Extreme Rainfall Indices Research Articles

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen’s slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies.

A new assessment in total and extreme rainfall trends over central and southern Peruvian Andes during 1965–2010

ABSTRACTUnderstanding the spatio‐temporal variability of rainfall over mountainous regions such as the Andes is crucial for the maintenance of water resources and ecosystems. This study provided a comprehensive analysis of the signal, statistical significance and spatial pattern of rainfall trends in central and southern Peruvian Andes (CSPA) from 1965 to 2010. Rainfall from 47 quality‐controlled rain gauge stations was examined using the hydrologic calendar year. Total and extreme rainfall indices proposed by the Expert Team on Climate Change Detection and Indices (ETCCDI) were calculated and trends were examined with Mann–Kendall test and Sen's slope estimator. Significant regional patterns of changes in rainfall extremes were investigated and compared with previous studies. Four major regions of stations were identified based on principal component analysis and clustering techniques: Amazon, central Pacific, southern Pacific and Titicaca basins. Statistically significant trend patterns showed that the annual total rainfall has decreased in the Amazon basin, despite the increase in the number of rainy days and some extreme rainfall indices. Decrease in 1‐day and 5‐day yearly maximum rainfall was observed in central Pacific, along with an increase in the number of wet days. Positive trends in indices related to the intensity of very strong daily rainfall were detected in southern Pacific. Titicaca basin showed an increase in the intensity of rainfall extremes. Rainfall variability and trends were evaluated during contrasting El Niño‐Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Most stations in the CSPA exhibited positive (negative) anomaly of total and extreme rainfall indices (consecutive dry days) during La Niña (El Niño) years. Positive (negative) anomalies of annual total rainfall and consecutive dry days during positive (negative) PDO occurred in the Amazon, southern Pacific and Titicaca basins, respectively. The ENSO–PDO conditions may have influenced the complex and mostly non‐statistically significant long‐term trends in CSPA.

Trend Analysis of Some Indices of Extreme Rainfall Events

Climate change events results in increased temperature, changing rainfall patterns, floods and droughts. These will not only affect human but also affect how environment responds to the events. In this study, analyses of the trend change of 10 indices of Extreme Rainfall Events were carried in three stations of middle belt of Nigeria namely Jos, Lokoja and Makurdi using the RclimDex software. Daily rainfall data for the 3 stations were collected for the period of 1971 to 2005. The results from analyses of trend change of extreme rainfall indices depicted a sequence of alternating decrease and increase trends in the variables with a varying value due to population and size distribution for the study period. This inevitable climate effect needs to be adapted in order to make life and environment worthwhile.

Spatiotemporal trends in extreme rainfall and temperature indices over Upper Tapi Basin, India

The flood risk across the globe is intensified due to global warming and subsequent increase in extreme temperature and precipitation. The long-term trends in extreme rainfall (1944–2013) and temperature (1969–2012) indices have been investigated at annual, seasonal, and monthly time scales using nonparametric Mann-Kendall (MK), modified Mann-Kendall (MMK), and Sen’s slope estimator tests. The extreme rainfall and temperature indices, recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI), have been analyzed at finer spatial scales for trend detection. The results of trend analyses indicate decreasing trend in annual total rainfall, significant decreasing trend in rainy days, and increasing trend in rainfall intensity over the basin. The seasonal rainfall has been found to decrease for all the seasons except postmonsoon, which could affect the rain-fed agriculture in the basin. The 1- and 5-day annual maximum rainfalls exhibit mixed trends, wherein part of the basin experiences increasing trend, while other parts experience a decreasing trend. The increase in dry spells and concurrent decrease in wet spells are also observed over the basin. The extreme temperature indices revealed increasing trends in hottest and coldest days, while decreasing trends in coldest night are found over most parts of the basin. Further, the diurnal temperature range is also found to increase due to warming tendency in maximum temperature (T max) at a faster rate compared to the minimum temperature (T min). The increase in frequency and magnitude of extreme rainfall in the basin has been attributed to the increasing trend in maximum and minimum temperatures, reducing forest cover, rapid pace of urbanization, increase in human population, and thereby increase in the aerosol content in the atmosphere. The findings of the present study would significantly help in sustainable water resource planning, better decision-making for policy framework, and setting up infrastructure against flood disasters in Upper Tapi Basin, India.

