Change in extreme precipitation events: Exposure and vulnerability in the Poyang Lake Basin, China

Detection and attribution of extreme precipitation changes from 1961 to 2012 in the Yangtze River Delta in China

Changes in precipitation extremes in the Yangtze River Basin during 1960–2019 and the association with global warming, ENSO, and local effects

This study examines the potential impacts of climate change on the characteristics of precipitation over the Drakensberg Mountain Range (DMR) at different global warming levels (GWLs: 1.5, 2.0, 2.5 and 3.0°C) under the Representative Concentration Pathway 8.5 (RCP8.5) scenario, using dynamical and statistical downscaled datasets. The dynamical datasets consist of 19 multi‐model simulations datasets from the Coordinated Regional Climate Downscaling Experiment (CORDEX), whereas the statistical downscaled datasets comprise 19 multi‐model simulations from the National Aeronautics and Space Administration (NASA) Earth Exchange (NEX) Global Daily Downscaled Projections (NEX‐GDDP, hereafter NEX). The capacity of the CORDEX and NEX datasets to represent past characteristics of extreme precipitation over the DMR was evaluated against eight observation datasets. The precipitation characteristics were represented by eight precipitation indices. Both CORDEX and NEX realistically capture the characteristics of extreme precipitation over the Drakensberg and, in most cases, their biases lie within the observation uncertainty. However, NEX performs better than CORDEX in reproducing most of the precipitation characteristics, except in simulating the threshold of extreme rainfall. The ensemble means of CORDEX and NEX agree on a future increase in the intensity of normal precipitation, in the frequency and intensity of extreme precipitation, as well as an increase in widespread extreme events, with a decrease in the number of precipitation days and continuous wet days. However, they disagree on the projected changes of annual precipitation, for which CORDEX projects an increase over most parts of the DMR, whereas NEX indicates a decrease. The self‐organizing‐map analysis, which reveals diversity in the projection patterns hidden in the ensemble means, shows the most probable combinations of projected changes in the annual precipitation and extreme precipitation events (in terms of intensity and frequency): (a) increase in both annual precipitation and extreme precipitation events; (b) decrease in both annual precipitation and extreme precipitation events; (c) decrease in annual precipitation but increase in extreme precipitation events. The results of this study can thus provide a basis for developing climate change adaptation and mitigating strategies over the DMR.

Increased flood risk in Indian sub-continent under the warming climate

Radley Horton,1,a Daniel Bader,1,a Yochanan Kushnir,2 Christopher Little,3 Reginald Blake,4 and Cynthia Rosenzweig5 1Columbia University Center for Climate Systems Research, New York, NY. 2Ocean and Climate Physics Department, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY. 3Atmospheric and Environmental Research, Lexington, MA. 4Physics Department, New York City College of Technology, CUNY, Brooklyn, NY. 5Climate Impacts Group, NASA Goddard Institute for Space Studies; Center for Climate Systems Research, Columbia University Earth Institute, New York, NY

Introduction: Limited understanding exists regarding the association between extreme weather events and risk of Campylobacteriosis, particularly for communities in coastal regions. Methods: Laboratory culture-confirmed cases of Campylobacteriosis were obtained from the Maryland Foodborne Diseases Active Surveillance Network for Maryland from 2002 to 2012 along with clinical and demographic information. This data was combined with location and calendar day specific extreme temperature and precipitation events calculated using a 30-year baseline (1960-1989). Multivariate negative binomial regression utilizing generalized estimation equations was used to investigate the associations between Campylobacteriosis and extreme weather events. Results: There were 4,804 cases of Campylobacteriosis from 2002-2012 in Maryland. Through stratified analysis, we observed a 2% increase in risk of Campylobacteriosis for Non-Hispanic Whites associated with a one-unit increase in extreme precipitation events, but a marginally significant decrease in risk for extreme temperature events (IRR 0.98, 95% CI: 0.97, 1.00). For a one-unit increase in extreme precipitation events, this risk was considerably higher in the Eastern Shore region (IRR 1.05, 95% CI: 1.01, 1.09), and during the El Niño period (IRR 1.10, 95% CI: 1.06, 1.14). Discussion: Our data suggest that Campylobacteriosis is associated with extreme precipitation events in Maryland. The risk was more pronounced in the coastal areas and during El Niño periods. Extreme precipitation related flooding in coastal areas could bring water contaminated with bacterial pathogens (originating from point sources such as municipal wastewater treatment plants and animal feeding operations) into close proximity with individuals, where frequency of contact (via swimming or recreation) may be higher. Increased risk associated with the El Niño period could be related to the more intense precipitation events during this time period.

