Extreme Precipitation Research Articles

A case study of the “21.7” Henan extremely rainfall event: From the perspective of water vapor monitored with GNSS tomography

Water vapor plays a vital role in the development of heavy rainfall system. The “21.7” Henan rainfall event, a record-breaking event, was investigated from the perspective of water vapor based on in-situ measurements, namely the 220 continuously operating GNSS ground stations in Henan Province, with GNSS tomography technique. Results showed that during and after the heavy rainfall, the error RMS of water vapor density from tomography was 21 % lower than that of GFS prediction data at the height of about 1450 m by comparing with radiosonde data. Taking ERA5 as the reference, the average relative error of tomographic water vapor density at the height below 4 km was within 10 % before and during the rainfall. The analyses of spatiotemporal variations of water vapor illustrated that tomographic products can, compared to ERA5 reanalysis data, more distinctly reflect the formation and convergence process of low-level water vapor bands before the occurrence of the extreme rainfall, as well as the fracture of the water vapor bands before the end of the rainfall. By combining the tomographic water vapor and GFS wind field data, the water vapor flux divergence can be calculated to further elucidate the movement of water vapor where significant variations of water vapor at the height of 10 to12 km (near the tropopause) and 1 to 4 km in both the vertical and horizontal directions were found before the extreme precipitation.

Projected changes of thermal, rainfall and drought indices in Morocco from high resolution climate models

Abstract Over the past decade, global changes in temperature, average and extreme precipitation have been observed many times. The increase in temperature or even the change in precipitation systems is directly affect extreme weather events, for example, heat waves, heavy rainfall, storms, and droughts are becoming more frequent and more powerful worldwide due to climate change caused by several factors including human activity. This is why there is a necessity to monitor future changes in climate extremes. The objective of this paper is to evaluate the future changes in thermal and rainfall extremes projected by the four climate models over time horizon 2041-2060 relative to the 1981-2010 reference period, based on the 5 climate indices, including Tmm, Tx90p, WSDI, PRCPTOT and SPI. The projections are given under the RCP 4.5 medium scenario. The analysis in thermal aspect shows that Morocco could experience by 2041-2060, a significant warming, has manifested by an increase in average temperature. Future changes in rainfall indices show that the spatial distribution of rainfall in Morocco could change significantly by 2041-2060 compared to the reference period 1971-2010. The four climate models agree on a decrease in annual precipitation that could affect most of the Kingdom. In the same way to dryness, the future changes of the SPI index that characterizes the drought, indicates a move to a dry climate.

Assessing and Mitigating Dwelling Collapse Risk due to Extreme Precipitation: A Comprehensive Study Using CNN-RF and GeoDetector

Dragon boat rain, the most common extreme precipitation form in South China from May to June with more similar spatial distribution, caused serious loss of people's lives and property. The dwelling collapse is one of the main losses. Previous studies have paid little attention to the dwelling collapse risk caused by dragon boat rain (DCRDBR), the coupling model with CNN and RF applied to its assessment, and the influence of the precipitation process and interaction of natural and social factors on it. To fill these gaps, the CNN-RF was used to calculate the DCRDBR and the DCRDBR map was drawn. The Geodetctor was used to identify the main influencing factors and influencing factor interactions of DCRDBR, due to the spatial stratified heterogeneity of DCRDBR and the ability to obtain the determinant power of single factor and factor interaction. The results show that the F1 score and the AUC value of CNN-RF are 0.96 and 0.81, respectively. The spatial distribution of DCRDBR obtained by CNN-RF is high in the northeast and low in the southwest Guangdong Province. The total precipitation has the strongest determinant power (q=0.54) followed by Slope (q=0.52). The average determinant power of factors describing the precipitation process is 0.25. The combination of total precipitation and GDP/capita has the strongest determinant power of all combinations of natural and socio-economic factors (q=0.72) followed by the total precipitation and ratio of urban population (q=0.71). This study demonstrates the ability of CNN-RF applied to the DCRDBR assessment due to the integration of feature extraction and anti-overfitting ability, and identifies the influence of precipitation processes and the interaction of natural and socio-economic factors on the DCRDBR. It provides a solid scientific basis for crafting strategies to mitigate the impact of dragon boat rain and is conducive to the city's sustainable development.

