Extreme Heavy Precipitation Research Articles

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.

The driving of North American climate extremes by North Pacific stationary-transient wave interference

Wave interference between transient waves and climatological stationary waves is a useful framework for diagnosing the magnitude of stationary waves. Here, we find that the wave interference over the North Pacific Ocean is an important driver of North American wintertime cold and heavy precipitation extremes in the present climate, but that this relationship is projected to weaken under increasing greenhouse gas emissions. When daily circulation anomalies are in-phase with the climatological mean state, the anomalous transport of heat and moisture causes the enhanced occurrence of cold extremes across the continental U.S. and a significant decrease of heavy precipitation extremes in the western U.S. In a future emissions scenario, the climatological stationary wave over the eastern North Pacific weakens and shifts spatially, which alters and generally weakens the relationship between wave interference and North American climate extremes. Our results underscore that the prediction of changes in regional wave interference is pivotal for understanding the future regional climate variability.

Diurnal Cycle of Precipitation and Extremes in Nepal

This study examines the spatio-temporal distribution of hourly precipitation across Nepal using Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) data from 2015 to 2021. The findings indicate that hourly precipitation intensity during the monsoon season can reach up to 0.7 mm/hr, while pre-monsoon intensities peak at 0.2 mm/hr. These intensities are predominantly concentrated in mid- and low-elevation areas of central and eastern Nepal. Post-monsoon and winter seasons exhibit high-intensity precipitation patches over high-elevation regions in the western, central, and eastern peripheries of the country. The annual distribution of hourly precipitation shows a pronounced peak during the monsoon season, indicating that a significant portion of the total annual precipitation occurs during this period. Extreme precipitation events follow a similar seasonal distribution, with monsoon extremes exceeding 15 mm/hr. The diurnal cycle of monsoonal precipitation shows unique characteristics, peaking at 0.65 mm/hr around midnight and decreasing to 0.2 mm/hr by late morning, then increasing steadily in the afternoon and evening. Additionally, the study contrasts hourly heavy precipitation extremes (≥10 mm/hr or day) with daily extremes, noting that hourly extremes, despite being accumulated into daily measures, present a higher frequency, and pose greater short-term hazard risks. This analysis over a seven-year period suggests the need for continued research to determine spatial and temporal trends in hourly versus daily extreme precipitation patterns, particularly in the context of climate change and its impacts on regional hydrology and meteorology.

Multifactor Mathematical Modeling and Analysis of the Impact of Extreme Climate on Geological Disasters

Objective: To investigate the impact of extreme climate on geological disasters in Shanxi and propose effective disaster prevention and mitigation strategies. Methods: Using daily temperature and precipitation data from 27 meteorological stations in Shanxi Province from 1975 to 2020, 32 extreme climate indices were calculated. Combined with geological disaster site data, the distribution characteristics of extreme climates and their relationship with geological disasters were analyzed, and a regression model for geological disaster risk zones was constructed. Results: Sixteen extreme climate indices in Shanxi Province showed significant changes, especially TMAXmean (100% significant). Indices related to negative precipitation effects showed a declining trend, with 77.78% being significant, while 96.3% of positive temperature effect indices showed an increasing trend, with 73.6% being significant. Geological disaster hotspots were concentrated in the mid-altitude (500–1500 m) hilly and low mountain areas along the central north–south axis and on Q and Pz strata. Extreme high-temperature indices were significantly positively correlated with geological disaster hotspots, while extreme low-temperature indices were negatively correlated. Indices related to extreme heavy precipitation (e.g., R99p.Slope, RX5day.Slope) were associated with an increase in geological disaster hotspots, whereas higher total precipitation and frequent heavy precipitation events were associated with a decrease in disaster hotspots. The grey relational degree between the Z-score and TXn.Slope, TXx.Slope, GSL.Slope, and TX90P.Slope was greater than 0.8. The random forest model performed best in evaluation metrics such as MAE, RMSE, and R2. Conclusions: Shanxi is likely to experience more extreme high-temperature and precipitation events in the future. The low-altitude hilly and terraced areas in Zones III and VII are key regions for geological disaster prevention and control. High temperatures and extreme rainfall events generally increase the disaster risk, while higher total precipitation reduces it. The random forest model is the optimal tool for predicting geological disaster risks in Shanxi Province.

