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1.
Shared nearest neighbour (SNN) cluster algorithm has been applied to seasonal (June–September) rainfall departures over 30 sub-divisions of India to identify the contiguous homogeneous cluster regions over India. Five cluster regions are identified. Rainfall departure series for these cluster regions are prepared by area weighted average rainfall departures over respective sub-divisions in each cluster. The interannual and decadal variability in rainfall departures over five cluster regions is discussed. In order to consider the combined effect of North Atlantic Oscillation (NAO) and Southern Oscillation (SO), an index called effective strength index (ESI) has been defined. It has been observed that the circulation is drastically different in positive and negative phases of ESI-tendency from January to April. Hence, for each phase of ESI-tendency (positive and negative), separate prediction models have been developed for predicting summer monsoon rainfall over identified clusters. The performance of these models have been tested and found to be encouraging.  相似文献   

2.
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.  相似文献   

3.
Temporal distribution of southwest monsoon (June –September) rainfall is very useful for the country’s agriculture and food grain production. It contributes more than 75% of India’s annual rainfall. In view of this, an attempt has been made here to understand the performance of the monthly rainfall for June, July, August and September when the seasonal rainfall is reported as excess, deficient or normal. To know the dependence of seasonal rainfall on monthly rainfall, the probabilities of occurrence of excess, deficient and normal monsoon when June, July, August and also June + July and August + September rainfall is reported to be excess or deficient, are worked out using the long homogenous series of 124 years (1871-–1994) data of monthly and seasonal rainfall of 29 meteorological sub-divisions of the plain regions of India. In excess monsoon years, the average percentage contribution of each monsoon month to the long term mean (1871–1994) seasonal rainfall (June –September) is more than that of the normal while in the deficient years it is less than normal. This is noticed in all 29 meteorological sub-divisions. From the probability analysis, it is seen that there is a rare possibility of occurrence of seasonal rainfall to be excess/deficient when the monthly rainfall of any month is deficient/excess.  相似文献   

4.
The usefulness of principal component analysis for understanding the temporal variability of monsoon rainfall is studied. Monthly rainfall data of Karnataka, spread on 50 stations for a period of 82 years have been analysed for interseasonal and interannual variabilities. A subset of the above data comprising 10 stations from the coherent west zone of Karnataka has also been investigated to bring out statistically significant interannual signals in the southwest monsoon rainfall. Conditional probabilities are proposed for a few above normal/below normal transitions. A sample prediction exercise for June–July using such a transition probability has been found to be successful.  相似文献   

5.
Observed summer (May–October) rainfall in Myanmar for the period 1981–2010 was used to investigate the interannual variability of summer monsoon rainfall over Myanmar. Empirical orthogonal function, the sequential Mann-Kendall test, power spectrum analysis, and singular value decomposition (SVD) were deployed in the study. Results from spectral analysis showed that the variability of rainfall over Myanmar exhibits a 2- to 6-year cycle. An abrupt change in rainfall over the country was noted in 1992. There was a notable increasing rainfall trend from 1989. After the sudden change, the mean rainfall increased by 36.1 mm, compared with the mean rainfall before the sudden change, and was associated with a rise in temperature of about 0.2 °C. An increase in heavy rainfall days was observed from the early 1990s to 2010. IOD and ENSO play an important role in the interannual variability of the summer rainfall over Myanmar. The covariability between rainfall over Myanmar and Indian Ocean SST generally suggests that a positive IOD mode is associated with suppressed rainfall in the central and northern parts of Myanmar. During a negative IOD mode, nearly the whole Myanmar experiences enhanced rainfall, which is associated with devastating socioeconomic impacts. The covariability between the rainfall over Myanmar and the sea surface temperature in the Pacific Ocean in the first and second SVD modes was dominated by warming in the east and central Pacific—an El Niño-like pattern—resulting in dry conditions in central Myanmar.  相似文献   

