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1.
Analysis of summer monsoon (June to September) rainfall series of 29 subdivisions based on a fixed number of raingauges (306 stations) has been made for the 108-year period 1871–1978 for interannual and long-term variability of the rainfall. Statistical tests show that the rainfall series of 29 sub-divisions are homogeneous, Gaussian-distributed and do not contain any persistence. The highest and the lowest normal rainfall of 284 and 26 cm are observed over coastal Karnataka and west Rajasthan sub-divisions respectively. The interannual variability (range) varies over different sub-divisions, the lowest being 55 and the highest 231% of the normal rainfall, for south Assam and Saurashtra and Kutch sub-divisions respectively. High spatial coherency is observed between neighbouring sub-divisions; northeast region and northern west and peninsular Indian sub-divisions show oppositic correlation tendency. Significant change in mean rainfall of six sub-divisions is noticed. Correlogram and spectrum analysis show the presence of 14-year and QBO cycles in a few sub-divisional rainfall series.  相似文献   

2.
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   

3.
The study assessed changes in the rainfall regime in Nigeria between 1961 and 2004 in terms of (a) absolute seasonality—the length of dry and wet season; (b) relative seasonality—rainfall contrast during the year; (c) number of rainfall maxima and minima; and (d) timing of rainfall maxima and minima. Trends in the mean monthly surface locations of the Inter-tropical Discontinuity (ITD) were also examined as a prominent factor of the rainfall regime. Changes in the regime were examined over four time slices: 1961–1971, 1972–1982, 1983–1993 and 1994–2004. The results show that, in the area of single rainfall maximum regime, the length of the wet season has increased from 4 months (in 1961–1971) to 5 months (since 1972–1982). The rainfall relative seasonality has consistently been ‘most rain in 3 months or less’. The rainfall maxima still indicate single rainfall maximum but shift in the peak from August to July. Rainfall during the months of June to September appears to have witnessed declining trends over the first three time slices. The last time slice however indicates trends towards a wetter condition. For the area of double maxima rainfall regime, the length of the wet season has consistently been 8 months. The rainfall relative seasonality has consistently been ‘rather seasonal with a short drier season’. The rainfall maxima and minima still indicate double rainfall maxima with August as the month of the minimum but shift in the primary peak from July to September. The northward latitudinal distance of the surface location of the ITD from the equator indicates significant upward trends during the months of May to September only and for a period of 1983–2000. The trend results of the ITD appears to account for most of the observed changes in the rainfall regime in Nigeria.  相似文献   

4.
Using a historical database (1952–2007) of sea surface temperature (SST) from a subtropical high-controlled area (110°E–140°E, 15°N–35°N) of the west Pacific Ocean and the precipitation over Hunan Province of southeast China, we analyzed time series variations of precipitation in relation to the East Asian summer monsoon and a global warming setting. The results show that there has been a significant increase in SST of the subtropical high-controlled area in the recent 50 years. Although the increase in annual summer monsoon precipitation during the same period has been subtle over Hunan province, seasonal rainfall distribution has obviously changed, represented by a reduction in May, but a significant increase through June to August, especially in July. We suggest that the mechanism of seasonal redistribution of monsoon precipitation is primarily due to the increasing SST that delays the intrusion of the west Pacific Subtropical High, therefore leading to a postponing of migration of the East Asian summer monsoon rainfall belt inland and northward.  相似文献   