Variation of nitrate sources affected by precipitation with different intensities in groundwater in the piedmont plain area of alluvial-pluvial fan

A substantial reservoir of nitrogen (N) in soil poses a threat to the quality and safety of shallow groundwater, especially under extreme precipitation that hastens nitrogen leaching into groundwater. However, the specific impact of varying precipitation intensities on the concentration and sources of nitrate (NO3−) in groundwater across diverse hydrogeological zones and land uses remains unclear. This study aims to elucidate the fluctuations in NO3− concentration, sources, and controlling factors in shallow groundwater under different intensities of precipitation (extreme heavy precipitation and continuous heavy precipitation) in a typical alluvial-pluvial fan of the North China Plain by using stable isotopes (δ2H–H2O, δ18O–H2O, δ15N–NO3-, δ18O–NO3-), hydrochemical analyses and the SIAR model. Affected by extreme heavy precipitation the depleted isotopes of δ2H–H2O and δ18O–H2O in groundwater of the entire area suggested the rapid recharge of fast flow by precipitation. The enriched isotopes of δ2H–H2O and δ18O–H2O of north part in alluvial fan after continuous heavy precipitation showed the recharge of translatory flow of soil water. NO3−concentrations increased to 78.9 mg/L after extreme heavy precipitation and increased to 105.3 mg/L after continuous heavy precipitation when compared to those in normal year (56.8 mg/L) of north part of the alluvial fan. However, NO3− concentrations had slight variation after continuous heavy precipitation of south part of the fan due to the deep vadose zone. The contribution ratio of sources of NO3− in groundwater by using SIAR analysis revealed manure & sewage (MS) as the primary NO3− source (accounting for 59.7–78.1%) before extreme heavy precipitation, chemical fertilizer (CF) making a minor contribution (6.9–17.3%). Different precipitation events and land use types lead to changes in NO3− sources. Affected by extreme heavy precipitation, the contribution of MS decreased while CF increased, particularly in vegetables (26.2–28.1%) and farmland (29.2–34.7%). After continuous heavy precipitation, MS increased again, particularly in vegetables (50.0%) and farmlands (20.4–66.4%), with CF either increasing or remaining steady. This indicated that continuous heavy precipitation accelerated the leaching of nitrogen (organic manure application) stored in deep soil to groundwater and it has a larger influence on the increasing of NO3− concentrations of groundwater than extreme heavy precipitation which carried nitrogen (chemical fertilizer application) in shallow soil to groundwater by fast flow. These findings underscore the importance of considering soil chemical N stores and their implications for groundwater contamination mitigation under future extreme climate scenarios, particularly in agricultural management practices.

A triggering mechanism of quasi-stationary convective bands in the vicinity of southwestern Japan during the summer season as deduced from moisture origins

