Nonstationary extreme value analysis of temperature extremes in China

In a changing climate, the common assumption of stationarity of climate extremes has been increasingly challenged, raising the need to incorporate non-stationarity in extreme value modeling. In this study, quantile regression is used to identify the trends of annual temperature extremes and their correlations with two large climate patterns, the western Pacific subtropical high (WPSH) and the Arctic Oscillation (AO) at 357 stations in China. Statistical significant positive trends and correlations between warm (or cold) temperature extremes and WPSH (or AO) have been detected at most stations. The influence of WPSH on warm extremes is significant in southern China, while the AO mainly affects the cold extremes in northern and eastern China. Then, annual temperature extremes are fitted to generalized extreme value (GEV) distributions with time-varying parameters. The summer (or winter) mean daily maximum (or minimum) temperatures and two climate indices, the WPSH index and the AO index, are chosen as covariates. In total, 16 candidate GEV distribution models are constructed, and the best fitting model with the lowest Bayesian information criterion (BIC) is selected. The 20-year return levels of annual warm (or cold) extremes in the period 1961–1980 and 1991–2010 are computed and compared. The changes of 20-year return levels of annual warm and cold extremes are jointly determined by trend and distributional changes of annual temperature extremes. Analysis of large scale atmospheric circulation changes indicate that a strengthening anticyclonic circulation and increasing geopotential height in recent decades may have contributed to the changes in temperature extremes in China.     

MM5V3模式对IPCCA1B情景下中国地区极端事件的模拟和预估

利用MM5V3区域气候模式单向嵌套ECHAM5全球环流模式,对中国地区1978-2000年及IPCC A1B情景下2038-2070年气候分别进行了水平分辨率为50 km的模拟试验.文章首先检验了模式模拟的当代极端气候结果,在此基础上对6个极端温度指数和6个极端降水指数的未来变化进行了预估.检验结果表明:MM5V3模式对中国地区当代日最高、最低温度及强降水(大雨和暴雨)日数的空间分布和概率特征均具有一定的模拟能力,但模拟的日最高温度在大部分地区偏低,日最低温度在南方地区偏低、西北地区偏高.概率统计结果显示日最高温度向低值频段偏移,日最低温度在0℃的峰值附近明显偏高.模式对大雨和暴雨年平均日数的模拟在东部地区偏多,概率统计结果则为一致偏大.未来中国地区极端气候预估结果表明:极端高温、极端低温和相对高温在全国范围内都将升高,且线性趋势均为上升;霜日日数则为减少,并具有下降趋势;暖日日数和相对低温在青藏高原和新疆部分地区有所减少、其它地区均为增加,且线性趋势暖日日数为上升,相对低温不明显.极端降水指数的变化具有区域特征,其中单日最大降水、连续五日最大降水、最长无雨期、强降水日数、简单降水强度和极端降水总量均在江淮、华南及西南地区有所增多,而在东北及内蒙古地区有所减少,未来中国南方地区降水的极端化趋势将更加显著.极端降水指数的线性趋势除最长无雨期外其它均为上升.     

Relationships between the North Atlantic Oscillation index and temperatures in Europe in global climate models

The study evaluates relationships between the North Atlantic Oscillation (NAO) index and winter temperatures (including indices of extremes) over Europe in an ensemble of transient simulations of current global climate models (GCMs). We focus on identification of areas in which the NAO index is linked to winter temperatures and temperature extremes in simulations of the recent climate (1961–2000), and evaluate how these relationships change in climate change scenarios for the late 21st century (2071–2100). Most GCMs are able to reproduce main features of the observed links. The NAO index is more important for cold than warm extremes, which is also reproduced by the GCMs. However, all GCMs underestimate the magnitude of the NAO influence on cold extremes when averaged over northern and western Europe. For future scenarios, the links between the NAO and temperatures are mostly analogous to those in the recent climate, except for one GCM (CM3) in which the influence of the NAO on temperature almost disappears over whole Europe. This suggests that future scenarios from this particular GCM should be evaluated with caution. The NAO index is found to represent a useful covariate that explains an important fraction of variability of cold extremes in winter, and its incorporation into extreme value models for daily temperatures (and their possible changes under climate change) may improve performance of these models and reliability of estimates of extremes and their uncertainty.     

