Multifractal analysis of 1-min summer rainfall time series from a monsoonal watershed in eastern China

Multifractal analysis can provide parameters associated with different scales of rainfall, which may be useful for setting up parsimonious downscaling models of rainfall, or for revealing climate-specific properties. Time series of rain rate with 1-min resolution collected from ten stations over a monsoon watershed in eastern China were used to study the multifractal properties. The power spectra estimated by fast Fourier transform (FFT) and discrete Haar wavelet transform (DWT) showed three scaling regimes: the sub-hourly scaling regime with β?≈?1.2, the scaling regime from 1 h to 1 day with β close to 0.6, and the low-frequency spectra plateau with β?≈?0.1. From the hyperbolic tails of exceeding probability distributions, the estimated values of parameter q _c are in 2–2.5, which were consistent with the critical order of K(q) curves. The statistical moments display two main scaling regimes: the high-frequency regime from 3 min to 5 days and the scaling regime beyond 5 days. The scales of 5–10 days seem a transitional regime. The reason that the regimes, revealed by the power spectra, disagree with the statistical moments may be that both FFT and DWT power spectra have limited abilities of analyzing low-frequency scaling but are sensitive to the properties in high-frequency scales. The H values estimated for the regime of sub-hourly scales are larger than 0.4, and the values for the regime 1 h–1 day are close to 0.1. For the low-frequency scales beyond 1 day, negative H is obtained by DWT power spectra. The parameters of universal multifractal models were also estimated. The values of α for the scaling range of 1 min–5 days are 0.486?±?0.047, and for the low-frequency scaling range, its values are 0.808?±?0.323. For the high- and low-frequency scaling ranges, the values of C ₁ are 0.5 and 0.169, respectively, which is different from the values for daily rainfall series collected at the same rain gages.     

Effects of climate change on annual streamflow using climate elasticity in Poyang Lake Basin, China

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration (PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year^?1, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1–16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by ?10.2 to ?2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed.     

Carbon and water flux responses to physiology by environment interactions: a sensitivity analysis of variation in climate on photosynthetic and stomatal parameters

Sensitivity of carbon uptake and water use estimates to changes in physiology was determined with a coupled photosynthesis and stomatal conductance (g _s) model, linked to canopy microclimate with a spatially explicit scheme (MAESTRA). The sensitivity analyses were conducted over the range of intraspecific physiology parameter variation observed for Acer rubrum L. and temperate hardwood C₃ (C₃) vegetation across the following climate conditions: carbon dioxide concentration 200–700 ppm, photosynthetically active radiation 50–2,000 μmol m^?2 s^?1, air temperature 5–40 °C, relative humidity 5–95 %, and wind speed at the top of the canopy 1–10 m s^?1. Five key physiological inputs [quantum yield of electron transport (α), minimum stomatal conductance (g ₀), stomatal sensitivity to the marginal water cost of carbon gain (g ₁), maximum rate of electron transport (J _max), and maximum carboxylation rate of Rubisco (V _cmax)] changed carbon and water flux estimates ≥15 % in response to climate gradients; variation in α, J _max, and V _cmax input resulted in up to ~50 and 82 % intraspecific and C₃ photosynthesis estimate output differences respectively. Transpiration estimates were affected up to ~46 and 147 % by differences in intraspecific and C₃ g ₁ and g ₀ values—two parameters previously overlooked in modeling land–atmosphere carbon and water exchange. We show that a variable environment, within a canopy or along a climate gradient, changes the spatial parameter effects of g ₀, g ₁, α, J _max, and V _cmax in photosynthesis-g _s models. Since variation in physiology parameter input effects are dependent on climate, this approach can be used to assess the geographical importance of key physiology model inputs when estimating large scale carbon and water exchange.     

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.     

