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1.
In the present study the Principal Component Analysis (PCA) is used to determine the dominant rainfall patterns from rainfall records over India. Pattern characteristics of seasonal monsoon rainfall (June–September) over India for the period 1940 to 1990 are studied for 68 stations. The stations have been chosen on the basis of their correlation with all India seasonal rainfall after taking the ‘t’ Student distribution test (5% level). The PCA is carried out on the rainfall data to find out the nature of rainfall distribution and percentage of variance is estimated. The first principal component explains 55.50% of the variance and exhibits factor of one positive value throughout the Indian subcontinent. It is characterized by an area of large positive variation between 10°N and 20°N extending through west coast of India. These types of patterns mostly occur due to the monsoon depression in the head Bay of Bengal and mid-tropospheric low over west coast of India. The analysis identifies the spatial and temporal characteristics of possible physical significance. The first eight principal component patterns explain for 96.70% of the total variance.  相似文献   

2.
Misra  Vasubandhu  Bhardwaj  Amit  Mishra  Akhilesh 《Climate Dynamics》2018,51(5-6):1609-1622

This paper introduces an objective definition of local onset and demise of the Indian summer monsoon (ISM) at the native grid of the Indian Meteorological Department’s rainfall analysis based on more than 100 years of rain gauge observations. The variability of the local onset/demise of the ISM is shown to be closely associated with the All India averaged rainfall onset/demise. This association is consistent with the corresponding evolution of the slow large-scale reversals of upper air and ocean variables that raise the hope of predictability of local onset and demise of the ISM. The local onset/demise of the ISM also show robust internannual variations associated with El Nino and the Southern Oscillation and Indian Ocean dipole mode. It is also shown that the early monsoon rains over northeast India has a predictive potential for the following seasonal anomalies of rainfall and seasonal length of the monsoon over rest of India.

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3.
Surface pressure and summer monsoon rainfall over India   总被引：1，自引：0，他引：1  
The relationship between the all-India summer monsoon rainfall and surface pressure over the Indian region has been examined to obtain a useful predictor for the monsoon rainfall. The data series of all-India monsoon rainfall and the mean pressures of three seasons before and after the monsoon season as well as the winter-to-spring pressure tendency (MAM-DJF) at 100 stations for the period 1951-1980 have been used in the analysis. The all-India monsoon rainfall is negatively correlated with the pressure of the spring (MAM) season preceding the monsoon and winter-to-spring seasonal difference as pressure tendency (MAM-DJF), at almost all the stations in India, and significantly with the pressures over central and northwestern regions. The average mean sea level pressure of six stations (Jodhpur, Ahmedabed, Bombay, Indore, Sagar and Akola) in the Western Central Indian (WCI) region showed highly significant (at 1% level) and consistent CCs of -0.63 for MAM and -0.56 for MAM-DJF for the period 1951–1980. Thus, the pre-monsoon seasonal pressure anomalies over WCI could provide a useful parameter for the long-range forecasting scheme of the Indian monsoon rainfall.  相似文献   

4.
Large scale aspects of India-China summer monsoon rainfall   总被引：1，自引：0，他引：1  
This study investigates the dominant modes of variability in monthly and seasonal rainfall over the India-China region mainly through Empirical Orthogonal Function (EOF) analysis. The EOFs have shown that whereas the rain-fall over India varies as one coherent zone, that over China varies in east-west oriented bands. The influence of this banded structure extends well into India.Relationship of rainfall with large scale parameters such as the subtropical ridge over the Indian and the western Pacific regions, Southern Oscillation, the Northern Hemispheric surface air temperature and stratospheric winds have also been investigated. These results show that the rainfall over the area around 40oN, 110oE over China is highly related with rainfall over India. The subtropical ridge over the Indian region is an important predictor over India as well as over the northern China legion.  相似文献   

5.
The NOAA daily outgoing longwave radiation (OLR) and the Global Precipitation Climatology Project （GPCP） daily precipitation data are used to study the variation of dominant convection modes and their relationships over Asia, the Indian Ocean, and the western Pacific Ocean during the summers from 1997 to 2004. Major findings are as follows: (1) Regression analysis with the OLR indicates the convective variations over Asian monsoon region are more closely associated with the convective activities over the western subtropical Pacific (WSP) than with those over the northern tropical Indian Ocean (NTIO). (2) The EOF analysis of OLR indicates the first mode (EOF1) exhibits the out-of-phase variations between eastern China and India, and between eastern China and the WSP. The OLR EOF1 primarily exhibits seasonal and even longer-term variations. (3) The OLR EOF2 mostly displays in-phase convective variations over India, the Bay of Bengal, and southeastern China. A wavelet analysis reveals intraseasonal variation (ISV) features in 2000, 2001, 2002, and 2004. However, the effective ISV does not take place in every year and it seems to occur only when the centers of an east--west oriented dipole reach enough intensity over the tropical Indian and western Pacific Oceans. (4) The spatial patterns of OLR EOF3 are more complicated than those of EOF1 and EOF2, and an effective ISV is noted from 1999 to 2004. The OLR EOF3 implies there is added complexity of the OLR pattern when the effective ISV occurs. (5) The correlation analysis suggests the precipitation over India is more closely associated with the ISV, seasonal variations, and even longer-term variations than precipitation occurring over eastern China.  相似文献   