To find a plausible initiation mechanism of quasi-stationary convective bands (QSCBs) that lead to disasters, we investigated an extreme heavy precipitation event in Kyushu, southwestern Japan, in the middle of August 2021, using a regional spectral model incorporated with isotopic tracers aided by a water-tagging method. In the synoptic environment, the horizontal pressure gradient at low levels between an eastward-migrating Baiu frontal depression (BFD) and the North Pacific subtropical high (NPSH) is intensified to the south of a synoptic-scale front. To the south of the front, QSCBs also lie from the East China Sea to inland Kyushu. We confirm that the merging of the Asian monsoon moisture and the NPSH moisture creates a deep moist layer reaching middle levels from the surface in the vicinity of the QSCBs, providing an extremely unstable condition. Although such an unstable condition is indispensable for the maintenance of the QSCBs, an initiation mechanism is required that accounts for why the QSCBs emerge around the oceanic region where the two primary moisture merges; that appears to be the Ekman pumping mechanism. The strong boundary layer inflow of the NPSH moisture origin enhances the convective instability to the south of the QSCBs. Since the horizontal pressure gradient is attenuated in the vicinity of the BFD's center, on the contrary, the boundary layer flow north of the QSCBs decelerates rapidly, giving rise to upwelling due to the Ekman convergence. The persistent upwelling estimated in this event can lift the air of the Ekman layer up to a few hundred meters in a few hours, allowing it to readily reach the level of free convection. It is reasonable to conjecture that the persistent upwelling triggers the release of enhanced convective instability, leading to the formation of QSCBs. Continuous merging of the two remote moisture origins under the pronounced horizontal pressure gradient will further contribute to the reinforcement of the QSCBs.

Analysis of Extreme Precipitation Variation Characteristics and the Influencing Factors in the Yunnan-Guizhou Plateau Region, China

The increase of extreme precipitation (EP) frequency and the aggravation of disasters have seriously disrupted the normal economic and social development of human beings. The complex topography of the Yunnan-Guizhou Plateau region (YGPR) and the fact that moisture originates from two different directions, the Pacific Ocean and the Indian Ocean, make the mechanism of EP more complicated. Exploring the variation characteristics and influencing factors of EP in YGPR is of great significance for regional disaster prevention and mitigation and water resources management. In this study, 11 extreme precipitation indices (EPIs) defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) were calculated based on daily precipitation data of 1960–2020 from 83 national meteorological stations in the study area. The Mann–Kendall test and Wavelet analysis were used to analyze the variation characteristics of EP and explore the influence mechanisms of geographical factors and atmospheric circulation on EP in the spatial and temporal perspective. The conclusions are as follows: (1) The EP of the study area has an overall increasing trend in the research period, with the increase of persistent dry days, the precipitation concentration, intensity, and extreme heavy precipitation (EHP); (2) It shows the obvious spatial difference in the study area, with the high-value areas of extreme drought (ED) in the northwestern region and the total annual precipitation, EHP, and intensity in the southeastern region. In addition, ED and EHP tends to increase in the western region of the study area as well as in the middle east and southeast; (3) EHP is significantly positively correlated with longitude and highly negatively with latitude. Meanwhile, EHP shows a correlation with altitude (negative at low altitude and positive at high altitude); (4) The degree of drought change is greatly affected by North Atlantic Oscillation/El Niño-Southern Oscillation (ENSO) events. The variation of extreme heavy precipitation is greatly influenced by the summer monsoon of South Asian, East Asian, and South China Sea; (5) All the EPIs show persistence. The study results can contribute to the understanding of EP variation in the study area and provide some scientific references for regional water resource management, meteorological warning, and agricultural production safeguard.

Performance of regional climate model RegCM4 with a hydrostatic or non‐hydrostatic dynamic core at simulating precipitation extremes in China

AbstractIn this study, we investigated the performance of RegCM4 with a hydrostatic or non‐hydrostatic dynamic core and different land surface models at simulating the mean and extreme precipitation during 1991–1999 in China and the Beijing–Tianjin–Hebei urban agglomeration (JJJ) in northern China. The resolutions were 12 km with the whole of China included and 3 km nested over the JJJ region. The observed daily precipitation data comprised the CN05.1 data set from China Meteorological Administration. First, RegCM4 with a hydrostatic dynamic core forced by the Max Planck Institute Earth System Model (MPI‐ESM1.2‐HR) that participated in CMIP6 was used to simulate the east Asia area at a resolution of 12 km. Next, the RegCM4 results with 12 km resolution forced RegCM4 with a non‐hydrostatic dynamic core (RegCM4‐NH) to run over the JJJ region with a 3 km convection‐permitting scale through one‐way nesting. The results showed that RegCM4 with a hydrostatic and non‐hydrostatic core could obtain more detailed seasonal and annual precipitation in China and the JJJ region relative to MPI‐ESM1.2‐HR although their performance varied over different regions. RegCM4 with the community land surface model 4.5 (CLM4.5) generally performed better at simulating the mean and extreme precipitation over the four subregions of China than that with the Biosphere–Atmosphere Transfer Scheme because of more detailed descriptions of land surface processes of CLM4.5. RegCM4‐NH with convection‐permitting resolution improved the simulations of heavy precipitation extremes over JJJ compared with RegCM4 with a hydrostatic core and resolution of 12 km. In addition, RegCM4‐NH with CLM4.5 performed better at simulating heavy precipitation extremes over JJJ compared with all other simulations, with higher correlation coefficients and larger relative root mean squared errors.

