An ensemble approach for the analysis of extreme rainfall under climate change in Naples (Italy)

In the present paper, an ensemble approach is proposed to estimate possible modifications caused by climate changes in the extreme precipitation regime, with the rain gauge Napoli Servizio Idrografico (Naples, Italy) chosen as test case. The proposed research, focused on the analysis of extremes on the basis of climate model simulations and rainfall observations, is structured in several consecutive steps. In the first step, all the dynamically downscaled EURO‐CORDEX simulations at about 12 km horizontal resolution are collected for the current period 1971–2000 and the future period 2071–2100, for the RCP4.5 and the RCP8.5 concentration scenarios. In the second step, the significance of climate change effects on extreme precipitation is statistically tested by comparing current and future simulated data and bias‐correction is performed by means of a novel approach based on a combination of simple delta change and quantile delta mapping, in compliance with the storm index method. In the third step, two different ensemble models are proposed, accounting for the variabilities given by the use of different climate models and for their hindcast performances. Finally, the ensemble models are used to build novel intensity–duration–frequency curves, and their effects on the early warning system thresholds for the area of interest are evaluated.     

Assessment on variability of extreme climate events for the Upper Thames River basin in Canada

Climate change may affect magnitude and frequency of regional extreme events with possibility of serious impacts on the existing infrastructure systems. This study investigates how the current spatial and temporal variations of extreme events are affected by climate change in the Upper Thames River basin, Ontario, Canada. A weather generator model is implemented to obtain daily time series of three climate variables for two future climate scenarios. The daily time series are disaggregated into hourly to capture characteristics of intense and rapidly changing storms. The maximum annual precipitation events for five short durations, 6‐, 12‐, 24‐, 48‐, and 72‐h durations, at each station are extracted from the generated hourly data. The frequency and seasonality analyses are conducted to investigate the temporal and spatial variability of extreme precipitation events corresponding to each duration. In addition, this study investigates the impacts of increase in temperature using reliability, resilience, and vulnerability. The results indicate that the extreme precipitation events under climate change will occur earlier than in the past. In addition, episodes of extremely high temperature may last longer up to 19·7% than under the no‐change climate scenario. This study points out that the revision of the design storms (e.g. 100‐ or 250‐year return period) is warranted for the west and the south east region of the basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Trend and extreme occurrence of precipitation in a mid‐latitude Eurasian steppe watershed at various time scales

The confounding effects of step change invalidate the stationarity assumption of commonly used trend analysis methods such as the Mann–Kendall test technique, so previous studies have failed to explain inconsistencies between detected trends and observed large precipitation anomalies. The objectives of this study were to (1) formulate a trend analysis approach that considers nonstationarity due to step changes, (2) use this approach to detect trends and extreme occurrences of precipitation in a mid‐latitude Eurasian steppe watershed in North China, and (3) examine how runoff responds to precipitation trends in the study watershed. Our results indicate that annual precipitation underwent a marginal step jump around 1995. The significant annual downward trend after 1994 was primarily due to a decrease in summer rainfall; other seasons exhibited no significant precipitation trends. At a monthly scale, July rainfall after 1994 exhibited a significant downward trend, whereas precipitation in other months had no trend. The percentage of wet days also underwent a step jump around 1994 following a significant decreasing trend, although the precipitation intensity exhibited neither a step change nor any significant trend. However, both low‐frequency and high‐frequency precipitation events in the study watershed occurred more often after than before 1994; probably as either a result or an indicator of climate change. In response to these precipitation changes, the study watershed had distinctly different precipitation‐runoff relationships for observed annual precipitations of less than 300 mm, between 300 and 400 mm, and greater than 400 mm. Copyright © 2013 John Wiley & Sons, Ltd.     

Variations and statistical probability characteristic analysis of extreme precipitation events under climate change in Haihe River Basin,China

