Extreme Rainfall Intensity Research Articles

Role of Quasi‐Biweekly Cloud‐Radiative Feedback in Modulating and Simulating Extreme Rainfall Intensity Over Asian Monsoon Regions

AbstractAlthough Cloud‐radiative feedback (CRF) has been investigated in terms of its modulation of extreme precipitation over tropical oceans, the specific timeframe of CRF variability and the associated processes driving extreme rainfall over Asian monsoon regions remain unclear. Based on observational analyses and model sensitivity experiments, this study reveals that longwave CRF at the quasi‐biweekly timescale is most closely linked to the intensity of persistent (≥3‐day) heavy rainfall events in southern China and northern India by efficiently maintaining the large‐scale convective perturbations. When CRF is disabled, the quasi‐biweekly convective anomalies supporting extreme precipitation are weakened. Additional assessments of Coupled Model Intercomparison Project historical simulations confirm that models with more accurate quasi‐biweekly longwave CRF exhibit smaller biases in capturing the amplitude of persistent heavy rainfall. These results have implications for improving model capability in simulating and forecasting quasi‐biweekly CRF to mitigate the risks of extreme precipitation events in monsoonal Asia.

Decadal trends and climatic influences on flash droughts and flash floods in Indian cities

Flash droughts/floods are extreme weather phenomena that are expected to become increasingly frequent and severe with the changing climate. Flash droughts result from a rapid decline in soil moisture, while flash floods occur due to a high extreme rainfall intensity over a short duration. This study analyzes the ERA5 reanalysis data (hourly temperature, soil moisture, and precipitation) from 1992 to 2022 to assess flash drought/flood attribute variations across fourteen Indian cities. Flash drought events are identified based on specific conditions using the obtained Soil Moisture Index (SMI) values. At the same time, we propose a novel approach to attribute flash floods by setting thresholds for precipitation and soil moisture.This study examines the frequency and trends of flash drought and flood events across India's various Köppen-Geiger climatic zones from 1992 to 2022. Jaipur and Dehradun show a statistically significant decrease in flash drought events with magnitudes of −0.0833 events/year and −0.0769 events/year, respectively. Conversely, Hyderabad exhibits a highly significant increase in flash flood events with a magnitude of 1.1851 events/year. Similarly, Bengaluru, Varanasi, and Vishakhapatnam also show substantial increases in flash flood events. These findings underscore the impact of climate change on flash droughts/floods, highlighting the necessity for sustainable strategies.

Forecasting extreme hourly rainfall in South Africa for disaster risk reduction: thresholds and return periods

Highest and percentile values determined for daily, hourly and 5-min rainfall data (July 1994 to June 2021) from 64 automatic weather stations across South Africa were used to define extreme hourly and 5-min rainfall intensity. Internationally, 99.9th and 99.99th percentiles are typically considered as thresholds for hourly and sub-hourly extreme rainfall when forecasting for disaster risk reduction assessments. In South Africa (SA), the average of the 99.9th percentile for hourly rainfall values is 29.9 mm/h. This represents a good indicator of extreme hourly rainfall in SA and is a useful threshold for forecasting flash floods. The average highest of the hourly rainfalls for SA, 53.9 mm/h, should be a good indicator of more extreme hourly rainfalls for the country. The average of the 99.99th percentile for 5-min rainfall values is 12.8 mm/5 min, which equates to 2.6 mm/min. Significantly, the 5-min rainfall data is used to establish South African categories based on rainfall intensity and total rainfall, whereby an event can be classified as a cloudburst, downpour or shower. Using the newly established local categories, the severe thunderstorm of 4 April 2000 at Hoedspruit that produced 132.2 mm in 25 min from an intensifying upper air trough system was classified as a cloudburst. Interestingly, the 66.2 mm recorded in 5 min during this event makes it the world record holder for all-time highest 5-min rainfall, passing the previous world 5-min rainfall record of 63.0 mm in 5 min recorded at Porto Bello, Panama, on 29 November 1911. Return periods of expected maximum daily, hourly and 5-min rainfall, based on yearly highest values, were also calculated for South Africa. This study presents expected maximums for 5-min rainfall in return periods of 10, 25, 50 and 100 years, a first for South Africa, which can inform strategies for disaster risk reduction.

