Multi-Fractal Analysis of Daily Air Temperature Time Series in Coastal Areas of China

In this article, the Multi-Fractal Detrended Fluctuation Analysis(MF-DFA) method is adopted to study the temperature, i. e., the maximum temperature(Tmax), mean temperature(Tavg) and minimum(Tmin) air temperature,multifractal characteristics and their formation mechanism, in the typical temperature zones in the coastal regions in Guangdong, Jiangsu and Liaoning Provinces. Following are some terms and concepts used in the present study.Multifractality is defined as a term that characterizes the complexity and self-similarity of objects, and fractal characteristics depict the distribution of probability over the whole set caused by different local conditions or different levels in the process of evolution. Fractality strength denotes the fluctuation range of the data set, and long-range correlation(LRC) measures the stability of the climate system and the trend of climate change in the future. In this research, it is found that the internal stability and feedback mechanism of climate systems in different regions show regional differences. Furthermore, the research also proves that the Tavg, Tmaxand Tminof the above three provinces are highly multifractal. The temperature series multifractality of each province decreases in the order of temperature series multifractality of Liaoning temperature series multifractality of Guangdong temperature series multifractality of Jiangsu, and the corresponding long-range correlations follow the same order. It reveals that the most stable temperature series is that of Liaoning, followed by the temperature series of Guangdong, and the most unstable one is that of Jiangsu.Liaoning has the most stable climate system, and it will thus be less responsive to the future climate warming. The stability of the climate system in Jiangsu is the weakest, and its temperature fluctuation will continue to increase in the future, which will probably result in the meteorological disasters of high temperature and heat wave there. Guangdong possesses the strongest degree of multifractal strength, which indicates that its internal temperature series fluctuation is the largest among the three regions. The Tmaxmultifractal strength of Jiangsu is stronger than that of Liaoning, while the Tavgand Tminmultifractal strength of Jiangsu is weaker than that of Liaoning, showing that Jiangsu has a larger internal Tmaxfluctuation than Liaoning does, while it has a smaller fluctuation of Tavgand Tminthan Liaoning does. Guangdong and Liaoning both show the strongest Tminmultifractal strength, followed by Tavgmultifractal strength, and the weakest Tmax multifractal strength. However, Jiangsu has the strongest Tmax, followed by Tavg, and the weakest Tmin. The research findings show that these phenomena are closely related to solar radiation, monsoon strength, topography and some other factors. In addition, the multifractality of the temperature time series results from the negative power-law distribution and long-range correlation, in which the long-range correlation influence of temperature series itself plays the dominant role. With the backdrop of global climate change, this research can provide a theoretical basis for the prediction of the spatial-temporal air temperature variation in the eastern coastal areas of China and help us understand its characteristics and causes, and thus the present study will be significant for the environmental protection of coastal areas.     

Assessment of Air Temperature Trends in the Source Region of Yellow River and Its Sub-Basins,China

Changes in climatic variables at the sub-basins scale (having different features of land cover) are crucial for planning, development and designing of water resources infrastructure in the context of climate change. Accordingly, to explore the features of climate changes in sub-basins of the Source Region of Yellow River (SRYR), absolute changes and trends of temperature variables, maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tavg) and diurnal temperature range (DTR), were analyzed annually and seasonally by using daily observed air temperature dataset from 1965 to 2014. Results showed that annual Tmax, Tmin and Tavg for the SRYR were experiencing warming trends respectively at the rate of 0.28, 0.36 and 0.31°C (10 yr)^?1. In comparison with the 1st period (1965-1989), more absolute changes and trends towards increasing were observed during the 2nd period (1990-2014). Apart from Tangnaihai (a low altitude sub-basin), these increasing trends and changes seemed more significant in other basins with highest magnitude during winter. Among sub-basins the increasing trends were more dominant in Huangheyan compared to other sub-basins. The largest increase magnitude of Tmin, 1.24 and 1.18°C (10 yr)^?1, occurred in high altitude sub-basins Jimai and Huangheyan, respectively, while the smallest increase magnitude of 0.23°C (10 yr)^?1 occurred in a low altitude sub-basin Tangnaihai. The high elevation difference in Tangnaihai probably was the main reason for the less increase in the magnitude of Tmin. In the last decade, smaller magnitude of trend for all temperature variables signified the signal of cooling in the region. Overall, changes of temperature variables had significant spatial and seasonal variations. It implies that seasonal variations of runoff might be greater or different for each sub-basin.     