A study on summer monsoon season and rainfall characteristics in summer monsoon season over Southern Vietnam in 1981-2014 period

This study determines the summer monsoon season over Southern Vietnam in 1981-2014 period by using observed daily rain-gauge data and reanalyzed daily 850 hPa wind data. The results show that the mean onset and retreat dates of summer monsoon over Southern Vietnam occur on May 15 and October 13, with standard deviations of 14.12 and 13.55 days, respectively. The results also show that the onset and retreat dates tend to precede in the recent years. In summer monsoon period, the values of RX1day and RX5day are high in Rach Gia and Ca Mau but low in Can Tho, CDD of all stations are low. In all stations, the values of extreme rainfall indices in 1998-2014 period are higher compared to those in 1981-1997 period.

Assessing climatic trends of extreme rainfall indices over northeast Bangladesh

This study analyzes the trends of extreme rainfall indices over northeast Bangladesh for the period of 1984 to 2016 for the pre-monsoon and monsoon seasons. The research was framed as part of a project co-producing knowledge of climate variability and impacts through collaboration between scientific and local communities in northeast Bangladesh, which found pre-monsoon and monsoon rainfall to be most important. With access to a greater number of rainfall stations than previous work in northeast Bangladesh, we investigated trends in extreme rainfall events using the Mann–Kendall trend test and Sen’s slope estimator. To appraise the quality of the data, we used the Standard Normal Homogeneity and the Pettitt tests to check its homogeneity. Among the seven stations, only Sunamganj was found inhomogeneous, and was not considered for trend analysis. All indices of rainfall extremes showed a decreasing trend in both seasons, with the most significant decrease during the monsoon. Importantly, we saw a decreasing trend in the seasonal total rainfall and consecutive wet days, whereas there was an increasing trend in consecutive dry days. Moreover, we saw a decreasing trend in 1-day maximum rainfall, 5-day maximum rainfall, the intensity of the daily rainfall over 25 mm during the pre-monsoon and 50 mm during monsoon, which together may indicate a future decrease in the magnitude and intensity of flash floods and monsoon floods. If this trend continues, the northeast Bangladesh may suffer from water stress, which could affect the lives and livelihoods of communities living there.

Decreasing Past and Mid-Century Rainfall Indices over the Ouémé River Basin, Benin (West Africa)

This study analyzed the trends of extreme daily rainfall indices over the Ouémé basin using the observed data from 1950 to 2014 and the projected rainfall of regional climate model REMO (REgional MOdel) for the period 2015–2050. For future trends analysis, two Intergovernmental Panel on Climate Change (IPCC) new scenarios are considered, namely RCP4.5 and RCP8.5. The indices considered are number of heavy rainfall days, number of very heavy rainfall days, consecutive dry days, consecutive wet days, daily maximum rainfall, five-day maximum rainfall, annual wet-day total rainfall, simple daily intensity index, very wet days, and extremely wet days. These indices were calculated at annual and seasonal scales. The Mann-Kendall non-parametric test and the parametric linear regression approach were used for trends detection. As result, significant declining in the number of heavy and very heavy rainfall days, heavy and extremely heavy rainfall, consecutive wet days and annual wet-day rainfall total were detected in most stations for the historical period as well as the future period following the scenario RCP8.5. Furthermore, few stations presented significant trends for the scenario RCP4.5 and the high proportion of stations with the inconsistence trends invites the planners to get ready for an uncertain future climate following this scenario.