Characterization of extreme rainfall changes and response to temperature changes in Guizhou Province, China

Different geographical zones have regional heterogeneity in underlying earth surface structure and microclimate which result in different evolution trends and their response to climate change varies in extreme rainfalls in these zones. In the Guizhou province of China, there are complex landforms, which lead to spatial redistribution of rainfall, frequent extreme rainfall, and disasters high risk of geologic disasters. Research on extreme climate in Guizhou mostly paid attention to its spatio-temporal characteristics and modeling, but lack of analysis on its characteristics of extreme rainfall variability and response to temperature changes under different subsurface conditions. This study investigated the characteristics of the extreme rainfall spatiotemporal and recurrence periods in Guizhou province and discussed the relationship between the response of extreme rainfall to temperature change. Daily rainfall data from 1990 to 2020 and 2021–2100 at 31 meteorological observation stations throughout the province were collected to calculate extreme precipitation. This research had the following results. (1) Both historical and future periods show an upward trend in extreme rainfall in Guizhou province, with a spatial distribution pattern of “high in the south and low in the north, high in the east and low in the west” and “high in the southeast and low in the northwest”, respectively; the spatial distribution of extreme rainfall under each recurrence period is consistent with the non-recurrence period. (2) Both historical and future periods show an upward trend in temperature in Guizhou province, with a spatial distribution consistent with that of the extreme rainfall in the corresponding period. (3) The change in extreme rainfall intensity with increasing temperature is almost always greater than the C–C rate for different periods and underlying earth surface structure; Extreme rainfall has a Hook response structure to temperature change, and the climate response structure shifts to the right with climate warming. The results of the study can provide a basis for decision-making on regional disaster prevention and mitigation in the context of temperature change.

Observed Changes in Extreme Precipitation Associated with U.S. Tropical Cyclones

Abstract Numerous recent tropical cyclones have caused extreme rainfall and flooding events in the CONUS. Climate change is contributing to heavier extreme rainfall around the world. Modeling studies have suggested that tropical cyclones may be particularly efficient engines for transferring the additional water vapor in the atmosphere into extreme rainfall. This paper develops a new indicator for climate change using the enhanced rainfall metric to evaluate how the frequency and/or intensity of extreme rainfall around tropical cyclones has changed. The enhanced rainfall metric relates the amount of rain from a storm over a given location to the 5-yr return period rainfall in that location to determine the severity of the event. The annual area exposed to tropical-cyclone-related 5-yr rainfall events is increasing, which makes it a compelling climate change indicator. Quantile regression illustrates that the distribution of tropical cyclone rainfall is also changing. For tropical storms, all quantiles are increasing. However, major hurricanes show large increases in their most extreme rainfall. This study does not attempt to make any detection claims (vs natural variability) or attribution of the observed trends to anthropogenic forcing. However, the sensitivity of the results to natural variability in tropical cyclone frequency was somewhat constrained by comparing 2 decades from the previous active era (1951–70) with two from the current era (2001–20). This comparison also shows that both the mean rainfall and the maximum rainfall associated with tropical cyclones are increasing over most areas of the eastern CONUS with the most significant increases from northern Alabama to the southern Appalachians. Significance Statement The purpose of this study is to analyze the changes in frequency and magnitude of extreme precipitation events associated with tropical cyclones with the goal of developing a new indicator for climate change. This is important because heavy rainfall and associated flooding is one of the primary causes of tropical cyclone destruction and fatalities, especially in inland locations away from where storms initially make landfall. Our results show that both the frequency and magnitude of extreme rainfall events from tropical cyclones have increased over the CONUS. The strongest storms (major hurricanes) also show more of an increase in extreme rainfall than storms of weaker intensities.

Cultural and Spiritual Adaptations to Extreme Weather Events of Ethnic Farming Communities of the Three Watersheds Situated at Different Altitudinal Locations along Agno River Basin, Benguet and Pangasinan, Philippines

