Spatial patterns and temporal trends of daily precipitation indices in Iran

Spatial patterns of daily precipitation indices and their temporal trends over Iran are investigated using the APHRODITE gridded daily precipitation dataset for the period 1961–2004. The performance and limitations of the gridded dataset are checked against observations at ten rain-gauge stations that are representative of different climates in Iran. Results suggest that the spatial patterns of the indices reflect the role of orography and sea neighborhoods in differentiating central-southern arid and semi-arid regions from northern and western mountainous humid areas. It is also found that western Iran is impacted by the most extreme daily precipitation events occurring in the country, though the number of rainy days has its maximum in the Caspian Sea region. The time series of precipitation indices is checked for long-term trends using the least squares method and Mann-Kendall test. The maximum daily precipitation per year shows upward trends in most of Iran, though being statistically significant only in western regions. In the same regions, upward trends are also observed in the number of wet days and in the accumulated precipitation and intensity during wet days. Conversely, the contribution of precipitation events below the 75th percentile to the annual total precipitation is decreasing with time, suggesting that extreme events are responsible for the upward trend observed in the total annual precipitation and in the other indices. This tendency towards more severe/extreme precipitation events, if confirmed by other datasets and further analyses with longer records, would require the implementation of adequate water resources management plans in western Iran aimed at mitigating the increasing risk of intense precipitation and associated flash floods and soil erosion.     

Extreme daily precipitation: the case of Serbia in 2014

The extreme daily precipitation in Serbia was examined at 16 stations during the period 1961–2014. Two synoptic situations in May and September of 2014 were analysed, when extreme precipitation was recorded in western and eastern Serbia, respectively. The synoptic situation from 14 to 16 May 2014 remained nearly stationary over the western and central Serbia for the entire period. On 15 May 2014, the daily rainfall broke previous historical records in Belgrade (109.8 mm), Valjevo (108.2 mm) and Loznica (110 mm). Precipitation exceeded 200 mm in 72 h, producing the most catastrophic floods in the recent history of Serbia. In Negotin (eastern Serbia), daily precipitation of 161.3 mm was registered on 16 September 2014, which was the maximum value recorded during the period 1961–2014. The daily maximum in 2014 was registered at 6 out of 16 stations. The total annual precipitation for 2014 was the highest for the period 1961–2014 at almost all stations in Serbia. A non-significant positive trend was found for all precipitation indices: annual daily maximum precipitation, the total precipitation in consecutive 3 and 5 days, the total annual precipitation, and number of days with at least 10 and 20 mm of precipitation. The generalised extreme value distribution was fitted to the annual daily maximum precipitation. The estimated 100-year return levels were 123.4 and 147.4 mm for the annual daily maximum precipitation in Belgrade and Negotin, respectively.

     

Variability of daily precipitation over Nigeria

This study identified coherent daily precipitation regions in Nigeria by analyzing the spatial and temporal homogeneity of daily precipitation; investigating the dependence of wet day amount (WDAMT) and percentage of wet day (PWD) on latitude, longitude, elevation and distance from the ocean and finally regionalizing the daily precipitation stations. Non-parametric spatial homogeneity test was carried out on daily precipitation over 23 stations in Nigeria between 1992 and 2000 while the temporal analysis was done from 1971 to 2000. Regression analysis was used to determine the dependence of WDAMT and PWD on latitude, longitude, elevation and distance from the ocean. Principal component and cluster analyses were conducted to regionalize the precipitation stations. Seven homogeneous groups of stations were identified. Elevation explains 19.9 and 4.8 % of the variance in WDAMT and PWD, respectively, while latitude explains 76.2 % of variance in PWD. Eight principal components that explain 63.1 % of the variance in the daily precipitation data were retained for cluster analysis. Precipitation in the six daily precipitation regions that emerged from the cluster analysis is influenced by the Inter-tropical Convergence Zone, latitude, distance from ocean and southwesterlies while the northern region alone is influenced by the African Easterly Wave. In addition, precipitation in all the regions is influenced by topography. Low to medium spatial coherence exists in the precipitation regions. The spatial variations of PWD and WDAMT have implications for agricultural productivity and water resources in different parts of the country.     

