) and spring (MAM). Moderate increase in drought indicated in the greater Mashreq in spring (MAM) can be linked to sand and dust storm risk. Thirdly, autumn drought (SON) is linked to increased forest fire risk in the Levant. Projected increases in drought frequency and severity call for adaptation measures to reduce impacts. [ABSTRACT FROM AUTHOR]

Drought is a natural phenomenon in which the natural amount of water in an area is below the normal level. It has negative impacts on production in numerous industries and people's lives, especially in the context of climate change. Investigating the spatial–temporal variation of drought is of great importance in water resource allocation and management. For a better understanding of how drought has changed in China from 1961 to 2020 and will change in the future period of this century (2021–2100), a spatial–temporal assessment of drought based on the standardized precipitation evapotranspiration index (SPEI) was carried out. The trends and characteristics (number, duration, and severity) of historical and future droughts in China were evaluated based on 12-month SPEI by employing the Mann–Kendall test, Sen's slope and run theory. The similarities, differences, and spatial–temporal evolution of droughts in these two periods were analyzed. The results showed that in the historical period the number of droughts decreased gradually from the south of China to the north. Less frequent drought but with longer duration and stronger severity occurred in the northeast and the northern areas. In the future period, most parts of China are projected to suffer more severe droughts with longer duration, especially for Northeast China, North China, Qinghai–Tibetan Plateau, and Southwest China. The likely increasing severity and duration of droughts in most areas of China in the future makes it very necessary to formulate the corresponding drought prevention and relief strategies to reduce the possible losses caused by droughts. [ABSTRACT FROM AUTHOR]

Many studies have been undertaken on climate variability in West Africa since the drastic drought of 1970s. These studies rely in many cases on different baseline periods chosen with regard to the reference periods defined by the World Meteorological Organization. A method is developed in this study to determine a stationary baseline period for rainfall variability analysis. The method is based on an application of three statistic tests (on deviation and trend) and a test of shifts detection in rainfall time series. The application of this method on six different gridded rainfall data and observations from 1901 to 2018 shows that the 1917–1946 period is the longest stationary period. An assessment of the significance of the difference between the mean annual rainfall amount during this baseline period and the annual rainfall amount during the other years shows that the "Normal" annual rainfall amount is defined by an interval delineated by ±the standard deviation (STD). With regard to this interval, a very wet/dry year is defined with a surplus/gap over/below the STD. Overall the 1901–2018 period, the 1950–1970 period presents the most important number of significant wet years and the 1971–1990 period presents the most important number of significant dry years. [ABSTRACT FROM AUTHOR]

Drought has a great impact on agriculture and food security, and climate change is increasing its frequency and exacerbating its intensity. Given the enormous interest in studying the recent drought evolution, in this work, agricultural drought trends over the past four decades on the Iberian Peninsula (IP) were analyzed. A trend analysis was performed with soil moisture based on the study of the evolution of anomalies and the Soil Water Deficit Index (SWDI). Two soil moisture databases (Lisflood and ERA5-Land) were used and the analysis was performed at daily and weekly temporal scales. Climate characteristics and soil properties were also considered to detect whether a trend spatial pattern could be identified. The results have shown a clear predominance of negative trends. A marked temporal pattern with negative trends was obtained over a 10-month period that coincided with the growing season of most of the crops on the IP, while a positive trend was observed over 2 months. No differences were found based on the climatic zone or soil characteristics. However, negative trends were observed to decrease as the clay content increased. These results can provide useful information for better water management and agriculture of the IP and other Mediterranean areas. [ABSTRACT FROM AUTHOR]

For the investigation of geographical, monthly, seasonal, and annual distributions of aridity and its annual trend in the region of the Central and Southern Pannonian Basin (CSPB), which includes the territories of Hungary and Vojvodina (Northern Serbia), the De Martonne Aridity Index (DMAI) was used. The DMAI was originally calculated from a total of 78 meteorological stations with the maximum available time series of climatological data in three cases: 1931–2017 for Hungary; 1949–2017 for Vojvodina; and 1949–2017 for Hungary and Vojvodina jointly. The Palmer Drought Severity Index (PDSI) was used to control the DMAI results. Temperature and precipitation trends were also investigated to understand their effects on the aridity trend. Three aridity types are distinguished on the annual level, five on the seasonal level, and four on the monthly level. The annual aridity had no trends in all three periods. It seems that aridity can be considered a more stable climate indicator of climate change than the temperature, at least in the CSPB. [ABSTRACT FROM AUTHOR]