Spatial distribution and temporal trends of mean precipitation and extremes in the arid region,northwest of China,during 1960–2010

On the basis of daily precipitation records at 76 meteorological stations in the arid region, northwest of China, the spatial and temporal distribution of mean precipitation and extremes were analysed during 1960–2010. The Mann–Kendall trend test and linear least square method were utilized to detect monotonic trends and magnitudes in annual and seasonal mean precipitation and extremes. The results obtained indicate that both the mean precipitation and the extremes have increased except in consecutive dry days, which showed the opposite trend. The changes in amplitude of both mean precipitation and extremes show seasonal variability. On an annual basis, the number of rain days (R0.1) has significantly increased. Meanwhile, the precipitation intensity as reflected by simple daily intensity index (SDII), number of heavy precipitation days (R10), very wet days (R95p), max 1‐day precipitation amount (RX1day) and max 5‐day precipitation amount (RX5day) has also significantly increased. This suggests that the precipitation increase in the arid region is due to the increase in both precipitation frequency and intensity. Trends in extremes are very highly correlated with mean trends of precipitation. The spatial correlation between trends in extremes and trends in the mean is stronger for winter (DJF) than for annual and other seasons. The regional annual and seasonal precipitation and extremes are observed the step jump in mean in the late 1980s. Overall, the results of this study are good indicators of local climate change, which will definitely enhance human mitigation to natural hazards caused by precipitation extremes. Copyright © 2012 John Wiley & Sons, Ltd.     

Temporal change of spatial heterogeneity and its effect on regional trend of annual precipitation heterogeneity indices

A statistical test on climate and hydrological series from different spatial resolution could obtain different regional trend due to spatial heterogeneity and its temporal variability. In this study, annual series of the precipitation heterogeneity indices of concentration index (CI) and the number of wet days (NW) along with annual total amount of precipitation were calculated based on at‐site daily precipitation series during 1962–2011 in the headwater basin of the Huaihe River, China. The regional trends of the indices were first detected based on at‐site series by using the aligned and intrablock methods, and field significance tests that consider spatial heterogeneity over sites. The detected trends were then compared with the trends of the regional index series derived from daily areal average precipitation (DAAP), which averages at‐site differences and thus neglects spatial heterogeneity. It was found that the at‐site‐based regional test shows increasing trends of CI and NW in the basin, which follows the test on individual sites that most of sites were characterized by increasing CI and NW. However, the DAAP‐derived regional series of CI and NW were tested to show a decreasing trend. The disparity of the regional trend test on at‐site‐based regional series and the DAAP‐derived regional series arises from a temporal change of the spatial heterogeneity, which was quantified by the generalized additive models for location, scale, and shape. This study highlights that compared with averaging indices, averaging at‐site daily precipitation could lead to an error in the regional trend inference on annual precipitation heterogeneity indices. More attention should be paid to temporal variability in spatial heterogeneity when data at large scales are used for regional trend detection on hydro‐meteorological events associated with intra‐annual heterogeneity.     

Changes in daily temperature and precipitation extremes in the Yellow River Basin, China

Spatiotemporal changes in climatic extremes in the Yellow River Basin from 1959 to 2008 were investigated on the basis of a suite of 27 climatic indices derived from daily temperature and precipitation data from 75 meteorological stations with the help of the Mann–Kendall test, linear regression method and GIS technique. Furthermore, the changes in the probability distribution of the extreme indices were examined. The results indicate: (1) The whole basin is dominated by significant increase in the frequency of warm days and warm nights, and dominated by significant decrease in the frequency of cold days and cold nights. Although trends in absolute temperature indices show less spatial coherence compared with that in the percentile-based temperature indices, overall increasing trends can be found in Max Tmax (TXx), Min Tmax (TXn), Max Tmin (TNx) and Min Tmin (TNn). (2) Although the spatial patterns and the number of stations with significant changes for threshold and duration temperature indices are also not identical, general positive trends in warm indices (i.e., summer days (SU25), tropical nights (TR20), warm spell duration indicator and growing season length) and negative trends in cold indices (i.e., frost days, ice days and cold spell duration indicator) can be found in the basin. Annual nighttime temperature has increased at a faster rate than that in daytime temperature, leading to obvious decrease in diurnal temperature range. (3) The changes in precipitation indices are much weaker and less spatially coherent compared with these of temperature indices. For all precipitation indices, only few stations are characterized by significantly change in extreme precipitation, and their spatial patterns are always characterized by irregular and insignificant positive and negative changes. However, generally, changes in precipitation extremes present drying trends, although most of the changes are insignificant. (4) Results at seasonal scale show that warming trends occur for all seasons, particularly in winter. Different from that in other three seasons, general positive trends in max 1-day precipitation (Rx1DAY) and max 5-day precipitation (Rx5DAY) are found in winter. Analysis of changes in probability distributions of indices for 1959–1983 and 1984–2008 indicate a remarkable shift toward warmer condition and a less pronounced tendency toward drier condition during the past decades. The results can provide beneficial reference to water resource and eco-environment management strategies in the Yellow River Basin for associated policymakers and stakeholders.     

