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1.
Urbanisation has burdened cities with many problems associated with growth and the physical environment. Some of the urban locations in India are becoming increasingly vulnerable to natural hazards related to precipitation and flooding. Thus it becomes increasingly important to study the characteristics of these events and their physical explanation. This work studies rainfall trends in Delhi and Mumbai, the two biggest Metropolitan cities of Republic of India, during the period from 1951 to 2004. Precipitation data was studied on basis of months, seasons and years, and the total period divided in the two different time periods of 1951–1980 and 1981–2004 for detailed analysis. Long-term trends in rainfall were determined by Man-Kendall rank statistics and linear regression. Further this study seeks for an explanation for precipitation trends during monsoon period by different global climate phenomena. Principal component analysis and Singular value decomposition were used to find relation between southwest monsoon precipitation and global climatic phenomena using climatic indices. Most of the rainfall at both the stations was found out to be taking place in Southwest monsoon season. The analysis revealed great degree of variability in precipitation at both stations. There is insignificant decrease in long term southwest monsoon rainfall over Delhi and slight significant decreasing trends for long term southwest monsoon rainfall in Mumbai. Decrease in average maximum rainfall in a day was also indicated by statistical analysis for both stations. Southwest monsoon precipitation in Delhi was found directly related to Scandinavian Pattern and East Atlantic/West Russia and inversely related to Pacific Decadal Oscillation, whereas precipitation in Mumbai was found inversely related to Indian ocean dipole, El Ni?o- Southern Oscillation and East Atlantic Pattern.  相似文献   

2.
Rainfall is a principal element of the hydrological cycle and its variability is important from both the scientific as well as practical point of view. Wavelet regression (WR) technique is proposed and developed to analyze and predict the rainfall forecast in this study. The WR model is improved combining two methods, discrete wavelet transform and linear regression model. This study uses rainfall data from 21 stations in Assam, India over 102 years from 1901 to 2002. The calibration and validation performance of the models is evaluated with appropriate statistical methods. The root mean square errors (RMSE), N-S index, and correlation coefficient (R) statistics were used for evaluating the accuracy of the WR models. The accuracy of the WR models was then compared with those of the artificial neural networks (ANN) models. The results of monthly rainfall series modeling indicate that the performances of wavelet regression models are found to be more accurate than the ANN models.  相似文献   

3.
Mann?CKendall non-parametric test was employed for observational trend detection of monthly, seasonal and annual precipitation of five meteorological subdivisions of Central Northeast India (CNE India) for different 30-year normal periods (NP) viz. 1889?C1918 (NP1), 1919?C1948 (NP2), 1949?C1978 (NP3) and 1979?C2008 (NP4). The trends of maximum and minimum temperatures were also investigated. The slopes of the trend lines were determined using the method of least square linear fitting. An application of Morelet wavelet analysis was done with monthly rainfall during June?CSeptember, total rainfall during monsoon season and annual rainfall to know the periodicity and to test the significance of periodicity using the power spectrum method. The inferences figure out from the analyses will be helpful to the policy managers, planners and agricultural scientists to work out irrigation and water management options under various possible climatic eventualities for the region. The long-term (1889?C2008) mean annual rainfall of CNE India is 1,195.1?mm with a standard deviation of 134.1?mm and coefficient of variation of 11%. There is a significant decreasing trend of 4.6?mm/year for Jharkhand and 3.2?mm/day for CNE India. Since rice crop is the important kharif crop (May?COctober) in this region, the decreasing trend of rainfall during the month of July may delay/affect the transplanting/vegetative phase of the crop, and assured irrigation is very much needed to tackle the drought situation. During the month of December, all the meteorological subdivisions except Jharkhand show a significant decreasing trend of rainfall during recent normal period NP4. The decrease of rainfall during December may hamper sowing of wheat, which is the important rabi crop (November?CMarch) in most parts of this region. Maximum temperature shows significant rising trend of 0.008°C/year (at 0.01 level) during monsoon season and 0.014°C/year (at 0.01 level) during post-monsoon season during the period 1914?C2003. The annual maximum temperature also shows significant increasing trend of 0.008°C/year (at 0.01 level) during the same period. Minimum temperature shows significant rising trend of 0.012°C/year (at 0.01 level) during post-monsoon season and significant falling trend of 0.002°C/year (at 0.05 level) during monsoon season. A significant 4?C8?years peak periodicity band has been noticed during September over Western UP, and 30?C34?years periodicity has been observed during July over Bihar subdivision. However, as far as CNE India is concerned, no significant periodicity has been noticed in any of the time series.  相似文献   

