Projection of precipitation extremes over South Asia from CMIP6 GCMs

Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.

Changes of Frequency of Summer Precipitation Extremes over the Yangtze River in Association with Large-scale Oceanic-atmospheric Conditions

Changes of the frequency of precipitation extremes （the number of days with daily precipitation exceeding the 90th percentile of a daily climatology,referred to as R90N） in summer （June-August） over the mid-lower reaches of the Yangtze River are analyzed based on daily observations during 1961-2007.The first singular value decomposition （SVD） mode of R90N is linked to an ENSO-like mode of the sea surface temperature anomalies （SSTA） in the previous winter.Responses of different grades of precipitation events to the climatic mode are compared.It is notable that the frequency of summer precipitation extremes is significantly related with the SSTA in the Pacific,while those of light and moderate precipitation are not.It is suggested that the previously well-recognized impact of ENSO on summer rainfall along the Yangtze River is essentially due to a response in summer precipitation extremes in the region,in association with the East Asia-Pacific （EAP） teleconnection pattern.A negative relationship is found between the East Asian Summer Monsoon （EASM） and precipitation extremes over the mid-lower reaches of the Yangtze River.In contrast,light rainfall processes are independent from the SST and EASM variations.

Future changes in precipitation extremes over China using the NEX-GDDP high-resolution daily downscaled data-set

Recently, a new high-resolution daily downscaled data-set derived from 21 CMIP5 model simulations has been released by NASA, called ＇NASA Earth Exchange Global Daily Downscaled Projections＇ （NEX-GDDP）. In this study, the performance of this data-set in simulating precipitation extremes and long-term climate changes across China are evaluated and compared with CMIP5 GCMs. The results indicate that NEX-GDDP can successfully reproduce the spatial patterns of precipitation extremes over China, showing results that are much closer to observations than the GCMs, with increased Pearson correlation coefficients and decreased model relative error for most models. Furthermore, NEX-GDDP shows that precipitation extremes are projected to occur more frequently, with increased intensity, across China in the future. Especially at regional to local scales, more information for the projection of future changes in precipitation extremes can be obtained from this high-resolution data-set. Most importantly, the uncertainties of these projections at the regional scale present significant decreases compared with the GCMs, making the projections by NEX-GDDP much more reliable. Therefore, the authors believe that this high-resolution data-set will be popular and widely used in the future, particularly for climate change impact studies in areas where a finer scale is required.

Assessment of model performance of precipitation extremes over the mid-high latitude areas of Northern Hemisphere:from CMIP5 to CMIP6

This study explores the model performance of the Coupled Model Intercomparison Project Phase 6(CMIP6)in simulating precipitation extremes over the mid–high latitudes of Asia,as compared with predecessor models in the previous phase,CMIP5.Results show that the multimodel ensemble median generally outperforms the individual models in simulating the climate means of precipitation extremes.The CMIP6 models possess a relatively higher capability in this respect than the CMIP5 models.However,discrepancies also exist between models and observation,insofar as most of the simulated indices are positively biased to varying degrees.With respect to the temporal performance of indices,the majority are overestimated at most time points,along with large uncertainty.Therefore,the capacity to simulate the interannual variability needs to be further improved.Furthermore,pairwise and multimodel ensemble comparisons were performed for 12 models to evaluate the performance of individual models,revealing that most of the new-version models are better than their predecessors,albeit with some variance in the metrics amongst models and indices.

Recent Changes in Precipitation Extremes in the Heihe River Basin,Northwest China

