Climate change impact on rainfall spatio-temporal variability (Macta watershed case,Algeria)

This work describes the climate change impact study on rainfall patterns in Macta watershed, located in the northwest of Algeria. The monthly rainfall data collection, verification and validation have built a database with 42 stations, each with 42 years of observations from 1970 to 2011. The study of annual total rainfall has identified a downward trend and quantifies the deficits that are within the observation time series. The division of the annual rainfall series into four periods allowed to highlighting the increase in inter-year temporal variability with the coefficient of variation increases from 17 to 27%. The study shows an annual rainfall deficit increment from 13 to 25%. The standard deviation values decrease significantly for the last two periods showing a spatial variability. Multivariate statistical study by the hierarchical clustering method resulted in the formation of station groups indicating the unification of monthly rainfall patterns.     

Analyses of precipitation,temperature and evapotranspiration in a French Mediterranean region in the context of climate change

This study is focused on the western part of the French Mediterranean area, namely the Pyrénées-Orientales and Aude administrative departments. The water resources (surface and groundwater) in the region are sensitive to climate change. The study addresses the question of whether any trend in the annual and monthly series of temperature, rainfall and potential evapotranspiration (PET) already appears at the scale of this region. Two data sources have been used: (a) direct local measurements using the meteorological network; and (b) spatially interpolated data from the French weather service model SAFRAN for the period 1970–2006. The non-parametric Mann–Kendall test was applied to identify significant trends at the local scale and, because of the natural spatial variability of the Mediterranean climate, regional interpretation was also performed. The trends observed in the 13 catchments of interest are consistent with those observed at a larger scale. An increase in annual mean temperature and annual PET was observed throughout the study area, whereas annual precipitation has not exhibited any trend. The monthly scale has revealed strong seasonal variability in trend. The trend for an increase in monthly PET has been observed mainly in the spring, and has not been seen in the coastal areas. A trend for an increase in monthly temperature has been observed in June and in the spring throughout the entire area. Monthly rainfall has been found to decrease in June and increase in November throughout the area. The significant trends observed in rainfall and temperature seem to be consistent between the different data sources.     

西藏参考作物蒸发蒸腾量的时空变异规律

根据西藏高原区38个气象站点自建站到2006年的逐日气象观测资料,利用FAO-56标准Penman-Monteith公式计算各站逐日参考作物蒸发蒸腾量(ET₀)。重点分析了7个站点逐日、逐月ET₀年内变化规律,采用Mann-Kendall法对其月际和年际ET₀进行趋势检验;利用Kriging插值及Surfer8.0空间分析功能,得到西藏高原区年ET₀均值的等值线图,分析了全区年ET₀均值的空间分布特征。结果表明:昌都、林芝和那曲的逐日ET₀在年内变化曲线基本一致,呈现单峰抛物线形状,拉萨、泽当和日喀则的逐日ET₀年内变化趋势基本一致,6～9月变化曲线呈现较快的下降趋势,狮泉河的ET₀呈现单独变化趋势;所有站点的逐月ET₀年内变化规律与逐日ET₀相同,最大值均出现在6月份,最小值出现在12月份;日喀则各月及干湿季ET₀的Mann-Kendall检验大多呈现显著的降低趋势,其次是泽当,呈现增加趋势较多的是林芝;全系列年ET₀均值Mann-Kendall检验呈现降低趋势的站点偏多;西藏高原区年ET₀均值具有东部和中南部高,东北部和东南缘低的空间分布规律。     

Spatial and temporal trends of dust storms across desert regions of Iran

Dust storms are among natural and anthropogenic hazards for socioeconomic resources, especially in desert regions. In recent years, dust storms have become a serious problem, especially in desert regions of Iran. This study investigates temporal and spatial variation of dust storm frequency in desert regions of Iran. The number of dusty days (NDD) are collected from 22 stations across the region. The statistical analysis of NDD time series is carried out to show both spatial and seasonal pattern of dust storm occurrence in the region. The regional map of statistical characteristics indicates a north to south increasing dust storm frequency. The spatial map also reveals higher year-to-year variation in south eastern Iran. The seasonality of NDD shows the highest frequency for summer followed by the spring and autumn seasons. The popular Mann–Kendall and the bootstrap MK test to consider serial correlation are then applied for Trend assessment. Results showed both negative (across the north and northwestern regions) and positive trend (across south and south eastern regions) in the annual and seasonal NDD time series. This north-to-south gradient in the spatial and temporal frequency NDD may arise from harsh dry and gusty winds as well as intense land use change in the south eastern territories of Iran. However, more careful and detailed studies are required to connect environmental conditions to change in NDD frequency.     