The magnitude and frequency of regional extreme precipitation events may have variability under climate change. This study investigates the time–space variability and statistical probability characteristics of extreme precipitation under climate change in the Haihe River Basin. Hydrological alteration diagnosis methods are implemented to detect the occurrence time, style and degree of alteration such as trend and jump in the extreme precipitation series, and stationarity and serial independence are tested prior to frequency analysis. Then, the historical extreme precipitation frequency and spatio‐temporal variations analyses are conducted via generalized extreme value and generalized Pareto distributions. Furthermore, the occurrence frequency of extreme precipitation events in future is analysed on the basis of the Fourth Assessment Report of the Intergovermental Panel on Climate Change multi‐mode climate models under different greenhouse gases emission scenarios (SRES‐A2, A1B and B1). Results indicate that (1) in the past, alteration of extreme precipitation mainly occurred in the area north of 38°N. Decreasing trends of extreme precipitation are detected at most stations, whereas jump alteration is not obvious at most stations. (2) Spatial variation of estimated extreme precipitation under different return periods shows similarity. Bounded by the Taihang Mountain–Yan Mountain, extreme rainfall in the Haihe River Basin gradually reduces from the southeast to the northwest, which is consistent with the geographical features of the Haihe River Basin. (3) In the future, extreme precipitation with return period 5–20 years accounts for a significant portion of the total occurrence times. The frequency of extreme precipitation events has an increase trend under A1B and A2 scenarios. The total occurrence times of extreme precipitation under A1B senario are not more than that under B1 senario until the 2030s. Copyright © 2012 John Wiley & Sons, Ltd.     

Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario,Canada

Abstract

Southern Ontario, Canada, has been impacted in recent years by many heavy rainfall and flooding events that have exceeded existing historical estimates of infrastructure design rainfall intensity–duration–frequency (IDF) values. These recent events and the limited number of short-duration recording raingauges have prompted the need to research the climatology of heavy rainfall events within the study area, review the existing design IDF methodologies, and evaluate alternative approaches to traditional point-based heavy rainfall IDF curves, such as regional IDF design values. The use of additional data and the regional frequency analysis methodology were explored for the study area, with the objective of validating identified clusters or homogeneous regions of extreme rainfall amounts through Ward's method. As the results illustrate, nine homogeneous regions were identified in Southern Ontario using the annual maximum series (AMS) for daily and 24-h rainfall data from climate and rate-of-rainfall or tipping bucket raingauge (TBRG) stations, respectively. In most cases, the generalized extreme value and logistic distributions were identified as the statistical distributions that provide the best fit for the 24-h and sub-daily rainfall data in the study area. A connection was observed between extreme rainfall variability, temporal scale of heavy rainfall events and location of each homogeneous region. Moreover, the analysis indicated that scaling factors cannot be used reliably to estimate sub-daily and sub-hourly values from 24- and 1-h data in Southern Ontario.

Citation Paixao, E., Auld, H., Mirza, M.M.Q., Klaassen, J. & Shephard, M.W. (2011) Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario, Canada. Hydrol. Sci. J. 56(7), 1067–1089.     

Impact of climate change on 24‐h design rainfall depth estimation in Qiantang River Basin,East China

The frequency and magnitude of extreme meteorological or hydrological events such as floods and droughts in China have been influenced by global climate change. The water problem due to increasing frequency and magnitude of extreme events in the humid areas has gained great attention in recent years. However, the main challenge in the evaluation of climate change impact on extreme events is that large uncertainty could exist. Therefore, this paper first aims to model possible impacts of climate change on regional extreme precipitation (indicated by 24‐h design rainfall depth) at seven rainfall gauge stations in the Qiantang River Basin, East China. The Long Ashton Research Station‐Weather Generator is adopted to downscale the global projections obtained from general circulation models (GCMs) to regional climate data at site scale. The weather generator is also checked for its performance through three approaches, namely Kolmogorov–Smirnov test, comparison of L‐moment statistics and 24‐h design rainfall depths. Future 24‐h design rainfall depths at seven stations are estimated using Pearson Type III distribution and L‐moment approach. Second, uncertainty caused by three GCMs under various greenhouse gas emission scenarios for the future periods 2020s (2011–2030), 2055s (2046–2065) and 2090s (2080–2099) is investigated. The final results show that 24‐h design rainfall depth increases in most stations under the three GCMs and emission scenarios. However, there are large uncertainties involved in the estimations of 24‐h design rainfall depths at seven stations because of GCM, emission scenario and other uncertainty sources. At Hangzhou Station, a relative change of ?16% to 113% can be observed in 100y design rainfall depths. Copyright © 2012 John Wiley & Sons, Ltd.     

Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima

The conventional approach to the frequency analysis of extreme precipitation is complicated by non-stationarity resulting from climate variability and change. This study utilized a non-stationary frequency analysis to better understand the time-varying behavior of short-duration (1-, 6-, 12-, and 24-h) precipitation extremes at 65 weather stations scattered across South Korea. Trends in precipitation extremes were diagnosed with respect to both annual maximum precipitation (AMP) and peaks-over-threshold (POT) extremes. Non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with model parameters made a linear function of time were applied to AMP and POT respectively. Trends detected using the Mann–Kendall test revealed that the stations showing an increasing trend in AMP extremes were concentrated in the mountainous areas (the northeast and southwest regions) of South Korea. Trend tests on POT extremes provided fairly different results, with a significantly reduced number of stations showing an increasing trend and with some stations showing a decreasing trend. For most of stations showing a statistically significant trend, non-stationary GEV and GPD models significantly outperformed their stationary counterparts, particularly for precipitation extremes with shorter durations. Due to a significant-increasing trend in the POT frequency found at a considerable number of stations (about 10 stations for each rainfall duration), the performance of modeling POT extremes was further improved with a non-homogeneous Poisson model. The large differences in design storm estimates between stationary and non-stationary models (design storm estimates from stationary models were significantly lower than the estimates of non-stationary models) demonstrated the challenges in relying on the stationary assumption when planning the design and management of water facilities. This study also highlighted the need of caution when quantifying design storms from POT and AMP extremes by showing a large discrepancy between the estimates from those two approaches.     

Physically based maximum precipitation estimation under future climate change conditions

Estimation of the extreme precipitation over a target watershed under a changing climate would be necessary to design safe large hydraulic structures. For this purpose, the maximum precipitation (MP) estimation approach was applied to the American River Watershed (ARW) in Northern California under several future climate conditions over 90 water years (2010–2099). These future climate conditions were obtained using 13 future climate projections from two general circulation models (ECHAM5 and CCSM3) based on four future climate scenarios (Special Report on Emissions Scenarios: A1B, A1FI, A2, and B1). A total of 1,170 future projected severe storm events (90 years × 13 projections) were selected with respect to the 72‐hr basin‐average precipitation over the ARW. The 72‐hr basin‐average precipitation for each of the selected severe storm events was maximized over the ARW by horizontally shifting the atmospheric boundary conditions of a regional atmospheric model in order to optimize the path of the storm system that corresponded to the particular event. After maximization, the MP estimates, which are the largest precipitation depths among the maximized results, were obtained as 836.7 mm for the early half‐century period (2010–2054) and 1,056.5 mm for the late half‐century period (2055–2099).     

Estimates of changes in design rainfall values for Canada

Annual maximum rainfall data from 51 stations in Canada were analyzed for trends and changes by using the Mann–Kendall trend test and a bootstrap resampling approach, respectively. Rainfall data were analyzed for nine durations ranging from 5 min to 24 h. The data analyzed are typically used in the development of intensity‐duration‐frequency (IDF) curves, which are used for estimating design rainfall values that form an input for the design of critical water infrastructure. The results reveal more increasing than decreasing trends and changes in the data with more increasing changes and larger changes, noted for the longer rainfall durations. The results also indicate that a traditional trend test may not be sufficient when the interest is in identifying changes in design rainfall quantiles. Copyright © 2012 John Wiley & Sons, Ltd.     

Climate change impacts on extreme precipitation of water supply area in Istanbul: use of ensemble climate modelling and geo-statistical downscaling

ABSTRACT

Numerous statistical downscaling models have been applied to impact studies, but none clearly recommended the most appropriate one for a particular application. This study uses the geographically weighted regression (GWR) method, based on local implications from physical geographical variables, to downscale climate change impacts to a small-scale catchment. The ensembles of daily precipitation time series from 15 different regional climate models (RCMs) driven by five different general circulation models (GCMs), obtained through the European Union (EU)-ENSEMBLES project for reference (1960–1990) and future (2071–2100) scenarios are generated for the Omerli catchment, in the east of Istanbul city, Turkey, under scenario A1B climate change projections. Special focus is given to changes in extreme precipitation, since such information is needed to assess the changes in the frequency and intensity of flooding for future climate. The mean daily precipitation from all RCMs is under-represented in the summer, autumn and early winter, but it is overestimated in late winter and spring. The results point to an increase in extreme precipitation in winter, spring and summer, and a decrease in autumn in the future, compared to the current period. The GWR method provides significant modifications (up to 35%) to these changes and agrees on the direction of change from RCMs. The GWR method improves the representation of mean and extreme precipitation compared to RCM outputs and this is more significant, particularly for extreme cases of each season. The return period of extreme events decreases in the future, resulting in higher precipitation depths for a given return period from most of the RCMs. This feature is more significant with downscaling. According to the analysis presented, a new adaption for regulating excessive water under climate change in the Omerli basin may be recommended.     