Ethnic farming communities in Agno River Basin face climate stressors that threaten their agricultural production. This paper investigated and assessed the cultural/spiritual adaptations to climate variabilities and extremes of ethnic farming communities in Agno River Basin, Philippines. How the presence of these cultural/spiritual practices moderate or mitigate the effects of climate variabilities and extremes were likewise investigated. The climate-related hazards considered in this study which are pronounced in the river basin are prolonged and extreme rainfall intensity, typhoons and extreme winds, drought, flood and occurrence of pests and diseases. These hazards are becoming more frequent and intense resulting to limited agricultural production. This paper considered only the sectors of agriculture/socioeconomic, water and health. The descriptive method employed in this study was based on the works of Oppenheimer et al (2014); Saroar, Routray and Leal Filho (2015) and Brooks and Adgers(undated). The data-gathering activities were household survey using pre-tested questionnaires, focused group discussions and key informant interviews. The ethnic affiliations of the farming communities were I-Karao, Ibaloi, Kankanaey and Kalanguya tribes. Secondary data on changing rainfall and erratic temperature characteristics were consistent with the general perception of the ethnic farming communities. Cultural/ spiritual traditions of Ethnic farming communities in the Agno River Basin form part of their adaptations to climate extremes and variabilities. The greatest number of rituals and activities (5) such as childless couples raising plant materials, burning of rice straws and Alay, Leppas, Maepdesan, and Ibkas or maboteng. are dedicated to ensuring a good harvest. Canyao, Libot, and Begnas are undertaken to prevent the occurrence of hazards. On the other hand, Ubob, Bayanihan, and Sakdo are adaptations to mitigate the impact of climate extremes and variabilities. Both Canyao and Leppas are also thanksgiving activities while Tagainep or dream interpretation serves as a coping mechanism.

Modeling nonstationary intensity-duration-frequency curves for urban areas of India under changing climate

Enhancing stormwater drainage systems is paramount amid evolving climate dynamics, necessitating robust design and continual upgrades to address changing environmental conditions. The present work constructs the nonstationary Intensity-Duration-Frequency (IDF) curves for prominent urban areas of India. It develops 2313 nonstationary Generalized Extreme Value (GEV) models in annual and seasonal timeframes by integrating the influence of local and global climate-informed covariates, including time covariates. The work involves analyzing 1, 2, 3, 4, 6, 12, 24, 36, and 48 hourly maximum rainfall series with return periods of 2, 5, 10, 25, 50, and 100 years. Among the 16 urban areas examined, there's a significant shift from stationary to nonstationary extreme rainfall intensities, marked by a 38.7% increase in shorter duration series with a 5-year return period in New Delhi and Visakhapatnam. AMO, DMI, GTA, and LTA in New Delhi play significant roles. Similarly, in Visakhapatnam, SST in Niño 3.4 and DMI are significant covariates influencing nonstationarity. Recently, in the 2023 monsoon, the 25-year flood wreaked havoc in New Delhi, Rajkot, Surat, and Visakhapatnam. Generating nonstationary IDF curves for the annual and seasonal timeframes offers a comprehensive approach to stormwater design and infrastructure upgradation and effective adaptation strategies across sixteen Indian cities.

A new conceptual model for understanding and predicting life-threatening rainfall extremes

The motivation of our study is to provide forecasters and users complementary guidance and tools to identify and predict atmospheric conditions that could lead to life-threatening flash floods. Using hourly and sub-hourly rainfall datasets, proximity radiosondes, ERA5 reanalysis of extreme rainfall events in the UK during 2000–2020, and case studies in 2021, we observe a three-layered atmospheric structure, consisting of Moist Absolute Unstable Layers (MAULs) embedded in a conditional unstable layer sandwiched between a stable upper layer and a near-stable low layer. Based on our analysis, we propose a conceptual model to describe the atmospheric properties of a ‘rainfall extreme’ environment, with a particular focus on the thermodynamics associated with sub-hourly rainfall production processes. We then set this model within a wider framework to describe the precursor synoptic and mesoscale environments necessary for sub-hourly rainfall extremes in the mid-latitudes. We show that evolution of the Omega block and Rex Vortex couplet provides the optimal environmental conditions for sub-hourly rainfall extremes. These results provide the potential to develop a ‘4-stage’ warning system to assist in the identification and forecasting of life threatening short-duration extreme rainfall intensities and flash floods.