Spatio-temporal characteristics of extreme precipitation events during 1951–2011 in Shandong,China and possible connection to the large scale atmospheric circulation

Analyses of the spatio-temporal variability of precipitation extremes defined by eleven extreme precipitation indices in Shandong were conducted by utilizing the methods of linear regression, ensemble empirical mode decomposition (EEMD) and Mann–Kendall test. The results revealed that statistically significant decreasing trends existed for almost all extreme precipitation indices except for the consecutive dry days (CDD) and simple daily intensity index. A periodicity of 10–15 years for precipitation extremes is detected by EEMD analysis. Greatest 5-day total rainfall (RX5day), very wet days (R95p) and annual total wet-day precipitation (PRCPTOT) experienced decreasing trends in the region stretching from the southeast coast to the west, while the spatial distribution of the decreasing trends for other indices was more complicated. Moreover, the frequency of occurrence in precipitation extremes at Changdao station, surrounded by the sea in the northeast region, increased in contrast to surrounding stations. This may suggest a possible effect from the local marine environment on extreme precipitation. In addition, the stations with statistically significant positive trends for CDD were mainly located in mid-west Shandong and along the southeast coast, where the extreme precipitation and total rainfall were, on the contrary, characterized by decreasing trends. These results indicate that drought or severe drought events have become more frequent in those regions. Analysis of large-scale atmospheric circulation changes indicates that a strengthening anticyclonic circulation and increasing geopotential height as well as decreasing strength of monsoonal flow in recent decades may have contributed to the variations in extreme precipitation in Shandong.     

Hydrological extreme variability in the headwater of Tarim River: links with atmospheric teleconnection and regional climate

Variability and possible relationship between monthly 1-day maximum/minimum flow from headwater of Tarim River basin, climatic indices and regional climate were detected by Mann–Kendall test, continuous wavelet transform, cross-wavelet and wavelet coherence methods. The results showed that: (1) hydrological extremes have increased during past 50 years, and the trends of 1-day minimum flow were larger than that of 1-day maximum flow. The most significant change occurred in winter; (2) the hydrological extremes exhibited significant 1-year period and 0.5-year period along the whole hydrological series; (3) different circulation indices may influence the trends of hydrological extremes in different river. The area of polar vortex in North American (i25) and area of Northern Hemisphere polar vortex (i5) showed most significant correlation with 1-day maximum flow and 1-day minimum flow in Aksu River, respectively. In Hotan River, the most significant correlated climate indices with 1-day maximum and minimum flow were Southern oscillation index and area of Northern American Subtropical High (i15), respectively. The area of polar vortex in Atlantic and Europe Sector (i35) showed significant relationships with 1-day minimum flow in Yarkand River; (4) regions of shared power at 0.8–1.5 year mode were found between selected climate indices and the hydrological extremes, anti-phase relations were detected for most of the series; (5) the fluctuations of temperature have strong effects on hydrological extremes, and significant coherence between regional climate and extremes was found at 0.7–1.5 year scale. The results of the study provide valuable information for improving the long-term forecasting of the hydrological extremes using its relationship with climate indices.     

Seasonal temperature extremes in Potsdam

The awareness of global warming is well established and results from the observations made on thousands of stations. This paper complements the large-scale results by examining a long time-series of high-quality temperature data from the Secular Meteorological Station in Potsdam, where observation records over the last 117 years, i.e., from January 1893 are available. Tendencies of change in seasonal temperature-related climate extremes are demonstrated. “Cold” extremes have become less frequent and less severe than in the past, while “warm” extremes have become more frequent and more severe. Moreover, the interval of the occurrence of frost has been decreasing, while the interval of the occurrence of hot days has been increasing. However, many changes are not statistically significant, since the variability of temperature indices at the Potsdam station has been very strong.     

