Extreme Precipitation Intensity Research Articles

Projected future changes in extreme precipitation over China under stratospheric aerosol intervention in the UKESM1 climate model

Abstract. Extreme precipitation events are linked to severe economic losses and casualties in China every year; hence, exploring the potential mitigation strategies to minimize these events and their changes in frequency and intensity under global warming is of importance, particularly for the populous subregions. In addition to global warming scenarios, this study examines the effects of the potential deployment of stratospheric aerosol injection (SAI) on hydrological extremes in China based on the SAI simulations (G6sulfur) of the Geoengineering Model Intercomparison Project (GeoMIP) by the UK Earth System Model (UKESM1) simulations. G6sulfur is compared with simulations of the future climate under two different emission scenarios (SSP5-8.5 and SSP2-4.5) and a reduction in the solar constant (G6solar) to understand the effect of SAI on extreme precipitation patterns. The results show that under global warming scenarios, precipitation and extreme wet climate events during 2071–2100 are projected to increase relative to the control period (1981–2010) across all the subregions in China. Extreme drought events show a projected increase in southern China. The G6sulfur and G6solar experiments show statistically similar results to those under SSP2-4.5 in extreme precipitation intensities of China in UKESM1. These results are encouraging. The efficacy of SAI in decreasing extreme precipitation events and consecutive wet days is more pronounced than that of G6solar when compared to SSP2-4.5. While both G6sulfur and G6solar show drying at high-latitude regions, which is consistent with our understanding of the spin-down of the hydrological cycle under SRM. Given the limitations of the current model and the small ensemble size, and considering that the hydrological effects are less beneficial than those indicated for temperature, it is recommended that further, more comprehensive research be performed, including using multiple models, to better understand these impacts.

Climate Change Impact on the Stability of Soil Slopes from a Hydrological and Geotechnical Perspective

Climate change (CC) is expected to cause significant changes in weather patterns, leading to extreme phenomena. Specifically, the intensity of precipitation extremes is continuously escalating, even in regions with decreasing average precipitation levels. Given that CC leads to long-term shifts in weather patterns and may affect the precipitation characteristics (i.e., frequency, duration, and intensity) directly related to groundwater table fluctuations and soil erosion phenomena, it has the potential to significantly affect soil slope instabilities. In turn, slope stability and the structural integrity of nearby structures and infrastructure will be affected. Accordingly, the present paper focuses on the impact of CC on the geohazard of soil slope instability by considering both hydrological aspects, i.e., the impact on rainfall intensity on the groundwater table and the geotechnical aspects of this complex problem. The findings reveal that the impact of CC on potential slope instabilities can be detrimental or even beneficial, depending on the specific site and water conditions. Therefore, it is essential to do the following: (a) collect all the available data of the area of interest, (b) assess their variations over time, and (c) examine each potentially unstable slope on a case-by-case basis to properly mitigate this geohazard.

Evaluating Factors Affecting Flood Susceptibility in the Yangtze River Delta Using Machine Learning Methods

AbstractFloods are widespread and dangerous natural hazards worldwide. It is essential to grasp the causes of floods to mitigate their severe effects on people and society. The key drivers of flood susceptibility in rapidly urbanizing areas can vary depending on the specific context and require further investigation. This research developed an index system comprising 10 indicators associated with factors and environments that lead to disasters, and used machine learning methods to assess flood susceptibility. The core urban area of the Yangtze River Delta served as a case study. Four scenarios depicting separate and combined effects of climate change and human activity were evaluated using data from various periods, to measure the spatial variability in flood susceptibility. The findings demonstrate that the extreme gradient boosting model outperformed the decision tree, support vector machine, and stacked models in evaluating flood susceptibility. Both climate change and human activity were found to act as catalysts for flooding in the region. Areas with increasing susceptibility were mainly distributed to the northwest and southeast of Taihu Lake. Areas with increased flood susceptibility caused by climate change were significantly larger than those caused by human activity, indicating that climate change was the dominant factor influencing flood susceptibility in the region. By comparing the relationship between the indicators and flood susceptibility, the rising intensity and frequency of extreme precipitation as well as an increase in impervious surface areas were identified as important reasons of heightened flood susceptibility in the Yangtze River Delta region. This study emphasized the significance of formulating adaptive strategies to enhance flood control capabilities to cope with the changing environment.