Downscaling daily precipitation over the Yellow River source region in China: a comparison of three statistical downscaling methods

Three statistical downscaling methods are compared with regard to their ability to downscale summer (June–September) daily precipitation at a network of 14 stations over the Yellow River source region from the NCEP/NCAR reanalysis data with the aim of constructing high-resolution regional precipitation scenarios for impact studies. The methods used are the Statistical Downscaling Model (SDSM), the Generalized LInear Model for daily CLIMate (GLIMCLIM), and the non-homogeneous Hidden Markov Model (NHMM). The methods are compared in terms of several statistics including spatial dependence, wet- and dry spell length distributions and inter-annual variability. In comparison with other two models, NHMM shows better performance in reproducing the spatial correlation structure, inter-annual variability and magnitude of the observed precipitation. However, it shows difficulty in reproducing observed wet- and dry spell length distributions at some stations. SDSM and GLIMCLIM showed better performance in reproducing the temporal dependence than NHMM. These models are also applied to derive future scenarios for six precipitation indices for the period 2046–2065 using the predictors from two global climate models (GCMs; CGCM3 and ECHAM5) under the IPCC SRES A2, A1B and B1scenarios. There is a strong consensus among two GCMs, three downscaling methods and three emission scenarios in the precipitation change signal. Under the future climate scenarios considered, all parts of the study region would experience increases in rainfall totals and extremes that are statistically significant at most stations. The magnitude of the projected changes is more intense for the SDSM than for other two models, which indicates that climate projection based on results from only one downscaling method should be interpreted with caution. The increase in the magnitude of rainfall totals and extremes is also accompanied by an increase in their inter-annual variability.     

Regional trends in recent precipitation indices in China

Summary Regional characteristics of recent precipitation indices in China were analyzed from a daily rainfall dataset based on 494 stations during 1961 to 2000. Some indices such as precipitation percentiles, precipitation intensity, and precipitation persistence were used and their inter-decadal differences were shown in this study. Over the last 40 years, precipitation indices in China showed increasing and decreasing trends separated into three main regions. A decreasing trend of annual precipitation and summer precipitation was observed from the southern part of northeast China to the mid-low Yellow River valley and the upper Yangtze River valley. This region also showed a decreasing trend in precipitation intensity and a decreasing trend in the frequency of persistent wet days. On the other hand, increasing trends in precipitation intensity were found in the Xinjiang region (northwest China), the northern part of northeast China, and southeast China, mainly to the south of the mid-low Yangtze River. The indices of persistent wet days and strong rainfall have contributed to the increasing frequency of floods in southeast China and the Xinjiang region in the last two decades. Persistent dry days and weakening rainfall have resulted in the increasing frequency of drought along the Yellow River valley including North China. Regional precipitation characteristics and trends in precipitation indices indicate the climate state variations in the last four decades. A warm-wet climate state was found in northwest China and in the northern part of northeast China. A warm-dry climate state extends from the southern part of northeast China to the Yellow River valley, while a cool-wet summer was found in southeast China, particularly in the mid-low Yangtze River valley over the last two decades.     

Variability and probability of annual and extreme precipitation over Serbia and Montenegro

Summary Annual precipitation over Serbia and Montenegro is studied in terms of its variability. The dependence of three selected absolute measures of variability (standard deviation, absolute mean deviation and mean absolute interannual variability) from the mean annual precipitation are examined for the area of interest. Two cases of extreme precipitation in Serbia were analysed using the gamma probability density function and some transformations.     

近20年中国气象灾害损失的初步分析

采用全国气象部门收集的县（区）域行政单元灾情普查资料,结合全国气象站点降水观测资料,分析了1984—2008年中国暴雨及其引发的洪涝灾害的时空演变特点及灾害损失情况,揭示了气候变化及人类活动双重作用下中国暴雨洪涝灾害变化趋势和演变特点,以及暴雨洪涝灾害影响的时空差异性。结果表明：近25 a来中国暴雨日数总体上稍有增加,暴雨强度和暴雨天数的空间分布均表现为南方高于北方,东部高于西部的特点,20世纪90年代中后期为中国暴雨高发期。研究时段内,中国暴雨洪涝灾害造成的直接经济损失呈增加趋势,但直接经济损失占当年GDP的比例则呈下降趋势,平均每年经济损失约为573亿元人民币,损失较高的地区主要集中在中国南方地区,县域年平均损失超过2 000万元的县约占15%,其中有34个县超过亿元。受灾人口呈增加趋势,但因灾死亡人口呈下降趋势;暴雨洪涝灾害对农作物受灾面积和绝收面积的影响均呈微弱上升趋势,年平均作物受灾面积近9.00×10⁶ hm²,作物绝收面积为1.27×10⁶ hm²。

     