4.
In this work we apply the wavelet transform to the Pelotas (southern Brazil) total annual rainfall series (1894–1995). Classical, wavelet and cross-wavelet analyses were performed in the El Niño Southern Oscillation (ENSO), Quasi-Biennial Oscillation (QBO), sunspot number (Rz) and Pelotas rainfall time series. Classical spectral analysis for Pelotas has shown a large number of short periods – between 2.2–5.6 years (yr) and periods at 8.9, 11.7 and 24.9 yr. Further, we have found that the Pelotas rainfall wavelet spectrum shows the most significant periodicities around 2–8 yr, but they have an intermittent character. Cross-wavelet spectrum showed that: rainfall and QBO series are correlated at 2–3 yr (QBO) scales and this cross-power is continuous along the time series interval; rainfall and SOI have higher cross-power around 4–8 yr, but this signal is sporadic; rainfall and sunspot number (Rz) showed higher cross-power around the 11-yr solar cycle period, but this cross-power is sporadically high and low; finally, the rainfall cross-spectrum with the double sunspot number (Rz22) revealed a high cross-power around 20–22 yr which is more persistent in duration, compared to the 11-yr period. These wavelet results are compared with classical spectral analysis and with previous work results. We concluded that the phenomenon that influences most of Pelotas rainfall variability is ENSO, but only a minor part of the variance (～30%) can be described by a simple multi-linear dependence on solar/ENSO/QBO phenomena, this result could imply that non-linear coupling among sun and internal climatic variability (QBO, ENSO) has an important role in the local/regional climate variations.  相似文献   

5.
In order to study the imprint of solar and ENSO signals on terrestrial archives, the wavelet spectrum analysis was applied to solar-geophysical indices and tree ring data. Time series of Sunspot Number (SSN), southern oscillation index (SOI) and tree-ring indices from Southern Brazil, for the period 1876–1991, were used in this work. The 11-year solar cycle was present during the whole period in tree ring data, being more intense during 1930–1980, in agreement with an earlier study that was performed for thesame region but a different time range (1836–1996). ENSO effects on treering data from Southern Brazil were studied by the first time in this work using wavelet analysis. Short-term variations, between 2–5 years, arealso present in tree ring data. This represents the signature of ENSO events and was also observed in the SOI, as expected. The cross-wavelet spectrum analysis shows that both solar and climatic factors are recorded in tree ring data.  相似文献   

6.
中国雨季的一种客观定量划分   总被引：5，自引：0，他引：5  
黄琰  张人禾  龚志强  冯爱霞 《气象学报》2014,72(6):1186-1204
从客观分析角度出发,利用有序样本最优分割法对中国610个台站的气候平均（1961—2010年）候降水序列进行有序分割,给出中国不同区域的雨季定量划分。根据中国13个区域候降水量的气候平均值分布特征,并基于有序样本最优分割法的划分结果需同时满足分割段内波动小、段间差异大的要求,确定了各区域的合理分割数,通过制定3种雨季划分方案,对中国区域雨季进行了细致的定量划分。第1种方案将全年降水划分为雨季和旱季,结果表明,雨、旱两季差异明显的地区出现在华南西部沿海和新疆邻近区域;第2种方案将全年降水划分为雨季相对干期、雨季相对湿期和旱季3个降水阶段,这种特征出现的区域为华南大部分地区、江南地区、长江中下游地区、西南地区东部和南部,以及西北地区中东部;第3种方案将全年降水划分为春雨季、主雨季、秋雨季和旱季,出现这种特征的区域为长三角及淮河流域、黄淮和华北地区、东北地区、西北地区中部、内蒙古地区西部、青藏高原中东部及其以东地区。与已有的中国不同区域降水特征研究结果的比较表明,有序样本最优分割法不仅对中国雨季的划分客观有效,且其划分结果合理并具有明确的气象意义。  相似文献   