Ground-based GPS measurements: time behavior from half-hour to years

Ground-based GPS and weather stations time series for the period 2010–2012 of precipitable water vapor (PWV), relative humidity (RH), and surface temperature (T) of half-hourly resolution are analyzed to demonstrate their value for dynamical analyses and weather forecasting. Three sample stations in the USA from the SoumiNet network are considered, which have rather continuous data for the last 3 years and a few missing values. Results for the three stations reveal the following features: (1) PWV time behavior is dominated by the annual cycle superimposed on high-frequency fluctuations with missing daily cycle, indicating a prevailing large-scale transport source of precipitable water at these sites; (2) RH is characterized by the daily cycle and high-frequency variability, while the annual cycle is missing; (3) T mainly varies following the annual and diurnal cycles; and (4) all variables show similar scaling properties of their variance spectra, S(f)?～?f ^–β , with a high-frequency regime of red noise type scaling (β?～?2) up to a day and long-term persistence beyond a week (β?～?0.5), with a week-long frequency interval of transition. Detrended fluctuation analysis of relative humidity indicates a clear long-term persistence scaling covering more than three decades. Implications of these findings on weather forecasting and climate modeling are discussed.     

Changes of erosive rainfall for El Niño and La Niña years in the northern Andean highlands of Peru

Information related to rainfall erosivity in the Andes is scarce. This study was carried out to determine the characteristics of rainfall events at the La Encañada watershed, northern Peru, using daily rainfall data from the 1995 to 2000 period that included all the El Niño and Southern Oscillation (ENSO) phases. Three weather stations were installed within the study area, at the top, middle and bottom of the watershed. We analysed the total amount, duration, intensity, kinetic energy and probability of return of rainfall events. In general, 80% of the rainfall events at watershed level had an average rainfall intensity lower than 2.5 mm h^?1 and only 4% had an average intensity larger than 7.5 mm h^?1. Rainfall erosivity registered at the bottom of the watershed was slightly higher than in the rest of the area. The highest intensities were observed during an El Niño year whereas a La Niña year was characterized by the highest amount of total rainfall compared to the other ENSO phases and by the low intensity rain events. Simulations using the WEPP model estimated higher sediment yield and runoff for the bottom of the watershed during a La Niña year versus El Niño or Neutral years. Even when the analysed rainfall data was too limited to conclude erosion and runoff during any ENSO phase, the simulated results showed us the trend of the behaviour of rainfall erosivity under the ENSO phases at different locations.     

Estimation of atmospheric surface layer parameters and numerical simulation using MM5 at Mangalore, West Coast of India

Atmospheric surface layer meteorological observations obtained from 20-m-high meteorological tower at Mangalore, situated along the west coast of India are used to estimate the surface layer scaling parameters of roughness length (z _o) and drag coefficient (C _D), surface layer fluxes of sensible heat and momentum. These parameters are computed using the simple flux–profile relationships under the framework of Monin–Obukhov (M–O) similarity theory. The estimated values of z _o are higher (1.35–1.54 m) than the values reported in the literature (>0.4–0.9 m) probably due to the undulating topography surrounding the location. The magnitude of C _D is high for low wind speed (<1.5 m s^?1) and found to be in the range 0.005–0.03. The variations of sensible heat fluxes (SHF) and momentum fluxes are also discussed. Relatively high fluxes of heat and momentum are observed during typical days on 26–27 February 2004 and 10–11 April 2004 due to the daytime unstable atmospheric conditions. Stable or near neutral conditions prevail after 1700 h IST with negative SHF. A mesoscale model PSU/NCAR MM5 is run using a high-resolution (1 km) grid over the study region to examine the influence of complex topography on the surface layer parameters and the simulated fluxes are compared with estimated values. Spatial variations of the frictional velocity (u _*), C _D, surface fluxes, planetary boundary layer (PBL) height and surface winds are noticed according to the topographic variations in the simulation.     