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.

Investigation on flooding dynamic response and mitigation measure of river bridge

Flood-induced failure of river bridges is intense due to frequently extreme and undesigned precipitation for global climate change. To reveal the dynamic characteristics and failure mechanism of bridges, flooding dynamic analysis is fully investigated via fluid–structure interaction simulation and Arbitrary Lagrangian-Eulerian method. Parametric analysis of different fluids and bridge configurations and pre-ballast mitigation measure are further conducted based on a simply-supported box-girder bridge. This study reveals several significant findings: the narrow channel can accelerate downstream flood velocity of the bridge piers to over double that of the upstream flow; moreover, unsubmerged piers experience vertical downward wave force surpassing buoyancy; the box girders exhibit three flood-response states, i.e., intact, slip and collapse, dependent on the hydraulic loading and bridge resistance capacity. Maximum horizontal wave force and displacement increase exponentially with the depth of water storage. Post-slip damage, bearing stress on the wave-facing side tends towards zero, while the wave-backing side presents a twofold increase. Maximum horizontal displacement (Xmax) distinguishes the failure states, such as 0 m ≤ Xmax ≤ 0.03 m (intact), 0.03 m < Xmax ≤ 1.39 m (slip), Xmax > 1.39 m (collapse), whose relation to the maximum horizontal wave force has been proposed for design reference and the inversion analysis of the bridge force. Applying a pre-ballast equivalent to 75 % of girder weight reduces Xmax by up to 91.5 %, shifting failure from collapse to slip. These insights offer crucial guidance for enhancing bridge safety amidst escalating flood risks.

A novel urban flood risk assessment framework based on refined numerical simulation technology

Due to urbanization and climate change, urban areas are becoming more susceptible to flooding, posing significant risks to human life and property. Numerical simulation techniques can provide valuable support in mitigating urban flood risks. The objective of this study is to establish a novel framework for flood risk assessment based on refined urban flood simulations. To achieve refined urban flood simulations, the Torricelli’s law is incorporated into a two-dimensional fluid dynamics model, and a numerical analysis model is developed to estimate the inundation within buildings and accurately simulate the entire inundation process. The model was used to reproduce a real flood event in Omihachiman City, Japan, with the Nash-Sutcliffe Efficiency (NSE) values of 0.6488 and 0.7182, demonstrating the credibility of the model. Based on the simulation results, the hydrological causes of the flood event were analyzed, and flood prevention measures were proposed. After implementing these measures, the maximum water depths at the study area were reduced to 0.14 m, 0.62 m, and 0.12 m, respectively, proving the effectiveness of the flood prevention measures. To address the issue of inundation depth not fully reflecting flood risk, the instability of human bodies in floodwaters is conducted to evaluate flood risk for adults and children in the target area. In response to increasingly frequent extreme rainfall events, the extreme precipitation events of three different return periods (10-year, 50-year, and 100-year) are used to assess the flood risk and the effectiveness of flood prevention measures. Based on the assessment results, the flood prevention measures not only reduced the flood risk levels but also decreased the flood risk area, further confirming their effectiveness.