Changes in rainfall extremes pose a serious and additional threat to water resources planning and management, natural and artificial oasis stability, and sustainable development in the fragile ecosystems of arid inland river basins. In this study, the trend and temporal variation of extreme precipitation are analyzed using daily precipitation datasets at 11 stations over the arid inland Heihe River basin in Northwest China from 1960 to 2011. Eight indices of extreme precipitation are studied. The results show statistically significant and large-magnitude increasing and decreasing trends for most indices, primarily in the Qilian Mountains and eastern Hexi Corridor. More frequent and intense rainfall extremes have occurred in the southern part of the desert area than in the northern portion. In general, the temporal variation in precipitation extremes has changed throughout the basin. Wet day precipitation and heavy precipitation days show statistically significant linear increasing trends and step changes in the Qilian Mountains and Hexi Corridor. Consecutive dry days have decreased obviously in the region in most years after approximately the late 1980s, but meanwhile very long dry spells have increased, especially in the Hexi Corridor. The probability density function indicates that very long wet spells have increased in the Qilian Mountains. The East Asian summer monsoon index and western Pacific subtropical high intensity index possess strong and significant negative and positive correlations with rainfall extremes, respectively. Changes in land surface characteristics and the increase in water vapor in the wet season have also contributed to the changes in precipitation extremes over the river basin.

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).

Spatial-temporal Analysis and Prediction of Precipitation Extremes: A Case Study in the Weihe River Basin, China

Extreme precipitation events bring considerable risks to the natural ecosystem and human life.Investigating the spatial-temporal characteristics of extreme precipitation and predicting it quantitatively are critical for the flood prevention and water resources planning and management.In this study,daily precipitation data(1957–2019)were collected from 24 meteorological stations in the Weihe River Basin(WRB),Northwest China and its surrounding areas.We first analyzed the spatial-temporal change of precipitation extremes in the WRB based on space-time cube(STC),and then predicted precipitation extremes using long short-term memory(LSTM)network,auto-regressive integrated moving average(ARIMA),and hybrid ensemble empirical mode decomposition(EEMD)-LSTM-ARIMA models.The precipitation extremes increased as the spatial variation from northwest to southeast of the WRB.There were two clusters for each extreme precipitation index,which were distributed in the northwestern and southeastern or northern and southern of the WRB.The precipitation extremes in the WRB present a strong clustering pattern.Spatially,the pattern of only high-high cluster and only low-low cluster were primarily located in lower reaches and upper reaches of the WRB,respectively.Hot spots(25.00%–50.00%)were more than cold spots(4.17%–25.00%)in the WRB.Cold spots were mainly concentrated in the northwestern part,while hot spots were mostly located in the eastern and southern parts.For different extreme precipitation indices,the performances of the different models were different.The accuracy ranking was EEMD-LSTM-ARIMA>LSTM>ARIMA in predicting simple daily intensity index(SDII)and consecutive wet days(CWD),while the accuracy ranking was LSTM>EEMD-LSTM-ARIMA>ARIMA in predicting very wet days(R95 P).The hybrid EEMD-LSTM-ARIMA model proposed was generally superior to single models in the prediction of precipitation extremes.

Increased population exposure to precipitation extremes in China under global warming scenarios

Precipitation extremes are among the most dangerous climate-related hazards over China, and they are expected to significantly increase in the future in both frequency and intensity. Exposure to precipitation extremes and changes therein are determined by extreme events and the corresponding population changes. Here, the authors analyze the changing population exposure across China in the future using ensembles of high-resolution simulations with Reg CM4 and population scenarios. The authors find that aggregate exposure over China increases by nearly 21.6% under the RCP4.5-SSP2 scenario by the end of this century, although populations are projected to decrease. East China will experience the largest absolute increase in exposure from 424 million person-events to 546 million person-events, while the Tibetan Plateau region will experience the largest relative increase of nearly 44.4%. This increase in exposure mainly results from the climate effect contribution. Further assessments indicate that the exposure increase over China does not rely on the greenhouse gas emissions and population growth scenarios, but the higher emissions scenario generally leads to higher exposure regardless of population growth, highlighting the efficacy of mitigation efforts in reducing exposure to precipitation extremes.

A Two-plume Convective Model for Precipitation Extremes

In the study of diagnosing climate simulations and understanding the dynamics of precipitation extremes,it is an essential step to adopt a simple model to relate water vapor condensation and precipitation,which occur at cloudmicrophysical and convective scales,to large-scale variables.Several simple models have been proposed;however,improvement is still needed in both their accuracy and/or the physical basis.Here,we propose a two-plume convective model that takes into account the subgrid inhomogeneity of precipitation extremes.The convective model has three components,i.e.,cloud condensation,rain evaporation,and environmental descent,and is built upon the zero-buoyancy approximation and guidance from the high-resolution reanalysis.Evaluated against the CMIP5 climate simulations,the convective model shows large improvements in reproducing precipitation extremes compared to previously proposed models.Thus,the two-plume convective model better captures the main physical processes and serves as a useful diagnostic tool for precipitation extremes.