Nonlinear dynamics of meteorological variables: multifractality and chaotic invariants in daily records from Pastaza, Ecuador

Weather represents the daily state of the atmosphere. It is usually considered as a chaotic nonlinear dynamical system. The objectives of the present study were (1) to investigate multifractal meteorological trends and rhythms at the Amazonian area of Ecuador and (2) to estimate some nonlinear invariants for describing the meteorological dynamics. Six meteorological variables were considered in the study. Datasets were collected on a daily basis from January 1st 2001 to January 1st 2005 (1,460 observations). Based on a new multifractal method, we found interesting fractal rhythms and trends of antipersistence patterns (Fractal Dimension >1.5). Nonlinear time series analyses rendered Lyapunov exponent spectra containing more than one positive Lyapunov exponent in some cases. This sort of hyperchaotic structures could explain, to some extent, larger fractal dimension values as the Kaplan–Yorke dimension was also in most cases larger than two. The maximum prediction time ranged from ξ?=?1.69 days (approximately 41 h) for E/P ratio to ξ?=?14.71 days for evaporation. Nonlinear dynamics analyses could be combined with multifractal studies for describing the time evolution of meteorological variables.     

Evaluation of the antarctic surface wind climate from ERA reanalyses and RACMO2/ANT simulations based on automatic weather stations

A continental scale evaluation of Antarctic surface winds is presented from global ERA-40 and ERA-Interim reanalyses and RACMO2/ANT regional climate model at 55 and 27 km horizontal resolution, based on a comparison with observational data from 115 automatic weather stations (AWS). The Antarctic surface wind climate can be classified based on the Weibull shape factor k _w . Very high values (k _w  > 3) are found in the interior plateaus, typical of very uniform katabatic-dominated winds with high directional constancy. In the coast and all over the Antarctic Peninsula the shape factors are similar to the ones found in mid-latitudes (k _w  < 3) typical of synoptically dominated wind climates. The Weibull shape parameter is systematically overpredicted by ERA reanalyses. This is partly corrected by RACMO2/ANT simulations which introduce more wind speed variability in complex terrain areas. A significant improvement is observed in the performance of ERA-Interim over ERA-40, with an overall decrease of 14 % in normalized mean absolute error. In escarpment and coastal areas, where the terrain gets rugged and katabatic winds are further intensified in confluence zones, ERA-Interim bias can be as high as 10 m s^?1. These large deviations are partly corrected by the regional climate model. Given that RACMO2/ANT is an independent simulation of the near-surface wind speed climate, as it is not driven by observations, it compares very well to the ERA-Interim and AWS-115 datasets.     

Indirect determination of broadband turbidity coefficients over Egypt

Long-term data from diffuse and global irradiances were used to calculate direct beam irradiance which was used to determine three atmospheric turbidity coefficients (Linke T _L , Ångström β and Unsworth–Monteith δ _a ) at seven sites in Egypt in the period from 1981 to 2000. Seven study sites (Barrani, Matruh, Arish, Cairo, Asyut, Aswan and Kharga) have been divided into three categories: Mediterranean climate (MC), desert Nile climate (DNC) and urban climate (UC, Cairo). The indirect method (i.e., global irradiance minus diffuse irradiance) used here allows to estimate the turbidity coefficients with an RMSE% ≤20 % (for β, δ _a and T _L ) and ~30 % (for β) if compared with those estimated by direct beam irradiance and sunphotometeric data, respectively. Monthly averages of T _L , β and δ _a show seasonal variations with mainly maxima in spring at all stations, due to Khamsin depressions coming from Sahara. Secondary maxima is observed in summer and autumn at DNC and MC (Barrani and Arish) stations in summer due to dust haze which prevails during that season and at UC (Cairo) in autumn, due to the northern extension of the Sudan monsoon trough, which is accompanied by small-scale depressions with dust particles. The mean annual values of β, δ _a , and T _L (0.216, 0.314, and 4.6, respectively) are larger in Cairo than at MC stations (0.146, 0.216, and 3.8, respectively) and DNC stations (0.153, 0.227, and 3.8, respectively). Both El-Chichon and Mt. Pinatubo eruptions were examined for all records data at MC, UC and DNC stations. The overburden caused by Mt. Pinatubo’s eruption was larger than El-Chichon’s eruption and overburden for β, and T _L at DNC stations (0.06, and 0.58 units, respectively) was more pronounced than that at MC (0.02, and 0.26, respectively) and UC (0.05 and 0.52 units, respectively) stations. The annual variations in wind speed and turbidity parameters show high values for both low and high wind speed at all stations. The wind directions have a clear effect on atmospheric turbidity, and consequently, largest turbidities occur when the wind carries aerosols from the main particle sources, such as industrial particle sources around Cairo or to some extent from the Sahara surrounding all study stations.     