北京地区夏季极端降水变化特征及城市化影响

利用1981-2016年京津冀地区174个国家站逐日降水资料,采用百分位方法和线性倾向估计方法对京津冀地区极端降水的时空分布特征及演变趋势进行了分析。结果表明：（1）对于京津冀地区极端降水空间分布,不同百分位降水阈值表现为一致的分布特征,年平均极端降水量、平均极端降水强度与百分位极端降水阈值分布大体一致,而年平均极端降水日数的分布则与其相反。（2）年平均极端降水量在103.6~259.1 mm之间,年平均极端降水日数在3.0~4.0 d之间,平均极端降水强度在大雨到暴雨之间,极端降水量对总降水量贡献达28%以上。（3）极端降水总站次和极端降水日数年变化趋势一致,7月、8月和10月是极端降水较活跃月份。（4）在36 a期间,年平均极端降水量、年平均极端降水日数、平均极端降水强度以及极端降水量对总降水量贡献的变化趋势分布情况基本一致,呈减少趋势的站点均相对较多,年平均极端降水量增减幅度较大,年平均极端降水日数变化在1 d·（10 a）^-1以内,平均极端降水强度和极端降水量对总降水量贡献减少趋势相对明显。

     

Recent precipitation trends over the polar ice sheets

Summary Meteorological and glaciological analyses are integrated to examine the precipitation trends during the last three decades over the ice sheets covering Antarctica and Greenland. For Antarctica, the best data source is provided by glaciologically-measured trends of snow accumulation, and for limited sectors of East Antarctica consistency with precipitation amounts calculated from the atmospheric water balance equation is obtained. For Greenland, precipitation rates parameterized from atmospheric analyses yield the only comprehensive depiction. The precipitation rate over Antarctica appears to have increased by about 5% over a time period spanning the accumulation means for the 1955–65 to 1965–75 periods, while over Greenland it has decreased by about 15% since 1983 with a secondary increase over the southern part of the ice sheet starting in 1977. At the end of the 10-year overlapping period, the global sea-level impact of the precipitation changes over Antarctica dominates that for Greenland and yields a net ice-sheet precipitation contribution of roughly 0.02 mm yr^–1. These changes are likely due to marked variations in the cyclonic forcing affecting the ice sheets, but are only weakly reflected in the temperature regime, consistent with the episodic nature of cyclonic precipitation. These conclusions are not founded on high quality data bases. The importance of such changes for understanding global sea-level variations argues for a modest research effort to collect simultaneous meteorological and glaciological observations in order to describe and understand the current precipitation variations over both ice sheets. Some suggestions are offered for steps that could be taken.With 8 Figures     

Spatial and temporal variability of winter and summer precipitation over Serbia and Montenegro

Summary The main characteristics of the spatial and temporal variability of winter and summer precipitation observed at 30 stations in Serbia and Montenegro were analysed for the period 1951–2000. The rainfall series were examined spatially by means of Empirical Orthogonal Functions (EOF) and temporally by means of the Mann-Kendall test and spectral analysis. The Alexandersson test was used to detect the inhomogeneity of the data set.The EOF analysis gave three winter and summer dominant modes of variations, which explained 89.7% and 70.4% of the variance, respectively. The time series associated with the first pattern showed a decreasing trend in winter precipitation. The spectral analysis showed a 16-year oscillation for the dominant winter pattern, around a 3-year oscillation for the dominant summer pattern, and a quasi-cycle of 2.5 years for the winter third pattern.     

江苏省火箭人工增雨作业指标研究

本文以南京、徐州地区为代表,收集1998-2005历年作业数据,利用数字化天气雷达资料以及对应时次的探空、天气形势等资料,分析每次作业时所处天气系统的位置、天气系统的演变趋势,火箭发射仰角的高低,统计作业效果,就省内不同季节目标云的选择、作业时机、火箭发射角、催化剂量等多项作业指标进行研究,总结出适宜江苏省人工增雨作业技术方法.     

Complexity analysis of the air temperature and the precipitation time series in Serbia

Regional Atmospheric Modeling System (RAMS) was applied to the study of the effect of the topographical altitude of the Tibetan Plateau (TP) on a severe drought event which took place in eastern China from November 2008 to January 2009. Two simulations of this drought event were conducted: a control simulation (CNTRL run) using original model settings and a sensitive simulation (TOPO run), where no change other than to reduce the TP topography by 50 %. The results show that the CNTRL simulation validates RAMS by reproducing this drought event fairly accurately. However, as part of the TOPO simulation, the total heat flux showed a decrease over most parts of the TP, latent heat flux underwent a significant increase over the southeastern TP, contrary to sensible heat, and a universal decrease over eastern China; this led to an increase in precipitation over the southeastern TP and a decrease in precipitation over eastern China. The decrease of total heat flux over the TP is collocated with an anomalous anticyclonic circulation from the TP to the coasts of southeastern China. Changes in atmospheric circulation and low-level water vapor transport pathways were consistent with changes in precipitation. In general, reducing the topographical altitude of the TP worsens drought in eastern China and moreover causes a significant decrease in precipitation over southern China.     