Frequency analyses of annual extreme rainfall series from 5 min to 24 h

The parameter estimation methods of (1) moments, (2) maximum‐likelihood, (3) probability‐weighted moments (PWM) and (4) self‐determined PWM are applied to the probability distributions of Gumbel, general extreme values, three‐parameter log‐normal (LN3), Pearson‐3 and log‐Pearson‐3. The special method of computing parameters so as to make the sample skewness coefficient zero is also applied to LN3, and hence, altogether 21 candidate distributions resulted. The parameters of these distributions are computed first by original sample series of 14 successive‐duration annual extreme rainfalls recorded at a rain‐gauging station. Next, the parameters are scaled by first‐degree semi‐log or log‐log polynomial regressions versus rainfall durations from 5 to 1440 min (24 h). Those distributions satisfying the divergence criterion for frequency curves are selected as potential distributions, whose better‐fit ones are determined by a conjunctive evaluation of three goodness‐of‐fit tests. Frequency tables, frequency curves and intensity–duration–frequency curves are the outcome. Copyright © 2010 John Wiley & Sons, Ltd.     

Response of streamflow to climate change and human activity in Xitiaoxi river basin in China

In recent years, the Xitiaoxi river basin in China has experienced intensified human activity, including city expansion and increased water demand. Climate change also has influenced streamflow. Assessing the impact of climate variability and human activity on hydrological processes is important for water resources planning and management and for the sustainable development of eco‐environmental systems. The non‐parametric Mann–Kendall test was employed to detect the trends of climatic and hydrological variables. The Mann–Kendall–Sneyers test and the moving t‐test were used to locate any abrupt change of annual streamflow. A runoff model, driven by precipitation and potential evapotranspiration, was employed to assess the impact of climate change on streamflow. A significant downward trend was detected for annual streamflow from 1975 to 2009, and an abrupt change occurred in 1999, which was consistent with the change detected by the double mass curve test between streamflow and precipitation. The annual precipitation decreased slightly, but upward trends of annual mean temperature and potential evapotranspiration were significant. The annual streamflow during the period 1999–2009 decreased by 26.19% compared with the reference stage, 1975–1998. Climate change was estimated to be responsible for 42.8% of the total reduction in annual streamflow, and human activity accounted for 57.2%. Copyright © 2012 John Wiley & Sons, Ltd.     

The role of urban growth,climate change,and their interplay in altering runoff extremes

Changes in climate and urban growth are the most influential factors affecting hydrological characteristics in urban and extra‐urban contexts. The assessment of the impacts of these changes on the extreme rainfall–runoff events may have important implications on urban and extra‐urban management policies against severe events, such as floods, and on the design of hydraulic infrastructures. Understanding the effects of the interaction between climate change and urban growth on the generation of runoff extremes is the main aim of this paper. We carried out a synthetic experiment on a river catchment of 64 km² to generate hourly runoff time series under different hypothetical scenarios. We imposed a growth of the percentage of urban coverage within the basin (from 1.5% to 25%), a rise in mean temperature of 2.6 °C, and an alternatively increase/decrease in mean annual precipitation of 25%; changes in mean annual precipitation were imposed following different schemes, either changing rainstorm frequency or rainstorm intensity. The modelling framework consists of a physically based distributed hydrological model, which simulates fast and slow mechanisms of runoff generation directly connected with the impervious areas, a land‐use change model, and a weather generator. The results indicate that the peaks over threshold and the hourly annual peaks, used as hydrological indicators, are very sensitive to the rainstorm intensity. Moreover, the effects of climate changes dominate on those of urban growth determining an exacerbation of the fast runoff component in extreme events and a reduction of the slow and deep runoff component, thus limiting changes in the overall runoff.     

Assessing urban flood and drought risks under climate change,China

Risk analysis of urban flood and drought can provide useful guidance for urban rainwater management. Based on an analysis of urban climate characteristics in 2,264 Chinese cities from 1958 to 2017, this study evaluated urban flood and drought risks. The results demonstrated that the annual average values of precipitation, aridity index, frequency and intensity of extreme precipitation and extreme drought events differed significantly in these cities. The values of the above six climatic indicators in the cities ranged from 9.29–2639.30 mm, 0.47–54.73, 1.08–8.79 time, 7.82–107.25 mm, 0.76–2.99 time, and 10.30–131.19 days, respectively. The geographical patterns of urban precipitation, aridity index, intensity and frequency of extreme precipitation and drought events in China fit well to the Hu‐Huanyong Line that was created in 1940s to identify the pattern of population distribution. Extreme precipitation in most cities has upward trends, except for those around the Hu‐Huanyong Line. The extreme drought events had upward trends in the cities east of the Hu‐Huanyong Line, but there were downward trends in the cities west of the line. The risk assessment indicated that 3.80% cities were facing serious flood and 6.01% cities were facing serious drought risks, which are located in the coast of southern China and northwestern China, respectively, and other 90.19% cities were facing different types of drought and flood risks in terms of their intensity and frequency.     