TRMM卫星降雨雷达观测的南海降雨空间结构和季节变化

利用热带降雨计划卫星(TRMM)获得的雷达降雨资料,对南海及其周边区域(简称南海地区)降雨的空间分布和季节特征进行了研究。结果表明：南海地区的降雨在空间上分布很不均匀,同时具有显著的季节变化。除了副高活动、季风潮、冬季冷涌和热带低压活动等天气过程,南海周边广泛分布的山地地形对该地区的降雨分布也产生强烈影响,降雨呈现南部高于北部、东部高于西部的分布特征?与CAMP和台站资料相比,PR观测具有更丰富的空间结构,能够更好地体现降雨随时间和空间变化的特征、反映高大的山地地形对降雨分布的影响。     

Spatial contribution of one-day precipitations variability to rainy days and rainfall amounts in Iran

Rainfalls with short persistency are the tangible characteristics of arid and semiarid regions such as Iran. Iran is an arid and semiarid region with dramatic tempo-spatial changes of rainfall. In this regard, the short persistency of rainfall is approximately observed from 1 to 7 days in whole parts, while the greater ones are only separated in eastern parts of Iran. According to the results, the rainfall persistency is ranged from 1 to 45 days, but the maximum amount and rainy days are generated by rainfalls with short persistency. So, the rainfall events with long persistency are considered as an extreme event with extreme variability. One-day precipitations generate the maximum rainy days and rainfall amounts, especially in eastern parts of Iran. Decrease in the one-day precipitations contribution to eastern parts may indicate to decrease in regional precipitation. However, decrease in contribution in western parts may indicate to increased amounts of rainfall at other persistency rates. Our results revealed that the contribution of the one-day precipitation to general rainfall has reductive trends in almost 17.5 % of the whole Iran. The most integrated and significant reductive trend of one-day precipitation contribution to rainfall spreads northeastern and eastern parts of Iran. However, in the western parts of Iran, decreasing one-day precipitation contribution to rainy days affects to increase in the diurnal rainfall. The mentioned variability can be considered as the climate change signals in respect of one-day precipitation.     

Long-term trends of seasonal dusty day characteristics—West Iran

In order to examine the seasonal characteristics of the dust events over western parts of Iran, surface observations from 27 meteorological stations for the period 1951–2014 were analyzed to obtain spatial distributions and temporal variations and trend of dusty day frequency (DDF). Trends of DDF were analyzed by Mann–Kendall and Sen’s estimator of slope nonparametric statistics. Three meteorological stations were selected in north (Tabriz), middle (Kermanshah), and south of the study area (Ahwaz) as reference stations for detecting the regional differences of DDFs. The results showed that DDF is a variable season by season but in general, DDF increases from north to south and from east to west of Iran. The maximum of DDF is monitored in May, June, and July. There are tangible seasonal increasing–decreasing periods in which these changes are logically related with seasonal changes. Regardless of the existence of the maximum DDF in south and southwest of study area, the most intensive increasing DDF trend is calculated in west middle areas. The most widespread and intensive increasing DDF pattern in west of Iran is observed when it is spring. In this case, the dust storms replaced the rainfalls. Distance from dust sources, major movement ways of dust transporting synoptic systems, regional effective wind activity (such as Shamal wind), and arrangement of high mountains are the known factors affecting frequency variation, distribution, and rate of the trend of all the dust phenomena in west of Iran.     

