Changes In Extreme Precipitation Events Research Articles

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

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

Spatiotemporal variability of extreme precipitation events and their impacts on soil moisture and water table depth in Argentina’s core crop region

ABSTRACT This study reassesses the spatiotemporal variability of and changes in extreme precipitation events (EPEs) and examines the response of soil moisture and water table depth to EPEs in Argentina’s core crop region. Standardized nonparametric indices are applied to precipitation, soil moisture, and groundwater. The temporal variability of EPEs exhibits a decadal cycle and inter-annual modes with dominant frequencies between 2.5 and 4 years related to El Niño Southern Oscillation periodicities. The soil moisture and water table depth respond to precipitation variability replicating both decadal and inter-annual EPE variability. The response of soil moisture to EPEs attenuates in time as soil depth increases. Water table depth responds to EPEs with an average delay of 10 months. In recent decades, soil moisture increases (water table depth becomes shallower) rapidly when reacting to excess precipitation, while soil moisture decreases (water table depth deepens) slowly during and after drought events.

Spatiotemporal variability in extreme precipitation and associated large-scale climate mechanisms in Central Asia from 1950 to 2019

Increased sea surface temperature, evaporation, air temperature, and moisture holding capacity associated with climate change may the enhance transport of moisture to Central Asia (CA), resulting in increased extreme precipitation events (EPEs). Changes in EPEs may affect the socioeconomic and ecological environment in typical arid and semi-arid regions of CA. Therefore, based on meteorological station data and four reanalyzed precipitation datasets, we used the Taylor diagram, Geo-Detector method, and other methods to examine 10 EPE indices in CA from 1950 to 2019, analyzed their spatial-temporal trends, and quantified the influence of large-scale climate factors on EPEs. The results showed that GSWP3_W5E5 was the optimal option with better performance in terms of monthly and annual precipitation in CA. Overall, EPEs in CA showed an increasing trend, but an abrupt point was found in 1986, when very wet day precipitation (R95p) increased from 36.64 to 47.84 mm; the increasing rate also changed from 0.8 to 5.06 mm/10a. The changes in the Northern Hemisphere Subtropical High Intensity Index (NSI), NINO B Area Sea Surface Temperature Anomaly Index (NINOB), Asian Zonal Circulation Index, and Atlantic Multidecadal Oscillation Index are the main reasons for the increase in EPEs; the NSI and NINOB had the largest contributions to EPEs, with at 44.32 % and 43.80 %, respectively. Additionally, two-factor interactions had a more significant influence. Further analysis revealed that the abnormal warming of sea surface temperature and others led to the strengthen of water vapor transport in CA caused by a series of cyclones and anticyclonic anomalies in the westerly circulation zone, leading to the increase of EPEs. The results obtained in this study can contribute to a more comprehensive understanding of the changes in EPEs and provide a reference for water resource management and disaster prevention in CA.

Corrigendum to “Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models, part II: Future projections under 1.5, 2.0, and 3.0°C Global warming levels”

Corrigendum to “Changes in extreme precipitation events in the Zambezi River basins based on <scp>CORDEX‐CORE</scp> models, part <scp>II</scp>: Future projections under 1.5, 2.0, and 3.0°C Global warming levels”

Future Projection of Extreme Precipitation Indices over the Qilian Mountains under Global Warming.