Assessment of the impact of climate change on the flow regime of the Han River basin using indicators of hydrologic alteration

Most natural disasters are caused by water‐/climate‐related hazards, such as floods, droughts, typhoons, and landslides. In the last few years, great attention has been paid to climate change, and especially the impact of climate change on water resources and the natural disasters that have been an important issue in many countries. As climate change increases the frequency and intensity of extreme rainfall, the number of water‐related disasters is expected to rise. In this regard, this study intends to analyse the changes in extreme weather events and the associated flow regime in both the past and the future. Given trend analysis, spatially coherent and statistically significant changes in the extreme events of temperature and rainfall were identified. A weather generator based on the non‐stationary Markov chain model was applied to produce a daily climate change scenario for the Han River basin for a period of 2001–2090. The weather generator mainly utilizes the climate change SRES A2 scenario driven by input from the regional climate model. Following this, the SLURP model, which is a semi‐distributed hydrological model, was applied to produce a long‐term daily runoff ensemble series. Finally, the indicator of hydrologic alteration was applied to carry out a quantitative analysis and assessment of the impact of climate change on runoff, the river flow regime, and the aquatic ecosystem. It was found that the runoff is expected to decrease in May and July, while no significant changes occur in June. In comparison with historical evidence, the runoff is expected to increase from August to April. A remarkable increase, which is about 40%, in runoff was identified in September. The amount of the minimum discharge over various durations tended to increase when compared to the present hydrological condition. A detailed comparison for discharge and its associated characteristics was discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

Climate‐informed low‐flow frequency analysis using nonstationary modelling

Stationarity is often assumed for frequency analysis of low flows in water resources management and planning. However, many studies have shown that flow characteristics, particularly the frequency spectrum of extreme hydrologic events, were modified by climate change and human activities. Thus, the conventional frequency analysis that fails to consider the nonstationary characteristics may lead to costly design. The analysis presented in this paper was based on the more than 100 years of daily flow data from the Yichang gauging station 44 km downstream of the Three Gorges Dam. The Mann–Kendall trend test under the scaling hypothesis showed that the annual low flows had a significant monotonic trend, whereas an abrupt change point was identified in 1936 by the Pettitt test. The climate‐informed low‐flow frequency analysis and the divided and combined method were employed to account for the impacts from related climate variables and nonstationarities in annual low flows. Without prior knowledge of the probability density function for the gauging station, six distribution functions including the generalized extreme values (GEV), Pearson Type III, Gumbel, Gamma, Lognormal and Weibull distributions have been tested to find the best fit, in which the local likelihood method is used to estimate the parameters. Analyses show that GEV had the best fit for the observed low flows. This study has also shown that the climate‐informed low‐flow frequency analysis is able to exploit the link between climate indices and low flows, which would account for the dynamic feature for reservoir management and provide more accurate and reliable designs for infrastructure and water supply. Copyright © 2014 John Wiley & Sons, Ltd.     

The impact of climate change on extreme precipitation in Sicily,Italy

Increasing precipitation extremes are one of the possible consequences of a warmer climate. These may exceed the capacity of urban drainage systems, and thus impact the urban environment. Because short‐duration precipitation events are primarily responsible for flooding in urban systems, it is important to assess the response of extreme precipitation at hourly (or sub‐hourly) scales to a warming climate. This study aims to evaluate the projected changes in extreme rainfall events across the region of Sicily (Italy) and, for two urban areas, to assess possible changes in Depth‐Duration‐Frequency (DDF) curves. We used Regional Climate Model outputs from Coordinated Regional Climate Downscaling Experiment for Europe area ensemble simulations at a ~12 km spatial resolution, for the current period and 2 future horizons under the Representative Concentration Pathways 8.5 scenario. Extreme events at the daily scale were first investigated by comparing the quantiles estimated from rain gauge observations and Regional Climate Model outputs. Second, we implemented a temporal downscaling approach to estimate rainfall for sub‐daily durations from the modelled daily precipitation, and, lastly, we analysed future projections at daily and sub‐daily scales. A frequency distribution was fitted to annual maxima time series for the sub‐daily durations to derive the DDF curves for 2 future time horizons and the 2 urban areas. The overall results showed a raising of the growth curves for the future horizons, indicating an increase in the intensity of extreme precipitation, especially for the shortest durations. The DDF curves highlight a general increase of extreme quantiles for the 2 urban areas, thus underlining the risk of failure of the existing urban drainage systems under more severe events.     