Projected changes in mean climate and extremes from downscaled high-resolution CMIP6 simulations in Australia

High-resolution climate change projections are required to understand local and regional climate change impacts. We used CCAM (Conformal Cubic Atmospheric Model) to dynamically downscale CMIP6 GCMs (Global Climate Models) over Australia under three emissions scenarios, producing a set of 60 simulations at a 10 km resolution. Previous work has evaluated the performance of the downscaled models in the historical period. Here, we evaluate the impact of end-of-century climate change in the downscaled CMIP6-CCAM models for mean and extreme climate under three Shared Socioeconomic Pathways (SSP126, 245 and 370). We find the changes in mean climate are similar in the host CMIP6 and downscaled models. For extreme temperature, we find that extreme maximum temperatures (TXx) increase by 3.4°C, while extreme minimum temperatures (TNn) warm by 3.0°C. Extreme precipitation generally increases in summer and decreases in winter; however, there is a large amount of inter-model variation in the location and magnitude of change. Consecutive dry days also decrease in most areas in Austral summer and increase in Austral winter. Heatwaves become more frequent and hotter by the end of the century. These results suggest a hotter, wetter Austral summer, with longer, more frequent and more intense heatwaves, and a hotter and drier Austral winter in most areas. This dataset provides useful new high-resolution information on how climate change is likely to impact Australia, which will be a valuable resource to underpin local adaptation responses to future impacts.

Flash floods on the northern coast of the Black Sea: Formation and characteristics

Flash floods are one of the most dangerous hydrometeorological events in the world. The current study investigates flash floods on the northern Black Sea Coast. The data about stochastic and relatively stable factors of flash flood formation (such as hydrological, meteorological, lithological, geomorphological, and anthropogenic parameters) were collected for 22 events. The main trigger of flash floods is heavy rainfall of high intensity in the region but in some cases flash flood occurrence is connected with combinations of several “non-critical” factors. The small watershed area (≤ 351 km2) of river basins experiencing flash floodspromotes very rapid flow concentration. Analysis of extreme precipitation demonstrates significant increasing trends in river basins on the Crimean Peninsula and decreasing a maximum precipitation amount in 5 days (r5d) and 1 day (r1d) in river basins in the Caucasus Black Sea Coast in the 21st century as determined by processing of Integrated Multi-satellite Retrievals for Global precipitation measurement (IMEGR) satellite data. At the same time land network data indicates increasing r5d at the Anapa and r1d at the Tuapse meteorological stations in 1961–2020. More frequent occurrence of flash floods has been suggested in the area due to statistical analysis of the longest precipitation ranges. The main reason for significant social and economic damage is uncontrolled human activity in flooded areas on the northern Black Sea Coast.

Intercomparisons of the Latest Precipitation Estimates from Satellite, Reanalysis, and Merged Products over Alaska

Abstract This study uses National Centers for Environmental Prediction (NCEP) Stage IV (Stage IV) precipitation data over the state of Alaska to assess and cross compare precipitation estimates from the most recent versions of multiple precipitation products, including satellite-based passive microwave (PMW) [Special Sensor Microwave Imager/Sounder (SSMIS)–F17, Microwave Humidity Sounder (MHS)–MetOp-B, MHS–NOAA-19, Advanced Microwave Scanning Radiometer 2 (AMSR2), Advanced Technology Microwave Sounder (ATMS), and Global Precipitation Measurement Microwave Imager (GMI) in V05 and V07], active microwave [AMW or radar; Global Precipitation Measurement (GPM) dual-frequency precipitation radar (DPR) in V06 and V07], combined active and passive microwave (DPRGMI in V06 and V07), infrared [Atmospheric Infrared Sounder (AIRS)], reanalysis [fifth major global reanalysis produced by ECMWF (ERA5) and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and satellite–gauge [Global Precipitation Climatology Project (GPCP) V1.3 and GPCP V3.2] products. PMW estimates are generally improved in V07 compared to V05 in terms of overall bias, pattern, and capturing precipitation extremes. DPR and DPRGMI show low skill in capturing different precipitation features. ERA5 and MERRA-2 show the highest agreement with Stage IV for all precipitation rate metrics. AIRS and GPCP capture the overall precipitation pattern and magnitude fairly well, performing better than the radar and comparable to the PMW V07 products, although the geographical maps suggest that they provide a relatively smoothed spatial distribution of mean precipitation rates. The outcomes of this study shed light on the performance of various precipitation products over Alaska (partly representing high-latitude regions) and can be useful to guide the development of multisensor products.