Nonstationarity in Extreme Precipitation Return Values along the U.S. Gulf and Southeastern Coasts

Abstract This study estimates extreme rainfall trends across the Gulf Coast and southeastern coast of the United States while applying methods for extending the temporal record and aggregating across spatial trend variations. Nonstationary generalized extreme value (GEV) models are applied to historical annual daily maximum precipitation data (1890–2019) while using CMIP5 global mean surface temperature (GMST) as the covariate. County composites and multicounty regions are used for local data record extension and pooling. Unlike most previous studies, return periods as long as 100 years are analyzed. The local trend estimates themselves are found to be too noisy to be reliable as estimates of climate-driven trends. However, application of a Gaussian process model to the spatial distribution of observed trends yields overall trend detection at the 95% significance level. The overall historical increase due to nonstationarity across the study region, with associated 95% confidence intervals, is 9% (3%, 15%) for the 2-yr return period and 16% (4%, 26%) for the 100-yr return period. A trend is also detectable in the Gulf Coast subregion, but not in the smaller southeast subregion. Recent weather events and nonstationarity have caused the official return value estimates for parts of North and South Carolina to be much lower than the return values estimated here. Significance Statement Protection of people and infrastructure from flooding relies on accurate estimates of potential extreme rainfall intensity. Some official estimates of extreme rainfall near the Gulf Coast and southeastern coast of the United States are over 20 years old. We show that, across this region, there is a clear trend in daily rainfall so extreme that it only has a 1% chance of happening in any given year (the so-called 100-yr rainfall). This trend means that many existing estimates of extreme rainfall are too low, both now and in the future, so flooding risks based on those estimates would be underestimated as well.

Spatiotemporal Variation and Causes of Typical Extreme Precipitation Events in Shandong Province over the Last 50 Years

In this study, based on hourly ERA5 reanalysis data from July to September, from 1971 to 2020, for Shandong Province, we used mathematical statistical analysis, the Mann–Kendall nonparametric statistical test, cluster analysis, and other methods to extract and analyze the spatiotemporal variation characteristics and causes of typical extreme precipitation events. The results indicated the following: (1) The total number and duration of precipitation events show a nonsignificant upward trend, while the average and extreme rainfall intensities show a nonsignificant downward trend. (2) Extreme precipitation events are primarily concentrated in Qingdao, Jinan, Heze, and Binzhou, with fewer events occurring in central Shandong Province. (3) Extreme precipitation events are classified into four types (namely, patterns I, II, III, and IV). Pattern I exhibits two rain peaks, with the primary rain peak occurring after the secondary rain peak. Similarly, pattern II also displays two rain peaks, with equivalent rainfall amounts for both peaks. In contrast, pattern III has multiple, evenly distributed rain peaks. Finally, pattern IV shows a rain peak during the first half of the precipitation event. Pattern I has the highest occurrence probability (46%), while pattern IV has the lowest (7%). (4) The spatial distributions of the different rain patterns are similar, with most being found in the eastern coastal and western regions. (5) Extreme precipitation events result from interactions between large-scale circulation configurations and mesoscale convective systems. The strong blocking situation and significant circulation transport at middle and low latitudes in East Asia, along with strong convergent uplift, abnormally high specific humidity, and high-water-vapor convergence centers, play crucial roles in supporting large-scale circulation systems and triggering mesoscale convective systems.

On The Interannual Variability of Indonesian Monsoon Rainfall (IMR): A Literature Review of The Role of its External Forcing

The IMR variability is notorious for its hydrometeorological disasters. This paper examines recent studies on IMR and the main factors controlling its variability. The focus of this study is to investigate the impact of the atmosphere-ocean interaction that acts as the external forcing of IMR in the tropical Indian and Pacific Oceans. Specifically, the study will examine the influence of two climate phenomena, namely the El Nino Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) and their interdecadal changes associated Pacific Decadal Oscillation (PDO), on the IMR. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. Furthermore, data sets (such as rainfall, wind field, and SST) spanning 1990-2020 were used to verify the key findings. In general, this study concludes that the majority of the authors coincided with the following conclusion: ENSO and IOD events impact IMR by changing its amplitude, duration, intensity, and frequency of mean and extreme rainfall. Additionally, it has been shown that their impacts on IMR are most substantial during the dry seasons, specifically in June, July, and August (JJA), and not as strong as during the wet seasons, specifically in December, January, and February (DJF). Spatially, the effects of ENSO and IOD on IMR variability are clearly found more eastward and westward of the region, respectively. The expansions towards the east and west directions were facilitated by the displacement of the ascending and descending of Walker circulation patterns in the Indonesian region, respectively. Given the interannual fluctuations in IMR, caused mainly by ocean-atmosphere interactions, the knowledge gap of atmospheric factors like the Quasi-Biennial Oscillation (QBO) must be investigated in the future, as suggested by previous research and our preliminary study.