7.
Analysis of the All-India summer monsoon (June to September) rainfall for the period 1871 to 1978 has been made in order to understand the interannual and long-term variability of the monsoon. On a country level, India receives 85.31 cm mean monsoon rainfall which is 78%; of the annual rainfall. The coefficient of variation of monsoon rainfall at the country level is 9.5%;. The highest and lowest rainfall country level were observed in the years 1961 and 1877 respectively, the range being 41 cm about 48%; of the long term average. There are 13/9 years of large-scale deficit/excess in the 108-yr period. There is a continuous rise in the 10-yr mean rainfall from 1899 to 1953. There are four major climatic rainfall periods in the series. Correlogram and spectrum analysis showed significant 14-yr and 2.8-yr cycles respectively in 108-yr series; however detailed examination indicated that these cycles have developed during the last 30 yr of the data period.  相似文献   

8.
Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung–Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA–GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated.  相似文献   

9.
Iranian rainfall series analysis by means of nonparametric tests   总被引：1，自引：0，他引：1  
The study of the trends and fluctuations in rainfall has received a great deal of attention, since changes in rainfall patterns may lead to floods or droughts. The objective of this study was to analyze the annual, seasonal, and monthly rainfall time series at seven rain gauge stations in the west of Iran for a 40-year period (from October 1969 to September 2009). The homogeneity of the rainfall data sets at the rain gauge stations was checked by using the cumulative deviations test. Three nonparametric tests, namely Kendall, Spearman, and Mann–Kendall, at the 95 % confidence level were used for the trend analysis and the Theil–Sen estimator was applied for determining the magnitudes of the trends. According to the homogeneity analysis, all of the rainfall series except the September series at Vasaj station were found to be homogeneous. The obtained results showed an insignificant trend in the annual and seasonal rainfall series at the majority of the considered stations. Moreover, only three significant trends were observed at the February rainfall of Aghajanbolaghi station, the November series of Vasaj station, and the March rainfall series of Khomigan station. The findings of this study on the temporal trends of rainfall can be implemented to improve the water resources strategies in the study region.  相似文献   

10.
Summary Indian monsoon rainfall data is shown to be decomposable into six empirical time series, called intrinsic mode functions. This helps one to identify the first empirical mode as a nonlinear part and the remaining as the linear part of the data. The nonlinear part is handled by artificial neural network (ANN) techniques, whereas the linear part is amenable for modeling through simple regression concepts. It is found that the proposed model explains between 75 to 80% of the interannual variability (IAV) of eight regional rainfall series considered here. The model is efficient in statistical forecasting of rainfall as verified on an independent subset of the data series. It is demonstrated that the model is capable of foreshadowing the drought of 2002, with the help of only antecedent data. The statistical forecast of All India rainfall for the year of 2004 is 80.34 cms with a standard deviation of 3.3 cms. This expected value is 94.25% of the longterm climatic average.  相似文献   