Studies using drought index to examine return levels of drought can be classified into two approaches: univariate frequency analysis using annual series extracted from drought index time series and multivariate frequency analysis that simultaneously reflects various characteristics of drought. In the case of drought analysis, it is important to properly consider the duration, so, in this study, univariate frequency analysis is performed using the partial duration series. In addition, a bivariate frequency analysis is performed using a relatively simple bivariate exponential distribution to give a more realistic return level to major drought events in the past while reflecting the correlation between drought severities and durations. The drought severity–duration–frequency curves using each of the two frequency analyses are derived, and these curves are used to examine how the drought phenomenon currently in progress is evolving. From this, the advantages and disadvantages of the two approaches, as well as the points to be aware of in application, are discussed. Finally, using the two approaches to the proposed drought frequency analysis, the behavior of Korea's future extreme droughts is investigated under the conditions of various future climate change scenarios. [ABSTRACT FROM AUTHOR]

Climate change threatens the hydrological equilibrium with severe consequences for living beings. In that respect, considerable differences in drought features are expected, especially for mountain-Andean regions, which seem to be prone to climate change. Therefore, an urgent need for evaluation of such climate conditions arises; especially the effects at catchment scales, due to its implications over the hydrological services. However, to study future climate impacts at the catchment scale, the use of dynamically downscaled data in developing countries is a luxury due to the computational constraints. This study performed spatiotemporal future long-term projections of droughts in the upper part of the Paute River basin, located in the southern Andes of Ecuador. Using 10 km dynamically downscaled data from four global climate models, the standardized precipitation and evapotranspiration index (SPEI) index was used for drought characterization in the base period (1981–2005) and future period (2011–2070) for RCP 4.5 and RCP 8.5 of CMIP5 project. Fitting a generalized-extreme-value (GEV) distribution, the change ratio of the magnitude, duration, and severity between the future and present was evaluated for return periods 10, 50, and 100 years. The results show that magnitude and duration dramatically decrease in the near future for the climate scenarios under analysis; these features presented a declining effect from the near to the far future. Additionally, the severity shows a general increment with respect to the base period, which is intensified with longer return periods; however, the severity shows a decrement for specific areas in the far future of RCP 4.5 and near future of RCP 8.5. This research adds knowledge to the evaluation of droughts in complex terrain in tropical regions, where the representation of convection is the main limitation of global climate models (GCMs). The results provide useful information for decision-makers supporting mitigating measures in future decades. [ABSTRACT FROM AUTHOR]

Changes in climate extremes have become a hot issue in the research field of climate change recently. Many studies have reported that climate extremes have occurred more frequently and with increasing intensity in recent decades. In this study, thresholds of precipitation and drought extremes were determined by the cumulative distribution function, and their spatiotemporal changes over the past half-century in China were analyzed by relative change rate. The results show that: (1) precipitation extremes increased in all regions except North China, while increasing trends of drought extremes were detected in all regions except Northwest China and the Qing–Tibet Plateau; (2) the maximum change rates in frequency of precipitation extremes were found in Northwest China and the Qing–Tibet Plateau, with values of 16.13% and 8.12%, and the maximum change rates in frequency of drought extremes were in Southwest and Southeast China, whose increases in intensity of drought extremes were also the maximum; (3) variation in precipitation extremes showed a relatively mixed pattern with higher heterogeneity compared to that of drought extremes; and (4) changes in precipitation and drought extremes relate to mid-intensity, lower-intensity, and annual precipitation. [ABSTRACT FROM AUTHOR]

The climate in Central Europe (CEU) during the 20th century is characterized by an overall temperature increase. Severe and prolonged drought events began occurring towards the end and these have continued into the 21st century. This study aims to analyze variations in the moisture supply from the Mediterranean Sea (MDS) during meteorological drought episodes occurring over the CEU region over the last three decades. A total of 51 meteorological drought episodes (22 with summer onsets, and 29 with winter) are identified over the CEU during the period 1980–2015 through the one-month Standardized Precipitation Evapotranspiration Index (SPEI-1), and their respective indicators, including duration, severity, intensity, and peak values, are then computed. Lagrangian forward-in-time analysis reveals that negative anomalies of moisture coming from the MDS prevail in all episodes except seven. Linear regression analysis between variations in the MDS anomalies and indicators of the drought episodes shows a significant linear relationship between severity, duration, peak values (winter), and MDS anomalies, which implies that drought episodes last longer and are more severe with an increase in the negative anomaly of moisture supply from the MDS. Nevertheless, no linear relationship is found between the intensity and peak values (annual, summer) of drought episodes and anomalies in the moisture contribution from the MDS. [ABSTRACT FROM AUTHOR]