The Qilian Mountains are a climate-sensitive area in northwest China, and extreme precipitation events have an important impact on its ecological environment. Therefore, considering the global warming scenario, it is highly important to project the extreme precipitation indices over the Qilian Mountains in the future. This study is based on three CMIP6 models (CESM2, EC-Earth3, and KACE-1-0-G). A bias correction algorithm (QDM) was used to correct the precipitation outputs of the models. The eight extreme precipitation indices over the Qilian Mountains during the historical period and in the future were calculated using meteorological software (ClimPACT2), and the performance of the CMIP6 models to simulate the extreme precipitation indices of the Qilian Mountains in the historical period was evaluated. Results revealed that: (1) The corrected CMIP6 models could simulate the changes in extreme precipitation indices over the Qilian Mountains in the historical period relatively well, and the corrected CESM2 displayed better simulation as compared to the other two CMIP6 models. The CMIP6 models performed well while simulating R10mm (CC is higher than 0.71) and PRCPTOT (CC is higher than 0.84). (2) The changes in the eight extreme precipitation indices were greater with the enhancement of the SSP scenario. The growth rate of precipitation in the Qilian Mountains during the 21st century under SSP585 is significantly higher than the other two SSP scenarios. The increment of precipitation in the Qilian Mountains mainly comes from the increase in heavy precipitation. (3) The Qilian Mountains will become wetter in the 21st century, especially in the central and eastern regions. The largest increase in precipitation intensity will be observed in the western Qilian Mountains. Additionally, total precipitation will also increase in the middle and end of the 21st century under SSP585. Furthermore, the precipitation increment of the Qilian Mountains will increase with the altitude in the middle and end of the 21st century. This study aims to provide a reference for the changes in extreme precipitation events, glacier mass balance, and water resources in the Qilian Mountains during the 21st century.

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.

Spatiotemporal Variability in Precipitation Extremes in the Jianghuai Region of China and the Analysis of Its Circulation Features

In the context of global warming, changes in extreme-precipitation events are becoming increasingly complex, and investigating the spatial and temporal variation characteristics of extreme precipitation is extremely important for scientific water-resource planning, preventing new climate risks and maintaining ecosystem balances. Based on the daily precipitation from 1960–2017 at 15 meteorological stations in the Jianghuai region, the extreme-precipitation indices were calculated. The variations in 12 extreme-precipitation indices were detected by using the Mann–Kendall test in the Jianghuai region. The periodicity of indices was examined by wavelet analysis detecting significant time sections. Through the cross wavelet transform and wavelet coherence analyses, the nonlinear connections between extreme precipitation and atmospheric circulation were explored. The results indicate significant increasing trends in the max one-day precipitation amount (Rx1day), extreme wet days (R99p), and simple precipitation intensity index (SDII). The intensity of extreme precipitation increased significantly. The variation in extreme precipitation showed different trends in different regions, with a greater likelihood of increasing extreme-precipitation intensity and frequency in the southern region compared to the central and northern regions. The period of most oscillations of the indices tend toward be on a time scale of 2–4 years and are in the 1990s. The number of heavy precipitation days (R10 mm) and number of very heavy precipitation days (R20 mm) had, mainly, periods of 5.84 years. Additionally, there were significant resonance periods between the extreme-precipitation indices and the atmospheric circulation index; however, there were obvious differences in time domains. The North Atlantic Oscillation (NAO) and East Asian summer monsoon (EASM) had the most significant effect on the duration of extreme precipitation; Atlantic Oscillation (AO) and EASM had the most significant influence on the extreme-precipitation intensity. The results of the study can provide a scientific basis for water-resource management and disaster prevention and control in the Jianghuai region.

Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models: Part I—Evaluation of historical simulation

AbstractThis study evaluates the ability of the Coordinated Output for Regional Evaluations (CORE) initiated under the Coordinated Regional Climate Downscaling Experiment (CORDEX) to reproduce austral summer extreme precipitation indices over the Zambezi River basin (ZRB) from 1983 to 2005. The ability of the RCMs to simulate the spatial distributions of observed extreme precipitation was assessed using multiple datasets. The spatially averaged performance of the CORDEX‐CORE ensemble mean (CORE‐ENS) and RCM ensembles (RCM‐ENSEMBLES developed from different combinations of CORE‐ENS ensemble members) was evaluated using statistical metrics. The results showed similarities in the spatial distribution of extreme precipitation among the observations. However, there were considerable differences in the magnitude of extreme precipitation among the observations. The frequency of days with very heavy precipitation (R20) showed the largest differences in magnitude among the observations. Although there are differences in magnitude, CORE‐ENS, its ensemble members, and RCM‐ENSEMBLES can capture the spatial distribution of extreme precipitation. Specifically, CORE‐ENS, its ensemble members, and RCM‐ENSEMBLES overestimated (underestimated) the frequency of rainy days (RR1) and maximum consecutive wet days (CWD) (maximum consecutive dry days [CDD]). In contrast, some members of CORE‐ENS overestimate, while others underestimate, the simple daily intensity index (SDII), the frequency of days with heavy precipitation (R10), and R20, depending on the choice of reference data. The Consortium for Small‐scale MOdelling in CLimate Mode (CCLM) and Regional MOdel (REMO) performed better than the Regional Climate Model (RegCM4.7) in simulating the spatial distributions of extreme precipitation. The regionally averaged uncertainties (biases) of the CORE‐ENS, its ensemble members, and RCMENSEMBLES were within the range of those in the observational datasets, except for CWD (CWD and RR1). Overall, CORE‐ENS performed better than its ensemble members in simulating extreme precipitation.