<sec> <p indent="0mm">Extreme precipitation presents grand challenges for meteorological disaster prevention and water resource management, which becomes even more serious under global warming as the frequency and intensity of extreme precipitation are increasing. However, our understanding of the process and intensity of extreme precipitation remains limited. Ground-based gauge observations are generally considered the “ground truth”, but in complex terrain regions with high spatial variability in precipitation, they suffer from limited coverage and insufficient representativeness. Satellite precipitation retrievals, although offering global coverage, often underestimate the intensity of heavy precipitation and exhibit inaccurate diurnal variations. Numerical simulations of extreme precipitation events have shown their potential to improve our understanding of their occurrence and mechanisms. Advances in computational capabilities have enabled numerical models to operate at horizontal resolutions of <sc>4 km</sc> or higher, facilitating the simulation of extreme precipitation events without relying on semi-empirical convective parameterization schemes, which is a major source of uncertainty in precipitation simulations. These simulations, known as convection-permitting modeling, more accurately capture key characteristics of extreme precipitation, such as hourly precipitation intensity, mesoscale convective systems that drive heavy precipitation and strong winds, and precipitation patterns in complex terrain, compared to traditional large-scale convection-parameterized modeling with horizontal resolution coarser than <sc>10 km.</sc> Convection-permitting modeling has become a reliable tool for improving precipitation estimates and advancing our understanding of hydrological processes. Leading international institutions are at the forefront of research in this field, with numerous collaborative projects underway. As a result, the use of convection-permitting modeling to study extreme precipitation events has grown rapidly in recent years. </sec> <sec> This article systematically reviews studies on convection-permitting modeling of extreme precipitation over the past decade, with a focus on their main objectives, methods, and key findings. The reliability of convection-permitting modeling has led to innovative approaches, such as using it to correct near-real-time satellite precipitation products in complex terrain or to reconstruct extreme precipitation events from the past that lacked sufficient observational data. Research on historical extreme precipitation events has advanced to address the limitations of convection-permitting modeling and explore strategies to overcome these challenges. Two common approaches to improving model performance are increasing horizontal resolution and employing scale-aware convective parameterization schemes. However, issues such as the cost-effectiveness of simulations and uncertainties in simulating heavy precipitation during cold seasons require further investigation. For future extreme precipitation events, key topics include changes in precipitation driven by mesoscale convective systems and the relationship between extreme precipitation and temperature changes under climate change. The combination of convection-permitting modeling with the pseudo-global warming approach enables the estimation of extreme precipitation events under various future climate scenarios, offering more detailed insights into the physical processes underlying these events and allowing for a more comprehensive analysis of climate change impacts. This review highlights how study areas have expanded from typical regions with abundant observations to those with limited observational data, and how simulations have increasingly incorporated “multi-model and multi-physics ensemble, wide-range and long-term simulations”. The research focus has also evolved from studying precipitation characteristics to conducting in-depth analyses of dynamic and thermodynamic mechanisms. The major challenges in this field include the complexity of parameterization schemes beyond convection processes, limitations in evaluation datasets and methods, as well as large computing and storage requirements. Finally, this review proposes strategies to advance convection-permitting modeling of extreme precipitation, including enhancing domestic and international simulation collaborations, improving evaluation datasets and methods, developing more comprehensive regional and global unified models, and better aligning with downstream application needs. </sec>

Extreme precipitation events are climatic hazard phenomena that can lead to riverine floods, flash floods, and landslides, posing significant threats to society and the environment. In this study, we examine the effects of climate change on the frequency and intensity of extreme precipitation events in the Middle East and North Africa (MENA) region. Our analysis focuses on daily precipitation simulations at a spatial resolution of approximately 50 km, provided by both regional and global climate models. Detecting changes in extreme precipitation events is challenging due to their high variability in time and space. Therefore, we employ the Simplified Meta-statistical Extreme Value (SMEV) method, an advanced extreme precipitation frequency analysis approach that enables a more robust frequency analysis of extreme precipitation by reducing uncertainty compared to traditional methods. We find that, while average precipitation levels exhibit heterogeneous changes across the MENA region, a general intensification of extreme precipitation is expected. Notably, the intensification is stronger for rarer events. Our results also indicate that changes in both average and extreme precipitation across the MENA region are spatially non-uniform, with some areas experiencing intensification while others show a downward change, with regional variability in change strength. The strongest intensification in extreme precipitation is projected over central Africa and the northern Arabian Sea region. We also find that the regional patterns in extreme and average precipitation changes are not always aligned. Notably, mean annual precipitation is expected to decline over the Mediterranean, while extreme precipitation return levels are projected to intensify in much of the area.