11.
B. G. Hunt 《Climate Dynamics》2014,42(9-10):2271-2285
Output from a multi-millennial control simulation of the CSIRO Mark 2 coupled model has been used to investigate quantitatively the relation between the Indian summer monsoon rain and El Nino/Southern Oscillation events. A moving window correlation between these two features revealed marked interannual and multi-decadal variability with the correlation coefficient varying between ?0.8 and +0.2. This suggests that current observations showing a decline in this correlation are due to natural climatic variability. A scatter diagram of the anomalies of the Indian summer monsoon rainfall and NINO 3.4 surface temperature showed that in almost 40 % of the cases ENSO events were associated with rainfall anomalies opposite to those implied by the climatological correlation coefficient. Case studies and composites of global distributions of surface temperature and rainfall anomalies for El Nino (or La Nina) events highlight the opposite rainfall anomalies over India that can result from very similar ENSO surface temperature anomalies. Composite differences are used to demonstrate the unique sensitivity of Indian summer monsoon rainfall anomalies to ENSO events. The problem of predicting such anomalies is discussed in relation to the fact that time series of the monsoon rainfall, both observed and simulated, consist of white noise. Based on the scatter diagram it is concluded that in about 60 % of the cases seasonal or annual prediction of monsoon rainfall based on individual ENSO events will result in the correct outcome. Unfortunately, there is no way, a priori, of determining for a given ENSO event whether the correct or a rogue prediction will result. Analysis of the present model’s results suggest that this is an almost world-wide problem for seasonal predictions of rainfall.  相似文献   

12.
Summary The sensitivity of the simulation of the monsoon depressions to the cumulus parameterization schemes used in a numerical model is studied using the Pennsylvania State University – National Center for Atmospheric Research (PSU-NCAR) model MM5 version 3.6.2. Three different cases of monsoon depressions were studied with a two way interacting domains of 45 km and 15 km resolutions. Two different cumulus parameterization schemes namely Grell (GR) and Kain-Fritsch (KF) were used for the sensitivity study. The model was integrated for 48 hours with the initial and boundary conditions of European Center for Medium Range Weather Forecasting Reanalysis (ERA-40) data. The results show that both the schemes are able to simulate the large scale features of the monsoon depressions realistically. However, both the schemes failed to simulate the exact location of the depression after 24- and 48-hour simulation. The rainfall simulations of both the schemes were very different. The model with the GR scheme tends to over predict the rainfall. The KF scheme could simulate the distribution of the rainfall comparable to the observations. The KF scheme could simulate the maximum observed rainfall but due to locational errors of the simulated depression, the location of the maximum rainfall was not exact. It is also seen that the resolution of the model has a positive impact on the rainfall simulation. The GR and KF schemes were able to realistically simulate the apparent heat sources, but the apparent moisture profile simulated with KF scheme was more comparable to the verifying analysis. The root mean square errors of mean sea-level pressure, temperature, zonal wind and meridional wind were smaller for KF simulation compared to the GR simulation. Permanent affiliation: Center for Development of Advanced Computing, Pune University Campus, Ganeshkhind, Pune-411 007, India.  相似文献   

13.
A new approach to ensemble forecasting of rainfall over India based on daily outputs of four operational numerical weather prediction (NWP) models in the medium-range timescale (up to 5 days) is proposed in this study. Four global models, namely ECMWF, JMA, GFS and UKMO available on real-time basis at India Meteorological Department, New Delhi, are used simultaneously with adequate weights to obtain a multi-model ensemble (MME) technique. In this technique, weights for each NWP model at each grid point are assigned on the basis of unbiased mean absolute error between the bias-corrected forecast and observed rainfall time series of 366 daily data of 3 consecutive southwest monsoon periods (JJAS) of 2008, 2009 and 2010. Apart from MME, a simple ensemble mean (ENSM) forecast is also generated and experimented. The prediction skill of MME is examined against observed and corresponding outputs of each constituent model during monsoon 2011. The inter-comparison reveals that MME is able to provide more realistic forecast of rainfall over Indian monsoon region by taking the strength of each constituent model. It has been further found that the weighted MME technique has higher skill in predicting daily rainfall compared to ENSM and individual member models. RMSE is found to be lowest in MME forecasts both in magnitude and area coverage. This indicates that fluctuations of day-to-day errors are relatively less in the MME forecast. The inter-comparison of domain-averaged skill scores for different rainfall thresholds further clearly demonstrates that the MME algorithm improves slightly above the ENSM and member models.  相似文献   