Should we value rain harvesting more in Türkiye for mitigating precipitation extremes

Mitigating precipitation extremes is a major issue due to destructive global warming and climate change. Heavy rainfall and drought have posed a threat to human life and ecology. That said, new strategies and new action plans are needed at local and global levels through needed cooperation from different stakeholders to handle the possible risks associated with precipitation extremes. Turkey has become one of the most vulnerable countries involved in climate change due to its geographical location, rapid urbanization, and deforestation. Many forests have been destroyed to make room for agriculture, animal grazing as well as for manufacturing and construction. The impact has caused complications in landscapes. Precipitation extremes, such as heavy rainfalls and drought, are posing significant threats for many cities in Turkey. In recent years Turkey has faced a large number of extreme events regarding precipitation. In this line, the present study aims to explore the potential benefits of rainwater harvesting (RHH) in mitigating precipitation extremes by overviewing regulatory actions of rainwater harvesting and best practices worldwide. In addition an interview-based survey was conducted with domain experts in the water management field to better understand the current challenges of stormwater management in Turkey and discuss the role of rainwater harvesting against precipitation extremes. The results of the study have shown that Turkey has several problems with infrastructure to mitigate precipitation extremes, such as shortcomings in capacity and old water management systems, unseparated water collection and sewage systems, and lack of green infrastructure. In addition to urbanization, expansion in industry and tourism may cause water unavailability. The study has also indicated that many authorities around the globe try to boost RWH use by stipulating or encouraging RWH through incentives to save a large amount of water by implementing different projects. This research has argued that RWH promises several benefits thanks to its cost-effectiveness and contribution to water storage. Therefore, this study has recommended that policymakers should take immediate action against precipitation extremes by introducing new regulations, such as mandating rainwater harvesting for old buildings, industrial and touristic places. Preparing new guidelines and applying rooftop RWH systems that comply with Building Code requirements should also be considered for the widespread use of rainwater in rural and urban areas.

Characteristics of extreme hourly precipitation induced by tropical cyclones in Zhejiang, China: A comparative analysis based on two different datasets

This study investigates the characteristics of tropical cyclones (TCs) that cause extreme hourly precipitation (EXHP) in Zhejiang, China, using datasets from 67 national stations (Con-ST) and 1551 surface stations (All-ST), spanning 1973–2020 and 2011–2020, respectively. Our analysis revealed notable variations in the EXHP caused by individual TCs. The top 10 % of TCs contributed 37.2–38 % of the total TC-induced EXHP amount, while the bottom 50 % only accounted for 5.8–22.7 %. Using sparse stations may overestimate the impact of TCs causing EXHP in the lower to middle rankings. Long-term trend analysis suggested a consistent increase in TC-induced EXHP despite a decreasing trend in the number of TCs affecting Zhejiang. High-value EXHP centers tended to be concentrated in mountainous areas within 0–50 km from the coastline, where Con-ST stations are sparse and can significantly underestimate EXHP. The maximum amount of EXHP per TC increased logarithmically with the number of observation stations. In Zhejiang, EXHP predominantly occurred northeast of the TC centers (50.4–61.7 %) and within 500 km from the TC center (69.5–81.5 %). High-frequency EXHP centers exhibited a clockwise rotation with increasing distance from the TC center–a pattern resembling a “spiral rainband.” A key area where most EXHP in Zhejiang occurred when TC centers remained within this area was identified. The TC intensity within the key area was a key factor influencing EXHP occurrence in Zhejiang, whereas the duration of TC center residence within the key area and the distance of its movement were crucial predictors of significant EXHP occurrence. The analysis of large-scale environmental fields revealed that high-EXHP TCs are characterized by strong upper-level divergence, intense upward motion, and an expanded subtropical high. The southeasterly steering airflow drives these TCs northwestward, prolonging their impact on Zhejiang and resulting in significant moisture accumulation and EXHP.