Detection and Attribution of Changes in Precipitation Extremes in China and Its Different Climate Zones

Abstract Based on the observations and the phase 6 of Coupled Model Intercomparison Project (CMIP6) multimodel simulations, we conducted a detection and attribution analysis for the observed changes in intensity and frequency indices of extreme precipitation during 1961–2014 over the whole of China and within distinct climate regions across the country. A space–time analysis is simultaneously applied in detection so that spatial structure on the signals is considered. Results show that the CMIP6 models can simulate the observed general increases of extreme precipitation indices during the historical period except for the drying trends from southwestern to northeastern China. The anthropogenic (ANT) signal is detectable and attributable to the observed increase of extreme precipitation over China, with human-induced greenhouse gas (GHG) increases being the dominant contributor. Additionally, we also detected the ANT and GHG signals in China’s temperate continental, subtropical–tropical monsoon, and plateau mountain climate zones, demonstrating the role of human activity in historical extreme precipitation changes on much smaller spatial scales. Significance Statement The observed intensification of extreme precipitation globally has been attributed to human influences. Here, we demonstrate that anthropogenic forcing has discernably intensified extreme precipitation over the period 1961–2014, over China and in three of its four climate zones, with human-induced greenhouse gas increases being the dominant contributor. Our results strengthen the body of evidence that greenhouse gas increases are intensifying extreme precipitation by quantifying their role in observed changes at smaller regional scales than previously reported.

Global warming intensifies once-in-a-decade extreme precipitation in summer in China

The intensification of extreme precipitation (EP) under global warming presents a substantial risk to human safety and societal progress. Studying the specific impacts of global warming on rare EP events in China not only enhances our comprehension of these shifts, but also paves the way for the development of proactive strategies to alleviate associated damages. Results from large-ensemble simulation data demonstrate that global warming has led to an enhancement in once-in-a-decade EP events in parts of western and central China over the past few decades, with the strengthening of the South Asia high (SAH) caused by global warming playing a dominant role. The strengthening of the SAH corresponds to an intensification and westward extension of the western Pacific subtropical high in the lower troposphere. The region between these two systems experiences enhanced upward motion and increased southwesterly water vapor transport, leading to a rise in climatological precipitation in western and central China, thereby raising the threshold for once-in-a-decade EP events.

Global Assessment of Compound Climate Extremes and Exposures of Population, Agriculture, and Forest Lands Under Two Climate Scenarios

AbstractClimate change is expected to increase the global occurrence and intensity of heatwaves, extreme precipitation, and flash droughts. However, it is not well understood how the compound heatwave, extreme precipitation, and flash drought events will likely change, and how global population, agriculture, and forest will likely be exposed to these compound events under future climate change scenarios. This research uses eight CMIP6 climate models to assess the current and future global compound climate extreme events, as well as population, agriculture, and forestry exposures to these events, under two climate scenarios, Shared Socioeconomic Pathways (SSP), SSP1‐2.6 and SSP5‐8.5 for three time periods: early‐, mid‐, and late‐ 21st century. Climate extremes are derived for heatwaves, extreme precipitation, and flash droughts using locational‐dependent thresholds. We find that compound heatwaves and flash drought events result in the largest increases in exposure of populations, agriculture, and forest lands, under SSP5‐8.5 late‐century projections of sequential heatwaves and flash droughts. Late‐century projections of sequential heatwaves and flash droughts show hot spots of exposure increases in population exposure greater than 50 million person‐events in China, India, and Europe; increases in agriculture land exposures greater than 90 thousand km2‐events in China, South America, and Oceania; and increase in forest land exposure greater than 120 thousand km2‐events in Oceania and South America regions when compared to the historical period. The findings from this study can be potentially useful for informing global climate adaptations.