THE INTERDEPENDENCE OF CLIMATE AND SOCIOECONOMIC VULNERABILITY IN THE ABC PAULISTA REGION

Abstract This study aimed to analyze the socio-economic, demographic, health and climatic vulnerabilities in the ABC Paulista region that comprises the municipalities of Santo André, São Caetano do Sul, São Bernardo do Campo, Mauá, Diadema, Rio Grande da Serra and Ribeirão Pires. The vulnerabilities were analyzed through the construction of indices based on the aggregation of indicators collected in the IBGE census and climate indices of extreme rainfall. The municipalities of Diadema and Mauá were identified as the most vulnerable areas to heavy rains, presenting an increasing trend of days with moderate and intense rainfall (50 mm and 80 mm). In addition, these municipalities presented higher socio-economic and urban-demographic vulnerabilities, as a consequence of asymmetric social and economic development, poor environmental management and accelerated unplanned urbanization. Therefore, all these issues contributed to enhance the impact of heavy rains.

Evolution Des Indices Pluviométriques Extrêmes Par L'analyse De Modèles Climatiques Régionaux Du Programme CORDEX: Les Projections Climatiques Sur Le Sénégal

This study aims at characterizing the extreme rainfall events over West Africa particularly in the Sahel region and Senegal by 2100 (far future) under the greenhouse gas emission scenario RCP8.5 by analyzing the simulations of four (4) regional climate models (RCMs) of CORDEX (Regional COordinated climate Downscaling Experiment) program. The study of these extreme climate indices is crucial for the understanding of the impacts of climate change on some vital socio-economic sectors such as the agriculture in Sahel and Senegal. The results show that almost all the RCMs predict a decrease of the rainfall over most parts of the Sahel region particularly over the Western Sahel. The analysis of the climate indices such as the highest one day precipitation amount, the 99th percentile and the maximum dry spell length (CDD) shows that the RCMs (except CanRCM4) project an increase of these exceptional rainfall events over the Sahel (especially over the Western Sahel) by 2100. In Senegal, the RCMs (except RCA4) agree on a decrease of the precipitation and the number of wet days by 2100. When considering the evolution of rainfall events intensity, the highest one day precipitation amount and the 99th percentile, the RCMs (except CanRCM4) predict an increase of the extreme events which may translate into strong floods in Senegal. As for the dry and wet sequences, the RCMs projections (except those of RCA4) show an increase (respectively a decrease) of the maximum dry spell length (respectively of the maximum wet spell length) in Senegal. This increase in extreme rainfall indices may translate into a strengthening of natural disasters such as floods and drought. This work can be considered as a support for the policymakers in West Africa and particularly in Senegal for the better long-term planning of water resources and disaster management as wells as the build of a resilient agricultural system.

ANALYSIS OF EXTREME RAINFALL INDICES IN PENINSULAR MALAYSIA

Extreme rainfall events are the main cause of flooding. This study aimed to examine seven extreme rainfall indices, i.e. extreme rain sum (XRS), very wet day intensity (I95), extremely wet day intensity (I99), very wet day proportion (R95), extremely wet day proportion (R99), very wet days (N95) and extremely wet days (N99) using Mann-Kendall (MK) and the normalized statistic Z tests. The analyses are based on the daily rainfall data gathered from Bayan Lepas, Subang, Senai, Kuantan and Kota Bharu. The east coast states received more rainfall than any other parts in Peninsular Malaysia. Kota Bharu station recorded the highest XRS, i.e. 648 mm. The analyses also indicate that the stations in the eastern part of Peninsular Malaysia experienced higher XRS, I95, I99, R95 and R99 as compared to the stations located in the western and northern part of Peninsular Malaysia. Subang and Senai show the highest number of days for wet and very wet (N95) as compared to other stations. Other than that, all stations except for Kota Bharu show increasing trends for most of the extreme rainfall indices. Upward trends indicate that the extreme rainfall events were becoming more severe over the period of 1960 to 2014.

Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041–2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041–2060) compared to the base period (1961–2000).