Embryo dune development drivers: beach morphology,growing season precipitation,and storms

For development of embryo dunes on the highly dynamic land–sea boundary, summer growth and the absence of winter erosion are essential. Other than that, however, we know little about the specific conditions that favour embryo dune development. This study explores the boundary conditions for early dune development to enable better predictions of natural dune expansion. Using a 30 year time series of aerial photographs of 33 sites along the Dutch coast, we assessed the influence of beach morphology (beach width and tidal range), meteorological conditions (storm characteristics, wind speed, growing season precipitation, and temperature), and sand nourishment on early dune development. We examined the presence and area of embryo dunes in relation to beach width and tidal range, and compared changes in embryo dune area to meteorological conditions and whether sand nourishment had been applied. We found that the presence and area of embryo dunes increased with increasing beach width. Over time, embryo dune area was negatively correlated with storm intensity and frequency. Embryo dune area was positively correlated with precipitation in the growing season and sand nourishment. Embryo dune area increased in periods of low storm frequency and in wet summers, and decreased in periods of high storm frequency or intensity. We conclude that beach morphology is highly influential in determining the potential for new dune development, and wide beaches enable development of larger embryo dune fields. Sand nourishment stimulates dune development by increasing beach width. Finally, weather conditions and non‐interrupted sequences of years without high‐intensity storms determine whether progressive dune development will take place. Copyright © 2017 John Wiley & Sons, Ltd.     

区域气候模式RegCM3对华北地区未来气候变化的数值模拟

采用高水平分辨率区域气候模式进行区域未来气候变化预估,对理解全球增暖对区域气候的潜在影响和科学评估区域气候变化有很好的参考价值.这里对国家气候中心使用25 km高水平分辨率区域气候模式RegCM3单向嵌套全球模式MIROC3.2_hires在观测温室气体(1951—2000)和IPCC A1B温室气体排放情景下(2001—2100)进行的共计150年长时间模拟结果,进行华北地区未来气温、降水和极端气候事件变化的分析.模式检验结果表明:模式对当代(1981—2000)气温以及和气温有关的极端气候事件(霜冻日数、生长季长度)的空间分布和数值模拟较好;对降水及和降水有关的极端气候事件(强降水日期、降水强度、五日最大降水量)能够模拟出它们各自的主要空间分布特征,但在模拟数值上存在偏大、偏强的误差.和全球模式驱动场相比,区域模式模拟的气温、降水和极端气候事件有明显的改进.2010—2100年华北地区随时间区域平均气温升高幅度逐渐增大,随之霜冻日数逐渐减少,生长季长度逐渐增多;同时随温室效应的不断加剧,未来降水呈增加的趋势,强降水日期和五日最大降水量逐渐增多、降水强度逐渐增大.从空间分布看,21世纪末期(2081—2100)气温、降水以及有关的极端气候事件变化比21世纪中期(2041—2060)更加明显.     

Trend analysis in Turkish precipitation data

This study aims to determine trends in the long‐term annual mean and monthly total precipitation series using non‐parametric methods (i.e. the Mann–Kendall and Sen's T tests). The change per unit time in a time series having a linear trend was estimated by applying a simple non‐parametric procedure, namely Sen's estimator of slope. Serial correlation structure in the data was accounted for determining the significance level of the results of the Mann–Kendall test. The data network used in this study, which is assumed to reflect regional hydroclimatic conditions, consists of 96 precipitation stations across Turkey. Monthly totals and annual means of the monthly totals are formed for each individual station, spanning from 1929 to 1993. In this case, a total of 13 precipitation variables at each station are subjected to trend detection analysis. In addition, regional average precipitation series are established for the same analysis purpose. The application of a trend detection framework resulted in the identification of some significant trends, especially in January, February, and September precipitations and in the annual means. A noticeable decrease in the annual mean precipitation was observed mostly in western and southern Turkey, as well as along the coasts of the Black Sea. Regional average series also displayed trends similar to those for individual stations. Copyright © 2005 John Wiley & Sons, Ltd.