Effect of data homogenization on estimate of temperature trend: a case of Huairou station in Beijing Municipality

Daily minimum temperature (Tmin) and maximum temperature (Tmax) data of Huairou station in Beijing from 1960 to 2008 are examined and adjusted for inhomogeneities by applying the data of two nearby reference stations. Urban effects on the linear trends of the original and adjusted temperature series are estimated and compared. Results show that relocations of station cause obvious discontinuities in the data series, and one of the discontinuities for Tmin are highly significant when the station was moved from downtown to suburb in 1996. The daily Tmin and Tmax data are adjusted for the inhomogeneities. The mean annual Tmin and Tmax at Huairou station drop by 1.377°C and 0.271°C respectively after homogenization. The adjustments for Tmin are larger than those for Tmax, especially in winter, and the seasonal differences of the adjustments are generally more obvious for Tmin than for Tmax. Urban effects on annual mean Tmin and Tmax trends are ?0.004°C/10 year and ?0.035°C/10 year respectively for the original data, but they increase to 0.388°C/10 year and 0.096°C/10 year respectively for the adjusted data. The increase is more significant for the annual mean Tmin series. Urban contributions to the overall trends of annual mean Tmin and Tmax reach 100% and 28.8% respectively for the adjusted data. Our analysis shows that data homogenization for the stations moved from downtowns to suburbs can lead to a significant overestimate of rising trends of surface air temperature, and this necessitates a careful evaluation and adjustment for urban biases before the data are applied in analyses of local and regional climate change.     

Historical and future changes in maximum and minimum temperature records over Europe

Recent studies examining changes in temperature record frequency over the continental United States have reported that the number of Tmax records has been increasing over the past 50 years and occurring at twice the frequency of Tmin records. In a stationary climate, the number of records should decrease with time as 1/n, where n is the number of years of record-keeping. Here we seek to understand how European temperature records have changed during the late 20th century and how they are expected to change as greenhouse gases increase during the 21st century, using a new ensemble method to filter out the effect of the starting year in the calculation of the records. We find that until 1980, the ratio of Tmax to Tmin records remains close to one, indicating that the climate was relatively stationary. After 1980, there is a distinct positive trend where the observed ratio averages around four during the early part of the 21st century, indicative of a warming trend. We note considerable spatial variability in the observations. Further, the ratio of Tmax to Tmin records set by the year 2100 as simulated by five RCM simulations reaches values of up to several hundred by the end of the 21st century. However, the changes in record frequency vary spatially over Europe. The models project the highest numbers of Tmax records over the Mediterranean during summer, and Scandinavia during the spring and fall. Tmin records decrease most substantially over eastern Europe and western Russia, and the Mediterranean. Our analysis confirms the value of the use of maximum and minimum temperature records in regional climate change studies.     

The identification of distinct patterns in California temperature trends

Regional changes in California surface temperatures over the last 80 years are analyzed using station data from the US Historical Climate Network and the National Weather Service Cooperative Network. Statistical analyses using annual and seasonal temperature data over the last 80 years show distinctly different spatial and temporal patterns in trends of maximum temperature (Tmax) compared to trends of minimum temperature (Tmin). For trends computed between 1918 and 2006, the rate of warming in Tmin is greater than that of Tmax. Trends computed since 1970 show an amplified warming rate compared to trends computed from 1918, and the rate of warming is comparable between Tmin and Tmax. This is especially true in the southern deserts, where warming trends during spring (March?CMay) are exceptionally large. While observations show coherent statewide positive trends in Tmin, trends in Tmax vary on finer spatial and temporal scales. Accompanying the observed statewide warming from 1970 to 2006, regional cooling trends in Tmax are observed during winter and summer. These signatures of regional temperature change suggest that a collection of different forcing mechanisms or feedback processes must be present to produce these responses.     