Orographic Controls on Extreme Precipitation Associated with a Mei-Yu Front

Abstract Taiwan regularly receives extreme rainfall due to seasonal mei-yu fronts that are modified by Taiwan’s complex topography. One such case occurred between 1 and 3 June 2017 when a mei-yu front contributed to flooding and landslides from over 600 mm of rainfall in 12 h near the Taipei basin, and over 1500 mm of rainfall in 2 days near the Central Mountain Range (CMR). This mei-yu event is simulated using the Weather Research and Forecasting (WRF) Model with halved terrain as a sensitivity test to investigate the orographic mechanisms that modify the intensity, duration, and location of extreme rainfall. The reduction in WRF terrain height produced a decrease in rainfall duration and accumulation in northern Taiwan and a decrease in rainfall duration, intensity, and accumulation over the CMR. The reductions in northern Taiwan are linked to a weaker orographic barrier jet resulting from a lowered terrain height. The reductions in rainfall intensity and duration over the CMR are partially explained by a lack of orographic enhancements to mei-yu frontal convergence near the terrain. A prominent feature missing with the reduced terrain is a redirection of postfrontal westerly winds attributed to orographic deformation, i.e., the redirection of flow due to upstream topography. Orographically deforming winds converge with prefrontal flow to maintain the mei-yu front. In both regions, the decrease in mei-yu front propagation speed is linked to increased rainfall duration. These orographic features will be further explored using observations captured during the 2022 Prediction of Rainfall Extremes Campaign in the Pacific (PRECIP) field campaign. Significance Statement This study examines the impact of terrain on rainfall intensity, duration, and location. A mei-yu front, an East Asian weather front known for producing heavy, long-lasting rainfall, was simulated for an extreme rain event in Taiwan with mountain heights halved as a sensitivity test. Reducing terrain decreased rainfall duration in northern and central Taiwan. Decreases in rainfall duration for both regions is attributed to increased mei-yu front propagation speed. This increase in northern Taiwan is attributed to a weakened barrier jet, a low-level jet induced by flow blocked by the steep mountains of Taiwan. A unique finding of this work is a change in winds north of the front controlling movement of the front near the mountains in central Taiwan.

Analyzing urban influence on extreme winter precipitation through observations and numerical simulation of two South China case studies

This study investigates the impact of urbanization on extreme winter rainfall in the South China Greater Bay Area (GBA) through the analysis of hourly station observations and simulations using the Weather Research and Forecasting Model with the Single Layer Urban Canopy Model (WRF-SLUCM). Data from 2008 to 2017 reveal that urban areas in the GBA experience lower 99th percentile hourly winter rainfall intensity compared to surrounding rural regions. However, urban locations exhibit higher annual maximum hourly rainfall (Rmax) and very extreme rainfall events (99.99th percentile) in winter, suggesting a positive influence of urbanization on extreme winter precipitation. A case study further underscores the role of the Urban Heat Island (UHI) effect in enhancing extreme rainfall intensity and probability in the GBA urban areas. Additionally, two extreme cases were dynamically downscaled using WRF-SLUCM, involving four parallel experiments: replacing urban land use with cropland (Nourban), using historical urban land use data from 1999 (99LS), projecting near-future urban land use for 2030 (30LS), and considering 2030 urban land use without anthropogenic heat (AH) (30LS-AH0). Synoptic analysis demonstrates that cold air intrusion suppresses the GBA UHI in Case 2013 but not in Case 2015. Reduced evaporation and humidity induced by urban surfaces significantly decrease urban precipitation in Case 2013. In contrast, the persistent UHI in Case 2015 enhances local convection and land–ocean circulation, leading to increased moisture flux convergence and amplified urban precipitation intensity and probability in 30LS compared to Nourban. This amplification is primarily attributed to AH, while the change in 99LS remains insignificant. These findings suggest that urban influences on extreme precipitation in the GBA persist during winter, particularly when the UHI effect is maintained.