14.
Summary The Indian rainfall has often been used as a proxy data for the Asian monsoon as a whole for understanding the energy budget of the major circulation features and also used as an input parameter in estimating the other regional parameters. In view of this, a long homogeneous rainfall series of All-India (India taken as one unit) has been prepared based on a fixed and well distributed network of 306 raingauge stations over India by giving proper area-weightage. This paper contains a listing of All-India monthly, seasonal and annual homogeneous data series for the period 1871–1993. Some statistical details and long-term changes of the All-India monsoon rainfall have been discussed.With 4 Figures  相似文献   

15.
Summary The relationship between the all-India summer monsoon rainfall and surface/upper air (850, 700, 500 and 200 mb levels) temperatures over the Indian region and its spatial and temporal characteristics have been examined to obtain a useful predictor for the monsoon rainfall. The data series of all-India and subdivisional summer monsoon rainfall and various seasonal air temperatures at 73 surface observatories and 9 radiosonde stations (1951–1980) have been used in the analysis. The Correlation Coefficients (CCs) between all-India monsoon rainfall and seasonal surface air temperatures with different lags relative to the monsoon season indicate a systematic relationship.The CCs between the monsoon rainfall and surface-air temperature of the preceding MAM (pre-monsoon spring) season are positive over many parts of India and highly significant over central and northwestern regions. The average surface air temperature of six stations i.e., Jodhpur, Ahmedabad, Bombay, Indore, Sagar and Akola in this region (Western Central India, WCI) showed a highly significant CC of 0.60 during the period 1951–1980. This relationship is also found to be consistently significant for the period from 1950 to present, though decreasing in magnitude after 1975. WCI MAM surface air temperature has shown significant CCs with the monsoon rainfall over eleven sub-divisions mainly in northwestern India, i.e., north of 15 °N and west of 80 °E.Upper air temperatures of the MAM season at almost all the stations and all levels considered show positive CCs with the subsequent monsoon rainfall. These correlations are significant at some central and north Indian stations for the lower and middle tropospheric temperatures.The simple regression equation developed for the period 1951–1980 isy = – 183.20 + 8.83x, wherey is the all-India monsoon rainfall in cm andx is the WCI average surface air temperature of MAM season in °C. This equation is significant at 0.1% level. The suitability of this parameter for inclusion in a predictive regression model along with five other global and regional parameters has been discussed. Multiple regression analysis for the long-range prediction of monsoon rainfall, using several combinations of these parameters indicates that the improvement of predictive skill considerably depends upon the selection of the predictors.With 9 Figures  相似文献   

16.
Using the NCEP/NCAR reanalysis wind and temperature data (1948–2011) and India Meteorological Department (IMD) rainfall data, a long-term trend in the tropical easterly jet stream and its effect on Indian summer monsoon rainfall has been explained in the present study. A decreasing trend in zonal wind speed at 100 mb (maximum decrease), 150 mb, and 200 mb (minimum) is observed. The upper-level (100, 150, and 200 mb) zonal wind speed has been correlated with the surface air temperature anomaly index (ATAI) in the month of May, which is taken as the difference in temperature anomaly over land (22.5°N–27.5°N, 80°E–90°E) and Ocean (5°S–0°S, 75°E–85°E). Significant high correlation is observed between May ATAI and tropical easterly jet stream (TEJ) which suggests that the decreasing land–sea temperature contrast could be one major reason behind the decreasing trend in TEJ. The analysis of spatial distribution of rainfall over India shows a decreasing trend in rainfall over Jammu and Kashmir, Arunachal Pradesh, central Indian region, and western coast of India. Increasing trend in rainfall is observed over south peninsular and northeastern part of India. From the spatial correlation analysis of zonal wind with gridded rainfall, it is observed that the correlation of rainfall is found to be high with the TEJ speed over the regions where the decreasing trend in rainfall is observed. Similarly, from the analysis of spatial correlation between rainfall and May ATAI, positive spatial correlation is observed between May ATAI and summer monsoon rainfall over the regions such as south peninsular India where the rainfall trend is positive, and negative correlation is observed over the places such as Jammu and Kashmir where negative rainfall trend is observed. The decreased land–sea temperature contrast in the pre-monsoon month could be one major reason behind the decreased trend in TEJ as well as the observed spatial variation in the summer monsoon rainfall trend. Thus, the study explained the long-term trend in TEJ and its relation with May month temperature over the Indian Ocean and land region and its effect on the trend and spatial distribution of Indian summer monsoon rainfall.  相似文献   