Changes in daily climate extremes in the arid area of northwestern China

There has been a paucity of information on trends in daily climate and climate extremes, especially for the arid region. We analyzed the changes in the indices of climate extremes, on the basis of daily maximum and minimum air temperature and precipitation at 59 meteorological stations in the arid region of northwest China over the period 1960–2003. Twelve indices of extreme temperature and six indices of extreme precipitation are examined. Temperature extremes show a warming trend with a large proportion of stations having statistically significant trends for all temperature indices. The regional occurrence of extreme cool days and nights has decreased by ?0.93 and ?2.36 days/decade, respectively. Over the same period, the occurrence of extreme warm days and nights has increased by 1.25 and 2.10 days/decade, respectively. The number of frost days and ice days shows a statistically significant decrease at the rate of ?3.24 and ?2.75 days/decade, respectively. The extreme temperature indices also show the increasing trend, with larger values for the index describing variations in the lowest minimum temperature. The trends of Min Tmin (Tmax) and Max Tmin (Tmax) are 0.85 (0.61) and 0.32 (0.17)?°C/decade. Most precipitation indices exhibit increasing trends across the region. On average, regional maximum 1-day precipitation, annual total wet-day precipitation, and number of heavy precipitation days and very wet days show insignificant increases. Insignificant decreasing trends are also found for consecutive dry days. The rank-sum statistic value of most temperature indices exhibits consistent or statistically significant trends across the region. The regional medians after 1986 of Min Tmin (Tmax), Max Tmin (Tmax), warm days (nights), and warm spell duration indicator show statistically more larger than medians before 1986, but the frost days, ice days, cool days (nights), and diurnal temperature range reversed. The medians of precipitation indices show insignificant change except for consecutive dry days before and after 1986.     

Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960–2013

Two homogenized datasets of daily maximum temperature (Tmax), mean temperature (Tm), and minimum temperature (Tmin) series in China have recently been developed. One is CHTM3.0, based on the Multiple Analysis of Series for Homogenization (MASH) method, and includes 753 stations for the period 1960–2013. The other is CHHTD1.0, based on the Relative Homogenization test (RHtest), and includes 2419 stations over the period 1951–2011. The daily Tmax/Tm/Tmin series at 751 stations, which are in both datasets, are chosen and compared against the raw dataset, with regard to the number of breakpoints, long-term climate trends, and their geographical patterns. The results indicate that some robust break points associated with relocations can be detected, the inhomogeneities are removed by both the MASH and RHtest method, and the data quality is improved in both homogenized datasets. However, the differences between CHTM3.0 and CHHTD1.0 are notable. By and large, in CHHTD1.0, the break points detected are fewer, but the adjustments for inhomogeneities and the resultant changes of linear trend estimates are larger. In contrast, CHTM3.0 provides more reasonable geographical patterns of long-term climate trends over the region. The reasons for the differences between the datasets include: (1) different algorithms for creating reference series for adjusting the candidate series—more neighboring stations used in MASH and hence larger-scale regional signals retained; (2) different algorithms for calculating the adjustments—larger adjustments in RHtest in general, partly due to the individual local reference information used; and (3) different rules for judging inhomogeneity—all detected break points are adjusted in CHTM3.0, based on MASH, while a number of break points detected via RHtest but without supporting metadata are overlooked in CHHTD1.0. The present results suggest that CHTM3.0 is more suitable for analyses of large-scale climate change in China, while CHHTD1.0 contains more original information regarding station temperature records.     

Climate changes in the Lhasa River basin,Tibetan Plateau: irrigation-induced cooling along with a warming trend

Characterizing the response of temperature variables to agricultural irrigation is expected to be an important challenge for understanding the full impact of water management on regional climate change. In this paper, the trend analysis and abrupt change test were applied to detect the global warming effect. Then, the quantitative irrigation-induced cooling effects on temperature variables between April and August from 1970 to 2010 in the Lhasa River basin were estimated using historical time series of gridded meteorological records and a map of the area equipped for irrigation. Trends in the maximum temperature (Tmax) were statistically positive, and a significant increasing trend for the minimum temperature (Tmin) was detected at the 0.01 and 0.05 confidence levels. No abrupt changing point of warming was detected in the time series for Tmax. The abrupt changes in Tmin in the irrigation concentration period took place in 1995, 5 years later than the corresponding change in April. Affected by global warming, the increase in temperature was the largest in July and August, when the irrigation-induced cooling effect was also the most significant. The irrigation-induced cooling effect for Tmax and Tmin in April–August (except for June) ranged from − 0.017 to − 0.009 °C/decade and from − 0.011 to − 0.001 °C/decade, respectively, and the cooling effect for diurnal temperature range (DTR) ranged from − 0.011 to 0 °C/decade. The cooling effect on temperature reached above 0.01 °C in July and August, but for the growing seasons, the effect was weak, only 0.001 °C. The Tmax and Tmin trends during the whole growing seasons decreased by both 0.002 °C/decade, respectively, with a 10% increase in irrigation land proportion. Even in July and August, the trends were expected to decrease by about 0.005 °C/decade with a 10% increase in irrigation land proportion. The irrigation-induced cooling effect could partially slow global warming.     