A hybrid approach for skillful multiseasonal prediction of winter North Pacific blocking

Wintertime atmospheric blocking often brings adverse environmental and socioeconomic impacts through its accompanying temperature and precipitation extremes. However, due to the chaotic nature of the extratropical atmospheric circulation and the challenges in simulating blocking, the skillful seasonal prediction of blocking remains elusive. In this study, we leverage both observational data and seasonal hindcasts from a state-of-the-art seasonal prediction system to investigate the prediction skill of North Pacific wintertime blocking frequency and its linkage to downstream cold extremes. The observational results show that North Pacific blocking has a local maximum over the central North Pacific Ocean and that the occurrence of North Pacific blocking drives significant cold anomalies over northwestern North America within a week, which are both well reproduced by the model. The model skillfully predicts the western North Pacific blocking frequency near the subtropical jet exit region at the shortest forecast lead, but skill drops off rapidly with lead time partly due to model drift in the background flow. To overcome this rapid drop in skill, we develop a linear hybrid dynamical-statistical model that uses the forecasted Niño 3.4 index and upstream precipitation as predictors and that maintains significant forecast skill of high-latitude North Pacific blocking up to 7 lead months in advance. Our results indicate that an improvement in the seasonal prediction skill of winter North Pacific blocking frequency may be achieved by the enhanced representation of the links among sea surface temperature anomalies, tropical convection, and the ensuing tropical-extratropical interaction that initiates North Pacific blocking.

Increasing contribution of the atmospheric vertical motion to precipitation in a warming climate

Global warming already influences precipitation, with more intense precipitation in many locations. Although the ‘wet-get-wetter, dry-get-drier’ tendency in mean precipitation holds in many locations, the situations for precipitation extremes are more complex, due to changes in dynamic and thermodynamic influences on atmospheric moisture distributions. Here, we build a dynamically interactive atmospheric moisture model for the present (2006–2025) and the future climate (2081–2100), using outputs from coupled ocean-atmosphere general circulation models. We find that the dynamic process of vertical advection of moisture dominates the same-day precipitation, while the smaller impact of the thermodynamic process provides available moisture for several days. As climate warms, we find that the dynamical-induced precipitation more completely exhausts the vertically-integrated moisture and the distribution of the dynamic process’s impact on precipitation exhibits a greater spread in the warmer future. The dynamical process is primarily responsible for more extreme heavy precipitation as climate warms, at all latitudes.

Trends of Extreme Temperature and Rainfall Indices for Addis Ababa City, Ethiopia

The extreme temperature and precipitation index trend analysis for Addis Ababa city is presented in this study. The Bole and Tikur Anbesa observatories, two stations in the capital city of Addis Ababa, provide the temperature and rainfall variation used in this analysis. The RClim-Dex software has been used to find climate extreme indices for Addis Ababa city stations based on climate data for the period 1954 to 2019. The annual total precipitation trend (PRCPTOT) at the 5% significant level exhibits a positive slope at the Addis Ababa observatory and a negative slope at the Addis Ababa Bole station. SDII trends indicate an increase at the 5% significant threshold for both stations. At the 5% significance level, the trends for both stations’ maximum and lowest temperatures show a positive slope. Conversely, both stations exhibit a negative slope in the diurnal temperature ranges. The RClim-Dex results indicate that, while rainfall intensity is decreasing, there is a tendency for annual rainfall indices to increase at the Addis Ababa observatory station, but to decrease at the Bole station. Additionally, there is an upward slope for consecutive wet days for all stations. Nevertheless, steady warming patterns are evident for both the maximum and minimum temperature indices. In contrast, declining trends are shown in the diurnal temperature ranges.