Exploring changes of precipitation extremes under climate change through global variable-resolution modeling

Understanding the responses of precipitation extremes to global climate change remains limited owing to their poor representations in models and complicated interactions with multi-scale systems.Here we take the record-breaking precipitation over China in 2021 as an example,and study its changes under three different climate scenarios through a developed pseudo-global-warming(PGW)experimental framework with 60-3 km variable-resolution global ensemble modeling.Compared to the present climate,the precipitation extreme under a warmer(cooler)climate increased(decreased)in intensity,coverage,and total amount at a range of 24.3%-37.8%(18.7%-56.1%).With the help of the proposed PGW experimental framework,we further reveal the impacts of the multi-scale system interactions in climate change on the precipitation extreme.Under the warmer climate,large-scale water vapor transport converged from double typhoons and the subtropical high marched into central China,enhancing the convective energy and instability on the leading edge of the transport belt.As a result,the mesoscale convective system(Mcs)that directly contributed to the precipitation extreme became stronger than that in the present climate.On the contrary,the cooler climate displayed opposite changing characteristics relative to the warmer climate,ranging from the large-scale systems to local environments and to the Mcs.In summary,our study provides a promising approach to scientifically assess the response of precipitation extremes to climate change,making it feasible to perform ensemble simulations while investigating the multi-scale system interactions over the globe.

Thermodynamic driving mechanisms for the formation of global precipitation extremes and ecohydrological effects

Global warming has altered the thermodynamic and dynamic environments of climate systems,affecting the biogeochemical processes between the geosphere and atmosphere,which has significant impacts on precipitation extremes and the terrestrial carbon budget of ecosystems.Existing studies have reported a hook structure for precipitation extreme-temperature relationships but have rarely examined the underlying physical mechanisms.Previous studies have also failed to quantify the impact of precipitation on ecosystem productivity,hindering the assessment of future extreme climatic hazards and potential ecosystem risks.To reveal the thermodynamic driving mechanisms for the formation of global precipitation extremes and ecohydrological effects,this study utilizes over ten multisource datasets(i.e.,satellite,reanalysis,climate model,land surface model,machine learning reconstruction,and flux tower measurements).We first assess the response of water-heat-carbon flux to precipitation extremes and explain the underlying physical mechanisms behind the hook structures in terms of atmospheric thermodynamics and dynamics.Based on outputs from five global climate models(GCMs)under ISIMIP3b,we project future changes in the hook structures as well as their impacts on precipitation extremes.Finally,we discuss the impact of precipitation on the terrestrial carbon budget by using outputs from the CLM4.5 model.The results show that precipitation extremes are usually accompanied by strong exchanges of water and heat and demonstrate a nonlinear relationship between precipitation and ecosystem productivity.The intensity(duration)of extreme precipitation is intensifying(decreasing)over most areas of the globe,whereas three-dimensional precipitation events are becoming more concentrated.Atmospheric dynamics play a key role in shaping the hook structure.The structure is not stable;it shifts under climate change and is projected to result in a 10–40%intensification in precipitation by the end of this century.Moderate levels of precipitation contribute to carbon assimilation in ecosystems,and the response of the carbon budget to precipitation is relatively stable under climate change.