The 20th century transitions in basic and extreme monsoon rainfall indices in India: Comparison of the ETCCDI indices

The mean and extreme matrices of the monsoon rainfall in India not only play an important role in depicting the global monsoon climate, but also their spatiotemporal patterns influence the socio-economic profile of a major proportion of the country's huge population. Given the reported conflicting trends at the global and national scales, the present study investigates the 20th century (1901–2004) changes in monsoon rainfall of India, particularly focusing the indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) to facilitate a global comparison. Result of this comprehensive analysis, which includes the response of fifteen indices over two study periods (i.e., 1901–1940 and 1961–2004), indicates clear signals of change with respect to the period and region of study and the choice of the ETCCDI indices. While wet day frequency, low-to-moderate events and consecutive wet days (CWD) exhibit a prominent transition from a pre-1940 wetting to a post-1960 drying tendency over a large part of the central-north India (CNI), both the wet and dry extremes have occurred in a spatially less consistent manner during the recent decades. For consecutive dry days (CDD), the reported less clear global signals could be related to the timescale of analysis, as our sub-seasonal scale results display consistent changes compared to that of the seasonal and annual scales. The Palmer Drought Severity Index (PDSI) provides clear indications of a post-1960 non-stationarity, showing changes in the mean as well as variance. Based on the partial Mann–Kendall test (PMK), some of the identified rainfall trends during 1961–2004 are found to be influenced more by the tropical Indian Ocean sea surface temperatures than the El Niño–Southern Oscillation index. These results have important implications for formulating the water resource management strategy, particularly over the drying central and northern parts of the country.

Performance evaluation of RegCM4 in simulating extreme rainfall and temperature indices over the CORDEX‐Southeast Asia region

ABSTRACTIn this study, simulations over Southeast Asia (15°S–40°N, 80°–145°E) at 36 km resolution were conducted for the period 1989–2007 using the Regional Climate Model version 4.3 (RegCM4.3) under the framework of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment – Southeast Asia (or SEACLID/CORDEX‐SEA) project. Forced by the European Centre for Medium‐Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA‐Interim), 18 experiments were carried out using different combinations of cumulus parameterization and ocean flux schemes. Twelve extreme indices for both rainfall and temperature were estimated from the model output. A statistical omega index was used to measure the degree of similarity among the 18 experiments in phase and shape. The results showed relatively high similarities among the experiments over mainland Asia compared to those over the Maritime Continent for both seasonal and inter‐annual variability. The extreme rainfall indices had a lower omega compared to that of temperature. Observed daily rainfall and temperature data at 52 meteorological stations over the SEA region were used to validate the simulated extreme indices. The results showed that extreme temperature indices were generally underestimated across the region. Systematic biases for each simulated rainfall index were also identified. A score ranking system was established to compare the relative performance of the 18 experiments over the 52 selected stations objectively. It was shown that the experiments with the Massachusetts Institute of Technology (MIT)‐Emanuel scheme performed relatively better than the other convective schemes. The combination of the MIT‐Emanuel convective scheme with the Biosphere–Atmosphere Transfer scheme (BATS1e) ocean flux scheme produced the best performance.

Searching for evidence of changes in extreme rainfall indices in the Central Rift Valley of Ethiopia

Extreme rainfall events have serious implications for economic sectors with a close link to climate such as agriculture and food security. This holds true in the Central Rift Valley (CRV) of Ethiopia where communities rely on highly climate-sensitive rainfed subsistence farming for livelihoods. This study investigates changes in ten extreme rainfall indices over a period of 40 years (1970–2009) using 14 meteorological stations located in the CRV. The CRV consists of three landscape units: the valley floor, the escarpments, and the highlands all of which are considered in our data analysis. The Belg (March–May) and Kiremt (June–September) seasons are also considered in the analysis. The Mann-Kendall test was used to detect trends of the rainfall indices. The results indicated that at the annual time scale, more than half (57 %) of the stations showed significant trends in total wet-day precipitation (PRCPTOT) and heavy precipitation days (R10mm). Only 7–35 % of stations showed significant trends, for the other rainfall indices. Spatially, the valley floor received increasing annual rainfall while the escarpments and the highlands received decreasing annual rainfall over the last 40 years. During Belg, 50 % of the stations showed significant increases in the maximum number of consecutive dry days (CDD) in all parts of the CRV. However, most other rainfall indices during Belg showed no significant changes. During Kiremt, considering both significant and non-significant trends, almost all rainfall indices showed an increasing trend in the valley floor and a decreasing trend in the escarpment and highlands. During Belg and Kiremt, the CDD generally showed increasing tendency in the CRV.