6.
The long-term variability of rainfall in the Soummam watershed (NE Algeria) has been analysed over the past 108 years using continuous wavelet method in order to identify the interannual modes controlling the rainfall variability. Statistical analyses of rainfall timeseries have shown its distribution following five periods of time, limited by a series of discontinuities around 1935, 1950, 1970 and 1990. The continuous wavelet transform have demonstrated different low frequency modes: 2–4, 4–8, 8–16 and 16–32 years.The annual band is expanded during the full study period with some pics around 1905, 1920–1935 and 1960; it shows a negative long-term trend, in particular since the period 1970–1990 when a major change has been identified. Then, the relationships between climate patterns of North Atlantic Oscillation (NAO) and Southern Oscillation Index (SOI) and the hydrological variability in the frequency domain have been investigated; they have shown a mean explained variance of 40 and 24 %, respectively. Such variances are less obvious for the annual mode and increase for the interannual frequencies. The coherence suffer from high perturbations since the period 1970–1990 when the NAO (SOI) shifts from negative (positive) phases to positive (negative) ones. Such anomalies are responsible for significant changes of rainfall variability, emphasising the global warming effects.  相似文献   

7.
Global change in land water storage and its effect on sea level is estimated over a 7-year time span (August 2002 to July 2009) using space gravimetry data from GRACE. The 33 World largest river basins are considered. We focus on the year-to-year variability and construct a total land water storage time series that we further express in equivalent sea level time series. The short-term trend in total water storage adjusted over this 7-year time span is positive and amounts to 80.6 ± 15.7 km3/yr (net water storage excess). Most of the positive contribution arises from the Amazon and Siberian basins (Lena and Yenisei), followed by the Zambezi, Orinoco and Ob basins. The largest negative contributions (water deficit) come from the Mississippi, Ganges, Brahmaputra, Aral, Euphrates, Indus and Parana. Expressed in terms of equivalent sea level, total water volume change over 2002–2009 leads to a small negative contribution to sea level of –0.22 ± 0.05 mm/yr. The time series for each basin clearly show that year-to-year variability dominates so that the value estimated in this study cannot be considered as representative of a long-term trend. We also compare the interannual variability of total land water storage (removing the mean trend over the studied time span) with interannual variability in sea level (corrected for thermal expansion). A correlation of ∼0.6 is found. Phasing, in particular, is correct. Thus, at least part of the interannual variability of the global mean sea level can be attributed to land water storage fluctuations.  相似文献   

8.
The present study is mainly concerned with detecting the trend of run-off over the mainland of India, during a time period of 35 years, from 1971–2005 (May–October). Rainfall, soil texture, land cover types, slope, etc., were processed and run-off modelling was done using the Natural Resources Conservation Service (NRCS) model with modifications and cell size of 5×5 km. The slope and antecedent moisture corrections were incorporated in the existing model. Trend analysis of estimated run-off was done by taking into account different analysis windows such as cell, medium and major river basins, meteorological sub-divisions and elevation zones across India. It was estimated that out of the average 1012.5 mm of rainfall over India (considering the study period of 35 years), 33.8% got converted to surface run-off. An exponential model was developed between the rainfall and the run-off that predicted the run-off with an R2 of 0.97 and RMSE of 8.31 mm. The run-off trend analysed using the Mann–Kendall test revealed that a significant pattern exists in 22 medium, two major river basins and three meteorological sub-divisions, while there was no evidence of a statistically significant trend in the elevation zones. Among the medium river basins, the highest positive rate of change in the run-off was observed in the Kameng basin (13.6 mm/yr), while the highest negative trend was observed in the Tista upstream basin (?21.4 mm/yr). Changes in run-off provide valuable information for understanding the region’s sensitivity to climatic variability.  相似文献   

9.
The main objective of this paper is to analyze the spatial variability of rainfall trends using the spatial variability methods of rainfall trend patterns in Iran. The study represents a method on the effectiveness of spatial variability for predicting rainfall trend patterns variations. In rainfall trend analysis and spatial variability methods, seven techniques were used: Mann–Kendall test, Sen’s slope method, geostatistical tools as a global polynomial interpolation and the spatial autocorrelation (Global Moran’s I), high/low clustering (Getis-Ord General G), precipitation concentration index, generate spatial weights matrix tool, and activation functions of semiliner, sigmoid, bipolar sigmoid, and hyperbolic tangent in the artificial neural network technique .For the spatial variability of monthly rainfall trends, trend tests were used in 140 stations of spatial variability of rainfall trends in the 1975–2014 period. We analyzed the long and short scale spatial variability of rainfall series in Iran. Spatial variability distribution of rainfall series was depicted using geostatistical methods (ordinary kriging). Relative nugget effect (RNE) predicted from variograms which showed weak, moderate, and strong spatial variability for seasonal and annual rainfall series. Moreover, the rainfall trends at each station were examined using the trend tests at a significance level of 0.05. The results show that temporal and spatial trend patterns are different in Iran and the monthly rainfall had a downward (decreasing) trend in most stations, and the trend was statistically significant for most of the series (73.5% of the stations demonstrated a decreasing trend with 0.5 significance level). Rainfall downward trends are generally temporal-spatial patterns in Iran. The monthly variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The variability patterns of monthly rainfall were statistically significant and spatially random. Activation functions in the artificial neural network models, in annual time scale, had spatially dispersed distribution with other clustering patterns. The results of this study confirm that variability of rainfall revealing diverse patterns over Iran should be controlled mainly by trend patterns in the west and north parts and by random and dispersed patterns in the central, southern, and eastern parts.  相似文献   