Quantifying impacts of precipitation scenarios projected under climate change on annual probability of rainfall-induced landslides at a specific slope

Because of climate change, the intensity, duration, and frequency of future extreme rainfalls are projected to increase in many regions worldwide according to results from global climate models (GCMs). As rainfall is a major triggering factor for landslides, the frequency and risks of landslides are expected to increase. Consequently, it is crucial to quantify the impacts of climate change on landslide risks at a specific site. This study develops a statistical downscaling method based on the generalized extreme value (GEV) distribution and a probabilistic method for assessing the annual probability of rainfall-induced landslides at a specific site under projected precipitation scenarios from GCMs. The GEV-based statistical downscaling method bridges the gap between site-specific extreme rainfall (e.g., annual maximum 1-day rainfall) projection for a future scenario and GCM outputs with large spatial and temporal scales. A physics-based slope model is also used to properly depict slope failure mechanisms. The results indicate that the projected increase in extreme rainfall due to climate change leads to increases in annual frequency of heavy rainstorms and the annual slope failure probability, which are primarily controlled by the increase in the standard deviation, instead of the mean, of future extreme rainfalls.

Precipitation Scaling in Extreme Rainfall Events and the Implications for Future Indian Monsoon: Analysis of High‐Resolution Global Climate Model Simulations

AbstractThe increase in water holding capacity of the atmosphere with temperature, given by the Clausius‐Clapeyron (CC) relationship, describes the changes in extreme rainfall intensities at warmer atmospheric states. We study the characteristics of extreme rainfall events (EREs) during the Indian summer monsoon season with respect to thermodynamic changes and precipitation‐scaling over the Indian subcontinent and its homogeneous rainfall zones. We utilize outputs from a present‐day climate simulation and a time‐slice future climate change projection experiments of a high‐resolution global climate model. Large changes are seen for very EREs (vEREs) which suggests their sensitivity to warmer temperatures. In future, the altered radiative forcing will heat up the upper atmosphere, stabilize it and offset the effect of increasing humidity on precipitation intensity. Our analysis also suggests that more convective clouds and the interplay of increased moisture content and circulation will result in future changes in EREs.

ANALISIS PENGARUH VARIABEL PENDUGA CUACA EKSTREM DI KOTA BENGKULU DENGAN MENGGUNAKAN STATISTICAL PRODUCT AND SERVICE SOLUTIONS (SPSS)

The Bengkulu City area often experiences extreme weather with the potential for flooding and affects various types of human activities. This study aims to determine the effect of extreme weather predictor variables in Bengkulu City by using Statistical Product and Service Solutions (SPSS). Extreme weather indicators are reviewed based on rainfall with estimating variables in the form of air pressure, humidity, air temperature, and wind speed, for 5 years (2017-2021) obtained from the BMKG Station on Baai Island, Bengkulu City. Data processing using SPSS method. Data analysis was carried out statistically and descriptively. Based on the results of the study, the correlation between the estimator variables on extreme rainfall is quite good with r = 0.661, and the error value (RMSE) is 27,124. Furthermore, the homogeneity test between extreme rainfall indicators and extreme weather estimators includes air pressure, air temperature, wind speed, and air humidity, showing homogeneity in 2019. This indicates the predictor variable has the same direction to extreme rainfall, where the error value is obtained tends to be relatively small. The estimator variables, namely air pressure and humidity, have a significant relationship with extreme rainfall. Predictions using data (2017-2021) show that in 2022, extreme rainfall events will occur for a relatively long time, namely in January, March, May, June, July, August, October, and December. The most extreme rainfall intensity occurs in January

Compounding Heatwave‐Extreme Rainfall Events Driven by Fronts, High Moisture, and Atmospheric Instability

AbstractHeatwaves have been shown to increase the likelihood and intensity of extreme rainfall occurring immediately afterward, potentially leading to increased flood risk. However, the exact mechanisms connecting heatwaves to extreme rainfall remain poorly understood. In this study, we use weather type data sets for Australia and Europe to identify weather patterns, including fronts, cyclones, and thunderstorm conditions, associated with heatwave terminations and following extreme rainfall events. We further analyze, using reanalysis data, how atmospheric instability and moisture availability change before and after the heatwave termination depending on whether the heatwave is followed by extreme rainfall, as well as the location of the heatwave. We find that most heatwaves terminate during thunderstorm and/or frontal conditions. Additionally, atmospheric instability and moisture availability increase several days before the heatwave termination; but only if heatwaves are followed by extreme rainfall. We also find that atmospheric instability and moisture after a heatwave are significantly higher than expected from climatology for the same time of the year, and that highest values of instability and moisture are associated with highest post‐heatwave rainfall intensities. We conclude that the joint presence of high atmospheric instability, moisture, as well as frontal systems are likely to explain why rainfall is generally more extreme and likely after heatwaves, as well as why this compound hazard is mainly found in the non‐arid mid and high latitudes. An improved understanding of the drivers of these compound events will help assess potential changing impacts in the future.