Evaluation of precipitation trends from high-resolution satellite precipitation products over Mainland China

Climate Dynamics - Many studies have reported the excellent ability of high-resolution satellite precipitation products (0.25° or finer) to capture the spatial distribution of precipitation....     

Monthly and daily precipitation trends in the Mediterranean (1950–2000)

Summary The aim of the paper lies in the identification of possible significant linear trends at monthly, seasonal and annual timescales in the Mediterranean during the second half of the 20th century. Monthly and daily records of 63 stations have been used to elaborate several precipitation indices: sum of daily precipitation (SDP) for rainfall >0.1 mm, >10 mm and >95^th percentile, of number of rainy days (RD) >0.1 mm and >10 mm and of mean daily precipitation (MDP) >0.1 mm and >10 mm. For each index the stations have been gathered together by Rotated Principal Component Analyses to determine 8 sub-areas which can be considered as identical for all the timescales at the spatial scale of the research. Trends have been estimated from the scores of each eigenvector retained in all RPCAs. They are mainly non existant or non significant decreasing, even if a few monthly trends appear to be significantly diminishing, primarily during winter months, March in the Atlantic region, October in the Mediterranean Spain, December in the Lions and Genoa Gulfs, January, winter and the year in Greece, winter and the year in Italy and winter in the Near East and increasing in April in the two gulfs. Correlation coefficients between SDP>0.1 mm and other indices have been computed: the significant trends seem mainly related to RD>10 mm, which represents a high percentage of the total rainfall amount. Greece is remarkable: SDP>0.1 mm and >10 mm decrease significantly during January, winter, the rainy season and the entire year whereas SDP>95^th percentile increases significantly, in accordance with the climatic change scenarios for the end of this century as does the decreasing of the total monthly and seasonal rainfall.     

Winter daily precipitation variability over the South West Peninsula of England

Summary Daily precipitation totals for five consecutive winters (1995–99) were obtained for 127 stations in Devon and Cornwall to explore spatial variations in rainfall. This dataset was assembled with the explicit aim of assessing the appropriateness of current arrangements for daily rainfall forecasts in the SW Peninsula of England. Firstly, the extent to which fundamental geographic variables determine precipitation was investigated by correlating each station’s mean wet day amount (WDA) and percentage of wet days (PERWET) with altitude, latitude, longitude and distance from the coast. Altitude emerged as the most important control on precipitation, with a two-variable multiple linear regression model containing altitude and latitude being able to explain 39.3% (29.8%) of the variance in WDA (PERWET) values. The main spatial modes of variability in the region’s precipitation field were identified by using S mode principal components analysis (PCA). Six PCs were statistically significant and explained 83.4% of the geographic variance in precipitation over Devon and Cornwall. The components were interpreted physically by examining the synoptic flow environment (pressure and wind anomalies) on days with high positive and negative PC scores. Explaining 25.1% of the variance, the most important pattern (PC1) depicts a location’s degree of exposure or shelter in a moist, unstable W–NW airflow. The higher PCs describe modes of variability that accentuate rainfall in East Devon (PC2), Cornwall (PC3), Dartmoor and Bodmin Moor (PC4), South Devon (PC5), and North Cornwall and NW Devon (PC6) relative to other areas of the Peninsula. Finally, a winter precipitation regionalisation was derived by applying agglomerative hierarchical cluster analysis to the PC loadings of the significant components. In most cases, the six coherent precipitation regions do not reflect the familiar administrative or topographic areas used for forecasting, suggesting that forecasts issued on such a basis are likely to be insufficiently detailed and misleading.     

