Trend and homogeneity analysis in temperature and rainfall series in western Black Sea region,Turkey

Theoretical and Applied Climatology - This paper includes a study which applied homogeneity and trend tests on time series of monthly mean temperature and monthly total rainfall recorded in the...     

Regional precipitation trend analysis at the Langat River Basin,Selangor, Malaysia

Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982–2011 were examined at the 95 % level of significance using the regional average Mann–Kendall (RAMK) test and the regional average Mann–Kendall coupled with bootstrap (RAMK–bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km?×?5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.     

1961—2008年淮河流域气温和降水变化趋势

利用淮河流域170个地面气象观测站观测数据,统计分析了淮河流域1961—2008年间气温和降水的时空变化趋势。结果表明:48 a间淮河流域年平均气温呈显著上升趋势,冬季平均气温的增温幅度最大,春、秋次之;年极端最低气温亦呈显著上升趋势,年极端低温日数(满足该站极端低温阈值)则呈明显下降趋势;流域西北部年极端最高气温呈显著下降趋势,流域西部年极端高温日数(满足该站极端高温阈值)呈显著下降趋势;降水量总体变化趋势未通过统计检验,但1990s开始,秋季降水量呈下降趋势,2000年之后年降水量明显增加,夏季降水量亦增加;春季和秋季降水日数呈显著下降趋势,夏季和冬季无明显变化。     

Homogeneity tests and non-parametric analyses of tendencies in precipitation time series in Keszthely,Western Hungary

This study aims to investigate the precipitation trends in Keszthely (Western Hungary, Central Europe) through an examination of historical climate data covering the past almost one and a half centuries. Pettitt’s test for homogeneity was employed to detect change points in the time series of monthly, seasonal and annual precipitation records. Change points and monotonic trends were analysed separately in annual, seasonal and monthly time series of precipitation. While no break points could be detected in the annual precipitation series, a significant decreasing trend of 0.2–0.7 mm/year was highlighted statistically using the autocorrelated Mann-Kendall trend test. Significant change points were found in those time series in which significant tendencies had been detected in previous studies. These points fell in spring and winter for the seasonal series, and October for the monthly series. The question therefore arises of whether these trends are the result of a shift in the mean. The downward and upward shift in the mean in the case of spring and winter seasonal amounts, respectively, leads to a suspicion that changes in precipitation are also in progress in these seasons. The study concludes that homogeneity tests are of great importance in such analyses, because they may help to avoid false trend detections.     

Performance of gridded precipitation products in the Black Sea region for hydrological studies

Theoretical and Applied Climatology - Gridded precipitation products are becoming good alternative data sources for regions with limited weather gauging stations. In this study, four climate...     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.     

Analysis of the series of precipitation at Padova,Italy

The series of rainfall at Padova, Italy, for the years 1725–1981, is among the longest in the world. This paper concerns itself with both the history and analysis of the data: in fact operational procedures, rain gauges, sites and data quality have been carefully investigated since the beginning of the series and are herewith described. Afterwards, seasonal variations, trends, periodicities, vacillations and recurrence intervals of the frequency, precipitation amount and intensity of the monthly totals are discussed. From this analysis, the seasonal variation and a secular trend are well evident; the periodicities are generally modest and not well defined; the vacillations appear to be recurrent through-out the entire series. In conclusion, the analysis of this long series may be a useful tool not only for helping in the practical utilization of the rainfall, but also for gaining an insight into the possible mechanisms of climatic fluctuations.     

Analysis of the long-term precipitation series at Athens,Greece

In this paper, the characteristics of the long-term precipitation series at Athens (1858–1985) have been statistically analyzed. This study covers both the history and the analysis of the data. The ten-year mean amounts, the monthly and annual amounts averaged over the intervals 1858–1890, 1891–1985, 1951–1980, 1858–1985, the mean number of hours of precipitation and the precipitation intensity are given. The analysis of long-term time series of climatic data (in particular precipitation) is a useful tool for the study of past climate. Different statistical techniques are used in order to depict monthly, seasonal and annual variations, as well as trends, periodicities and recurrence intervals of the amount, intensity and number of precipitation days. The analysis reveals many interesting characteristics. These characteristics of the precipitation regime are extended to a time scale from seasonal variation to a semi-secular trend. The study of such long-term series may be helpful not only in practical applications of rainfall, but also for explaining the possible physical or anthropogenic mechanisms of climatic fluctuations and tendencies. The series of precipitation at Athens is one of the longest in south-eastern Europe.     