Variability and trends of extreme dry and wet seasonal precipitation in Argentina. A retrospective analysis

The variability in seasonal mean and extreme precipitation is analyzed for several regions of Argentina to the north of 39º S, using long-term monthly time series data which expand from 1860 to 2006. The selected locations can be considered as representative of different climatic regions. This work focuses on the analysis of monthly rainfall distribution, significant seasonal trends, changes in variance and extreme monthly values, in order to establish the magnitude of the seasonal climatic rainfall variability through time for central Argentina. A 40-yr moving window was employed in order to analyze seasonal variability of rainfall extremes. Extremes were computed for different probability levels of a theoretical distribution function over/below the 80th/20th percentile. The gamma distribution was selected among five other theoretical distributions, and the scale and shape parameters were computed using the maximum likelihood estimation (MLE) and the bootstrap method for 1000 resample data sets, as well. Trend analysis was performed for each window on winter and summer means and tested for significance. The use of a moving window allowed detecting the window of maximum absolute values for the trends. Research results show significant temporal shifts in seasonal rainfall distribution and return values (RV) that were computed for different frequencies (once every five, 10 and 20 years). Generally, summer precipitation extremes have become wetter for the whole region. Rainfall amounts for summer wet/dry extremes (W/D) corresponding to the 90th (for W) and 10th (for D) percentiles were subjected to significant increase, but depending on the geographical area this effect spreads slightly differently over records of years. A common-for-all-stations period of such summer increase trend in extreme values spans from the window 1921-1960 to the last window analyzed: 1967-2006. This behavior was not observed for north and west Argentina during winter, except for the region represented by Bahía Blanca, where the 10% D extreme has increased throughout the study period.     

TRMM卫星降雨雷达观测的南海降雨空间结构和季节变化

利用热带降雨计划卫星（TRMM）获得的雷达降雨资料，对南海及其周边区域（简称南海地区）降雨的空间分布和季节特征进行了研究。结果表明：南海地区的降雨在空间上分布很不均匀，同时具有显著的季节变化。除了副高活动、季风潮、冬季冷涌和热带低压活动等天气过程，南海周边广泛分布的山地地形对该地区的降雨分布也产生强烈影响，降雨呈现南部高于北部、东部高于西部的分布特征。与CAMP和台站资料相比，PR观测具有更丰富的空间结构，能够更好地体现降雨随时间和空间变化的特征、反映高大的山地地形对降雨分布的影响。     

Spatio-temporal variability of summer monsoon rainfall over Orissa in relation to low pressure systems

The summer monsoon rainfall over Orissa occurs mostly due to low pressure systems (LPS) developing over the Bay of Bengal and moving along the monsoon trough. A study is hence undertaken to find out characteristic features of the relationship between LPS over different regions and rain-fall over Orissa during the summer monsoon season (June-September). For this purpose, rainfall and rainy days over 31 selected stations in Orissa and LPS days over Orissa and adjoining land and sea regions during different monsoon months and the season as a whole over a period of 20 years (1980-1999) are analysed. The principal objective of this study is to find out the role of LPS on spatial and temporal variability of summer monsoon rainfall over Orissa. The rainfall has been significantly less than normal over most parts of Orissa except the eastern side of Eastern Ghats during July and hence during the season as a whole due to a significantly less number of LPS days over northwest Bay in July over the period of 1980-1999. The seasonal rainfall shows higher interannual variation (increase in coefficient of variation by about 5%) during 1980-1999 than that during 1901-1990 over most parts of Orissa except northeast Orissa. Most parts of Orissa, especially the region extending from central part of coastal Orissa to western Orissa (central zone) and western side of the Eastern Ghats get more seasonal monsoon rainfall with the development and persistence of LPS over northwest Bay and their subsequent movement and persistence over Orissa. The north Orissa adjoining central zone also gets more seasonal rainfall with development and persistence of LPS over northwest Bay. While the seasonal rainfall over the western side of the Eastern Ghats is adversely affected due to increase in LPS days over west central Bay, Jharkhand and Bangladesh, that over the eastern side of the Eastern Ghats is adversely affected due to increase in LPS days over all the regions to the north of Orissa. There are significant decreasing trends in rainfall and number of rainy days over some parts of southwest Orissa during June and decreasing trends in rainy days over some parts of north interior Orissa and central part of coastal Orissa during July over the period of 1980-1999     