5.
In this study, the possible linkage between summer monsoon rainfall over India and surface meteorological fields (basic fields and heat budget components) over monsoon region (30‡E-120‡E, 30‡S30‡N) during the pre-monsoon month of May and summer monsoon season (June to September) are examined. For this purpose, monthly surface meteorological fields anomaly are analyzed for 42 years (1958-1999) using reanalysis data of NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research). The statistical significance of the anomaly (difference) between the surplus and deficient monsoon years in the surface meteorological fields are also examined by Student’s t-test at 95% confidence level. Significant negative anomalies of mean sea level pressure are observed over India, Arabian Sea and Arabian Peninsular in the pre-monsoon month of May and monsoon season. Significant positive anomalies in the zonal and meridional wind (at 2 m) in the month of May are observed in the west Arabian Sea off Somali coast and for monsoon season it is in the central Arabian Sea that extends up to Somalia. Significant positive anomalies of the surface temperature and air temperature (at 2 m) in the month of May are observed over north India and adjoining Pakistan and Afghanistan region. During monsoon season this region is replaced by significant negative anomalies. In the month of May, significant positive anomalies of cloud amount are observed over Somali coast, north Bay of Bengal and adjoining West Bengal and Bangladesh. During monsoon season, cloud amount shows positive anomalies over NW India and north Arabian Sea. There is overall reduction in the incoming shortwave radiation flux during surplus monsoon years. A higher magnitude of latent heat flux is also found in surplus monsoon years for the month of May as well as the monsoon season. The significant positive anomaly of latent heat flux in May, observed over southwest Arabian Sea, may be considered as an advance indicator of the possible behavior of the subsequent monsoon season. The distribution of net heat flux is predominantly negative over eastern Arabian Sea, Bay of Bengal and Indian Ocean. Anomaly between the two extreme monsoon years in post 1980 (i.e., 1988 and 1987) shows that shortwave flux, latent heat flux and net heat flux indicate reversal in sign, particularly in south Indian Ocean. Variations of the heat budget components over four smaller sectors of Indian seas, namely Arabian Sea, Bay of Bengal and west Indian Ocean and east Indian Ocean show that a small sector of Arabian Sea is most dominant during May and other sectors showing reversal in sign of latent heat flux during monsoon season.  相似文献   

6.
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   

7.
Between 1941 and 2002 there has been a decreasing trend in the frequency of monsoon disturbances (MDs) during the summer monsoon season (June–September). This downwards trend is significant at the 99.9% level for the main monsoon phase (July–August) and the withdrawal phase (September); however, it is not significant during the onset phase (June). The variability in rainfall over the homogeneous regions of India on the sub-seasonal scale also shows a significant decreasing trend with respect to the amount of rainfall over Northwest India (NWI) and Central India (CEI) during all three phases of the monsoon. Meteorological observations reveal that there has been an eastward shift of the rainfall belt with time over the Indian region on the seasonal scale and that this shift is more prominent during the withdrawal phase. This decreasing trend in MDs together with its restricted westerly movement seem to be directly related to the decreasing trend in rainfall over CEI during both the main monsoon and withdrawal phases and over NWI during the withdrawal phase. The low-level circulation anomalies observed during two periods (period-I: 1951–1976; period-ii: 1977–2002) are in accordance with the changes in rainfall distribution, with comparatively more (less) rainfall falling over NWI, CEI and Southern Peninsular India (SPI) during period-I (period-ii), and are accompanied by a stronger (weaker) monsoon circulation embedded with an anomalous cyclonic (anti-cyclonic) circulation over CEI during the main monsoon and withdrawal phases. During the onset phase, completely opposite circulation anomalies are observed during both periods, and these are associated with more (less) rainfall over NWI, CEI and SPI during period-ii (period-I).  相似文献   

8.
Large-scale interannual variability of the northern summer southwest monsoon over India is studied by examining its variation in the dry area during the period 1871–1984. On the mean summer monsoon rainfall (June to September total) chart the 800 mm isohyet divides the country into two nearly equal halves, named as dry area (monsoon rainfall less than 800 mm) and wet area (monsoon rainfall greater than 800 mm). The dry area/wet area shows large variations from one year to another, and is considered as an index for assessing the large-scale performance of the Indian summer monsoon. Statistical and fluctuation characteristics of the summer monsoon dry area (SMDA) are reported. To identify possible causes of variation in the Indian summer monsoon, the correlation between the summer monsoon dry area and eleven regional/global circulation parameters is examined. The northern hemisphere surface air temperature, zonal/hemispheric/global surface air and upper air temperatures, Southern Oscillation, Quasi-biennial oscillation of the equatorial lower stratosphere, April 500-mb ridge along 75°E over India, the Indian surface air temperature and the Bombay sea level pressure showed significant correlation. A new predictor parameter that is preceding year mean monsoon rainfall of a few selected stations over India has been suggested in the present study. The stations have been selected by applying the objective technique ‘selecting a subset of few gauges whose mean monsoon rainfall of the preceding year has shown the highest correlation coefficient (CC) with the SMDA’. Bankura (Gangetic West Bengal), Cuddalore (Tamil Nadu) and Anupgarh (West Rajasthan) entered the selection showing a CC of 0.724. Using a dependent sample of 1951–1980 a predictive model (multiple CC = 0.745) has also been developed for the SMDA with preceding year mean monsoon rainfall of the three selected stations and the sea level pressure tendency at Darwin from Jan–Feb to Mar–May as independent parameters.  相似文献   