城市化对北京气象站极端气温指数趋势变化的影响

利用5个乡村气象站和北京气象站(简称北京站)1960～2008年日最高、最低气温资料,比较分析了北京地区城市和乡村极端气温指数年、季节的时间变化以及城市化对北京站各极端气温指数趋势变化的影响.结果表明:1960～2008年北京站霜冻日数、冷夜日数、冷昼日数和平均日较差均显著减少,暖夜日数、暖昼日数、平均最高气温和平均最...     

Trends in extreme temperature indices in the Poyang Lake Basin,China

Based on daily maximum and minimum temperature records at 78 meteorological stations in the Basin of China’s largest fresh water lake (Poyang Lake Basin), the temporal and spatial variability of 11 extreme temperature indices are investigated for the period 1959–2010. The analysis indicates that the annual mean of daily minimum temperature (T_min) has increased significantly, while no significant trends were observed in the annual mean of daily maximum temperature (T_max), resulting in a significant decrease in the diurnal temperature range. Trends and percentages of stations with significant trends in T_min-related indices are generally stronger and higher than those in T_max-related indices; however, no significant trends can be found in T_max-related indices (TXMean, TX90p, TXx and TX10p) at both seasonal and annual time scale. Low correlations with Global-SST ENSO index are also detected in T_max-related indices. Significant positive relationships can be found in T_min-related indices (TNMean, TNx, TNn and TN90p), however, the most significant negative coefficient was also found in cold nights (TN10p) with the Global-SST ENSO index. Singular value decomposition (SVD) correlating extreme temperatures over the Poyang Lake Basin and the North Pacific SST indicates the East China Sea, Western Pacific and Bering Sea to be stronger linked with T_min than T_max with the first mode (SVD-1) explaining 90 and 94 % of annual T_max and T_min respectively.     

A spatial temporal downscaling approach to development of IDF relations for Perth airport region in the context of climate change

ABSTRACT

Downscaling of climate projections is the most adapted method to assess the impacts of climate change at regional and local scales. This study utilized both spatial and temporal downscaling approaches to develop intensity–duration–frequency (IDF) relations for sub-daily rainfall extremes in the Perth airport area. A multiple regression-based statistical downscaling model tool was used for spatial downscaling of daily rainfall using general circulation models (GCMs) (Hadley Centre’s GCM and Canadian Global Climate Model) climate variables. A simple scaling regime was identified for 30 minutes to 24 hours duration of observed annual maximum (AM) rainfall. Then, statistical properties of sub-daily AM rainfall were estimated by scaling an invariant model based on the generalized extreme value distribution. RMSE, Nash-Sutcliffe efficiency coefficient and percentage bias values were estimated to check the accuracy of downscaled sub-daily rainfall. This proved the capability of the proposed approach in developing a linkage between large-scale GCM daily variables and extreme sub-daily rainfall events at a given location. Finally IDF curves were developed for future periods, which show similar extreme rainfall decreasing trends for the 2020s, 2050s and 2080s for both GCMs.

Editor M.C. Acreman; Associate editor S. Kanae     

Statistical downscaling of extremes of precipitation and temperature and construction of their future scenarios in an elevated and cold zone

Reliable projections of extremes at finer spatial scales are important in assessing the potential impacts of climate change on societal and natural systems, particularly for elevated and cold regions in the Tibetan Plateau. This paper presents future projections of extremes of daily precipitation and temperature, under different future scenarios in the headwater catchment of Yellow River basin over the 21st century, using the statistical downscaling model (SDSM). The results indicate that: (1) although the mean temperature was simulated perfectly, followed by monthly pan evaporation, the skill scores in simulating extreme indices of precipitation are inadequate; (2) The inter-annual variabilities for most extreme indices were underestimated, although the model could reproduce the extreme temperatures well. In fact, the simulation of extreme indices for precipitation and evaporation were not satisfactory in many cases. (3) In future period from 2011 to 2100, increases in the temperature and evaporation indices are projected under a range of climate scenarios, although decreasing mean and maximum precipitation are found in summer during 2020s. The findings of this work will contribute toward a better understanding of future climate changes for this unique region.     