Precipitation extremes are among the most serious consequences of climate change around the world. The observed and projected frequency and intensity of extreme precipitation in some regions will greatly influence the social economy. The frequency of extreme precipitation and the population and economic exposure were quantified for a base period (1986–2005) and future periods (2016–2035 and 2046–2065) based on bias corrected projections of daily precipitation from five global climatic models forced with three representative concentration pathways (RCPs) and projections of population and gross domestic product (GDP) in the shared socioeconomic pathways (SSPs). The RCP8.5‐SSP3 scenario produces the highest global population exposure for 2046–2065, with nearly 30% of the global population (2.97 × 109 persons) exposed to precipitation extremes >10 days/a. The RCP2.6‐SSP1 scenario produces the highest global GDP exposure for 2046–2065, with a 5.56‐fold increase relative to the base period, of up to (2.29 ± 0.20) × 1015 purchasing power parity $‐days. Socioeconomic effects are the primary contributor to the exposure changes at the global and continental scales. Population and GDP effects account for 64–77% and 78–91% of the total exposure change, respectively. The inequality of exposure indicates that more attention should be given to Asia and Africa due to their rapid increases in population and GDP. However, due to their dense populations and high GDPs, European countries, that is, Luxembourg, Belgium, and the Netherlands, should also commit to effective adaptation measures.

Introduction: Several studies have shown associations between an increase in precipitation and a higher frequency of traffic accidents; a few have examined the relationship between high temperatures and motor vehicle crashes. However, to our knowledge, no studies exist assessing how extreme events, projected to grow in frequency, intensity, and duration in response to our changing climate, will impact the risk of injury from motor vehicle accidents. Our study quantified the association between frequency of extreme heat and precipitation events and change in injury risk from motor vehicle accident in Maryland between 2000 and 2012. Methods: Motor vehicle accident data was obtained from the Maryland Automated Accident Reporting System. Each observation in the data set corresponded to a unique collision event. A time-stratified case-crossover design was utilized to assess the association between exposure to extreme heat and precipitation events and risk of injury or death from motor vehicle accident. Additional stratified analyses examined risk by road type and season. Results: Over the study period, there were 461,009 motor vehicle accidents that resulted in injury or death. We observed an 18% increase (OR: 1.18; 95% CI: 1.17, 1.19) in risk of motor vehicle injury for every 1-day increase in extreme precipitation event, with the highest risk (29%) observed during autumn (OR: 1.29; 95% CI: 1.27, 1.32). Extreme precipitation related increase in motor vehicle injury was considerably higher when a road defect or obstruction was present (OR: 1.42, 95% CI: 1.32, 1.52). Changes in risk associated with extreme heat events were generally marginal. Conclusion: Extreme precipitation events, particularly in conjunction with a road defect or obstruction, are associated with an increased risk of injury from motor vehicle accidents in Maryland. Our results suggest that projected increases in frequency of extreme precipitation event will have a significant impact on public health.

Based on daily measured data from 25 stations in Xinjiang Province from 1963 to 2017, we discuss the statistical characteristics, linear trends, and temporal concentration of slight precipitation (SP) and extreme precipitation (EP) events, and consider relationships between SP and EP events and daily mean temperature. The results show that SP events contribute strongly to the total annual number of wet days, and that EP events contribute strongly to the total annual precipitation amount. In consist with the decrease in SP events and the increase in EP events over the 55-year period, the contribution of SP events to total annual number of wet days has decreased significantly while the contribution of EP events to total annual precipitation amount has increased significantly. SP event usually distributes through most months of the year, whereas EP event usually concentrates in summer (JJA). Influenced by the negative trends for SP events frequency and positive trends of EP events frequency during recent decades, the concentration degree for SP and EP events have significantly increased and decreased, respectively. Distinct differences are found between the relationships of SP events and EP events to daily mean temperature. The daily mean temperature recorded at the stations in Northern Xinjiang on days with SP events was between –35°C and +34°C, and for EP events ranged from –21°C to +30°C. Regionally averaged curves for the change in SP and EP event frequency with temperature have bimodal and unimodal distributions, respectively. Trends for daily mean temperatures and for the frequency of SP events at different temperatures agree well over nearly the entire temperature range, while trends for daily mean temperatures and for the frequency of EP events at different temperatures are not always consistent. These results will help to improve our understanding of the characteristics and variability of precipitation in arid regions within the context of climate warming.