9.
Anomalous behaviour of the Indian summer monsoon 2009   总被引:1,自引:0,他引:1  
The Indian subcontinent witnessed a severe monsoon drought in the year 2009. India as a whole received 77% of its long period average during summer monsoon season (1 June to 30 September) of 2009, which is the third highest deficient all India monsoon season rainfall year during the period 1901–2009. Therefore, an attempt is made in this paper to study the characteristic features of summer monsoon rainfall of 2009 over the country and to investigate some of the possible causes behind the anomalous behaviour of the monsoon.  相似文献   

10.
Based on Coastal Zone Color Scanner data from November 1978 through December 1981, the seasonal cycle of phytoplankton pigment in the upper part of the euphotic zone is established for the offshore Laccadive Sea. Year-round, the pigment content is low and the seasonal range is small, following the pattern of the nutrient-poor Arabian Sea to the west. Apparently, indigenous phytoplankton blooms are absent. July and August, however, were poorly studied because of cloud cover. Interannual differences during the northeast monsoon and the spring intermonsoon periods are minor. The abundant phytoplankton caused by the upwelling off India during the southwest monsoon remains essentially restricted to the shelf, but there are occasional large, zonal outbreaks into the Laccadive Sea, as well as others advected to the south of India. Visual inspection of the raw CZCS scenes for June through November 1982–1985, with almost no data until August or even September, shows such outbreaks of pigment-rich water to be common. Inspection of monthly SeaWiFS images for 1997 through part of 2001 confirms the absence of indigenous phytoplankton blooms.  相似文献   

11.
The summer monsoon rainfall over Orissa, a state on the eastern coast of India, is more significantly related than Indian summer monsoon rainfall (ISMR) to the cyclonic disturbances developing over the Bay of Bengal. Orissa experiences floods and droughts very often due to variation in the characteristics of these disturbances. Hence, an attempt was made to find out the inter-annual variability in the rainfall over Orissa and the frequencies of different categories of cyclonic disturbances affecting Orissa during monsoon season (June–September). For this purpose, different statistical characteristics, such as mean, coefficient of variation, trends and periodicities in the rainfall and the frequencies of different categories of cyclonic disturbances affecting Orissa, were analysed from 100 years (1901–2000) of data. The basic objective of the study was to find out the contribution of inter-annual variability in the frequency of cyclonic disturbances to the inter-annual variability of monsoon rainfall over Orissa. The relationship between summer monsoon rainfall over Orissa and the frequency of cyclonic disturbances affecting Orissa shows temporal variation. The correlation between them has significantly decreased since the 1950s. The variation in their relationship is mainly due to the variation in the frequency of cyclonic disturbances affecting Orissa. The variability of both rainfall and total cyclonic disturbances has been above normal since the 1960s, leading to more floods and droughts over Orissa during recent years. The inter-annual variability of seasonal rainfall over Orissa and the frequency of cyclonic disturbances affecting Orissa during monsoon season show a quasi-biennial oscillation period of 2–2.8 years. There is least impact of El Nino southern oscillation (ENSO) on inter-annual variability of both the seasonal rainfall over Orissa and the frequencies of monsoon depressions/total cyclonic disturbances affecting Orissa.  相似文献   