Recent trends of extreme temperature indices for the Iberian Peninsula

Climate change and extreme climate events have a significant impact on societies and ecosystems. As a result, climate change projections, especially related with extreme temperature events, have gained increasing importance due to their impacts on the well-being of the population and ecosystems. However, most studies in the field are based on coarse global climate models (GCMs). In this study, we perform a high resolution downscaling simulation to evaluate recent trends of extreme temperature indices. The model used was Weather Research and Forecast (WRF) forced by MPI-ESM-LR, which has been shown to be one of the more robust models to simulate European climate. The domain used in the simulations includes the Iberian Peninsula and the simulation covers the 1986–2005 period (i.e. recent past). In order to study extreme temperature events, trends were computed using the Theil-Sen method for a set of temperature indexes defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this, daily values of minimum and maximum temperatures were used. The trends of the indexes were computed for annual and seasonal values and the Mann-Kendall Trend test was used to evaluate their statistical significance. In order to validate the results, a second simulation, in which WRF was forced by ERA-Interim, was performed. The results suggest an increase in the number of warm days and warm nights, especially during summer and negative trends for cold nights and cold days for the summer and spring. For the winter, contrary to the expected, the results suggest an increase in cold days and cold nights (warming hiatus). This behavior is supported by the WRF simulation forced by ERA-Interim for the autumn days, pointing to an extension of the warming hiatus phenomenon to the remaining seasons. These results should be used with caution since the period used to calculate the trends may not be long enough for this purpose. However, the general sign of trends are similar for both simulations despite some differences in their magnitudes.     

Characterizing and understanding the variability of streamflow drought indicators within the USA

ABSTRACT

Low streamflow conditions can have adverse consequences for society and river ecology. The variability and drivers of streamflow drought indicators within the USA were investigated using observed streamflow records from 603 gauges across the USA. The analysis was based on two main approaches: (i) low-flow magnitude indicators, and (ii) streamflow deficit indicators. First, we examined how streamflow drought indicators vary spatially across the USA. Second, we used a data-driven clustering method to identify spatial clusters for each indicator. Finally, we assessed the association with regional climate drivers. The results show that the spatial variability of low-flow magnitude indicators is significantly different from the deficit indicators. Further, our clustering approach identifies regions of spatial homogeneity, which can be linked to the extreme regional climate drivers and land–atmosphere interactions. The influence of regional climate on streamflow drought indicators varies more between clusters than between indicators.     

Changes in thermal extremes in Poland

Changes in thermal extremes of the climate of Poland in 1951–2010 are examined. Warm extremes have become more frequent, while cold extremes have become less frequent. In the warming climate of Poland, the increase in the number of extremely warm days in a year and the decrease in the number of extremely cold days in a year have been observed. Also the increase of the maximum number of consecutive hot days in a year and the decrease of the maximum number of consecutive very cold and extremely cold days in a year have been observed. However, the trends are not of ubiquitous statistic significance, as the natural variability is strong.     

A method for finding the optimal predictor indices for local wave climate conditions

In this study, a method to obtain local wave predictor indices that take into account the wave generation process is described and applied to several locations. The method is based on a statistical model that relates significant wave height with an atmospheric predictor, defined by sea level pressure fields. The predictor is composed of a local and a regional part, representing the sea and the swell wave components, respectively. The spatial domain of the predictor is determined using the Evaluation of Source and Travel-time of wave Energy reaching a Local Area (ESTELA) method. The regional component of the predictor includes the recent historical atmospheric conditions responsible for the swell wave component at the target point. The regional predictor component has a historical temporal coverage (n-days) different to the local predictor component (daily coverage). Principal component analysis is applied to the daily predictor in order to detect the dominant variability patterns and their temporal coefficients. Multivariate regression model, fitted at daily scale for different n-days of the regional predictor, determines the optimum historical coverage. The monthly wave predictor indices are selected applying a regression model using the monthly values of the principal components of the daily predictor, with the optimum temporal coverage for the regional predictor. The daily predictor can be used in wave climate projections, while the monthly predictor can help to understand wave climate variability or long-term coastal morphodynamic anomalies.     