Spatiotemporally varied extreme precipitation events simultaneously controlled by multiple circulation factors in China's Loess Plateau

AbstractThe intensive and frequent extreme precipitation events (EPE) greatly contribute to the severe soil loss in China's Loess Plateau, and it is thus essential to understand how and why EPE varies with space and time. Particularly, the combined influence of multiple factors on EPE has rarely been explored. This study analysed the spatiotemporal variability of EPE for 1961–2017 after defining six indices for intensity, frequency, and duration of EPE (R5d, SDII, R90t, R90n, CDD, CWD). We employed 12 atmospheric circulation factors to determine their combined effects on EPE on different time scales over time by the multiple wavelet coherence. The EPE indices spatially varied with obvious southeast‐northwest gradients. Averaged across the whole plateau, SDII, R90t, and R90n increased insignificantly, while R5d, CDD, and CWD decreased insignificantly. In addition, the change trend had spatial variations with most wet EPE indices increasing in the north and the southernmost areas and decreasing in the middle‐south areas. SDII, R90t, and R90n at 68%, 66%, and 53% of stations tended to increase, respectively, and R5d, CDD, and CWD decreased at 66%, 70%, and 77% of stations, respectively. The temperature had a greater correlation with the duration of EPE in summer and on the intensity and frequency of EPE in winter. El Niño‐Southern Oscillation (ENSO), Pacific North American teleconnection pattern (PNA), ENSO‐Arctic Oscillation (AO), and ENSO‐AO‐PNA were found to be the main factors influencing EPE individually or simultaneously. This study provides technical support for the identification of combined effects of multiple factors, and the results are helpful for regional environmental management. Specific to the Loess Plateau, the identified individual or multiple factors can be used to project future changes in EPE, and the more frequent and intensive EPE in some regions may increase the difficulty in future soil loss control.

Extreme Precipitation Events in Alaska: Historical Trends and Projected Changes

While recent increases in heavy precipitation events in some midlatitude regions are consistent with climate model simulations, evidence of such increases in high latitudes is more tenuous, partly because of data limitations. The present study evaluates historical and future changes in extreme precipitation events in Alaska. Using the ERA5 reanalysis, station data, and output from two downscaled global climate models, we examine precipitation-driven flood events at five diverse locations in Alaska where major historical floods provide benchmarks: Fairbanks (August 1967), Seward (October 1986), Allakaket/Bettles (August 1994), Kivalina (August 2012), and Haines (December 2020). We place these precipitation events into a framework of historical trends and end-of-century (2065–2100) model projections. In all but one of the flood events, the amount of rainfall was the highest on record for the event duration, and precipitation events of this magnitude are generally projected by the models to remain infrequent. All of the cases had subtropical or tropical moisture sources. None of the locations show statistically significant historical trends in the magnitude of extreme precipitation events. However, the frequencies of heavy precipitation events are projected to increase at most of the locations. The frequency of events with 2 year and 5 year historical return intervals is projected to become more frequent, especially in the Interior, and in some cases increase to several times per year. Decreases are projected only for Seward along Alaska’s southern coast.

Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models, Part II: Future projections under 1.5, 2.0, and 3.0°C global warming levels

AbstractThis study examines the potential implications of 1.5, 2.0, and 3.0°C global warming levels (GWLs) on the austral summer (November–March) extreme precipitation indices over the Zambezi River basin (ZRB) relative to the control period (1971–2000). We computed extreme precipitation based on daily data from observations and the Coordinated Regional Downscaling Experiment (CORDEX)‐Coordinated Output for Regional Evaluations (CORE) multi‐model ensemble mean (ENSMean). First, we evaluated the performance of the CORDEX‐CORE ENSMean in simulating extreme precipitation based on six indices; the number of rainy days (RR1), simple daily intensity index (SDII), maximum consecutive wet days (CWD), maximum consecutive dry days (CDD), heavy precipitation days (R10), and very heavy precipitation days (R20). The results indicate that the CORDEX‐CORE ENSMean can simulate the spatial distributions of extreme precipitation over the ZRB. However, CORDEX‐CORE largely overestimates the magnitudes of RR1 and CWD. The projected changes show a decrease in RR1, CWD, and R10 under all GWLs, with a robust and pronounced decrease under 3.0°C GWL. In contrast, CDD and SDII are projected to increase under all GWLs, with a robust and pronounced increase in CDD under 3.0°C GWL. The regionally averaged changes show that the median values of CWD, RR1, and R10 (SDII and CDD) are projected to decrease (increase) under all GWLs over the ZRB and sub‐basins. The probability density function (PDF) shows negative (positive) shifts in the mean of CWD, RR1, and R10 (SDII and CDD) over the ZRB and sub‐basins under all GWLs. In contrast, R20 is projected to increase (decrease) over most of the western (eastern) ZRB under all GWLs. Assessing the implications of an additional 0.5 and 1.5°C (1.0°C) warming to 1.5°C (2.0°C) GWL shows that limiting GWL to 1.5°C would restrict the future exposure of the ZRB to extreme precipitation.

Simulation of Extreme Precipitation in Four Climate Regions in China by General Circulation Models (GCMs): Performance and Projections

In the context of global climate change, it is important to monitor abnormal changes in extreme precipitation events that lead to frequent floods. This research used precipitation indices to describe variations in extreme precipitation and analyzed the characteristics of extreme precipitation in four climatic (arid, semi-arid, semi-humid and humid) regions across China. The equidistant cumulative distribution function (EDCDF) method was used to downscale and bias-correct daily precipitation in eight Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs). From 1961 to 2005, the humid region had stronger and longer extreme precipitation compared with the other regions. In the future, the projected extreme precipitation is mainly concentrated in summer, and there will be large areas with substantial changes in maximum consecutive 5-day precipitation (Rx5) and precipitation intensity (SDII). The greatest differences between two scenarios (RCP4.5 and RCP8.5) are in semi-arid and semi-humid areas for summer precipitation anomalies. However, the area of the four regions with an increasing trend of extreme precipitation is larger under the RCP8.5 scenario than that under the RCP4.5 scenario. The increasing trend of extreme precipitation in the future is relatively pronounced, especially in humid areas, implying a potential heightened flood risk in these areas.

Assessing the Impacts of Extreme Precipitation Change on Vegetation Activity

Extreme climate events frequently have more severe effects on terrestrial vegetation activity than long-term changes in climate averages. However, changes in extreme climate events as well as their potential risk on vegetation activity are still poorly understood. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper aims to understand the vegetation response to changes in extreme precipitation events from 1982 to 2012 using the maximum normalized difference vegetation index (NDVI) as an indicator. By applying extreme value theory (EVT), the potential risks of extreme precipitation events on vegetation activity were analyzed by conducting return period analysis. Results indicated that vegetation activity could be affected by extreme precipitation events, especially the combined effects of the frequency and intensity of precipitation extremes. For instance, vegetation activity could be enhanced in the regions with weakened intensity but increased occurrence of extreme precipitation events. In addition, we found potential risk of extreme precipitation events on vegetation activity from the results of precipitation extreme trend and return period analysis. These phenomena can be associated with the local occurrence of extreme precipitation events, different land cover types, and soil moisture cumulative effect on vegetation growth. This study stresses the importance of considering both current changes in and the potential risk of extreme precipitation events to understand their effects on vegetation activity.