RegCM3 CORDEX东亚试验模拟和预估的中国夏季温度变化

按照CORDEX (COordinated Regional Downscaling Experiment) 计划试验设计要求,利用中国科学院大气物理研究所全球模式FGOALS-g2的数据驱动区域气候模式RegCM3,针对1986~2005年历史气候和2010~2065年RCP8.5排放情景下气候预估,对东亚地区进行了50 km动力降尺度模拟。首先评估了RegCM3模式及驱动模式FGOALS-g2对1986~2005年夏季中国地表气温和极端高温事件的模拟能力,然后比较了两个模式在RCP8.5排放情景下对中国夏季地表气温和极端高温事件预估的变化,重点分析了动力降尺度结果的优势。结果表明,两个模式均能合理再现夏季中国地表气温和极端高温事件的大尺度气候态特征。相对于全球模式,区域模式由于水平分辨率较高,能在刻画地表气温分布的细节上体现出优势。在RCP8.5排放情景下,两个模式预估的三个地表气温指标均显著升高,到21世纪中期 (2046~2065年),两个模式预估的全国平均地表气温增幅相当,气温日较差变化均较小。在FGOALS-g2模式预估中,到21世纪中期,三个地表气温指标的增幅相当,气温日较差没有明显变化,东北和青藏高原的地表气温增幅最大。在RegCM3模式预估中,到21世纪中期,中国大部分地区日最高气温 (Tmax) 增幅大于日最低气温 (Tmin) 增幅,气温日较差增加;而在青藏高原西部,Tmax的增幅较Tmin偏低,气温日较差减小。在RCP8.5排放情景下,两个模式预估的极端高温事件到21世纪中期也显著增加,RegCM3模式预估的极端高温事件全国平均增幅略高于FGOALS-g2模式的预估。在两个模式的预估中,日最高气温最大值 (TXx)、暖昼指数 (TX90p) 和持续暖期指数 (WSDI) 变化的空间分布特征与Tmax相似;和当代相比TX90p增加了60%以上,而WSDI增加了一倍以上。     

Multifractal detrended fluctuation analysis of the δ 18 O record of NGRIP ice core

The multifractal properties and scaling behaviors of the long-term and recent 2000-year δ ¹⁸ O records of NGRIP ice core are investigated by the multifractal detrended fluctuation analysis method. The generalized Hurst exponents, multifractal scaling exponents, and singularity spectrums of two δ ¹⁸ O records are derived to verify the multifractiality of two records. And the multifractal behaviors of two records are obviously different, which may reflect the climate change of the recent 2000-year time is quite different from one of the long-term time. In addition, the probability distribution analysis of two δ ¹⁸ O records is presented to manifest the different multifractality between two δ ¹⁸ O records of NGRIP ice core. Our results will be helpful to research the climate change.     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

广东省40多年来高温天气的时空变化特征

利用广东省76个气象站1962～2004年高温日数资料,通过经验正交函数分解和小波变换方法,对广东省高温天气的时空变化及低频振荡特征进行了研究。结果表明,广东高温天气的空间分布以全省一致型为主,部分年份还呈现南北差异型分布。高温日数波动在20世纪90年代末及以后最剧烈,其次为80年代,在60年代末至70年代初期间最稳定;气候突变发生在1998年。对时间系数进行小波变换发现,前两个特征向量的时间系数均具有显著的周期振荡特征,周期尺度也随时间的变化而变化。     