Evaluation of IMERG, TMPA, ERA5, and CPC precipitation products over China's Mainland: Spatiotemporal patterns and extremes

A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA)),reanalysis-based(fifth generation of atmospheric reanalysis by the European Centre for Medium Range Weather Forecasts(ERA5)),and gauge-estimated(Climate Prediction Center(CPC))precipitation products was conducted using the data from 807 meteorological stations across China's Mainland from 2001 to 2017.Error statistical metrics,precipitation distribution functions,and extreme precipitation indices were used to evaluate the quality of the four precipitation products in terms of multi-timescale accuracy and extreme precipitation estimation.When the timescale increased from daily to seasonal scales,the accuracy of the four precipitation products first increased and then decreased,and all products performed best on the monthly timescale.Their accuracy ranking in descending order was CPC,IMERG,TMPA,and ERA5 on the daily timescale and IMERG,CPC,TMPA,and ERA5 on the monthly and seasonal timescales.IMERG was generally superior to its predecessor TMPA on the three timescales.ERA5 exhibited large statistical errors.CPC provided stable estimated values.For extreme precipitation estimation,the quality of IMERG was relatively consistent with that of TMPA in terms of precipitation distribution and extreme metrics,and IMERG exhibited a significant advantage in estimating moderate and heavy precipitation.In contrast,ERA5 and CPC exhibited poor performance with large systematic underestimation biases.The findings of this study provide insight into the performance of the latest IMERG product compared with the widely used TMPA,ERA5,and CPC datasets,and points to possible directions for improvement of multi-source precipitation data fusion algorithms in order to better serve hydrological applications.

Evaluation of precipitation extremes over the Tibetan plateau using the NASA global daily downscaled datasets NEX-GDDP-CMIP6

The utility of statistically downscaled data is in its provision of detailed,high-resolution insights,surpassing global models,which is essential for precise assessments of climate impact.This study delves into the changes in extreme precipitation across the Tibetan Plateau(TP)and its five subregions,thereby deepening our understanding of climate impacts in the region.Employing NASA Earth Exchange Global Daily Downscaled Climate Projections(NEX-GDDP-CMIP6),which are bias-corrected and statistically downscaled,in conjunction with three gauge-based datasets(CN05.1,CMFD,GMFD)spanning from 1979 to 2014,this study conducts an extensive analysis using eight extreme precipitation indices in the TP.The findings reveal significant spatial disparities in extreme precipitation,with the southern subregion experiencing a sig-nificant increase while the two northern subregions show statistically insignificant changes.NEX-GDDP-CMIP6 performs best in the eastern subregion but fails to capture extreme precipitation characteristics in the southern and western subregions.Averaging over the whole period of 1979-2014(climatology),the NEX-GDDP-CMIP6 dataset performs better on the intensity and persistence indices than on the absolute and relative threshold indices.NEX-GDDP-CMIP6's performance on climate trends is significantly below that of climatology.The NEX-GDDP-CMIP6 dataset has limitations over the TP because of its reliance on the underperforming GMFD reference data.This study provides a comprehensive understanding of the variability of extreme precipitation and disparities among different subregions of the TP,laying a robust scientific groundwork for climate impact studies and future projection in this region.

Atlas of precipitation extremes for South America and Africa based on depth-duration-frequency relationships in a stochastic weather generator dataset

Information about extreme rainfall is lacking in regions of South America and Africa.This study attempts to fill this scientific gap by use of a gridded parameterization for the stochastic weather generator,CLIGEN,to map depth-duration-frequency(DDF)relationships.Analysis of 500-year point-scale precipitation time series generated at each grid point allowed maps of return period precipitation to be produced for a se-lection of sixteen durations ranging from 10-min to 1-year and for nine return periods from 2 to 500 years.The generalized extreme value(GEV)probability distribution was fitted for all durations,and given GEV quantiles,an interpolation method was applied to produce maps at 0.1° resolution that better resolve small-scale spatial climate gradients.In addition to uncertainties related to GEV fitting,this study quantifies prediction intervals based on ground validation.This validation was important for identifying biases in CLIGEN,although uncertainties were not always satisfactorily defined due to sampling design and other factors.For daily/multi-day durations,100 stations with daily observations and ≥50-year records were selected for validation against the 0.1° CLIGEN map series,resulting in a median and average absolute error of 13%and 16%,respectively.For sub-daily durations,prediction errors were larger overall.An analogy using available U.S.data established the degree of bias in CUGEN for sub-daily durations,and three records in Brazil with high temporal resolutions were used to confirm that applied bias adjustments resulted in error ranges similar to the daily/multi-day cases.This atlas is freely available for study of extreme precipitation.