A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics

Abstract. Intensity–duration–frequency (IDF) statistics describing extreme rainfall intensities in Norway were analysed with the purpose of investigating how the shape of the curves is influenced by geographical conditions and local climate characteristics. To this end, principal component analysis (PCA) was used to quantify salient information about the IDF curves, and a Bayesian linear regression was used to study the dependency of the shapes on climatological and geographical information. Our analysis indicated that the shapes of IDF curves in Norway are influenced by both geographical conditions and 24 h precipitation statistics. Based on this analysis, an empirical model was constructed to predict IDF curves in locations with insufficient sub-hourly rain gauge data. Our new method was also compared with a recently proposed formula for estimating sub-daily rainfall intensity based on 24 h rain gauge data. We found that a Bayesian inference of a PCA representation of IDF curves provides a promising strategy for estimating sub-daily return levels for rainfall.

Investigation of landslide hazard areas in the municipality of Cunha (Brazil) and climate projections from 2024 to 2040

Climate change can modify the frequency and intensity of extreme rainfall across the globe, leading to changes in hazards posed by rainfall-induced landslides. In Brazil, an example of a location with a high occurrence of landslides and with few studies on the subject is the municipality of Cunha, located in the State of São Paulo. In this way, the main aims of this study are twofold: 1) to identify and analyze areas susceptible to landslides and rainfall-induced landslide hazard in the municipality of Cunha; and 2) by using climate projections from the regional model Eta-HadGEM2-ES under RCP 4.5, to predict new extreme events and possible new landslides in this municipality, from 2024 to 2040. The susceptibility map has been prepared using selected physical-biotic environment elements whereas the hazard map has been produced using precipitation data. Using Eta-HadGEM2-ES climate projections under RCP 4.5, for precipitation events, results project the occurrence of 49 days with landslides for the period between 2024 and 2040. The outcomes of this study are considered of extreme relevance for the local community, public authorities, and decision-makers, to raise awareness regarding future urban planning strategies to prevent and mitigate the effects of catastrophes arising from natural hazard-induced disasters.

Quantitative attribution of historical anthropogenic warming on the extreme rainfall event over Henan in July 2021

The ‘21·7’ Henan extreme rainfall event (HNER) caused severe damage and many fatalities. The daily precipitation during this event (from 1200 UTC on 19 July 2021–1200 UTC on 20 July 2021) was 552.5 mm and the maximum hourly precipitation was 201.9 mm (at 0900 UTC on 20 July 2021). Previous studies have suggested that an evaluation of the role of anthropogenic climate change in extreme rainfall events is crucial in disaster prevention and mitigation under the current global climate crisis. We examined the changes in the coverage and intensity of extreme rainfall during the ‘21·7’ HNER event under anthropogenic climate change using a set of convective permitting simulations. Our results showed that the regional-average magnitude of the 48 h accumulated rainfall during the ‘21·7’ HNER was increased by 5.7% (95% confidence interval: 4%–11%), which is in agreement with the Clausius–Clapeyron rate, while the area of extreme rainfall (⩾500 mm) increased by 29.9% (95% confidence interval: 21%–40%) as a result of anthropogenic climate change over the Henan region during the late 20th century. Anthropogenic climate change has led to a warm moist tongue over the target region, which has increased the column-integrated water vapor content and induced an anomalous cyclone–anticyclone pair. Anthropogenic warming has caused stronger southerly and southeasterly winds, leading to stronger convergence in the lower troposphere, stronger updrafts in the mid-troposphere and stronger divergent winds in the upper levels. These effects have all contributed to the increase in rainfall. These results enhance our understanding of the dynamic effects of anthropogenic warming on the ‘21·7’ HNER and provide additional evidence that anthropogenic warming increased the magnitude of the ‘21·7’ HNER in China.