Changes in daily and monthly rainfall in the Middle Yellow River,China

Highly concentrated precipitation, where a large percentage of annual precipitation occurs over a few days, may include a high risk of flooding and severe soil erosion. Thus, areas with severe erosion such as the Loess Plateau in China are particularly vulnerable to highly concentrated precipitation events due to climate change. In this study, we investigated spatial and temporal patterns in the concentration of rainfall in the Middle Yellow River (MYR) from the last 56 years (1958–2013). We used daily and monthly precipitation data from 26 meteorological stations in the study area to calculate the precipitation concentration index (PCI) and the concentration index (CI). The southern and northern parts of the MYR were characterized by a lower CI with a decreasing trend, while the middle parts had a higher CI with an increasing trend. High PCI values occurred in the southern MYR, while lower PCIs with a more homogenous rainfall distribution were found mainly in the northern parts of the MYR. The annual PCI and CI exhibited positive trends at most stations, although only a minority of stations had significant trends (P < 0.05). At seasonal scales, CI exhibited significantly increasing trends in winter at most stations, while a few stations had significant trends in the other three seasons. These findings provide important reference information to facilitate ecological restoration and farming operations in the study region.     

Rainfall spatial organization and areal reduction factors in the metropolitan area of Barcelona (Spain)

The rainfall spatial organization in the metropolitan area of Barcelona (Spain) has been studied from records of an urban rain gauge network in the period 1994–2009. Using statistical and regional analysis techniques, correlation between data recorded by the different rain gauges has been calculated, and the effective number of independent stations (n _eq) equivalent to the used network has been determined. It has been found out that for durations longer than 20 min, the areal rainfall return period observed for a storm registered by the network approximately decreases by a factor of 1/n _eq in relation to the current point rainfall intensity–duration–frequency relationships for the metropolitan area of Barcelona. Using objective analysis techniques, continuous precipitation fields have been generated on a regular grid with a spatial resolution of 300?×?300 m for the storms registered by the rain gauges from 1994 to 2009, for durations from 10 min to 24 h. The precipitation fields obtained have been useful to estimate the characteristic areal reduction factors in the metropolitan area of Barcelona. A direct relationship has been found between the areal reduction factor for all the area corresponding to the urban rainfall network of Barcelona and the effective number of n _eq for every duration considered.     

Scaling fluctuation analysis and statistical hypothesis testing of anthropogenic warming

Although current global warming may have a large anthropogenic component, its quantification relies primarily on complex General Circulation Models (GCM’s) assumptions and codes; it is desirable to complement this with empirically based methodologies. Previous attempts to use the recent climate record have concentrated on “fingerprinting” or otherwise comparing the record with GCM outputs. By using CO₂ radiative forcings as a linear surrogate for all anthropogenic effects we estimate the total anthropogenic warming and (effective) climate sensitivity finding: ΔT _anth  = 0.87 ± 0.11 K, $\uplambda_{{2{\text{x}}{\text{CO}}_{2} ,{\text{eff}}}} = 3.08 \pm 0.58\,{\text{K}}$ . These are close the IPPC AR5 values ΔT _anth  = 0.85 ± 0.20 K and $\uplambda_{{2{\text{x}}{\text{CO}}_{2} }} = 1.5\!-\!4.5\,{\text{K}}$ (equilibrium) climate sensitivity and are independent of GCM models, radiative transfer calculations and emission histories. We statistically formulate the hypothesis of warming through natural variability by using centennial scale probabilities of natural fluctuations estimated using scaling, fluctuation analysis on multiproxy data. We take into account two nonclassical statistical features—long range statistical dependencies and “fat tailed” probability distributions (both of which greatly amplify the probability of extremes). Even in the most unfavourable cases, we may reject the natural variability hypothesis at confidence levels >99 %.     