Developing Low‐Likelihood Climate Storylines for Extreme Precipitation Over Central Europe

AbstractHeavy precipitation and associated flooding during the cold season, such as the 1993 flood in central Europe (CEU), are a major threat to society and ecosystems. Due to the lack of long homogenous climate data and methodological frameworks, it is challenging to estimate how extreme precipitation could get and what the physical drivers are. This study presents two complementary strategies to extrapolate beyond the precipitation records: (a) statistical estimates based on fitting generalized extreme value distributions, providing their probabilistic information on return periods and, (b) ensemble boosting, a model‐based re‐initialization of heavy precipitation in large ensembles, providing a physical coherent storyline in space and time, however, with no direct quantification of its probability. Both show that 3‐day accumulated precipitation maxima can be substantially exceeded over CEU of around 30%–40%, but even higher magnitudes cannot be ruled out in the near future. An empirical orthogonal function analysis reveals that certain sea level pressure patterns, partly reminding of atmospheric rivers are more often associated with heavy precipitation than more moderate events. Additionally, ensemble boosting is a suitable tool for case studies to analyze how extreme heavy precipitation as for the event in 1993 can be simulated. By boosting a 1993‐analog, one‐quarter of the resulting storylines show increased rainfall than observed, due to a stronger north‐south pressure gradient that may have exacerbated the flooding. Overall, the precipitation estimates demonstrate that ensemble boosting is a complementary method to statistical tools and suitable for stress testing, for example, infrastructure protection measures against potentially unseen heavy precipitation events.

Variation characteristics of extreme climate events in Southwest China from 1961 to 2017

Climate change is increasing the intensity of extreme climate events. Significant impacts of extreme climate events on human society and ecosystem have occurred in many places of the world, for example, Southwest China (SWC). In this study, the daily temperature and precipitation data from 438 meteorological stations are used to analyze the variation characteristics of extreme climate events in the SWC from 1961 to 2017. The annual extreme warm events show a significant increasing trend at 99% confidence level at most stations, and a few stations with a decreasing trend are mainly located in the southern Sichuan Province, the northern Yunnan Province and the western Guizhou Province. Meanwhile, the annual extreme cold events show a significant decreasing trend at 99% confidence level at most stations, and a few stations with an increasing trend are mainly distributed in the Sichuan Basin. Both the annual extreme heavy precipitation indexes and rainstorm indexes show nonsignificant increasing trends, but they differ greatly in the spatial distribution. These indexes in the western Tibet, Chongqing and most parts of Guizhou show significant increasing trends at 95% confidence level, while those in the central Sichuan and southeastern Yunnan show significant decreasing trends. The percentage of extreme heavy precipitation shows a significant increasing trend at 99% confidence level, especially in the northeastern Sichuan, the central-eastern Guizhou and the central Yunnan. Overall, under the background of global warming, the extreme warm events in SWC increase significantly from 1961 to 2017, and the extreme cold events decrease significantly. The variation trends of extreme precipitation events differ greatly in different regions, and the percentage of extreme heavy precipitation increases significantly.