2023: Weather and Climate Extremes Hitting the Globe with Emerging Features

Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 years.As in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the world.Here,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate change.We also highlight emerging features associated with some of these extreme events.Hot extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the Northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the North China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood conditions.Climate extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.

Increased population exposures to extreme precipitation in Central Asia under 1.5℃and 2℃global warming scenarios

The increase in extreme precipitation(EP)may pose a serious threat to the health and safety of population in arid and semi-arid regions.The current research on the impact of EP on population in Central Asia(CA)is insufficient and there is an urgent need for a comprehensive assessment.Hence,we opted for precipitation and temperature data under two Shared Socioeconomic Pathways(SSP2-4.5 and SSP5-8.5)from ten Global Climate Models(GCMs),which were obtained from the NASA Earth Exchange Global Daily Downscaled Projections(NEX-GDDP-CMIP6).By integrating population data in 2020 and 2050(SSP2 and SSP5),we investigated the future changes in EP and population exposure in CA under 1.5℃and 2℃global warming scenarios(GWSs).Our analysis indicates that EP in CA is projected to increase with global warming.Under the SSP5-8.5,the maximum daily precipitation(Rx1day)exhibits an average response rate to global warming of 3.58%/K(1.99-4.06%/K).With rising temperatures,an increasing number of areas and populations in CA will be impacted by EP,especially in the Fergana valley.Approximately 25%of the population(land area)in CA is exposed to Rx1day with increases of more than 8.31%(9.32%)under 1.5℃GWS and 14.18%(13.25%)under 2℃GWS.Controlling temperature rise can be effective in reducing population exposures to EP.For instance,limiting the temperature increase to 1.5℃instead of 2℃results in a 2.79%(1.75%-4.59%)reduction in population exposure to Rx1day.Finally,we found that climate change serves as the predominant factor influencing the population exposure to EP,while the role of population redistribution,although relatively minor,should not be disregarded.Particularly for prolonged drought,the role of population redistribution manifests negatively.

Analysis on characteristics of extreme precipitation indices and atmospheric circulation in Northern Shanxi

This article utilizes daily precipitation data from 28 national meteorological stations in northern Shanxi Province spanning from 1972 to 2020,and the US NCEP/NCAR monthly average reanalysis and ERA5 monthly average reanalysis data.The study employs techniques such as empirical orthogonal function(EOF)decomposition,MannKendall mutation and other methods to investigate the spatiotemporal distribution of extreme precipitation index in northern Shanxi and their correlation with atmospheric circulation.The research results show that:the absolute index,relative index,intensity index and sustained dry period index(CDD)in the continuous index appear from southwest to northeast.The spatial distribution characteristics of the central region decrease,while the continuous wet period(CWD)decreases from the central to the east and west.The three indices Rx1day,Rx5day,and CWD mutated in 1978,1975,and 1983 respectively,and other extreme precipitation indices all appeared in a sudden change from a low-value period to a high-value period occurred around 2010.In the high-value years of the summer extreme precipitation index,there is a significant negative anomaly in the height field in the mid-high latitude regions of Eurasia.Northern Shanxi is controlled by a broad low-pressure trough in the Lake Baikal area.Water vapor transported via the east,west,and south routes converges in the northern Shanxi region and encounters cold air from the north.There is a strong upward motion anomaly at 500 hPa in the troposphere,and the dynamic conditions of upper-level divergence and lower-level convergence lead to more summer extreme precipitation in the northern Shanxi region.Conversely,in the low-value years of the summer extreme precipitation index,northern Shanxi is affected by a strong high-pressure ridge north of Lake Baikal.There is a downward motion anomaly at 500 hPa,and the northern Shanxi region lacks water vapor.The cold and warm air cannot converge,and both the water vapor conditions and dynamic conditions are poor,which is not conducive to the production of extreme precipitation in northern Shanxi.