雪崩、分形与雷暴放电中强闪的自组织演化

强调了雪崩、分形与远离平衡系统自组织演化的联系。利用2003年夏季青藏高原中部地区雷暴放电的地面电场野外观测资料,基于近年来发展的分形及多重分形分析中的去势涨落分析(detrend-ed fluctuation analysis,DFA)方法,对强闪前电场信号的关联及多重分形特征进行了分析,发现强放电前过程具有明显的分形和多重分形特征,多重分形谱与推广的二项倍增串级模式符合。分析在一定程度上表明了雷暴强放电发生的可能的自组织演化性。     

Observed (1970–1999) climate variability in Central America using a high-resolution meteorological dataset with implication to climate change studies

High spatial resolution of precipitation (P) and average air temperature (Tavg) datasets are ideal for determining the spatial patterns associated with large-scale atmospheric and oceanic indexes, and climate change and variability studies, however such datasets are not usually available. Those datasets are particularly important for Central America because they allow the conception of climate variability and climate change studies in a region of high climatic heterogeneity and at the same time aid the decisionmaking process at the local scale (municipalities and districts). Tavg data from stations and complementary gridded datasets at 50 km resolution were used to generate a high-resolution (5 km grid) dataset for Central America from 1970 to 1999. A highresolution P dataset was used along with the new Tavg dataset to study climate variability and a climate change application. Consistently with other studies, it was found that the 1970-1999 trends in P are generally non-significant, with the exception of a few small locations. In the case of Tavg, there were significant warming trends in most of Central America, and cooling trends in Honduras and northern Panama. When the sea surface temperature anomalies between the Tropical Pacific and the Tropical Atlantic have different (same) sign, they are a good indicator of the sign of P (Tavg) annual anomalies. Even with non-significant trends in precipitation, the significant warming trends in Tavg in most of Central America can have severe consequences in the hydrology and water availability of the region, as the warming would bring increases in evapotranspiration, drier soils and higher aridity.     

Extreme Temperature Change of the Last 110 Years in Changchun,Northeast China

In China and East Asia,the long-term continuous observational data at daily resolution are insufficient,and thus there is a lack of good understanding of the extreme climate variation over the last 100 years plus.In this study,the extreme temperature indices defined by ETCCDI(Expert Team on Climate Change Detection and Indices)and local meteorological administrations were analyzed for Changchun City,Northeast China,by using the daily maximum temperature(Tmax)and daily minimum temperature(Tmin)over 1909?2018.The results showed that extreme cold events,such as cold days,cold nights,frost days,icing days,and low temperature days,decreased significantly at rates of?0.41 d(10 yr)^?1,?1.45 d(10 yr)^?1,?2.28 d(10 yr)^?1,?1.16 d(10 yr)?1 and?1.90 d(10 yr)^?1,respectively.Warm nights increased significantly at a rate of 1.71 d(10 yr)^?1,but warm days decreased slightly and the number of high temperature days decreased at a rate of?0.20 d(10 yr)?1.The frequency of cold surge events increased significantly at a rate of 0.25 d(10 yr)^?1,occurring mainly from the mid-1950s to late-1980s.The average Tmax,average Tmin and extreme Tmin increased at rates of 0.09℃(10 yr)^?1,0.36℃(10 yr)^?1 and 0.54℃(10 yr)^?1,respectively;and extreme Tmax decreased significantly at a rate of?0.17℃(10 yr)^?1.In 1909?2018,1951?2018 and 1979?2018,the indices related to cold events decreased,while the trends of the indices related to warm events were different for different periods.     

Time trend analysis of some agroclimatic variables during the last half century over Iran

Theoretical and Applied Climatology - We assessed the trends of precipitation, maximum and minimum temperature (Tmax and Tmin), diurnal temperature range (DTR), water requirement of autumn-planted...     