Application of Normalized Difference Vegetation Index (NDVI) for the Detection of Extreme Precipitation Change

Remote sensing has frequently been employed to monitor extreme climatic events, especially droughts, by identifying the anomalies of vegetation activity from the regional to global scale. However, limited research has addressed the performance of remote sensing on detecting extreme precipitation events. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper examines the application of the satellite-derived normalized difference vegetation index (NDVI) for detecting the change of extreme precipitation events from 1982 to 2012. The performances of three NDVI-based indices, including minimum, mean, and maximum NDVIs, were examined to capture the sensibility of vegetation activity to changes in extreme precipitation events. The results show not only common enhanced trends, but also obvious spatial discrepancies between the intensity and frequency of extreme precipitation events in the MLR-YR. As to its application on terrestrial vegetation, changes in extreme precipitation intensity coincided with that of the vegetation activity, which was represented as the maximum and the minimum NDVIs, especially the maximum NDVI. In addition, similar patterns were found between the standard deviation of the maximum NDVI and the trend of extreme precipitation intensity. Furthermore, the correlation coefficients were relatively greater between the maximum NDVI and extreme precipitation intensity than that of the minimum NDVI. Our results support the hypothesis that maximum NDVI is more suited to capture the response of vegetation activity to extreme precipitation events in the MLR-YR region, in comparison to the other two NDVI indices.

Projected changes in extreme precipitation events over Iran in the 21st century based on CMIP5 models

Climate extremes have large impacts on human societies and natural ecosystems. Projection of changes in climate extremes is very important for long-term planning. The current study investigated future changes in extreme precipitation events over Iran based on 18 CMIP5 models for the period 2006-2100. National gridded data from the Asfazari database were used to evaluate climate model simulation. Results indicate that models with higher spatial resolution (CCSM4 and MRI-CGCM3) perform better than those with lower resolution in capturing the spatial features of extreme precipitation events. Bias correction was applied to the models and the projected changes were assessed with the nonparametric modified Mann-Kendal trend test and Sen slope estimator at a 95% confidence level. Annual total precipitation (PRPCTOT) and rainy days (RD) were projected to decrease but the intensity and frequency of precipitation extremes were predicted to increase significantly. The projected decreases were larger in northwestern parts than other regions, with PRPCTOT decreasing by 18 to 22 mm decade-1 and RD by 4 to 4.8 d decade-1. Although there were discrepancies in rates between the models, extreme precipitation events over Iran were generally projected to increase. An increase in consecutive dry days (CDD) was predicted for most regions by the end of the 21st century under RCP8.5, with the largest increase of 5 to 6.8 d decade-1 found for northwestern Iran. In eastern areas of Iran, where precipitation occurs extremely rarely, the number of days with daily precipitation exceeding 10 mm (R10) or even 20 mm (R20) were projected to increase significantly. In conclusion, these changes suggest an increased risk of flash floods in Iran from increased extreme precipitation under the RCP8.5 emission scenario.

Assessment of extreme precipitation through climate change indices in Zacatecas, Mexico