10.
There is a close relationship between interannual variability of the Indian summer monsoon rainfall and the El Niño/Southern Oscillation (ENSO) (drought conditions over India accompany warm ENSO events and vice versa). However, recent observations suggest a weakening of this ENSO-monsoon relationship that may be linked to global warming. We report here an analysis of the ENSO-monsoon relationship within the framework of a 1000-year control simulation of the MRI-coupled general circulation model (GCM), MRI-CGCM2.2. An overall correlation between the June-July-August (JJA) Nino3.4 sea surface temperature and the JJA Indian monsoon rainfall is –0.39, with reasonable circulation characteristics associated with the modeled ENSO. The simulated ENSO-monsoon relationship reveals long-term variations, from –0.71 to +0.07, in moving 31-year windows. This modulation in the ENSO-monsoon relationship is associated with decadal variability of the climate system.  相似文献   

11.
Indian Monsoon Variability in a Global Warming Scenario   总被引：4，自引：0，他引：4  
The Intergovernmental Panel on Climate Change (IPCC) constituted by the World Meteorological Organisation provides expert guidance regarding scientific and technical aspects of the climate problem. Since 1990 IPCC has, at five-yearlyintervals, assessedand reported on the current state of knowledge and understanding of the climate issue. These reports have projected the behaviour of the Asian monsoon in the warming world. While the IPCC Second Assessment Report (IPCC, 1996) on climate model projections of Asian/Indian monsoon stated ``Most climate models produce more rainfall over South Asia in a warmer climate with increasing CO2', the recent IPCC (2001) Third Assessment Report states ``It is likely that the warming associated with increasing greenhouse gas concentrations will cause an increase in Asian summer monsoon variability and changes in monsoon strength.'Climate model projections(IPCC, 2001) also suggest more El Niño – like events in the tropical Pacific, increase in surface temperatures and decrease in the northern hemisphere snow cover. The Indian Monsoon is an important component of the Asian monsoon and its links with the El Niño Southern Oscillation (ENSO) phenomenon, northern hemisphere surface temperature and Eurasian snow are well documented.In the light of the IPCC globalwarming projections on the Asian monsoon, the interannual and decadal variability in summer monsoon rainfall over India and its teleconnections have been examined by using observed data for the 131-year (1871–2001) period. While the interannual variations showyear-to-year random fluctuations, thedecadal variations reveal distinct alternate epochs of above and below normal rainfall. The epochs tend to last for about three decades. There is no clear evidence to suggest that the strength and variability of the Indian Monsoon Rainfall (IMR) nor the epochal changes are affected by the global warming. Though the 1990s have been the warmest decade of the millennium(IPCC, 2001), the IMR variability has decreased drastically.Connections between the ENSO phenomenon, Northern Hemisphere surface temperature and the Eurasian snow with IMR reveal that the correlations are not only weak but have changed signs in the early 1990s suggesting that the IMR has delinked not only with the Pacific but with the Northern Hemisphere/Eurasian continent also. The fact that temperature/snow relationships with IMR are weak further suggests that global warming need not be a cause for the recent ENSO-Monsoon weakening.Observed snow depth over theEurasian continent has been increasing, which could be a result of enhanced precipitation due to the global warming.  相似文献   

12.
The interannual variability of all-India summer monsoon (June to September) rainfall and its teleconnections with the southern oscillation index (SOI) and sea surface temperature (SST) anomaly of the eastern equatorial Pacific ocean have been examined for the period 1871–1978 for different seasons (i.e., winter, spring, summer and autumn). The relationship (correlation coefficient) between all-India summer monsoon rainfall andSOI for different seasons is positive and highly significant. Further examination of 10-, 20- and 30-year sliding window lengths’ correlations, brings out the highly consistent and significant character of the relationships. The relationship between all-India monsoon rainfall andSST for different seasons is negative and is significant at 1 % level or above. Drought years are characterised by negative anomalies ofSOI and positive anomalies ofSST and vice versa with flood years. The relationship betweenSOI andSST is negative and significant at 0.1 % level. The relationships between all-India summer monsoon rainfall,SOI and sst are expected to improve our understanding of the interannual variability of the summer monsoon.  相似文献   