Spatial variability analysis of precipitation in northwest Iran

The spatial variability of precipitation was investigated in the northwestern corner of Iran using data collected at 24 synoptic stations from 1986 to 2015. Principal component analysis (PCA) and cluster analysis (CA) were used to regionalize precipitation in the study area. Eleven precipitation variables were averaged and arranged as an input matrix for the R-mode PCA to identify the precipitation patterns. Results suggest that the study area can be divided into four spatially homogeneous sub-zones. In addition, the spatial patterns of annual precipitation were identified by applying the T-mode PCA and CA to the annual precipitation data. The delineated spatial patterns revealed three distinct sub-regions. The resultant maps were compared with the spatial distribution of the rotated principal components (PCs). Results pointed out that the delineated clusters are characterized by different precipitation variability; and using different precipitation parameters can lead to different spatial patterns of precipitation over northwest Iran.     

Trend analysis of hydroclimatological variables in Urmia lake basin using hybrid wavelet Mann–Kendall and Şen tests

This paper investigates monthly, seasonal, and annual trends in rainfall, streamflow, temperature, and humidity amounts at Urmia lake (UL) basin and analyzes the interaction between these variables and UL’s water level fluctuation during the 1971–2013 period. Two new methods including nonparametric hybrid wavelet Mann–Kendall test and ?en’s methodology have been used to determine potential trends in the variables and their dominant periods. The results showed significant decreasing trends in the water level and streamflow series, moderate decreasing trend in the rainfall and relative humidity series, and increasing trends in the observed temperature data. The 8- , 12-month, and 2-year periods were detected as the dominant periods of the variables in monthly, seasonal, and annual timescales, respectively. The results from the interaction analysis revealed that the main factor influencing the water level at UL is decreasing trend in the streamflow series. Both the monthly series of UL’s water level and the streamflow series of the stations indicated two start points of significant decreasing trend in 1973 and 1998. Furthermore, a comparative analysis among the applied methods indicated a good agreement between the results of hybrid wavelet Mann–Kendall test and ?en’s trend analyzing method.     

Trends and the pole tide in Indian tidegauge records

This paper studies tidegauge records of stations on the Indian coastline. An analysis of trends did not reveal a monotonie trend. Trends were seen for limited periods at only five of the eight stations on the Indian coast. A spectral analysis of annual records produced evidence of long period cycles with shorter cycles riding on them. The shorter cycles had a period of 5.0 years. The spectra of monthly records revealed evidence of a pole tide and an annual cycle. The amplitude of the pole tide was estimated to be around 7.5 mm. This was larger than the equilibrium tide. A spectral analysis of monthly rainfall at Bombay, a station on the Indian west coast, also showed a 13.9 month cycle and a (3,1,0) autoregressive model. But the coherence between monthly rainfall and relative sealevel fluctuations was low.     

Trend analysis of rainfall pattern over the Central India during 1901–2010

In the present study, trends of rainfall of the Central India were evaluated in monthly, seasonal, and annual time scales using the Revised Mann-Kendall (RMK) test, Sen’s slope estimator, and innovative trend method (ITM). For this purpose, the monthly rainfall data for 20 stations in Madhya Pradesh (MP) and Chhattisgarh (CG) states in Central India during 1901–2010 was used. The Sen’s slope estimator was utilized for calculating the slope of rainfall trend line. Based on the obtained results of RMK test, there is no significant trend in the stations for the January and October months. The results also showed that for MP, two out of 15 considered stations indicate significant annual trend, while the CG has four out of five stations with significant trend. The results of applying ITM test indicated that most of the stations have decreasing trends in annual (16 stations), summer (16 stations), and monsoon (11 stations) seasons, while the winter (12 stations) and post monsoon (11 stations) seasons generally show increasing trend. Unlike the RMK, the ITM shows significant increasing trend in rainfall of November and December months. The finding of current study can be used for irrigation and water resource management purpose over the Central India.     

Some characteristics of very heavy rainfall over Orissa during summer monsoon season

Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥125 mm) over Orissa during summer monsoon season (June–September) by analysing 20 years (1980–1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa. Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rainfall does not show any significant trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the monsoon months and the season as a whole.     