Climate change and extreme climate events identified worldwide at the local, regional, and global scales have significant impact on ecosystems and on society. In this study, spatial and temporal changes in extreme precipitation events in north-central Mexico were investigated using daily precipitation data from 29 meteorological stations over a period of 54 years (1961–2014). The extreme precipitation events are described using ten of the indices established by the Expert Team on Climate Change Detection and Indices (ETCCDI), which characterize daily precipitation in terms of intensity, accumulation, and duration. The indices were calculated yearly and seasonally. The annual and seasonal trends of the indices were estimated with the Theil-Sen method, and its statistical significance was tested with the Mann-Kendall test (MK). The regional average indices of annual total precipitation from wet days (PRCPTOT), simple daily intensity (SDII), number of heavy precipitation days (R10), number of very heavy precipitation days (R20), and consecutive wet days (CWD) had downward trends, but only the last was statistically significant. The regional average of the indices of maximum 1-day precipitation (RX1day), maximum 5-day precipitation (RX5day), number of very wet days (R95p), number of extremely wet days (R99p), and number of consecutive dry days (CDD) showed upward trends, all statistically non-significant. The annual regional average PRCPTOT has decreased at a rate of − 6.20 mm/decade. The decrease was concentrated mainly in central and southern Zacatecas and is associated mainly with the decrease in autumn and summer precipitation. The annual regional average CDD index had increasing trends; 58.6% were statistically significant and concentrated mainly in central and southern Zacatecas. In terms of the general behavior of the PRCPTOT, RX1day, RX5day, R95p, R99p, CDD, and CWD indices, we observed that the precipitation events are decreasing but are becoming slightly more intense. The results will contribute to a better administration of water resources in the state of Zacatecas, Mexico, under the influence of climate change.

Spatial and Temporal Variations in Extreme Precipitation and Temperature Events in the Beijing–Tianjin–Hebei Region of China over the Past Six Decades

Extreme weather events can cause a lot of damage in highly populated regions, such as in the Beijing–Tianjin–Hebei Region (BTHR) in northern China. To understand where and how extreme precipitation and temperature events are changing within the BTHR, data for 1959–2018 from 25 mereological stations were used to detect trends in the intensity, frequency, and duration of these events. The results showed that intensity, accumulated amount, the duration of extreme precipitation events, and the annual number of days with precipitation greater than 50 mm decreased on a regional scale over this 60-year period. Changes in extreme precipitation events at most stations were not statistically significant, although a few stations had a significant downward trend. The combined effects of the East Asian summer monsoon and rapid urbanization are possible reasons for these trends. Both the annual maximum and minimum temperature increased on a regional and local scale. The frequency of extreme hot and cold weather also, respectively, increased and decreased, with consistent patterns on a regional and local scale. However, the spatial changes of these trends were different, reflecting the effects of irrigation and urbanization on the regional surface energy balance. These findings are valuable to decisionmakers involved in disaster prevention in the BTHR and in other highly populated regions worldwide.

Projected changes in extreme precipitation events over China in the 21st century using PRECIS

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 79:91-107 (2019) - DOI: https://doi.org/10.3354/cr01576 Projected changes in extreme precipitation events over China in the 21st century using PRECIS Yujing Zhang1, Liang Fu2, Chunchun Meng3, Lei Zhang3, Yinlong Xu3,* 1Hangzhou Meteorological Bureau, Hangzhou 310051, PR China 2Zhejiang Meteorological Observatory, Hangzhou 310018, PR China 3Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, PR China *Corresponding author: xuyinlong@caas.cn ABSTRACT: This study evaluates possible spatial and temporal changes in precipitation extremes over China under Representative Concentration Pathway (RCP) scenarios using the regional climate model system ‘Provide Regional Climates for Impacts Studies’ (PRECIS), driven with HadGEM2-ES. The extreme precipitation indices applied are consecutive dry days (CDDs), simple daily precipitation intensity index (SDII), maximum consecutive 5 d precipitation (RX5D) and total precipitation amount on extremely wet days (R95P). PRECIS can satisfactorily reproduce the spatial distribution of extreme precipitation indices compared to the observed data. By the end of the 21st century, CDD and SDII are projected to increase under all RCP scenarios in southern China, and R95P and RX5D are projected to increase under RCP4.5 and RCP8.5 scenarios, which indicates the possible increasing risks of prolonged dry spells and heightened floods in these regions. In northern China, CDDs are expected to decrease, while other indices are expected to increase in the future, implying a decrease in the risk of prolonged drought periods and an increase in flood risk; this pattern is most prominent over northwestern China. For the temporal evolution of the extreme precipitation indices, the change rates are most significant under the RCP8.5 scenario. Compared to present-day levels, from low to high emission scenarios, CDDs would decrease by ~1-10%, SDII would increase by ~6-14%, R95P would increase by ~9-21%, and RX5D would increase by ~6-26%, respectively, suggesting that dry extremes would be alleviated, while wet extremes would become more pronounced in general over China toward the end of the 21st century. KEY WORDS: Extreme precipitation events · China · Representative Concentration Pathway · Climate change · PRECIS Full text in pdf format Correction NextCite this article as: Zhang Y, Fu L, Meng C, Zhang L, Xu Y (2019) Projected changes in extreme precipitation events over China in the 21st century using PRECIS. Clim Res 79:91-107. https://doi.org/10.3354/cr01576 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 79, No. 2. Online publication date: November 14, 2019 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2019 Inter-Research.