13.
陈立华  王焰  易凯  赖河涛 《水文》2016,36(6):89-96
依据钦州市58a平均降雨量和3条入海河流控制站径流量长序列资料,采用滑动平均、线性回归、Spearman、M-K及R/S法综合分析降雨径流的趋势性及突变特征。结果表明,钦州市降雨量总体呈弱增加趋势,增加率为0.742mm/10a,而茅岭江、钦江、大风江流域径流量存在总体减少趋势,减少率分别为0.2×108m~3/10a、1.1×108m~3/10a、0.4×108m~3/10a。运用复Molet小波分析多时间尺度周期性,降雨量序列存在5个时间尺度,22a和15a时间尺度分别为序列第一、三主周期;径流量序列存在3个时间尺度,其中22a和8a时间尺度分别为径流量序列第一、二主周期。  相似文献   

14.
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.  相似文献   

15.
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  相似文献   

16.
Some statistical properties of the summer monsoon seasonal rainfall for India during the last 100 years (1881–1980) are presented. The most recent decade of 1971–1980 shows the lowest value of standard-decadal average monsoon rainfall (86.40 cm) and is also characterised by the second highest value of coefficient of variation in monsoon rainfall (12.4 %). The combined last two standard-decadal period of 1961–1980 was the period of the largest coefficient of variation and the lowest average monsoon rainfall for India. The possible influence of global climatic variability on the performance of the monsoon is also examined. Analyses of correlation coefficient show that a statistically significant positive relationship with a time-lag of about six months exists between monsoon rainfall and northern hemispheric surface air temperature. A cooler northern hemisphere during January/February leads to a poor monsoon. All the major drought years during the last 3 decades had much cooler January/February periods over the northern hemisphere—1972 having the coldest January/February with a temperature departure of −0.94°C and the most disastrous monsoon failure.  相似文献   

17.
The northeast (NE) monsoon season (October, November and December) is the major period of rainfall activity over south peninsular India. This study is mainly focused on the prediction of northeast monsoon rainfall using lead-1 products (forecasts for the season issued in beginning of September) of seven general circulation models (GCMs). An examination of the performances of these GCMs during hindcast runs (1982–2008) indicates that these models are not able to simulate the observed interannual variability of rainfall. Inaccurate response of the models to sea surface temperatures may be one of the probable reasons for the poor performance of these models to predict seasonal mean rainfall anomalies over the study domain. An attempt has been made to improve the accuracy of predicted rainfall using three different multi-model ensemble (MME) schemes, viz., simple arithmetic mean of models (EM), principal component regression (PCR) and singular value decomposition based multiple linear regressions (SVD). It is found out that among these three schemes, SVD based MME has more skill than other MME schemes as well as member models.  相似文献   