Spatiotemporal variation and teleconnections of extreme precipitation in the Upper Indus Basin: insights for natural hazard assessment

ABSTRACT The study investigates trends and teleconnections of extreme precipitation events in the Upper Indus Basin (UIB) within the Indian region, part of the crucial geo-ecological Hindu Kush Himalayan Mountain system. Utilizing high-resolution (10 km × 10 km) HAR data from 2002 to 2013, we analyzed 11 indices established by the Expert Team on Climate Change Detection and Indices (ETCCDI) to observe variations in extreme precipitation at the monthly, seasonal, and annual time scale. The result shows an increase in dry and wet extreme precipitation frequency and intensity, increasing monsoon precipitation and a shift of winter precipitation, increasing continuous dry days. Using the APHRODITE daily (0.25° × 0.25°) data from 1952 to 2014, continuous wavelet transform and wavelet coherence analysis indicate significant periodicities and correlations with large-scale climate anomalies such as the El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO). Wavelet coherence analysis reveals that monthly extreme precipitation events significantly correlate with ENSO at a 3–5 years periodicity, while annual extremes show significant coherence with NAO at 8–10 years and over 16 years periodicities. The study highlights the impact of global climate change on regional precipitation and the need for adaptive water management policies to mitigate flood risks during the rainy season and address water scarcity in the dry season.

Exploring patterns in precipitation intensity–duration–area–frequency relationships using weather radar data

Abstract. Accurate estimations of extreme precipitation return levels are critical for many hydrological applications. Extreme precipitation is highly variable in both space and time; therefore, to better understand and manage the related risks, knowledge of their probability at different spatial–temporal scales is crucial. We employ a novel non-asymptotic framework to estimate extreme return levels (up to 100 years) at multiple spatial–temporal scales from weather radar precipitation estimates. The approach reduces uncertainties and enables the use of relatively short archives typical of weather radar data (12 years in this case). We focus on the eastern Mediterranean, an area of high interest due to its sharp climatic gradient, containing Mediterranean, semi-arid, and arid areas across a few tens of kilometres, and its susceptibility to flash flood. At-site intensity–duration–area–frequency relations are derived from radar precipitation data at various scales (10 min–24 h, 0.25–500 km2) across the study area, using ellipses of varying axes and orientations to account for the spatial component of storms. We evaluate our analysis using daily rain gauge data over areas for which sufficiently dense gauge networks are available. We show that extreme return levels derived from radar precipitation data for 24 h and 100 km2 are generally comparable to those derived from averaging daily rain gauge data over a similar areal scale. We then analyse differences in multi-scale extreme precipitation over coastal, mountainous, and desert regions. Our study reveals that the power-law scaling relationship between precipitation and duration (simple scaling) weakens for increasing area sizes. This finding has implications for temporal downscaling. Additionally, precipitation intensity varies significantly for different area sizes at short durations but becomes more similar at long durations, suggesting that, in the region, areal reduction factors may not be necessary for computing return levels over long durations. Furthermore, the reverse orographic effect, which causes decreased precipitation for hourly and sub-hourly durations, diminishes for larger areas. Finally, we discuss the effects of orography and coastline proximity on extreme precipitation intensity over different spatial–temporal scales.

Spatiotemporal patterns in persistent precipitation extremes of the Chinese mainland (1961–2022) and association with the dynamic factors

Previous studies on extreme precipitation events have primarily focused on the intensity of such events during fixed periods, without considering the entirety of extreme precipitation events and conducting a comprehensive examination of the intensity and frequency of more disastrous persistent extreme precipitation (PEP) events. In this paper, persistent extreme precipitation indices (PEPIs) related to intensity, frequency, duration, and contribution rates were constructed, utilizing a gridded daily precipitation dataset and atmospheric circulation indices data from China for the period 1961–2022 to analyze the spatial distribution, spatiotemporal trends, and seasonal patterns and variations of PEPIs across different regions of China and the potential impact of the dynamic factors on the spatiotemporal variations of PEPIs. The results are crucial for effectively predicting future changes and informing planning for adaptation strategies: From 1961 to 2022, (1) China's PEP pattern displays distinct regional variations. PEP has been prevalent in Western Arid (Semi-Arid) Zone (WAS) and Qinghai-Tibet Plateau (QT) regions, with higher occurrence frequency, duration, and contribution rates to total extreme precipitation (44.91% and 42.01%) and overall precipitation (26.35% and 29.08%). Conversely, the humid eastern regions exhibit greater event intensity. (2) Intensity-related PEPIs show a significant increase, while the frequency and contribution rate-related PEPIs tend to decrease, indicating less frequent but more concentrated PEP events. (3) Seasonal distribution of PEP events shows a primary concentration in QT, North China (N), the Eastern arid zone (EA), and Northeast China (NE) from June to September and they occur more frequently during spring and summer in Central (C) and South China (S) regions. Summer variations predominantly account for annual PEP variability and trends. (4) WPSHII, SCSSHII, WPWPSII, APVII, NHPVII, NINO3 predominantly affect the WAS, QT, NE, C, and S regions, with WPSHII having the broadest impact, notably on the QT, C, S, and NE regions. In the WAS region during autumn, the interaction of NAO and WPSHII explains 72% of the intensity of PEP events.