17.
华北和印度夏季风降水变化的对比分析   总被引：3，自引：0，他引：3  
 利用华北和印度夏季降水资料，采用趋势分析、小波变换等方法，对两地区夏季风降水进行了对比分析。结果表明：1) 华北和印度夏季风降水量都存在线性减少倾向，但华北更为显著，减少达16 mm/10 a；2) 华北和印度夏季风降水变化都以18 a周期为主，近年都有逐渐缩短的趋势，而印度的这种周期缩短得比华北更快，近年降水变化周期接近15 a；3) 华北和印度夏季风降水变化在1956、1976、1992/1993年发生了趋势转折；4) 华北和印度降水量主要集中在6-9月，夏季风降水特征非常明显，但两地变化特征表现不尽相同。  相似文献   

18.
近50年安徽省暴雨气候特征   总被引：5，自引：1，他引：4  
谢五三  田红 《气象科技》2011,39(2):160-164
利用安徽省71个台站1961—2008年近50年的逐日降水资料,统计出每年各站暴雨量及暴雨次数,通过趋势分析、EOF分析、功率谱分析、小波分析、Mann-Kendall突变检验等方法分析安徽省暴雨气候特征。结果表明：安徽省常年暴雨量呈纬向空间分布,常年暴雨次数与其分布非常一致,暴雨量及暴雨站次最多出现在6月下旬和7月上旬;全省绝大部分地区的暴雨量呈现上升趋势,上升幅度较大的地区集中在淮北西部及江南南部,但绝大部分地区未通过显著性检验;暴雨量距平场EOF第1模态全省一致为正,大值区位于安徽西南部,第2模态表明南北暴雨量呈现相反的分布,北多（少）南少（多）,第3模态表明安徽暴雨量有南北多（少）中部少（多）的分布特征;暴雨量存在9～10年的主周期,此外还存在3年左右的次周期,在9～10年的时间尺度上,近50年安徽暴雨量经历了由多到少5个循环交替;在1978年前后暴雨量存在一次突变,1979—2008年年均暴雨量比1961—1978年年均值增加了58.3 mm。  相似文献   

19.
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.  相似文献   

20.
Annual series of light rainfall, moderate rainfall and heavy rainfall are computed for 4 zones arranged from south to north in Nigeria: Coastal, Guinea-Savanna, Midland and Sahelian zones. Daily rainfall data for the period 1919–85 are utilized. Each series is examined for evidence of change in structure in terms of pattern of decrease and increase in dry and wet years, the overall trend, and the occurrence of runs of dry and wet years. The northern Nigeria (Midland and Sahel) heavy rainfall series and the Sahel moderate rainfall series are found to depict evidence of climatic change as defined by Landsberg (1975) that climatic conditions must change to a new equilibrium position with the values of climatic elements changed significantly. On the other hand Landsberg's definition of climatic fluctuations as involving temporary deflection which can revert to earlier conditions is found to fit the 4 regional light rainfall series and the Midland area moderate rainfall series. The southern Nigeria moderate and heavy rainfall series are found to depict only evidence of high frequency oscillations about a stable long-term mean. The recent drought in Nigeria north of about 9° N is shown to be associated with a large decline in moderate and heavy rainfalls over this part of the country.  相似文献   

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