Spatiotemporal variations of precipitation regimes across Yangtze River Basin,China

Daily precipitation data during the period of 1960 to 2005 from 147 rain gauging stations over the Yangtze River Basin are analyzed to investigate precipitation variations based on precipitation indices and also consecutive rainfall regimes in both space and time. Results indicate decreasing annual/monthly mean precipitation. Distinct decreases in rainfall days are observed over most parts of the Yangtze River Basin, but precipitation intensity is increasing over most parts of the Yangtze River Basin, particularly the lower Yangtze River Basin. Besides, durations of precipitation regimes are shortening; however, the fractional contribution of short-lasting precipitation regimes to the total precipitation amount is increasing. In this sense, the precipitation processes in the Yangtze River Basin are dominated by precipitation regimes of shorter durations. These results indicate intensified hydrological cycle reflected by shortening precipitation regimes. This finding is different from that in Europe where the intensifying precipitation changes are reflected mainly by lengthening precipitation regimes, implying different regional responses of hydrological cycle to climate changes. The results of this study will be of considerable relevance in basin-scale water resources management, human mitigation of natural hazards, and in understanding regional hydrological responses to changing climate at regional scales.     

浙江省1901—2017年降水序列构建及变化特征分析

基于通过均一性检验的历史观测资料和GPCC格点降水数据,采用逐步回归方法,构建了可以代表浙江省的1901—2017年年降水序列,并通过Morlet小波分析、MK检验、气候趋势等分析了浙江百年降水变化特征。结果表明：浙江68个台站1951—2017年月降水序列数据质量较好,均通过RHtest均一性检验。交叉检验表明,采用逐步回归方法区别台站资料长度建立的最优拟合方程组,能很好地反演浙江68个台站1901—2013年年降水情况。1901—2017年浙江省年降水量无明显线性变化趋势,但存在56 a和35 a两个变化主周期,在1960年前后全省降水由多雨期向少雨期突变。1901—2017年浙江降水气候倾向率呈东北高西南低的分布特征,各地数值分布在-15.6~19.1 mm/10a之间;平均相对变率呈北低南高的分布特征,各地数值分布在11.1%~20.2%之间。     

1960—2018年辽河流域日降水集中程度分析

基于1960-2018年的日降水资料,计算辽河流域降水集中指数（CI）,分析日降水集中程度的时空特征。结果表明：降水集中指数CI可以有效描述辽河流域降水集中程度,辽河流域年CI指数平均为0.67,降水集中程度总体呈现出东部和西部低、南部和北部高的鞍型空间分布特征;夏季降水集中程度最高,各站点季平均CI指数为0.65,空间分布与年分布较一致,冬季平均CI指数最低,为0.60,由东南向西北递减;研究时段内年CI指数表现为不显著的减小趋势,其中东部区域减小的趋势最大;各子区域年CI指数平均变化周期为3 a左右,其中1985年以前,变化周期较短,在2 a左右,1985年以后,变化周期超过3 a。     

Detection of changes in the summer precipitation time series of the region Emilia-Romagna, Italy

Summary  The main characteristics of the spatial and temporal variability of summer precipitation observed in 40 rainfall stations of the Emilia-Romagna region in northern Italy, are analysed for the period 1922 to 1995. Non-parametric tests and Empirical Orthogonal Function (EOF) analysis were used as tools in order to achieve the paper’s objective. The Pettitt and Mann-Kendall tests detect shift points and trends in the precipitation time series, respectively, while the EOF analysis reveals the main characteristics of spatial variability. The Standard Normal Homogeneity Test (SNHT) was used to detect the inhomogeneity of the data set. Almost all stations exhibit an increasing trend with a systematic significant upward shift around 1962. The climate signal is more significant in the north-western, central and north-eastern part of the region, and the spatial extension strongly depends on the network density and the time period analysed. The change in summer precipitation is mainly due to a change during August and is confirmed by the SNHT test which does not reveal an inhomogeneity in the series. The first EOF pattern indicates that a common large-scale process could be responsible for summer precipitation variability in the Emilia-Romagna region. The second EOF pattern shows an opposite sign of climate variability between north-western and south-eastern areas. The Apennine mountains show the largest climate variability in the summer precipitation field. Received March 8, 2000 Revised July 17, 2000     

Dependence of heavy precipitation and the wind speed on the altitude of location of meteorological stations on the Black Sea coast of Krasnodar krai

Studied is the dependence of the frequency of severe weather phenomena (the wind and precipitation) on the altitude of the location of meteorological stations above the sea level for the period from 1984 to 2009. Obtained is the station distribution of probability of the formation of the mentioned phenomena for the warm and cold seasons.     