12.
The impact of Southern Oscillation on thecyclogenesis over the Bay of Bengal duringthe summer monsoon has been investigated.The analysis of correlation coefficients(CCs) between the frequency of monsoondepressions and the Southern OscillationIndex (SOI) reveals that more depressionsform during July and August of El Niñoyears. Due to this, the seasonal frequencyof monsoon depressions remains little higherduring El Niño epochs even though thecorrelations for June and September are notsignificant. The CCs for July and August aresignificant at the 99% level.The El Niño-Southern Oscillation (ENSO)is known to affect Indian MonsoonRainfall (IMR) adversely. The enhancedcyclogenesis over the Bay of Bengal duringJuly and August is an impact of ENSO whichneeds to be examined closely. Increasedcyclogenesis over the Bay of Bengal may bereducing the deficiency in IMR duringEl Niño years by producing more rainfallover the eastern parts of India duringJuly and August. Thus there is a considerablespatial variation in the impact of ENSOon the monsoon rainfall over India and El Niñoneed not necessarily imply a monsoonfailure everywhere in India.The area of formation of monsoon depressionsshifts eastward during El Niño years.Warmer sea surface temperature (SST) anomaliesprevail over northwest and adjoiningwestcentral Bay of Bengal during premonsoon andmonsoon seasons of El Niño years.May minus March SOI can provide useful predictionsof monsoon depression frequencyduring July and August.  相似文献   

13.
An analysis of the mean monthly data of 124 years reveals that the relationship between the Southern Oscillation Index in September and the winter monsoon rainfall (WMR) over Coastal Andhra Pradesh (CAP) is variable and non-stationary. In the recent four decades, however, SOI (Sept) is negatively and significantly correlated with CAP WMR. A similar analysis is performed using 50 years of mean monthly SSTs over Nino-3.4 region in August and September and CAP WMR to detect a possible relationship and there is a striking positive relation between them. In both of the above cases, the September signal is more significant in the recent four decades than for the other months and seasons for probable prediction of CAP WMR. Finally, to examine the influence of SO on the winter monsoon rainfall, a non-parametric test “Mann-Whitney Rank Statistics” test has been applied to the rainfall associated with extreme positive and negative SOI events  相似文献   

14.
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   

15.
Seasonal climate forecasts are one of the most promising tools for providing early warnings for natural hazards such as floods and droughts. Using two case studies, this paper documents the skill of a regional climate model in the seasonal forecasting of below normal rainfall in southern China during the rainy seasons of July–August–September 2003 and April–May–June 2004. The regional model is based on the Regional Spectral Model of the National Centers for Environmental Prediction of the United States. It is the first time that the model has been applied to a region dominated by the East Asian Monsoon. The article shows that the regional climate model, when being forced by reasonably good forecasts from a global model, can generate useful seasonal rainfall forecasts for the region, where it is dominated by the East Asia monsoon. The spatial details of the dry conditions obtained from the regional climate model forecast are also found to be comparable with the observed distribution.  相似文献   

16.
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   

17.
The change in the type of vegetation fraction can induce major changes in the local effects such as local evaporation, surface radiation, etc., that in turn induces changes in the model simulated outputs. The present study deals with the effects of vegetation in climate modeling over the Indian region using the MM5 mesoscale model. The main objective of the present study is to investigate the impact of vegetation dataset derived from SPOT satellite by ISRO (Indian Space Research Organization) versus that of USGS (United States Geological Survey) vegetation dataset on the simulation of the Indian summer monsoon. The present study has been conducted for five monsoon seasons (1998–2002), giving emphasis over the two contrasting southwest monsoon seasons of 1998 (normal) and 2002 (deficient). The study reveals mixed results on the impact of vegetation datasets generated by ISRO and USGS on the simulations of the monsoon. Results indicate that the ISRO data has a positive impact on the simulations of the monsoon over northeastern India and along the western coast. The MM5-USGS has greater tendency of overestimation of rainfall. It has higher standard deviation indicating that it induces a dispersive effect on the rainfall simulation. Among the five years of study, it is seen that the RMSE of July and JJAS (June–July–August–September) for All India Rainfall is mostly lower for MM5-ISRO. Also, the bias of July and JJAS rainfall is mostly closer to unity for MM5-ISRO. The wind fields at 850 hPa and 200 hPa are also better simulated by MM5 using ISRO vegetation. The synoptic features like Somali jet and Tibetan anticyclone are simulated closer to the verification analysis by ISRO vegetation. The 2 m air temperature is also better simulated by ISRO vegetation over the northeastern India, showing greater spatial variability over the region. However, the JJAS total rainfall over north India and Deccan coast is better simulated using the USGS vegetation. Sensible heat flux over north-west India is also better simulated by MM5-USGS.  相似文献   