Interannual and long-term variability of Indian summer monsoon rainfall

Analysis of summer monsoon (June to September) rainfall series of 29 subdivisions based on a fixed number of raingauges (306 stations) has been made for the 108-year period 1871–1978 for interannual and long-term variability of the rainfall. Statistical tests show that the rainfall series of 29 sub-divisions are homogeneous, Gaussian-distributed and do not contain any persistence. The highest and the lowest normal rainfall of 284 and 26 cm are observed over coastal Karnataka and west Rajasthan sub-divisions respectively. The interannual variability (range) varies over different sub-divisions, the lowest being 55 and the highest 231% of the normal rainfall, for south Assam and Saurashtra and Kutch sub-divisions respectively. High spatial coherency is observed between neighbouring sub-divisions; northeast region and northern west and peninsular Indian sub-divisions show oppositic correlation tendency. Significant change in mean rainfall of six sub-divisions is noticed. Correlogram and spectrum analysis show the presence of 14-year and QBO cycles in a few sub-divisional rainfall series.     

Spatial variability of aridity oyer northern India

Spatial variability of aridity over northern India (north of 20°N) is studied by examining variations in the arid area. Area with an objectively determined summer monsoon rainfall (June to September total) of less than 500 mm is identified as arid area. The summer monsoon rainfall of 212 rain-gauges from 212 districts of the region for the period 1871–1984 are used in the analysis. An interesting feature of the arid area series is that it shows decreasing trend from beginning of the present century. The summer monsoon rainfall fluctuations over five subjectively divided zones over northern India are examined to understand the association between rainfall and the arid area variations. The rainfall series for northwest India shows a significant increasing trend and that for northeast India a significant decreasing trend from the beginning of this century. Rainfall fluctuations over the remaining zones can be considered intermediate stages of a systematic spatial change in the rainfall pattern. This suggested that the recent decreasing trend in the arid area is due to a westward shift in the monsoon rainfall activities. From correlation analyses it is inferred that perhaps the recent decreasing trend in the arid area and increasing trend in the monsoon rainfall over northwest India are associated with a warming trend of the northern hemisphere.     

River catchment rainfall series analysis using additive Holt–Winters method

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt–Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010–2012. Most of the forecasts are acceptable.     

Spatially distributed rainfall information and its potential for regional landslide early warning systems

Crucial to most landslide early warning system (EWS) is the precise prediction of rainfall in space and time. Researchers are aware of the importance of the spatial variability of rainfall in landslide studies. Commonly, however, it is neglected by implementing simplified approaches (e.g. representative rain gauges for an entire area). With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on deterministic and geostatistical methods. With kriging usually being a labour-intensive, manual task, a simplified variogram modelling routine was applied for the automated processing of up-to-date point information data. Validation showed quite satisfactory results, yet it also revealed the drawbacks that are associated with univariate geostatistical interpolation techniques which solely rely on rain gauges (e.g. smoothing of data, difficulties in resolving small-scale, highly intermittent rainfall). In the perspective, the potential use of citizen scientific data is highlighted for the improvement of studies on landslide EWS.     

Investigation of spatial variability and pattern analysis of soil properties in the northwest of Iran

Analysis of the spatial variability of soil properties is important to explain the site-specific ecosystems. Spatial patterns of some soil properties such as soil texture, exchangeable sodium percentage (ESP), electrical conductivity (ECe), soil pH and cation exchange capacity (CEC) were analyzed in salt and sodic affected soils in the south of the Ardabil province, in the northwest of Iran, to identify their spatial distribution for performance of a site-specific management. Soil samples were collected from 0 to 30, 30 to 60, 60 to 90, 90 to 120 and 120 to 150 cm soil depths at sampling sites. Data were investigated both statistically and geostatistically on the basis of the semivariogram. The spatial distribution model and spatial dependence level varied in the study area. Among the considered parameters, maximum and minimum spatial variability were observed in EC and pH parameters, respectively. Soil properties showed moderate to strong spatial dependence, except for a few. ECe was strongly spatially dependent in the total soil depth and clay was strongly spatially dependent at the first depth. Sand and pH were moderately spatially dependent for three of the five depths. ESP was strongly spatially dependent and silt was moderate in the total soil depths, except at 90–120 cm depth. Furthermore, CEC had strong spatial dependence for three of the five depths. All geostatistical range values were >1,389 m in this study. It was concluded that the strong spatial dependency of soil properties would lead to extrinsic factors such as bedrock, agricultural pollution, drainage and ground water level.