The effects of climate change on historical and future extreme rainfall in Antalya, Turkey

There is increasing concern that flood risk will be exacerbated in Antalya, Turkey as a result of global-warming-induced, more frequent and intensive, heavy rainfalls. In this paper, first, trends in extreme rainfall indices in the Antalya region were analysed using daily rainfall data. All stations in the study area showed statistically significant increasing trends for at least one extreme rainfall index. Extreme rainfall datasets for current (1970–1989) and future periods (2080–2099) were then constructed for frequency analysis using the peaks-over-threshold method. Frequency analysis of extreme rainfall data was performed using generalized Pareto distribution for current and future periods in order to estimate rainfall intensities for various return periods. Rainfall intensities for the future period were found to increase by up to 23% more than the current period. This study contributed to better understanding of climate change effects on extreme rainfalls in Antalya, Turkey.

Recent trends in daily rainfall extremes over Montenegro (1951–2010)

Abstract. More intense rainfall may cause a range of negative impacts upon society and the environment. In this study we analysed trends in extreme ETCCDI (Expert Team on Climate Change Detection and Indices) rainfall indices in Montenegro for the period between 1951 and 2010. Montenegro has been poorly studied in terms of rainfall extremes, yet it contains the wettest Mediterranean region known as Krivošije. Several indices of precipitation extremes were assessed including the number of dry days and rainfall totals in order to identify trends and possible changes. A spatial pattern relationship between extreme rainfall indices and the North Atlantic Oscillation has also been examined. The results generally suggest that the number of days with precipitation decreased while rainfall intensity increased, particularly in south-western parts of the country. A slight tendency towards intense rainfall events is suggested. The examined rainfall indices and North Atlantic Oscillation over Montenegro seemed to be directly linked to changes in one of the major large-scale circulation modes such as the NAO pattern that is particularly evident during the winter season.

Regional Observed Trends in Daily Rainfall Indices of Extremes over the Indochina Peninsula from 1960 to 2007

This study analyzed the trends of extreme daily rainfall indices over the Indochina Peninsula from 1960 to 2007. The trends were obtained from high-resolution gridded daily rainfall data compiled by APHRODITE with coordinates of 4°N–25°N and 90E°–112°E. The indices were selected from the list of climate change indices recommended by ETCCDI, which is a joint group of WMO CCl, CLIVAR and JCOMM. The indices are based on the number of heavy rainfall days (≥10 mm), number of very heavy rainfall days (≥20 mm), number of extremely heavy rainfall days (≥25 mm), consecutive dry days (<1 mm), consecutive wet days (≥1 mm), daily maximum rainfall, five-day maximum rainfall, annual wet-day rainfall total, Simple Daily Intensity Index, very wet days, and extremely wet days. The indices were simulated by calculating different extreme characteristics according to wet and dry conditions, frequency, and intensity. Linear trends were calculated by using a least squares fit and significant or non-significant trends were identified using the Mann–Kendall test. The results of this study revealed contrasting trends in extreme rainfall in eastern and western Indochina Peninsula. The changes in extreme rainfall events in the east primarily indicate positive trends in the number of heavy rainfall days, very heavy rainfall days, extremely heavy rainfall days, consecutive wet days and annual wet-day rainfall total, with significant trends at times. These events correlated with the northeastern monsoon that influences the Indochina Peninsula from October to February annually. The results in the west primarily indicate negative trends in consecutive wet days, where significant trends were correlated with decreasing number of annual wet-day rainfall total, heavy rainfall days, very heavy rainfall days, and extremely heavy rainfall days. Daily maximum rainfall, five-day maximum rainfall, very wet days, and extremely wet days show random positive (negative) significant (non-significant) trends, while the simple daily intensity index shows positive trends that dominate the southern part of the Indochina Peninsula, with some grids show significant trends.