Extreme weather has variable effects on reproductive success of grassland songbirds at the northern extent of their range

Abstract Grassland songbirds breeding in Canada and the United States have experienced significant population declines likely because of habitat loss and degradation. Many climate change models predict an increase in the frequency, intensity, and duration of extreme precipitation and temperature events that could place further pressures on declining species. We monitored the fate of 1,868 individual nesting attempts of 7 grassland songbird species in response to various precipitation and temperature measures over a 10-yr period (1997 to 2002 and 2004 to 2008) in Saskatchewan, Canada. Daily nest survival rates of 5 species, including 3 at-risk species, were negatively influenced by high levels of precipitation, although the amount of precipitation where declines in daily nest survival occurred varied. Daily nest survival rates of 2 species were negatively correlated with high temperatures. We failed to detect any relationship between precipitation or temperature and the number of fledglings produced from successful nests. Extreme weather events could add additional stressors to declining populations of grassland birds in Canada. Increases in the frequency and intensity of extreme weather, specifically extreme precipitation events and short-term high temperatures, will likely lead to lower reproductive success for several species compared to current levels. This may be especially problematic for management of Anthus spragueii (Sprague’s Pipit) and Centronyx bairdii (Baird’s Sparrow), where a large proportion (> 75%) of the breeding population occurs near the northern edge of the Great Plains. The continuing loss and degradation of northern grasslands may limit the ability of these species to disperse and find favorable climate conditions.

Relationship Between Circulation Types and Extreme Precipitation Over Scandinavia Is Stable Under Climate Change

AbstractThe atmospheric large‐scale environment determines the occurrence of local extreme precipitation, and it is unclear how climate change affects this relationship. Here we investigate the present‐day relationship between large‐scale circulation types (CTs) and daily precipitation extremes over Scandinavia and its future change. A 50‐member EC‐Earth3 large ensemble is used to assess future changes against internal variability. We show that CTs are related to extreme precipitation over the entire domain. The intensity of extreme daily precipitation increases in all seasons in the future climate, generally following the strength of warming in the six different future scenarios considered. However, no significant future change is found in the relationship between extreme precipitation and the CTs in any season or scenario. The results have important implications for applications that rely on the stability of this relationship, such as statistical and event‐based dynamical downscaling of future weather and climate predictions and long‐term climate projections.

Characterisation of extreme precipitation changes in the upper reaches of the Yangtze River, China

ABSTRACT The paper analyses the spatial and temporal characteristics of extreme precipitation in the upper reaches of the Yangtze River through extreme precipitation indicators based on the trend method, the Mann–Kendall trend test, and the rescaled extreme deviation extreme deviation using daily precipitation data from 1961 to 2021. The following conclusions were obtained: The overall precipitation in the upper reaches of the Yangtze River is reduced, and the number of rainy days is reduced. The frequency of extreme precipitation is generally reduced, but the spatial difference in the intensity of extreme precipitation is greater, which makes the occurrence of extreme precipitation more concentrated and more destructive. Extreme precipitation indicators showed relatively large fluctuations after 2000, especially in terms of extreme precipitation intensity. The frequency of extreme precipitation in the upper reaches of the Yangtze River is the highest in the main stream of the Yangtze River Basin and the Wujiang River Basin, the intensity of extreme precipitation is in the Jialing River and the Wujiang River Basin, and the accumulation of extreme precipitation is the highest in the Jialing River and the Wujiang River Basin, whereas the maximum value of the station extreme precipitation intensity and frequency is in the Minjiang River Basin.