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.     

Influence of climate variability on land degradation (desertification) in the watershed of the upper Paraíba River

The study aimed to evaluate the influence of the rainfall and aridity index variability on the process of land degradation (desertification) in order to establish the current degree of increase or decrease in dryness in the watershed of the upper Paraíba River. It included all or part of 18 municipalities, distributed in the western and eastern Cariri regions of Paraíba state. The monthly average values of reference evapotranspiration according to Penman-Monteith method were applied in the annual hydrological balance for obtaining the annual time series of the aridity index for the period from 1950 to 2013. The Mann-Kendall test (MK) was used for trend identification in the annual time series of rainfall and aridity index, at a significance level of α = 0.05. The slope of the trends was obtained by Sen’s method, and the values of rainfall, aridity index, and statistics MK were spatially kriging, to generate thematic maps. The results indicate an increase in rainfall and reduced dryness in the watershed of the upper Paraíba River, conditions that do not contribute to trigger the process of land degradation (desertification), indicating that the cause of this environmental problem is not climatic. Thus, it can be suggested that the observed manifestations of land degradation (desertification) derive much of human than climatic actions. However, there is a trend of increasing dryness and reducing rainfall in the central portion of the watershed, with stronger core in the location of Camalaú. The spatial distribution of rainfall and aridity index shows that minimum values of rainfall coincide with maximum values of the aridity index. Higher values of rainfall were observed in the northwestern portion of the watershed, while the northeast and southeast portions had the lower rainfall values, with the strongest core in the locality of Cabaceiras. The eastern sector of the watershed has high dryness, unlike the western sector, rainier, with minimum values of dryness. In the western portion of the watershed, the aridity index was in the range considered semiarid, with moderate susceptibility to land degradation process. Similarly, in the eastern portion, the dryness stood in the range considered arid, with high susceptibility. The cores with more pronounced dryness correspond to the municipalities of Cabaceiras, Caraúbas, and São João do Cariri.     

Evaluating persistence and identifying trends and abrupt changes in monthly and annual rainfalls of a semi-arid region in Western India

In this study, 43-year (1965–2007) monthly and annual rainfall time series of ten rainfall stations in a semi-arid region of western India are analyzed by adopting three tests for testing normality and by applying autoregressive technique for exploring persistence. Gradual trends are identified by three tests, and their magnitudes are assessed by the Sen’s slope estimator. Also, abrupt changes are detected by using four tests and they are further confirmed by two tests. Box-whisker plots revealed that the rainfalls of June and September are right skewed for all the stations. The annual rainfalls of Bhinder, Dhariawad, and Gogunda stations are found considerably right skewed. The normality tests indicated that the rainfall of July does not deviate from the normal distribution at all the stations. However, the annual rainfall is found non-normal at five stations. The monthly rainfalls of June, July, and August have persistence respectively at three (Mavli, Salumber, and Sarada), two (Kherwara and Sarada), and one (Mavli) stations, whereas the annual rainfall has persistence at Girwa and Mavli stations. Significantly increasing trend is detected at Mavli in the rainfall of July and in the annual rainfall (p value?>?0.05), while the negative trend in August rainfall at Dhariawad is found significant (p value?>?0.10). This study revealed that the presence of serial correlation does not affect the performance of the Mann-Kendall test. Mean values of trend magnitudes for the rainfalls of June, July, August, and September are 0.3, 0.8, ?0.4, and 0.4 mm year^?1, respectively, and the overall mean value for the annual rainfall is 0.9 mm year^?1. It is found that the standard normal homogeneity test and the Pettitt test are biased towards the end of the series to locate a change point. Conversely, the Bayesian test has a tendency to look for a change point in the beginning of time series. Confirmed abrupt changes in the rainfall time series are found in the year 2003 (Bhinder) in June; years 1974 (Mavli) and 1989 (Dhariawad and Salumber) in July; years 1972 (Sarada), 1990 (Dhariawad), and 2003 (Mavli) in August; years 1977 (Dhariawad), 1991 (Sarada), and 2004 (Kotra) in September; and in the year 1972 (Mavli and Sarada stations) in the annual series. It is emphasized that the significantly increasing trend of rainfall may have linkages with climate change and/or variability. Finally, this study recommends use of multiple statistical tests for analyzing hydrologic time series in order to ensure reliable decisions.     