18.
To improve flood forecasting, the understanding of the atmospheric conditions associated with severe rainfall is crucial. We analysed the atmospheric conditions at Dhaka, Bangladesh, using upper-air soundings. We then compared these conditions with daily rainfall variations at Cherrapunjee, India, which is a main source of floodwater to Bangladesh, and a representative sample of exceptionally heavy rainfall events. The analysis focussed on June and July 2004. June and July are the heaviest rainfall months of the year at Cherrapunjee. July 2004 had the fourth-heaviest monthly rainfall of the past 31 years, and severe floods occurred in Bangladesh. Active rainfall periods at Cherrapunjee corresponded to “breaks” in the Indian monsoon. The monsoon trough was located over the Himalayan foothills, and strong westerly winds dominated up to 7 km at Dhaka. Near-surface wind below 1 km had southerly components, and the wind profile had an Ekman spiral structure. The results suggest that rainfall at Cherrapunjee strongly depends on the near-surface wind speed and wind direction at Dhaka. Lifting of the near-surface southerly airflow by the Meghalaya Plateau is considered to be the main contributor to severe rainfall at Cherrapunjee. High convective available potential energy (CAPE) also contributes to intense rainfall.  相似文献   

19.
The role of intraseasonal oscillations (ISOs) in modulating synoptic and interannual variations of surface winds over the Indian monsoon region is studied using daily averaged National Centers for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) reanalyses for the period 1987–1996. Two dominant ISOs are found in all years, with a period between 30–60 days and 10–20 days respectively. Although the ISOs themselves explain only about 10–25% of the daily variance, the spatial structure of variance of the ISOs is found to be nearly identical to that of high frequency activity (synoptic disturbances), indicating a significant control by the ISOs in determining the synoptic variations. Zonal and meridional propagation characteristics of the two modes and their interannual variability are studied in detail. The synoptic structure of the 30–60 day mode is similar in all years and is shown to be intimately related to the strong (‘active’) or weak (‘break’) phases of the Indian summer monsoon circulation. The peak (trough) phase of the mode in the north Bay of Bengal corresponds to the ‘active’ (‘break’) phase of monsoon strengthening (weakening) the entire large scale monsoon circulation. The ISOs modulate synoptic activity through the intensification or weakening of the large scale monsoon flow (monsoon trough). The peak wind anomalies associated with these ISOs could be as large as 30% of the seasonal mean winds in many regions. The vorticity pattern associated with the 30–60 day mode has a bi-modal meridional structure similar to the one associated with the seasonal mean winds but with a smaller meridional scale. The spatial structure of the 30–60 day mode is consistent with fluctuations of the tropical convergence zone (TCZ) between one continental and an equatorial Indian Ocean position. The 10–20 day mode has maximum amplitude in the north Bay of Bengal, where it is comparable to that of the 30–60 day mode. Elsewhere in the Indian Ocean, this mode is almost always weaker than the 30–60 day mode. In the Bay of Bengal region, the wind curl anomalies associated with the peak phases of the ISOs could be as large as 50% of the seasonal mean wind curl. Hence, ISOs in this region could drive significant ISOs in the ocean and might influence the seasonal mean currents in the Bay. On the interannual time scale, the NCEP/NCAR reanalysed wind stress is compared with the Florida State University monthly mean stress. The seasonal mean stress as well as interannual standard deviation of monthly stress from the two analyses agree well, indicating absence of any serious systematic bias in the NCEP/NCAR reanalysed winds. It is also found that the composite structure of the 30–60 day mode is strikingly similar to the dominant mode of interannual variability of the seasonal mean winds indicating a strong link between the ISOs and the seasonal mean. The ISO influences the seasonal mean and its interannual variability either through increased/decreased residence time of the TCZ in the continental position or through occurrence of stronger/weaker active/break spells. Thus, the ISOs seem to modulate all variability in this region from synoptic to interannual scales.  相似文献   

20.
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   

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