Evaluation of the RF-MEP Method for Merging Multiple Gridded Precipitation Products in the Chongqing City, China

Precipitation is a major component of the water cycle. Accurate and reliable estimation of precipitation is essential for various applications. Generally, there are three main types of precipitation products: satellite based, reanalysis, and ground measurements from rain gauge stations. Each type has its advantages and disadvantages. Recent efforts have been made to develop various merging methods to improve precipitation estimates by combining multiple precipitation products. This study evaluated for the first time the performance of the random forest-based merging procedure (RF-MEP) method in enhancing the accuracy of daily precipitation estimates in Chongqing city, China with a complex terrain and sparse observational data. The RF-MEP method was used to merge three widely used gridded precipitation products (CHIRPS, ERA5-Land, and GPM IMERG) with ground measurements from a limited number of rain gauge stations to produce the merged precipitation dataset. Eight stations (approximately 70% of the available stations) were used to train the RF-MEP approach, while four stations (30%) were used for independent testing. Various statistical metrics were employed to assess the performance of the merged precipitation dataset and the three existing precipitation products against the ground measurements. Our results demonstrated that the RF-MEP approach significantly enhances the accuracy of daily precipitation estimates, surpassing the performance of the individual precipitation products and two other merging methods (the simple linear regression model and the simple averaging). Among the three existing products, ERA5-Land exhibited the best performance in capturing daily precipitation, followed by GPM IMERG, while CHIRPS performed the worst. Regarding precipitation intensity, all three existing products and the RF-MEP merged dataset performed well in capturing light precipitation events with an intensity of less than 1 mm/day, which accounts for the majority (more than 70%) of occurrences. However, all datasets showed rather poor capability in capturing precipitation events beyond 1 mm/day, with the worst performance observed for extreme heavy precipitation events exceeding 50 mm/day. The RF-MEP approach significantly improves the detection ability for all precipitation intensities, except for the most extreme intensity (>50 mm/day), where only marginal improvement is observed. Analysis of the spatial pattern of precipitation estimates and the temporal bias of daily precipitation estimates further confirms the superior performance of the RF-MEP merged precipitation dataset over the three existing products.

Rainfall intensity affects the recharge mechanisms of groundwater in a headwater basin of the North China plain

Understanding the origins of groundwater and its movement from mountain to plain during different high intensity rainfall events is critical for conserving water supplies, determining water-use policies and controlling pollution. These factors are also the keys for understanding the dominant processes in hydrological models. In this study, groundwater resources and recharge processes during heavy precipitation were explored by using stable isotope tracers in the hilly area of Taihang Mountain. It was found that the δ2H and δ18O values of precipitation exhibited obvious precipitation amount effect during different precipitation intensity events. The stable isotopic values in groundwater and river water showed significantly varied during the single extreme heavy precipitation and the continuous heavy precipitation events. In the rainy season, precipitation amounts greater than 40 mm/d could effectively recharge the shallow groundwater in the study area. By comparing the spatial isotopic distribution of groundwater, soil water, and river water with precipitation, we showed distinct groundwater recharge patterns in terms of their water resources, timing, and the degree of river water and groundwater interaction during the single extreme heavy precipitation and the continuous heavy precipitation. After the single extreme heavy precipitation, the δ2H and δ18O values of groundwater, soil water, and river water showed stable over time and had the same similar variations, suggested that the groundwater recharge was mainly dominated by precipitation with preferential flow or bypass flow. While after the continuous heavy precipitation, the variation of δ2H and δ18O in all water is consistent with the previous precipitation, which shown a mixing effect of previous enrich precipitation and depleted heavy precipitation, suggested that groundwater source was dominated by a continuous recharge of previous heavier precipitation with translatory flow. The groundwater main recharge mechanism is not constant, but changes with rainfall intensity. The rainfall intensity play an important role in groundwater recharge change affecting runoff process. Overall, this paper presents a new insight to understand the effect of rainfall intensity on hydrological process, which could be used to provide vital information in the semi-humid and semi-arid regions where water resources are critical in climate change adaptation strategies.