中国均一化日平均温、最高温和最低温序列1960-2008

Inhomogeneities in the daily mean/maximum/ minimum temperature （Tm/Tmax/Tmin） series from 1960- 2008 at 549 National Standard Stations （NSSs） in China were analyzed by using the Multiple Analysis of Series for Homogenization （MASH） software package. Typical biases in the dataset were illustrated via the cases of Beijing （B J）, Wutaishan （WT）, Urumqi （UR） and Henan （HN） stations. The homogenized dataset shows a mean warming trend of 0.261/0.193/0.344℃/decade for the annual series of Tm/Tmax/Tmin, slightly smaller than that of the original dataset by 0.006/0.009/0.007℃/decade. However, considerable differences between the adjusted and original datasets were found at the local scale. The adjusted Tmin series shows a significant warming trend almost everywhere for all seasons, while there are a number of stations with an insignificant trend in the original dataset. The adjusted Tm data exhibit significant warming trends annually as well as for the autumn and winter seasons in northern China, and cooling trends only for the summer in the middle reaches of the Yangtze River and parts of central China and for the spring in southwestern China, while the original data show cooling trends at several stations for the annual and seasonal scales in the Qinghai, Shanxi, Hebei, and Xinjiang provinces. The adjusted Tmax data exhibit cooling trends for summers at a number of stations in the mid-lower reaches of the Yangtze and Yellow Rivers and for springs and winters at a few stations in southwestern China, while the original data show cooling trends at three/four stations for the annual/autumn periods in the Qinghai and Yunnan provinces. In general, the number of stations with a cooling trend was much smaller in the adjusted Tm and Tmax dataset than in the original dataset. The cooling trend for summers is mainly due to cooling in August. The results of homogenization using MASH appear to be robust; in particular, different groups of stations with consideration of elevation led to minor effects i     

Indices for extreme events in projections of anthropogenic climate change

Indices for temperature and precipitation extremes are calculated on the basis of the global climate model ECHAM5/MPI-OM simulations of the twentieth century and SRES A1B and B1 emission scenarios for the twenty-first century. For model evaluation, the simulated indices representing the present climate were compared with indices based on observational data. This comparison shows that the model is able to realistically capture the observed climatological large-scale patterns of temperature and precipitation indices, although the quality of the simulations depends on the index and region under consideration. In the climate projections for the twenty-first century, all considered temperature-based indices, minimum Tmin, maximum Tmax, and the frequency of tropical nights, show a significant increase worldwide. Similarly, extreme precipitation, as represented by the maximum 5-day precipitation and the 95th percentile of precipitation, is projected to increase significantly in most regions of the world, especially in those that are relatively wet already under present climate conditions. Analogously, dry spells increase particularly in those regions that are characterized by dry conditions in present-day climate. Future changes in the indices exhibit distinct regional and seasonal patterns as identified exemplarily in three European regions.     

Retrieving air humidity,global solar radiation,and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part I: humidity

The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h(q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h(q). However, the relationship between the width of the singularity spectrum (Δα) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.     

Prediction of temperature and precipitation in Sudan and South Sudan by using LARS-WG in future

Global warming has brought great pressure on the environment and livelihood conditions in Sudan and South Sudan. It is desirable to analyze and predict the change of critical climatic variables, such as temperature and precipitation, which will provide valuable reference results for future water resources planning and management in the region. The aims of this study are to test the applicability of the Long Ashton Research Station Weather Generator (LARS-WG) model in downscaling daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in Sudan and South Sudan and use it to predict future changes of precipitation; Tmin and Tmax for nine stations in Sudan and South Sudan are based on the SRA2 scenario of seven General Circulation Models (GCMs) outputs for the periods of 2011–2030, 2046–2065, and 2080–2099. The results showed that (1) the LARS-WG model produces good performance in downscaling daily precipitation and excellent performance in downscaling Tmax and Tmin in the study region; (2) downscaled precipitation from the prediction of seven GCMs showed great inconsistency in these two regions, which illustrates the great uncertainty in GCMs' results in the regions; (3) predicted precipitation in rainy season JJA (June, July, and August) based on the ensemble mean of seven GCMs showed a decreasing trend in the periods of 2011–2030, 2046–2065, and 2080–2099 in Sudan; however, an increasing trend can be found in SON (September, October, and November) in the future; (4) precipitation in South Sudan has an increasing trend in most seasons in the future except in MAM (March, April, and May) season in 2011–2030; and (5) predictions from seven GCMs showed a similar and continuous increasing trend for Tmax and Tmin in all three future periods, which will bring severe negative influence on improving livelihoods and reducing poverty in Sudan and South Sudan.