Impacts of extreme precipitation on water conservation in Beijiang River Basin, China

Water conservation, which has been regarded as one of the most crucial ecosystem service functions of river basins, is a key factor for sustainable development, that has garnered widespread attention in the context of climate change. However, little attention has been paid to daily water conservation and its response to extreme precipitation events. In this study, we selected the Beijiang River Basin (BJRB) as the study area, which is an important ecological barrier for the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), based on the distributed hydrological model WEP-L (Water and Energy transfer Processes in Large River basin) and water balance equation, the spatiotemporal characteristics of extreme precipitation and four daily water conservation indicators (maximum 1 day, maximum 3 day, maximum 5 day, maximum 7 day water conservation) in the BJRB from 1965 to 2009 were analysed, and the responses of these indicators to extreme precipitation were investigated. The results reveal that (1) the amount (RX1day, RX3day, RX5day, RX7day, R95p, and R99p), intensity (SDII), and frequency (R50mm) of extreme precipitation increased in the BJRB during 1965–2009, with SDII undergoing a significant increase. (2) The four water conservation indicators were positive, indicating that the watershed reduced peak flow during the extreme precipitation period by accumulating precipitation. The rate of increase of the four water conservation indicators were lower than that of extreme precipitation indices, there will be more extreme precipitation converted into surface runoff, thereby increasing the risk of flooding. The four indicators increased in the southern and northern regions of the BJRB, while decreased in the central region during 1965–2009. (3) The four indicators were generally positively correlated with most of the extreme precipitation indices in the northern BJRB, especially RX1day, RX3day, RX5day, RX7day, R99p, and R50mm. The results provide a scientific reference for water conservation adaptation to extreme precipitation variations, protection of the ecological environment, and the prevention and reduction of disasters in the region.

Climate risk assessment and adaption ability in China's coastal urban agglomerations - A case study of Guangdong-Hong Kong-Macao greater bay area

As climate change intensifies, extreme weather events, especially the coastal flooding is becoming increasingly severe. Carbon emissions exacerbate climate change, leading to increased frequency and intensity of extreme precipitation, which may result in flooding. This study focuses on the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a coastal city cluster in China, and adopts the scenario analysis approach to evaluate flood risks in the different carbon mitigation scenario from the perspectives of dangerousness, and adaption ability. The result shows that the Huizhou in the east of the GBA and the Zhaoqing in the northwest have the highest level of flood disaster risk. However, the central region of the GBA (Guangzhou, Dongguan, Zhongshan, and Foshan) is very vulnerable to disaster-inducing environments and hazard-affected bodies, which means that the flooding risk and the impact of such risk in the GBA display regional differentiation characteristics and the spatial patterns of them are different. According to the carbon neutrality scenario, the flood risk in the GBA peaks in 2030, and decreases during 2030–2090. In contrast, under the uneven development and high carbon pathways, the risk peaks in 2060, and the overall risk by 2090 is roughly the same as that in 2060. In addition, the regions with the highest flood disaster risk are Guangzhou, Foshan, Dongguan and Zhongshan along the Pearl River estuary. Overall, it shows that areas with higher levels of urbanization and more developed economies will face higher flooding risks. The “dangerousness-adaption ability” structure can reflect the spatial distribution pattern of flood disaster risks, identify the priority areas for flood prevention and control, and is conducive to risk management. At the same time, the research results show that ecological protection have a positive effect on reducing flood risk. In addition, corresponding policy recommendations for pre-disaster, mid-disaster and post-disaster have been proposed, providing references for flood risk management in the GBA.

The increases in extreme climatic events over the northeastern Tibetan Plateau and their association with atmospheric circulation changes