Spatiotemporal variability characteristics of extreme climate events in Xinjiang during 1960–2019

Under the global warming, it is particularly important to explore the response of extreme climate to global climate change over the arid regions. Based on daily temperature (maximum, minimum, and average) and precipitation data from meteorological stations in Xinjiang, China, we analyzed the spatiotemporal characteristics of extreme temperature and extreme precipitation events via combining thin plate smoothing spline function interpolation, Sen's slope, and Mann-Kendall test. Our results showed that during 1960-2019, the extreme low temperature index of frost days (FD), icing days (ID), cold days (TX10p), cold nights (TN10p), and cold speel duration index (CSDI) all showed the downward trend to varying degrees, and the extreme high temperature index of summer days (SD25), warm days (TX90p), warm night (TN90p), and warm speel duration index (WSDI) all showed an upward trend to varying degrees, and the extreme low temperature index of high altitude mountains decreases more than that of the basin and plains. In addition, all the extreme temperature indices are closely related to the annual average temperature in Xinjiang (R > 0.6). Among the extreme precipitation indices, except for the consecutive dry days (CDD), the other extreme precipitation indices showed increasing trends to different degrees, but the changes in extreme precipitation in Xinjiang were mainly manifested by the increase of heavy precipitation in a short period (the increase of heavy precipitation and extreme heavy precipitation was the largest, 44.8mm/10a and 17.6mm/10a, respectively) and spatially concentrated in the Ili River and Altai Mountains in northern Xinjiang. Meanwhile, annual precipitation was positively correlated with the extreme precipitation index (R > 0.4), except for the CDD. This study provides theoretical support for the prevention and control of natural disasters in the dry zone.

Projected Changes in Extreme Wet and Dry Conditions in Greece

Earth’s changing climate may have different effects around the planet. Regional changes in temperature and precipitation extremes are associated with damaging natural hazards. Decreases in precipitation are expected to occur in some places at mid-latitudes, for instance the Mediterranean, which has been classified as a climate change hotspot. Droughts are among the most damaging natural hazards with severe consequences in the socio-economic sectors, the environment, and living beings. In contrast, extreme heavy precipitation events may become more frequent. This study aims to project changes in precipitation extremes and assess drought variability and change across Greece. A better knowledge of the potential changes in drought variability under climate change is vital for managing potential risks and impacts associated with dry conditions. The spatiotemporal characteristics of heavy precipitation and drought events in Greece are investigated using extreme precipitation indices such as consecutive wet/dry days, total wet-day precipitation, fraction of total wet-day rainfall, maximum daily precipitation, and heavy precipitation days. The standardized precipitation index and the standardized precipitation and evapotranspiration index are also calculated to assess seasonal dryness variability. The analysis is performed using a sub-set of high-resolution simulations from EURO-CORDEX, under two different representative concentration pathway scenarios. The results show that the region is subject to future dry conditions. Total annual precipitation is found to decrease in most of the country, with western and southern parts tending to be the most vulnerable areas. The annual precipitation is estimated to decrease by 5–20% and 5–25% (RCP4.5 and RCP8.5 respectively) toward the period 2041–2070 and by 10–25% and 15–40% (RCP4.5 and RCP8.5) toward 2071–2100. Drought-related indices reveal positive trends, particularly under the high greenhouse-gas emission scenario, with the number of consecutive dry days increasing by 20–50% and 40–80% (during 2041–2070 and 2071–2100, respectively). On the contrary, extreme precipitation events tend to decrease in the future.