18.
Homogeneous Indian Monsoon rainfall: Variability and prediction   总被引：1，自引：0，他引：1  
The Indian summer monsoon rainfall is known to have considerable spatial variability, which imposes some limitations on the all-India mean widely used at present. To prepare a spatially coherent monsoon rainfall series for the largest possible area, fourteen subdivisions covering the northwestern and central parts of India (about 55% of the total area of the country), having similar rainfall characteristics and associations with regional/global circulation parameters are merged and their area-weighted means computed, to form monthly and seasonal Homogeneous Indian Monsoon (HIM) rainfall series for the period 1871–1990. This paper includes a listing of monthly and seasonal rainfall of HIM region. HIM rainfall series has been statistically analysed to understand its characteristics, variability and teleconnections for long-range prediction. HIM rainfall series isfound to be homogeneous, Gaussian distributed and free from persistence. The mean (R) rainfall is 757 mm (87% of annual) and standard deviation (S) 119 mm, with a Coefficient of Variation (CV) of 16%. There were 21 dry (K, -<R S) and 19 wet (R i R + S) years during 1871–1990. There were clusters of frequent negative departures during 1899–1920 and 1965–1987 and positive departures during 1942–1961. The recent three decades show very high rainfall variability with 10 dry and 6 wet years. The decadal averages were alternatively positive and negative for three consecutive decades, viz., 1871–1900 (positive); 1901–1930 (negative); 1931–1960 (positive) and 1961–1990 (negative) respectively. Significant QBO and autocorrelation at 14th lag have been found in HIM rainfall series. To delineate the changes in the climatic regime of the Indian summer monsoon, sliding correlation coefficients (CCs) between HIM rainfall series and (i) Bombay msl pressure, (ii) Darwin msl pressure and (iii) Northern Hemisphere surface air temperature over the period 1871–1990 have been examined. The 31-year sliding CCs showed the systematic turning points of positive and negative CCs around the years, 1900 and 1940. In the light of other corroborative evidences, these turning points seem to delineate ‘meridional’ monsoon regime during 1871–1900 and 1940–1990 and ‘zonal’ monsoon regime during 1901–1940. The monsoon signal is particularly dominant in many regional and global circulation parameters, during 1951–1990. Using the teleconnections ofHIM series with 12 regional/global circulation parameters during the recent 36-year period 1951–86 regression models have been developed for long-range prediction. In the regression equations 3 to 4 parameters were entered, explaining upto 80% of the variance, depending upon the data period. The parameters that prominently enter the multiple regression equations are (i) Bombay msl pressure, (ii) April 500 mb Ridge at 75°E, (iii) NH temperature, (iv) Nouvelle minus Agalega msl pressure and (v) South American msl pressure. Eleven circulation parameters for the period 1951–80 were subjected to Principal Component Analysis (PCA) and the PC’s were used in the regression model to estimate HIM rainfall. The multiple regression with three PCs explain 72% of variance in HIM rainfall.  相似文献   

19.
We examine the relationship between three tropical and two subtropical western Indian Ocean coral oxygen isotope time series to surface air temperatures (SAT) and rainfall over India, tropical East Africa and southeast Africa. We review established relationships, provide new concepts with regard to distinct rainfall seasons, and mean annual temperatures. Tropical corals are coherent with SAT over western India and East Africa at interannual and multidecadal periodicities. The subtropical corals correlate with Southeast African SAT at periodicities of 16–30 years. The relationship between the coral records and land rainfall is more complex. Running correlations suggest varying strength of interannual teleconnections between the tropical coral oxygen isotope records and rainfall over equatorial East Africa. The relationship with rainfall over India changed in the 1970s. The subtropical oxygen isotope records are coherent with South African rainfall at interdecadal periodicities. Paleoclimatological reconstructions of land rainfall and SAT reveal that the inferred relationships generally hold during the last 350 years. Thus, the Indian Ocean corals prove invaluable for investigating land–ocean interactions during past centuries. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.  相似文献   

20.
Water scarcity in the Yellow River, China, has become increasingly severe over the past half century. In this paper, wavelet transform analysis was used to detect the variability of natural, observed, and reconstructed streamflow in the Yellow River at 500-, 100-, and 50-year timescales. The periodicity of the streamflow series and the co-varying relationships between streamflow and atmospheric circulation indices/sunspot number were assessed by means of continuous wavelet transform (CWT) and wavelet transform coherence (WTC) analyses. The CWT results showed intermittent oscillations in streamflow with increasing periodicities of 1–6 years at all timescales. Significant multidecadal and century-scale periodicities were identified in the 500-year streamflow series. The WTC results showed intermittent interannual covariance of streamflow with atmospheric circulation indices and sunspots. At the 50-year timescale, there were significant decadal oscillations between streamflow and the Arctic Oscillation (AO) and the Pacific Decadal Oscillation (PDO), and bidecadal oscillations with the PDO. At the 100-year timescale, there were significant decadal oscillations between streamflow and Niño 3.4, the AO, and sunspots. At the 500-year timescale, streamflow in the middle reaches of the Yellow River showed prominent covariance with the AO with an approximately 32-year periodicity, and with sunspots with an approximately 80-year periodicity. Atmospheric circulation indices modulate streamflow by affecting temperature and precipitation. Sunspots impact streamflow variability by influencing atmospheric circulation, resulting in abundant precipitation. In general, for both the CWT and the WTC results, the periodicities were spatially continuous, with a few gradual changes from upstream to downstream resulting from the varied topography and runoff. At the temporal scale, the periodicities were generally continuous over short timescales and discontinuous over longer timescales.  相似文献   

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