Precipitation regional extreme mapping as a tool for ungauged areas and the assessment of climate changes

The spatial‐temporal characteristics of mean annual daily maximum precipitation events in the upper Yangtze River basin in China are examined using a framework termed precipitation regional extreme mapping (PREM). The framework consists of regional analyses and mapping methods, which have the capability to assess the presence or absence of climate change. The findings confirm the homogeneous regions identified by Wang (2002) using a heterogeneity measure, where all three regions have heterogeneity less than 1.0. The Pearson type III (PE3) distribution was found to be acceptable for all three regions, while the generalized extreme‐value distribution performs better than PE3 for Region I (eastern portion of the upper Yangtze basin). Two indices, root mean square error and mean bias, were used to access the performance of the extreme map, and the results show that the map of extreme can predict precipitation for ungauged regions with acceptable accuracy. The regional frequency maps were used in conjunction with the Student's t‐test to identify the statistical significance of changes of extremes in precipitation. Results indicate that there have been no significant changes in maximum daily precipitation magnitudes over the past four decades, a finding that is valuable for the safe planning of major hydraulic projects and the management and planning of water resources in the upper Yangtze River basin. Copyright © 2015 John Wiley & Sons, Ltd.     

Trends in precipitation extremes over the Yellow River basin in North China: Changing properties and causes

The Mann–Kendall test, composite analysis, and 68 high‐quality meteorological stations were used to explore the spatiotemporal variations and causes of precipitation extremes over the Yellow River basin (YRB) during the period of 1960–2011. Results showed that (a) the YRB is characterized by decreases of most precipitation indices, excluding the simple daily intensity index, which has increasing trends in most locations, suggesting that the intensity of rainfall and the probability of occurrence of droughts have increased during the last decades. (b) Trends of extreme precipitation show mixed patterns in the lower reach of the YRB, where drought–flood disasters have increased. The increases in heavy rainfall and decreases in consecutive wet days in recent years over the northwestern portions of the YRB indicate that the intensity and frequency of above‐normal precipitation have been trending upward in domains. In the central‐south YRB, the maximum 1‐day precipitation (RX1day) and precipitation on extremely wet days (R99p) have significantly increased, whereas the number of consecutive dry days has declined; these trends suggest that the intensity of precipitation extremes has increased in those regions, although the frequency of extreme and total rainfall has decreased. (c) The spatial distributions of seasonal trends in RX1day and maximum 5‐day precipitation (RX5day) exhibited less spatial coherence, and winter is becoming the wettest season regionwide, particularly over the central‐south YRB. (d) There were multiple and overlapping cycles of variability for most precipitation indices, indicating variations of time and frequency. (e) Elevation is intimately correlated with precipitation indices, and a weakening East Asian summer monsoon during 1986–2011 compared to that in 1960–1985 may have played an important role in the declines in most indices over the YRB. Therefore, the combined effects from local and teleconnection forcing factors have collectively influenced the variations in precipitation extremes across the YRB. This study may provide valuable evidence for the effective management of water resources and the conduct of agricultural activities at the basin scale.     

Investigation into the daily precipitation variability in the Yangtze River Delta,China

In this article, by using the daily precipitation data measured at 58 meteorological stations, spatial and temporal variability of daily precipitation including zero rainfall values (called “precipitation”) and without zero rainfall values (called “rain”) and four precipitation extrema (P₀, P₂₀, P₅₀, and P₁₀₀ representing the daily precipitation with the magnitude smaller than 0.1 mm, bigger than 20 mm, 50 mm, and 100 mm per day, respectively) in the Yangtze River Delta (YRD) during 1958–2007 were analyzed, and the effects of urbanization were further investigated. Results indicate that (i) differing from the downward trends in 1958–1985, daily precipitation and rain in 1986–2007 show slowly downward trends in the mid YRD but show upward trends in the northern and southern YRD. (ii) Spatial and temporal variability of the rain is more complex than daily precipitation. Both of them become smaller but show more obvious fluctuations in 1986–2007. (iii) Urbanizations cause not only the urban rainfall island problem but also more obvious fluctuations of rain intensity in the mid YRD, reflecting more uncertainty of daily precipitation variability. (iv) Urbanizations have little effects on the variability of P₀ and P₁₀₀ but cause notable increases of P₂₀ and P₅₀. (v) The spatial variability of daily precipitation and precipitation extrema in 1958–1985 clearly shows a breakpoint at 30°20′N latitude, but the breakpoint disappears afterward because of the effects of urbanization. Copyright © 2012 John Wiley & Sons, Ltd.