Impact of precipitation change in the Yangtze River source area on groundwater from the perspective of ground-based and satellite-based observations

In the context of global climate change, the hydrological cycle of the Yangtze River source area has produced significant changes. It is of great practical value to study the influence of regional precipitation changes and precipitation events on regional water resources, especially groundwater. This study uses base flow segmentation and GRACE groundwater reserve calculation technology to examine precipitation’s spatial and temporal variation, especially extreme precipitation events, in the Yangtze River source area. The events analyzed were the extreme precipitation-runoff-base flow response from the Yangtze River source, the extreme precipitation-terrestrial water (surface water and groundwater) response, and the comparison of these events. The findings indicated that extremely strong precipitation, maximum precipitation for five consecutive days, days of moderate rain and above moderate rain intensity precipitation, the longest number of precipitation days, and other extreme precipitation indices had a significantly increasing trend and increased intensity of extreme precipitation events, the regional differences in precipitation trended less significantly. The base flow index gradually increased at a rate of 0.0014 yr-1, suggesting the overall increase of water resources and the contribution rate of groundwater to the runoff was an increased trend . There is a high correlation between the change of water resources in the source area and the change of precipitation, and the increased precipitation influenced an increase in groundwater and regional water resources. These findings inform current knowledge of precipitation-groundwater response mechanisms in alpine and arid regions such as the Qinghai-Tibet Plateau.

Changes in temperature and precipitation extremes over Western Asia: A regional ensemble from CMIP6

This study investigates the impacts of climate change on temperature and precipitation extremes in eight West Asian countries (Iran, Afghanistan, Pakistan, Turkmenistan, Azerbaijan, Armenia, Turkey, and Iraq) using a regional ensemble of CMIP6 models. Ten models were evaluated based on their performance in simulating historical temperature and precipitation using the KGE index. Four climate extreme indices (Tmax, Pmax, TX90p and R95p) were employed to assess changes in temperature and precipitation extremes in the study area. The analysis of climate extremes reveals significant projected changes. Tmax is expected to increase in all countries, with the most pronounced rise anticipated in Turkmenistan, where Tmax in the main part of the country is projected to increase by more than 5 °C under the SSP585. Projections for Pmax show a more nuanced picture. Pakistan is expected to experience the highest overall Pmax. TX90p is projected to increase in all countries, indicating a rise in the frequency of extreme heat events. Pakistan is expected to experience the most significant increase in TX90p, reaching up to 36.1 % under the SSP585 (FF) scenario by 2074, followed by Iran and Afghanistan. R95p does not show a clear future trend. Pakistan is anticipated to see the highest increase in R95p, reaching up to 15.2 mm under the SSP585 scenario by 2074, while Turkey might experience a decrease of up to 7.8 mm under the SSP245 scenario. These findings highlight the diverse and concerning impacts of climate change on temperature and precipitation extremes across West Asia. The projected increase in Tmax, TX90p and potential shifts in precipitation patterns pose significant challenges for the region. This study emphasizes the need for region-specific adaptation strategies to address the multifaceted challenges of climate change in West Asia.

Quantitative study on the water vapor transport characteristics of an extreme precipitation event in North China

Quantitative study on the water vapor transport characteristics of an extreme precipitation event in North China

A dataset of high-resolution climate change projections over South America with bias correction

Accurate and detailed datasets are crucial for assessing climate change impacts. Regional climate models provide high-resolution simulations and are key tools but often exhibit systematic biases. Therefore, this paper presents a dataset derived from bias-corrected Eta regional model simulations and projections driven by four global CMIP5 models. The correction applied to daily precipitation, potential evapotranspiration, actual evapotranspiration, and 2-m air temperature, was conducted on a 0.2° x 0.2° grid over South America. The dataset covers two periods: 1976-2005 (baseline) and 2006-2099 (future) under RCP4.5 and RCP8.5 scenarios. Empirical quantile mapping was used to adjust the Eta model outputs to better match observational data. This method modified the accumulated probability curves of the Eta model outputs to align with observational curves for both baseline and future climates. Two observational datasets were used for correction and evaluation. The new dataset shows that bias correction significantly reduced the errors in the Eta simulations, especially for the frequent values of precipitation, potential evapotranspiration, and 2-m temperature, and also corrected the annual cycle and frequency distribution of these variables, approaching the observations. The pattern of extreme precipitation indices from the bias-corrected Eta dataset also reduced error. Bias correction was applied to future projections. The comparison against the raw Eta dataset showed that the trends of changes were preserved, but in general, the peaks of the changes were smoothed. As in the raw Eta dataset, the RCP8.5 scenario showed a higher change rate than RCP4.5. This work also revealed the large uncertainty of the observational dataset; some of the remaining errors after the bias correction were mostly due to differences between the two correction and evaluation observational datasets. The described dataset is freely available from the CNPq LattesData repository at the following link: https://doi.org/10.57810/lattesdata/WAVGSL.