Statistical Modelling of Extreme Precipitation Indices Supporting Urban Spatial Planning Processes

In this paper,we analyze how statistical modelling of extreme precipitation indices can support urban planners in the analysis and classification of the level of climate sensitivity of the territory and in the subsequent definition of sustainable adaptive planning and design choices.These activities are part of a research project that addresses the issue of climate change from the urban planning perspective to identify solutions to current and future environmental challenges,increasing the climate resilience of infrastructures and communities in urban,rural and coastal areas.These research activities are based on the desire to promote integration between the approaches commonly adopted by urban planners and climate specialists to plan adequate joint risk reduction strategies.As part of this study,the focus will be on the risks produced by the greater frequency and intensity of floods,assessed by the IPCC(Intergovernmental Panel on Climate Change)as one of the key risks for Europe.Specifically,our attention focuses on pluvial flooding,proposing the definition of a statistical modelling of indices related to extreme precipitation and its application to the context of the Calabria Region,in Italy.The indices are recommended by the ETCCDI(Expert Team on Climate Change Detection and Indices)and elaborated starting from official historical data recorded by 146 telemetry active rain gauges,disseminated in the experimentation context.

Spatial Variation and Trend of Extreme Precipitation in Africa during 1981-2019 and Its Projected Changes at the End of 21st Century

This study comprehensively examines the patterns and regional variation of severe rainfall across the African continent, employing a suite of eight extreme precipitation indices. The analysis extends to the assessment of projected changes in precipitation extremes using five General Circulation Models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathways (SSPs) scenarios at the long-term period (2081-2100) of the 21st century. Furthermore, the study investigates potential mechanisms influencing precipitation extremes by correlating extreme precipitation indices with oceanic system indices, specifically Ni?o 3.4 for El Ni?o-Southern Oscillation (ENSO) and Dipole Mode Index (DMI) for the Indian Ocean Dipole (IOD). The findings revealed distinct spatial distributions in mean trends of extreme precipitation indices, indicating a tendency toward decreased extreme precipitation in North Africa, Sahel region, Central Africa and the Western part of South Africa. Conversely, West Africa, East Africa and the Eastern part of South Africa exhibit an inclination toward increased extreme precipitation. The changes in precipitation extreme indices indicate a general rise in both the severity and occurrence of extreme precipitation events under all scenarios by the end of the 21st century. Notably, our analysis projects a decrease in consecutive wet days (CWD) in the far-future. Additionally, correlation analysis highlights significant correlation between above or below threshold rainfall fluctuation in East Africa and South Africa with oceanic systems, particularly ENSO and the IOD. Central Africa abnormal precipitation variability is also linked to ENSO with a significant negative correlation. These insights contribute valuable information for understanding and projecting the dynamics of precipitation extreme in Africa, providing a foundation for climate adaptation and mitigation efforts in the region.

Changes of Precipitation and Extremes and the Possible Effect of Urbanization in the Beijing Metropolitan Region during 1960–2012 Based on Homogenized Observations

Daily precipitation series at 15 stations in the Beijing metropolitan region（BMR） during 1960–2012 were homogenized using the multiple analysis of series for homogenization method,with additional adjustments based on analysis of empirical cumulative density function（ECDF） regarding climate extremes.The cumulative density functions of daily precipitation series,the trends of annual and seasonal precipitation,and summer extreme events during 1960–2012 in the original and final adjusted series at Beijing station were comparatively analyzed to show the necessity and efficiency of the new method.Results indicate that the ECDF adjustments can improve the homogeneity of high-order moments of daily series and the estimation of climate trends in extremes.The linear trends of the regional-mean annual and seasonal（spring,summer,autumn,and winter）precipitation series are-10.16,4.97,-20.04,5.02,and-0.11 mm（10 yr）-1,respectively.The trends over the BMR increase consistently for spring/autumn and decrease for the whole year/summer; however,the trends for winter decrease in southern parts and increase in northern parts.Urbanization affects local trends of precipitation amount,frequency,and intensity and their geographical patterns.For the urban-influenced sites,urbanization tends to slow down the magnitude of decrease in the precipitation and extreme amount series by approximately-10.4% and-6.0%,respectively; enhance the magnitude of decrease in precipitation frequency series by approximately 5.7%; reduce that of extremes by approximately-8.9%; and promote the decreasing trends in the summer intensity series of both precipitation and extremes by approximately 6.8% and51.5%,respectively.