Application of Markov models to area-average daily precipitation series and interannual variability in seasonal totals

This paper examines the success of various Markov-chain models of daily precipitation series in reproducing the characteristics of area-average rainfall in Britain. The first model considered is the standard twos-tate first-order Markov renewal process coupled to an amount model using the incomplete -probability distribution. We find that variability of seasonal totals and autocorrelation of daily amounts are both too small in this model, compared with observations. These are serious deficiencies, often overlooked, and possibly related. We proceed to consider models involving Markov chains of higher (temporal) order and many states, both of which generalizations may increase autocorrelation. A second-order two-state model is no better than the first-order, but a first-order many-state model captures a high fraction of the seasonal variability, because use of many states improves the model's representation of spells of heavy precipitation, which appear to have a considerable influence on the seasonal variance. Better still is a second-order many-state model, a type which, to our knowledge, has not previously been investigated. We suggest that the best model would have a continuum of states, rather than a discrete set. Our conclusion is that a large proportion of seasonal variability may be explained in terms of the average daily structure, but there may be a residual component caused by processes operating on longer time-scales and possibly predictable with reference to these. Reproduction of long-period (e.g. monthly or seasonal) variance and of the structure of daily autocorrelation provide crucial tests of stochastic weather generators, and we recommend that models which fail to simulate these statistics realistically be used only with great caution.     

Sensitivity of simulated temperature,precipitation, and global radiation to different WRF configurations over the Carpathian Basin for regional climate applications

In this study, the Weather Research and Forecasting (WRF) model is used to produce short-term regional climate simulations with several configurations for the Carpathian Basin region. The goal is to evaluate the performance of the model and analyze its sensitivity to different physical and dynamical settings, and input data. Fifteen experiments were conducted with WRF at 10 km resolution for the year 2013. The simulations differ in terms of configuration options such as the parameterization schemes, the hydrostatic and non-hydrostatic dynamical cores, the initial and boundary conditions (ERA5 and ERA-Interim reanalyses), the number of vertical levels, and the length of the spin-up period. E-OBS dataset 2 m temperature, total precipitation, and global radiation are used for validation. Temperature underestimation reaches 4–7 °C for some experiments and can be reduced by certain physics scheme combinations. The cold bias in winter and spring is mainly caused by excessive snowfall and too persistent snow cover, as revealed by comparison with satellite-based observations and a test simulation without snow on the surface. Annual precipitation is overestimated by 0.6–3.8 mm day⁻¹, with biases mainly accumulating in the period driven by large-scale weather processes. Downward shortwave radiation is underestimated all year except in the months dominated by locally forced phenomena (May to August) when a positive bias prevails. The incorporation of downward shortwave radiation to the validation variables increased the understanding of underlying problems with the parameterization schemes and highlighted false model error compensations.

     

1978—2019年鄱阳湖流域小时强降水气候变化特征

利用鄱阳湖流域79个国家气象站逐时降水资料,采用Sen斜率估计、Mann-Kendall检验、小波分析等统计诊断方法,分析了1978—2019年鄱阳湖流域小时强降水的时空变化特征.结果表明:1)鄱阳湖流域小时强降水量及其对总降水贡献率呈现显著的增加趋势,小时强降水时数增加显著而强度则几乎无变化.2)鄱阳湖流域小时强降水量主要呈现准4—5 a短周期变化.3)鄱阳湖流域小时强降水在6月出现次数最多,8月的小时强降水贡献率最大;4—9月小时强降水量和降水时数均呈增加趋势,但3月两者均呈现减少趋势.4)鄱阳湖流域小时强降水日变化分布呈现双峰结构,16—20时是主峰时段,06—09时为次峰时段.5)鄱阳湖流域小时强降水量分布主要呈现"东多西少"特征,且部分强降水量中心呈现增长趋势,需引起足够重视.