In the context of global warming, increasing frequency of climate extremes poses a great challenge to natural systems and humankind. However, the spatial and temporal characteristics, as well as the mechanisms of extreme climate change, remain insufficiently understood, particularly in arid and semi-arid mountainous regions with high climate sensitivity and ecological fragility. In this study, we analyzed the spatial and temporal characteristics of 27 extreme climate indices (including intensity, duration, and frequency) in the Qilian Mountains, northeastern Tibetan Plateau, from 1961 to 2016 using the CN05.1 meteorological grid dataset, explored the relationship between the extreme climate indices and internal variability of the climate system (e.g., the North Atlantic Multi-decadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO), and the Arctic Oscillation (AO)), and further probed into the mechanisms affecting climate extremes using ERA5 reanalysis dataset. The results showed that extreme temperatures in the Qilian Mountains were significantly enhanced in terms of intensity, frequency, and duration during 1961–2016. The decrease rates of frost days (FD0) and ice days (ID0) were − 4.4 d per decade and − 4.7 d per decade, respectively, and the increase rate of growing season length (GSL) was 2.9 d per decade. Extreme precipitation intensity increased significantly, with the intensity indices R95P and PRCPTOT showing the most significant change trends of 4 mm per decade and 14.9 mm per decade, respectively (p < 0.05). The number of consecutive dry days (CDD) displayed a significant downward trend, with a rate of −6 d per decade, the number of moderate precipitation days (R10) showed an increasing trend of 0.12 d per decade. Correlation analyses revealed significant associations between the increases in extreme climates and the AMO and PDO. Additionally, the enhancement of the AO contributed to the increased extreme precipitation. Enhanced anticyclonic circulation in Eurasia and geopotential height, as well as increased cloud cover in winter, were the main reasons for the increase in extreme temperatures in the Qilian Mountains, whereas the significant increase in water vapor transport entering the east boundary of the Qilian Mountains in summer mainly contributed to the increase in extreme precipitation. This study highlights internal oscillations in the climate system that regulate the extreme climate variability in the Qilian Mountains at various spatial-temporal scales.

Future changes in the influence of the NAO on Mediterranean winter precipitation extremes in the EC-Earth3 large Ensemble: The prominent role of internal variability

One of the largest uncertainties in future climate projections is the interplay between internally generated and externally forced changes. This study investigates the changes in the link between the North Atlantic Oscillation (NAO) and Mediterranean winter extreme rainfall and dry days by the end of the 21st century compared to present day. We compare two different future pathways and estimate the extent to which the NAO imprint is affected by the global warming level using the latest EC-Earth3 large ensemble historical and future experiments. It is shown that the expected range of winter extremes changes due to internal and unpredictable fluctuations of the NAO largely overcomes the signal associated with externally-forced NAO variations. The NAO is found to exert a similar control on European climate variability, regardless of the amount of warming. For most of the Mediterranean region, magnitude and even sign of projected changes in the NAO-congruent precipitation indices vary substantially across the individual ensemble members according to the corresponding evolution of the NAO. Internal variability provides an average basin-wide contribution of up to 90% or more to the total NAO-driven variability in SSP1–1.9, and of about 80% in SSP5–8.5. Sub-regionally, the anthropogenic component of the NAO link is more evident over the Iberian Peninsula and parts of the central Mediterranean. This emphasises the role of internal variability and related uncertainty in determining the future impact of the NAO via the large spread in the circulation responses. However, the NAO is found to exert a weaker influence on the extreme precipitation total variability in both future scenarios given their future marked increase in total intensity and variance as opposed to the negligible NAO-related trends. Opposite conclusions are drawn for dry days, which are projected to decrease in the future, especially in the northern Mediterranean. Thus, this study also highlights how the variability of future extreme precipitation intensity in the Mediterranean basin will be less dependent on the principal mode of internal climate variability, posing further challenges for prediction and adaptation to weather-related hazards.

Convection‐Permitting Climate Models Can Support Observations to Generate Rainfall Return Levels

AbstractInformation about the frequency and intensity of extreme precipitation is generally derived from fitting extreme value models using point‐observations, but the regionalization of these models is challenging. Here we propose using high‐resolution convection‐permitting climate model output as covariates for the estimation of observation‐based spatial rainfall return levels. We apply the Weather and Forecasting Research (WRF) model at a 1.5 km resolution driven by ERA5 reanalysis data over southern Germany, where 1,132 rain gauges provide observations of daily rainfall. For this complex topography, we build three different smooth spatial Generalized Extreme Value (GEV) models: (a) a reference model using latitude, longitude and elevation as covariates; (b) a model adding mean annual precipitation from the WRF; (c) a model adding extreme value statistical model estimates using WRF output. We show that the additional information provided by the WRF model can improve the representation of 10‐year and 100‐year return levels of daily rainfall by lowering the percentage bias, mean absolute error, and root‐mean‐square error. Furthermore, we conduct an extensive cross‐validation, where only 5%, 10%, 20%, 50%, 80%, 90%, and 95% of all rain gauges are considered when building spatial GEV models. Again, the additional information provided by the WRF model can improve results here. This cross‐validation study also highlights the robustness of our approach, showing great potential for use in data‐scarce regions.