The influence of El Niño on springtime synoptic-scale precipitation extremes in Southeastern China: insights from CMIP6 model simulations

This study focuses on El Niño impacts on springtime extreme precipitation in Southeastern China (SEC) by comparing observations with data from the Coupled Model Intercomparison Project phase 6 (CMIP6) historical runs. Observational and simulated results suggest that synoptic-scale temperature advection patterns over East Asia (EA) are closely associated with extreme precipitation in SEC, encompassing the Pearl River Basin (PRB), Yangtze River Basin (YRB), and Huaihe River Basin (HRB). Based on this, we introduce a temperature advection index (TAI) tailored to capture the cold-warm temperature advection dipole, which shows a significant positive correlation with SEC precipitation. Both observations and CMIP6 indicate that TAI-related circulations, characterized by upper-level synoptic-scale waves and a north–south oriented temperature gradient over EA, are conducive to extreme precipitation in northern PRB (NPRB)–YRB–HRB. However, the TAI-related synoptic-scale activities have a lesser impact on extreme precipitation in southern PRB (SPRB), as these disturbances mainly affect the mid-latitude weather. Further investigation reveals that during boreal spring following El Niño, 85% of extreme events in YRB–HRB are associated with positive TAI values, compared to 76% under climatological conditions. However, such a change in the association with TAI is not evident in CMIP6 simulations. From observations, atmospheric baroclinicity along the East Asian westerly jet is enhanced during El Niño, which promotes the development of TAI-related synoptic-scale disturbances. In contrast, CMIP6 models struggle to reproduce these observed baroclinicity signals during El Niño. This challenge arises from the background westerly jet bias and mean-state cold tongue bias in tropical Pacific temperature in models.

Precipitation patterns strongly affect vertical migration and methylation of mercury in legacy contaminated sites

Legacy-contaminated sites act as significant sources of mercury (Hg) to their surrounding surface and underground environments. Intensified extreme precipitation is posing great threats to the environment and human health by changing the fate of pollutants, yet little is known about its effect on the vertical migration and methylation of Hg in contaminated sites. Here, we applied a range of simulated extreme precipitation patterns (frequency and intensity) to column leaching assays with soils collected near a contaminated site. We observed that precipitation with high frequency but low intensity resulted in more vertical migration of Hg through the soil profile than that with low frequency but high intensity. The majority (> 90%) of leached Hg was prone to migrate vertically within the top 10 cm of the soil profile. Furthermore, rainfall stimulated microbial Hg methylation, as demonstrated by enhanced production of methylmercury (MeHg) in both simulated and field-contaminated soils. We identified specific microbial taxa including Geobacteraceae, Desulfuromonadaceae, Syntrophaceae, Oscillospiraceae, and Methanomicrobiaceae as key predictors of MeHg production, which differed from those typically observed in overlying water of croplands. Particularly, the relative abundance of these dominant Hg methylators significantly increased during rainfall-induced leaching compared to that of the control, suggesting the crucial yet previously overlooked impacts of increased precipitation events on the process of microbial Hg methylation in industry-contaminated sites. Given the rising incidences of extreme precipitation events worldwide due to climate change, this study highlights the significance of assessing Hg mobility and microbial transformation in legacy contaminated sites.