Projected changes in extreme precipitation events over various subdivisions of India using RegCM4

Present study attempts to project extreme precipitation indices over 34 different meteorological subdivisions and six homogeneous regions such as Northwest, Central Northeast, Northeast, West Central, Peninsular India and Hilly Region during summer monsoon season in the twenty-first century. For this purpose, the Regional Climate Model version4 (RegCM4) had been run at 50 km horizontal resolution forced with the global model GFDL-ESM2 M, during reference period 1976–2005 for the model validation, and the mid- (2031–2060) and far-future (2070–2099) for projections under RCP8.5 scenario over the South Asia CORDEX domain. In this paper, model simulated precipitation has been validated against IMD, APHRODITE and NCEP/NCAR data sets. The results indicate that RegCM4 captures the important features of seasonal precipitation and various extreme indices over the study area. The RegCM4 has projected an increase in the mean seasonal precipitation by 0.56 mm/day whereas in case of GFDL model the rate is 0.39 mm/day during the far-future relative to the reference period. The heavy precipitation indices are projected to increase more frequently (0.264/decade) than the mean precipitation rate (0.01/decade) over India. The correlations between the extreme precipitation indices and the seasonal mean precipitation are found to be strong. In addition, the consecutive dry days are projected to occur more frequently (3–5 days) over West Central (Telangana, Vidarbha and Marathwada) and west Rajasthan while consecutive wet days are projected to decrease over larger parts of India during far-future. Similarly, 1 day maximum precipitation and the simple daily intensity index are projected to increase consistently from mid- to far- futures over some sub-divisions of West coast, Hilly and Northeast regions. From a spatial probability perspective, model projection indicates more frequent severe drought and flood conditions over India.

Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed

Changes in extreme precipitation events may require revisions of civil engineering standards to prevent water infrastructures from performing below the designated guidelines. Climate change may invalidate the intensity-duration-frequency (IDF) computation that is based on the assumption of data stationarity. Efforts in evaluating non-stationarity in the annual maxima series are inadequate, mostly due to the lack of long data records and convenient methods for detecting trends in the higher moments. In this study, using downscaled high resolution climate simulations of the historical and future periods under different carbon emission scenarios, we tested two solutions to obtain reliable IDFs under non-stationarity: (1) identify quasi-stationary time windows from the time series of interest to compute the IDF curves using data for the corresponding time windows; (2) introduce a parameter representing the trend in the means of the extreme value distributions. Focusing on a mountainous site, the Walker Watershed, the spatial heterogeneity and variability of IDFs or extremes are evaluated, particularly in terms of the terrain and elevation impacts. We compared observations-based IDFs that use the stationarity assumption with the two approaches that consider non-stationarity. The IDFs directly estimated based on the traditional stationarity assumption may underestimate the 100-year 24-h events by 10% to 60% towards the end of the century at most grids, resulting in significant under-designing of the engineering infrastructure at the study site. Strong spatial heterogeneity and variability in the IDF estimates suggest a preference for using high resolution simulation data for the reliable estimation of exceedance probability over data from sparsely distributed weather stations. Discrepancies among the three IDFs analyses due to non-stationarity are comparable to the spatial variability of the IDFs, underscoring a need to use an ensemble of non-stationary approaches to achieve unbiased and comprehensive IDF estimates.