Extreme precipitation changes over the Yangtze River Basin in 1901-2020

To better understand the characteristics of long-term change and variability in regional extreme precipitation and to examine possible regional responses to global climate warming, we analyzed temporal and spatial patterns of precipitation and extreme precipitation index changes in the Yangtze River Basin (YRB) over the last 120 yr. Based on the China Meteorological Administration’s daily precipitation data set of 60 city stations in mainland China from 1901-2020, we found that total annual precipitation and daily precipitation intensity of the Upper Reaches (UR) experienced a downward trend, but those of the Middle and Lower Reaches (MLR) showed an upward trend. Precipitation amount and intensity increased, while the number of precipitation days slightly decreased over the YRB during 1901-2020. Most extreme precipitation indices showed a decreasing trend in the first 60 yr that reversed after 1961 into slightly upward trends, except for consecutive dry days and wet days in the YRB during 1901-2020. There were significant downward trends for consecutive dry days and maximum 1 and 5 d precipitation during the first 60 yr, and significant upward trends for maximum 1 d precipitation, total extreme heavy precipitation, and very heavy precipitation days in the last 60 yr. The trends for extreme precipitation in the UR were lower than those in the MLR during 1901-2020, particularly in the last 60 yr, whereas the trends in the UR were higher than those in the MLR during 1901-1960. The fluctuations of extreme precipitation indices in the UR were more dramatic than those in the MLR, and the extreme precipitation indices all showed 5-10 or 20 yr periodic variabilities. The analysis also showed that observed changes in regional extreme events were directly related to rapid urbanization around the stations and multi-decadal variability of the East Asian monsoon.

Simulation Performance and Case Study of Extreme Events in Northwest China Using the BCC-CSM2 Model

The BCC-CSM2 model is the second generation of the Beijing Climate Center Climate System Model developed by the National Center of China Meteorological Administration. Using the outputs of two versions of the BCC-CSM2 model with different resolutions, namely: BCC-CSM2-MR and BCC-CSM2-HR, their performance in simulating the climate characteristics of Northwest China was compared. The BCC-CSM2-HR had a better ability to simulate the detailed distribution of the average temperature and precipitation in Northwest China, and could delineate the influence of the topography in detail. The extreme events in Northwest China were evaluated further using the BCC-CSM2-HR and the observation data from China Meteorological Data Center. The BCC-CSM2-HR provided a good simulation of the spatial distribution of extreme climate events in Northwest China, and the spatial distribution of TXx, TNx, TXn, and TNn in Northwest China show closer proximity to the observation than that of TX90p, TN90p, TX10p, and TN10p, even in the case of extreme heavy precipitation. This case study of the extreme weather events showed that the BCC-CSM2-HR model had the best simulation performance for extreme high temperature events in Northwest China, followed by extreme low temperature events, and had the worst simulation ability for extreme precipitation events.

How Well Does the ERA5 Reanalysis Capture the Extreme Climate Events Over China? Part I: Extreme Precipitation

ERA5 is the fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts, with high spatiotemporal resolution and global coverage. However, the reliability of ERA5 for simulating extreme precipitation events is still unclear over China. In this study, 12 extreme precipitation indices and a comprehensive quantitative distance between indices of simulation and observation were used to evaluate ERA5 precipitation from three fundamental aspects: intensity, frequency, and duration. The geomorphological regionalization method was used to divide the subregions of China. The results showed that the ability of ERA5 to simulate annual total precipitation was better than that of daily precipitation. For the intensity indices, ERA5 performs well for simulating the PRCPTOT (annual total wet days precipitation) over China. ERA5 performs better on RX5day (max 5-days precipitation amount) and R95p (very wet days), especially in eastern China, than on RX1day (max 1-day precipitation amount) and R99p (extremely wet days). For the frequency indices, the ability of the ERA5 simulation increased as the amount of precipitation increased, except for northwestern China. However, the ability of ERA5 to simulate R50 mm (number of extreme heavy precipitation days) decreased. For the duration indices, ERA5 was better at simulating drought events than wet events in eastern China. Our results highlight the need for ERA5 to enhance the simulation of trend changes in extreme precipitation events.