Spatial modeling of extreme rainfall in northeast Thailand

It is well recognized that the generalized extreme value (GEV) distribution is widely used for any extreme events. This notion is based on the study of discrete choice behavior; however, there is a limit for predicting the distribution at ungauged sites. Hence, there have been studies on spatial dependence within extreme events in continuous space using recorded observations. We model the annual maximum daily rainfall data consisting of 25 locations for the period from 1982 to 2013. The spatial GEV model that is established under observations is assumed to be mutually independent because there is no spatial dependency between the stations. Furthermore, we divide the region into two regions for a better model fit and identify the best model for each region. We show that the regional spatial GEV model reflects the spatial pattern well compared with the spatial GEV model over the entire region as the local GEV distribution. The advantage of spatial extreme modeling is that more robust return levels and some indices of extreme rainfall can be obtained for observed stations as well as for locations without observed data. Thus, the model helps to determine the effects and assessment of vulnerability due to heavy rainfall in northeast Thailand.

Spatial Modelling of Extreme Rainfall in Northeast Thailand

It is well recognized that the generalized extreme value (GEV) distribution is widely used for any extreme events. This notion is based on the study of discrete choice behavior, however, there is a limit for predicting the distribution at ungauged sites. Hence, there has been studies on spatial dependence within extreme events in continuous space using recorded observations. We model the annual maximum daily rainfall data consisting of 25 locations for the period from 1982 to 2013. The spatial GEV model that is established under observations is assumed to be mutually independent because there is no spatial dependency between the stations. Further, we divide the region into two regions for a better model fit and identify the best model for each region. We show that the regional spatial GEV model reflects the spatial pattern well compared to the spatial GEV model over the entire region as the local GEV distribution. The advantage of spatial extreme modeling is that more robust return levels and some indices of extreme rainfall can be obtained for observed stations as well as for locations without observed data. Thus, the model helps to determine the effects and assessment of vulnerability due to heavy rainfall in northeast Thailand.

最近50年长江流域极端降水特征的再分析

长江流域是中国重要的水能基地，水患灾害频繁，研究该流域的极端降水事件的分布及变化特征，对预测及应对旱涝灾害影响有重要意义。本文利用长江流域1961~2010年最近50年逐日降水量资料，分析了4个极端降水量指标和2个极端降水频率指标的时空变化及趋势变化特征，特别地利用Logistic回归模型，分析了2个极端降水频率指标的非线性趋势特征。结果表明：整个长江流域各种极端降水量指标的空间差异明显，大值区分布在长江流域上游四川盆地向青藏高原的过渡区和中下游地区，极端最大值分布在流域中几个典型的高山测站；最大1日降水量和超90%阈值降水总量随时间有显著的线性增大现象，但是区域平均年降水量和极端过程降水随时间没有明显的线性趋势；长江上游和中游一带极端频率指标中存在显著非线性增大趋势，四川盆地和下游地区极端频率的非线性趋势不明显。极端降水量大的区域，极端指标出现频率也很高，对年降水量贡献很大，是产生洪涝灾害的重要原因。 The Yangtze River basin is the most important hydropower base in China; however, drought and flood occurred frequently in this region recently. It is important to investigate extreme events for predicting and coping with the drought and flood disasters. On the basis of daily precipitation (1961-2010, 138 meteorological sites) for the Yangtze River basin, the temporal and spatial varia-tion of 6 indices of extreme rainfall is analyzed. What’s more, the nonlinear characteristics of 2 extreme rainfall frequency indices are analyzed by Logistic Regression Model. The results show that the spatial differences between the 6 indexes are obvious. The extreme values for the indices distribute in the transition zone from the Sichuan basin to the Qinghai-Tibet plateau and the middle to the lower reach areas of the Yangtze River basin, and the extreme maximum values distribute in several typical mountain stations. There is no obvious linear trend for the mean annual rainfall and extreme duration rainfall; however, the maximum 1-day rainfall and the total rainfall exceeding 90% threshold increase significantly. Nonlinear increasing trend of extreme frequency indices exists in the upstream and middle reaches of the Yangtze River, while it is not significant in the Sichuan basin and the downstream reaches. In a word, there are more extreme indices in districts with more extreme rainfall, contributing a lot to annual rainfall. This is the main reason of flood disaster.