中国东部冬季降水的动力结合统计预测方法研究

针对中国东部6个气候关键区,首先,通过相关分析指出,冬季降水既与前期气候因子有关,又受同期大气环流的影响。因此,有必要采用动力与统计相结合的方法进行气候预测研究。然后,从实时预测的角度出发,综合考虑前期预测因子的观测信息和具有数值可预测性的同期气候因子的数值模式结果,使用多元线性回归分析方法就各区域平均冬季降水逐一建立了短期气候预测模型,并在预测模型中考虑了模型结果中系统误差的订正。交叉检验分析结果表明,所建立的各区域预测模型普遍具有较好的预测效果,预测优势主要表现在对冬季降水的变化趋势、年际变化、以及异常符号的预测准确率上。就6个区域平均而言,1982—2008年交叉检验结果与实况间的相关系数和距平同号率分别为0.69和78%,表明该预测思想具有可行性。     

Winter daily precipitation variability over Cumbria, Northwest England

Daily precipitation totals at 55 sites were used to investigate geographic variability in winter (DJF) rainfall over Cumbria, NW England, over an 11-year period. Winter is the wettest season (>800?mm in the mountainous Lake District), with rainfall mechanisms closely linked to North Atlantic forcing. The Lamb weather type catalogue was used to identify rainfall distributions under different wind directions. Precipitation magnitude over Cumbria is much more sensitive to a change in wind direction than the geographic pattern in rainfall, with southwesterly (easterly) winds producing the highest (lowest) spatially averaged daily rainfall totals of 8.2?mm (0.6?mm). S-mode principal components analysis was used to identify the main patterns of precipitation variability. Three principal components (PCs) were retained as being statistically significant (cumulative explained variance for unrotated PCs?=?84.3%), with a correlated PC structure (direct oblimin rotation) best describing the spatial variance in rainfall. PC 1 has a very high index of strength (variance measure?=?40.9), indicating that there is one dominant rainfall pattern. PC 1 shows a gradient between wetter conditions in southwest Cumbria and over the central Lake District and drier conditions in NE Cumbria, and is usually caused by active zonal west to southwest flows. Almost of equal importance to PC 1 is PC 3 (variance measure?=?39.3), which has a more uniform rainfall distribution than PC 1 and is usually caused by fronts stalling over the region. PC 2, which shows an east to west decline in rainfall totals, is much less important than PCs 1 and 3 (variance measure?=?18.6). PC 2??s rainfall pattern can be caused by easterly flows with high pressure over Scandinavia and low pressure over the Continent, or by strong southwesterly flows, with depressions often centred over Scotland. Finally, cluster analysis was carried out to identify precipitation regions for all days and for each wind direction. Clusters were found to be largely stable to changes in wind direction, with stations in the central Lake District often clustered together, thus highlighting the importance of orographic enhancement of rainfall in this region.     

Assessing seasonal precipitation trends in India using parametric and non-parametric statistical techniques

This paper provides an insight into the long-term trends of the four seasonal and annual precipitations in various climatological regions and sub-regions in India. The trends were useful to investigate whether Indian seasonal rainfall is changing in terms of magnitude or location-wise. Trends were assessed over the period of 1954?C2003 using parametric ordinary least square fits and non-parametric Mann?CKendall technique. The trend significance was tested at the 95% confidence level. Apart from the trends for individual climatological regions in India and the average for the whole of India, trends were also specifically determined for the possible smaller geographical areas in order to understand how different the trends would be from the bigger spatial scales. The smaller geographical regions consist of the whole southwestern continental state of Kerala. It was shown that there are decreasing trends in the spring and monsoon rainfall and increasing trends in the autumn and winter rainfalls. These changes are not always homogeneous over various regions, even in the very short scales implying a careful regional analysis would be necessary for drawing conclusions regarding agro-ecological or other local projects requiring change in rainfall information. Furthermore, the differences between the trend magnitudes and directions from the two different methods are significantly small and fall well within the significance limit for all the cases investigated in Indian regions (except where noted).     

The influence of the East Atlantic Oscillation to climate indices based on the daily minimum temperatures in Serbia

In this study, the influence of the East Atlantic Oscillation (EAO) on the climate indices based on the daily minimum temperature at eight stations in Serbia was examined. The following climate indices were analyzed: frost days (FD), cold nights (TN10p), warm nights (TN90p), minimum value of daily minimum temperature (TNn), tropical nights (TR), and cold spell duration indice (CSDI). Analysis of correlation between the East Atlantic Index (EAI) and the geopotential at 500 hPa, as well as between the EAI and climate indices was realized for all seasons and months during the period 1950–2009. Two characteristic situations for the extreme positive and negative values of the EAI were analyzed. Seasonal and monthly trend analyses of climate indices were performed. Decreases of FD and TN10p and increases of TN90p and TR were observed. It was found that the negative correlation prevailed between the EAI and TN10p/FD, and positive one between the EAI and TN90p/TR for all seasons and months. The highest correlation was observed between the EAI and TN90p in February.