Extreme precipitation events, which have intensified with global warming over the past several decades, will become more intense in the future according to model projections. Although many studies have been performed, the occurrence patterns for extreme precipitation events in past and future periods in China remain unresolved. Additionally, few studies have explained how extreme precipitation events developed over the past 58 years and how they will evolve in the next 90 years as global warming becomes much more serious. In this paper, we evaluated the spatiotemporal characteristics of extreme precipitation events using indices for the frequency, quantity, intensity, and proportion of extreme precipitation, which were proposed by the World Meteorological Organization. We simultaneously analyzed the spatiotemporal characteristics of extreme precipitation in China from 2011 to 2100 using data obtained from the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Despite the fixed threshold, 95th percentile precipitation values were also used as the extreme precipitation threshold to reduce the influence of various rainfall events caused by different geographic locations; then, eight extreme precipitation indices (EPIs) were calculated to evaluate extreme precipitation in China. We found that the spatial characteristics of the eight EPIs exhibited downward trends from south to north. In the periods 1960–2017 and 2011–2100, trends in the EPIs were positive, but there were differences between different regions. In the past 58 years, the extreme precipitation increased in the northwest, southeast, and the Tibet Plateau of China, while decreased in northern China. Almost all the trends of EPIs are positive in the next two periods (2011–2055 and 2056–2100) except for some EPIs, such as intensity of extreme precipitation, which decrease in southeastern China in the second period (2056–2100). This study suggests that the frequency of extreme precipitation events in China will progressively increase, which implies that a substantial burden will be placed on social economies and terrestrial ecological processes.

Based on the observation data from the Poyang Lake Basin (China), an extreme precipitation event (EPE) is defined as that for which daily precipitation exceeded a threshold of 50 mm over a continuous area for a given time scale. By considering the spatiotemporal continuity of EPEs, the intensity–area–duration method is applied to study both the characteristics of EPEs and the population and gross domestic product (GDP) exposures. The main results are as follows. (1) During 1961–2014, the frequencies and the intensities of the EPEs are found to be increasing. (2) The annual area impacted by EPEs is determined as 7.4 × 104 km2 with a general upward trend of 400 km2/year. (3) The annually exposed population is estimated as 19% of the entire population of the Basin, increasing by 1.37 × 105/year. The annual exposure of GDP is 8.5% of the entire GDP of the Basin, increasing by 3.8 billion Yuan/year. The Poyang Lake Basin experiences serious extreme precipitation with increasing trends in frequency, intensity, and exposure (for both GDP and population). It is imperative that effective disaster prevention and reduction measures be adopted in this area to mitigate the effects of extreme precipitation.

Increase in extreme precipitation events under anthropogenic warming in India

The intensification of global climate change and regional human activities has led to an increase in the frequency and intensity of extreme precipitation, posing significant challenges to regional sustainable development. Using daily precipitation observation data from 108 meteorological stations during 1960–2020, the spatiotemporal distribution characteristics of extreme precipitation in the Dongting Lake Basin (DLB) are revealed, and the mechanisms driving extreme precipitation variation in the DLB are investigated. The results showed that with the increase in the frequency, intensity and amount of extreme precipitation, the DLB is trending towards increased humidity. However, consecutive wet days have declined significantly at a rate of −0.015 days/year, indicating that more short‐duration but high‐intensity extreme precipitation are likely to occur in the future. These changes have intensified with the increase in regional average warming. In contrast, the weakening of the East Asian Summer Monsoon (EASM) amplifies changes in extreme precipitation through nonlinear enhancement mechanisms, particularly when interacting with other climate drivers. Additionally, extreme precipitation exhibits a sensitive response to elevation. Specifically, low‐altitude areas tend to experience more frequent and intense extreme events, whereas high‐altitude regions are more prone to short‐duration heavy rainfall. The fastest growth in extreme precipitation was observed in the hilly‐valley transition zone between the northern Xuefeng Mountains and southern Wuling Mountains. At the sub‐basin level, the Lishui River Basin exhibits relatively minor variations in most extreme precipitation indices, while the Xiangjiang River Basin records the greatest increase in the frequency of extreme precipitation. These patterns may be explained by differences in the categories of dominant climate drivers and the strength of their associated impacts.