Trends in extreme temperature indices in Huang-Huai-Hai River Basin of China during 1961–2014

Spatial and temporal characteristics of temperature extremes have been investigated in Huang-Huai-Hai (HHH) region based on the daily series of temperature observations from 162 meteorological stations. A total of 11 indices were used to assess the changes of temperature pattern. Linear trend analyses revealed that the daily maximum temperature (TXx) increased at α = 0.05 level with a magnitude of 0.15 °C per decade on the regional scale during the period of 1961–2014. More pronounced warming trend of the daily minimum temperature (TNn) was detected at a rate of 0.49 °C per decade (α = 0.01 level). Consequently, a decreasing trend of the temperature range of TXx and TNn (extreme temperature range) was observed. The frequency of hot days (TXf90) and annual average of warm events (warm spell duration indicator, WSDI) showed significant increasing trends, while that of cold nights (TNf10) and cold events (cold spell duration indicator, CSDI) showed opposite behaviors. Both warm winter (W-W) and hot summer (H-S) series displayed significant increasing trends at α = 0.01 confidence level. The cold winter (C-W) series showed a decreasing trend at α = 0.01 confidence level, while the cool summer (C-S) series showed a nonsignificant decreasing trend that is not passing the 90% confidence level (α = 0.1). Abrupt increments of warm­related extremes (TXx, TXf90, WSDI) have been detected since 1990s, and a steadily decreasing trend of cold related extremes (TNf10, CSDI) was found since 1970s. Ten hot summers out of 11 and nine warm winters out of 10 occurred after 1990s. Altitude has a large impact on spatial pattern of extreme temperature indices, and the urban heat island effect also has an impact on amplitude of variation in extreme temperature. Trend magnitudes are significantly larger at sites with high altitudes for warm­related indices (TXx, TXf90, WSDI), while those involving cold-related indices (TNn, TNf10) are remarkably larger for stations with low altitudes.     

Falling Lake Victoria water levels: Is climate a contributing factor?

Recently, and perhaps most threatening, Lake Victoria water level has been receding at an alarming rate. A recent study suggested the possibility of the expanded hydroelectric power station in Uganda. However, since the lake receives 80% of its refill through direct rainfall and only 20% from the basin discharge, climatic contributions cannot be ignored, since the 80% water is directly dependant on it. It is therefore necessary to investigate climatic contribution to the declining Lake Victoria water level observed over a long period, i.e., 30 years. This contribution uses 30 years period anomalies for rainfall, river discharge and lake level changes of stations within Lake Victoria basin to analyse linear and cyclic trends of climate indicators in relation to Lake levels. Linear trend analysis using the Student’s t test indicate a decreasing pattern in rainfall anomalies, with the slope being statistically similar to those of water levels at both Kisumu, Maziba and Jinja stations for the same period of time (1976–1999), thus showing a strong correlation. On the other hand, cyclic trend analysis using Discrete Fourier Transform (DFT) shows cyclic period of water level to coincide with those of droughts and rainfall. The strong relationship between climatic indicators of drought and rainfall on one-hand and lake levels on the other hand signifies the need to incorporate climate information in predicting, monitoring and managing lake level changes.     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.