Performance of satellite-based and reanalysis precipitation products under multi-temporal scales and extreme weather in mainland China

Gridded precipitation products are efficient supplements to surface meteorological gauges and thus a comprehensive evaluation of such products is essential. This study systematically evaluated the performance of 4 gridded precipitation datasets with hourly scale in mainland China, with ground gauge precipitation as a benchmark. In particular, we assessed the performance of two satellite-based precipitation estimations (SPEs): Integrated Multi-satellite Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP), and two reanalysis precipitation estimations (RPEs): Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA) and Climate Forecast System Reanalysis (CFSR). The results reveal that all the products have better performance in low-latitude areas, and have worse performance in the high-latitude mountainous regions. SPE products have similar features of temporal-spatial performance and diurnal cycle estimation, and so have RPE products. The overall summer SPE accuracy surpasses that of all RPE products, and vice versa in winter. The error decomposition of each product linked the summer bias to excessive false events of light precipitation. In winter, the SPE error is generally a result of missed and false events, while that of the RPEs originates from false precipitation. The product accuracy increases with the time scale, and the daily MERRA accuracy exceeds that of other products. However, due to the challenge in representing convective precipitation, the accuracy of the diurnal cycle and peak hour is lower than that of the SPEs, and representing weaker amplitudes compared to the gauge precipitation. This consequently results in RPEs’ poorer performance in extreme heavy precipitation compared to the SPE products. The results of this study are useful for both developers and users of gridded precipitation products.

Climatology of the extreme heavy precipitation events in Slovakia in the 1951–2020 period

Climatology of the extreme heavy precipitation events in Slovakia in the 1951–2020 period

Variation of Hourly Extreme Precipitation in the Three Gorges Reservoir Region, China, from the Observation Record

Extreme hourly precipitation is amongst the most prominent driving factors of flash floods and geological disasters. Based on the hourly precipitation data of 35 stations in the Three Gorges Reservoir Region (TGRR) from 1998 to 2020, we analyzed the spatiotemporal variation characteristics of hourly extreme precipitation indexes. The selected indicators included the frequency, intensity, period, annual maximum, trend of hourly heavy precipitation (20–50 mm/h) and hourly extreme heavy precipitation (≥50 mm/h) in the TGRR. Closely related climatic factors such as the Western Pacific Subtropical High Intensity (WPSHI) were also discussed. The results showed that in 2010–2020, the cumulative frequency of heavy precipitation magnitude between 25 and 40 mm/h slightly increased, while the corresponding frequency for magnitudes ≥50 mm/h decreased. In summer, the frequency of both heavy and extreme heavy precipitation increased in June and decreased in August, indicating a shift of extreme events to an earlier time in the flood season. The cumulative frequency of heavy precipitation in July had a period of about 7a, and that of extreme heavy precipitation had a period of 3a. The annual average intensity of heavy precipitation and extreme heavy precipitation in the TGRR was 28.9 mm/h and 61.4 mm/h per station, respectively, and both fluctuated and insignificantly decreased from 1998 to 2020. The annual maximum hourly precipitation center in the TGRR moved downstream from west to northeast. The frequency of heavy precipitation was relatively small along the main stream of the river valley. Both the frequency and total amount of heavy precipitation in southeast of the TGRR were significantly higher than those in other regions. Heavy precipitation in the majority of stations with high elevation (higher than 500 m) showed a decreasing trend. The cumulative frequency of precipitation with an intensity of 20–50 mm/h was closely correlated with the Western Hemisphere Warm Pool (WHWP) Index in February and the WPSHI Index in January, and especially, the abnormal large annual frequency (top 20%) showed strong correlation with the two indexes, implying highly predictable factors for extreme events. The frequency of precipitation intensity above 50 mm/h was correlated with the Western Pacific Warm Pool (WPWP) Area Index in January and the WPWP Intensity Index in November of last year. The research results provide a strong and refined factual basis for the assessment and prediction of extreme precipitation, and for disaster prevention and mitigation, in the TGRR.