Influence of season and photoperiod in severe dog attack cases on humans in a Mediterranean climate region

Influence of season and photoperiod in severe dog attack cases on humans in a Mediterranean climate region

Climatic characteristics of hourly extreme precipitation during the warm season in Chongqing

The study analyzed hourly extreme precipitation events in Chongqing and its six sub-regions from 2011 to 2021 during the warm season. Results showed uneven distribution of the 99.7th percentile hourly extreme precipitation threshold, with lower thresholds along the Yangtze River valley and higher thresholds in the Daba Mountains and Wuling Mountains. Both hourly extreme precipitation amount (HEPA) and intensity (HEPI) exhibited higher values in surrounding areas and lower values in the center, with the western, northeast, and southeastern regions experiencing the highest values. Spatial distribution of hourly extreme precipitation frequency varied, with higher frequencies in the northwestern and southern parts of Chongqing. Interannually, hourly extreme precipitation amount slightly increased, while intensity fluctuated. Monthly peak values for amount, frequency, and intensity occurred in July or August, and on a daily scale, the periods from 03:00 to 07:00 and 17:00 to 21: 00 exhibited higher values for amount and frequency, while the period from 11 :00 to 16:00 showed lower values. In summary, the study provided insights into the spatial and temporal patterns of hourly extreme precipitation events in Chongqing and its sub-regions during the warm season, highlighting variations in thresholds, distribution, and trends over the studied period.

Evaluation of Multisource Datasets in Characterizing Spatiotemporal Characteristics of Extreme Precipitation from 2001 to 2019 in China

Abstract The spatiotemporal characteristics of extreme precipitation intensity are crucial for hydroclimatic studies. This study delineates the spatiotemporal distribution features of extreme precipitation intensity across China from 2001 to 2019 using the gridded daily precipitation dataset CN05.1, constructed from an observation network of over 2400 stations. Furthermore, we evaluate the reliability of 12 widely used precipitation datasets (including gauge-based, satellite retrieval, reanalysis, and fusion products) in monitoring extreme precipitation events. Our findings indicate the following: 1) CN05.1 reveals a consistent spatial distribution characterized by a decline in extreme precipitation intensity from the southeastern coastal regions toward the northwestern inland areas of China. From 2001 to 2019, more pronounced declining intensity trends are discernible in the northern and southwestern regions of China, whereas marked increasing trends manifest in the northeastern and the Yangtze River plain regions. National mean extreme precipitation indices consistently exhibit significant increasing trends throughout China. 2) Datasets based on station observations generally exhibit superior applicability concerning spatiotemporal distribution. 3) Multisource weighted precipitation fusion products effectively capture the temporal variability of extreme precipitation indices. 4) Satellite retrieval datasets exhibit notable performance disparities in representing various intensity indices. Most products tend to overestimate the increasing trends of national mean intensity indices. 5) Reanalysis datasets tend to overestimate extreme precipitation indices, and inadequately capture the trends. ERA5 and JRA-55 underestimate trends, while CFSR and MERRA-2 significantly overestimate the trends. These findings serve as a basis for selecting reliable precipitation datasets for extreme precipitation and hydrological simulation research in China. Significance Statement Extreme precipitation events have increasingly become more widespread, posing significant threats to human lives and property. Accurately understanding the spatiotemporal patterns of these events is imperative for effective mitigation. Despite the proliferation of precipitation products, their capacity to faithfully represent extreme events remains inadequately validated. In this study, we utilize a gauge-based dataset derived from over 2400 gauge stations across China to investigate the spatiotemporal changes in extreme precipitation events from 2001 to 2019. Subsequently, we conduct a rigorous evaluation of 12 widely used precipitation datasets to assess their efficacy in depicting extreme events. The results of this research offer valuable insights into the strengths and weaknesses of various precipitation products in depicting extreme events.