6.
The day-to-day behavior of Indian summer monsoon rainfall (IMR) is associated with a hierarchy of quasi-periods, namely 3?C7, 10?C20 and the 30?C60?days. These two periods, the 10?C20?days and the 30?C60?days have been related with the active and break cycles of the monsoon rainfall over the Indian sub-continent. The seasonal strength of Indian summer monsoon rainfall may depend on the frequency and duration of spells of break and active periods associated with the fluctuations of the above intra-seasonal oscillations (ISOs). Thus the predictability of the seasonal (June through September) mean Indian monsoon depends on the extent to which the intra-seasonal oscillations could be predicted. The primary objective of this study is to bring out the dynamic circulation features during the pre-monsoon/monsoon season associated with the extreme phases of these oscillations The intense (weak) phase of the 10?C20 (30?C60) days oscillation is associated with anti-cyclonic circulation over the Indian Ocean, easterly flow over the equatorial Pacific Ocean resembling the normal or cold phase (La Nina) of El Nino Southern Oscillation (ENSO) phenomenon, and weakening of the north Pacific Sub-tropical High. On the other hand the weak phase of 10?C20?days mode and the intense phase of 30?C60?days mode shows remarkable opposite flow patterns. The circulation features during pre-monsoon months show that there is a tendency for the flow patterns observed in pre-monsoon months to persist during the monsoon months. Hence some indications of the behavior of these modes during the monsoon season could be foreshadowed from the spring season patterns. The relationship between the intensity of these modes and some of the long-range forecasting parameters used operationally by the India Meteorological Department has also been examined.  相似文献   

7.
Summary Hindcasts for the Indian summer monsoons (ISMs) of 2002 and 2003 have been produced from an ensemble of numerical simulations performed with a global model by changing SST. Two sets of ensemble simulations have been produced without vegetation: (i) by prescribing the weekly observed SST from ECMWF (European Centre for Medium Range Weather Forecasting) analyses, and (ii) by adding weekly SST anomalies (SSTA) of April to the climatological SST during the simulation period from May to August. For each ensemble, 10 simulations have been realized with different initial conditions that are prepared from ECMWF data with five each from April and May analyses of both the years. The predicted June–July monsoon rainfall over the Indian region shows good agreement with the GPCP (observed) pentad rainfall distribution when 5 member ensemble is taken from May initial conditions. The All-India June–July simulated rainfall time series matches favourably with the observed time series in both the years for the five member ensemble from May initial condition but drifts away from observation with April initial conditions. This underscores the role of initial conditions in the seasonal forecasting. But the model has failed to capture the strong intra-seasonal oscillation in July 2002. Heating over equatorial Indian Ocean for June 2002 in a particular experiment using 29th May 12 GMT as initial conditions shows some intra-seasonal oscillation in July 2002 rainfall, as in observation. Further evaluation of the seasonal simulations from this model is done by calculating the empirical orthogonal functions (EOFs) of the GPCP rainfall over India. The first four EOFs explain more than 80% of the total variance of the observed rainfall. The time series of expansion coefficients (principal components), obtained by projecting on the observed EOFs, provide a better framework for inter-comparing model simulations and their evaluation with observed data. The main finding of this study is that the All-India rainfall from various experiments with prescribed SST is better predicted on seasonal scale as compares to prescribed SST anomalies. This is indicative of a possible useful seasonal forecasts from a GCM at least for the case when monsoon is going to be good. The model responses do not differ much for 2002 and 2003 since the evolution of SST during these years was very similar, hence July rainfall seems to be largely modulated by the other feedbacks on the overall circulation.  相似文献   

8.
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   

9.
Understanding the relationship between gradually varying soil moisture (SM) conditions and monsoon rainfall anomalies is crucial for seasonal prediction. Though it is an important issue, very few studies in the past attempted to diagnose the linkages between the antecedent SM and Indian summer monsoon rainfall. This study examined the relationship between spring (April–May) SM and June rainfall using observed data during the period 1979–2010. The Empirical Orthogonal Function (EOF) analyses showed that the spring SM plays a significant role in June rainfall over the Central India (CI), South India (SI), and North East India (NEI) regions. The composite anomaly of the spring SM and June rainfall showed that excess (deficit) June rainfall over the CI was preceded by wet (dry) spring SM. The anomalies in surface-specific humidity, air temperature, and surface radiation fluxes also supported the existence of a positive SM-precipitation feedback over the CI. On the contrary, excess (deficit) June rainfall over the SI and NEI region were preceded by dry (wet) spring SM. The abnormal wet (dry) SM over the SI and NEI decreased (increased) the 2-m air temperature and increased (decreased) the surface pressure compared to the surrounding oceans which resulted in less (more) moisture transport from oceans to land (negative SM-precipitation feedback over the Indian monsoon region).  相似文献   

10.
South Asian summer monsoon (June through September) rainfall simulation and its potential future changes are evaluated in a multi-model ensemble of global coupled climate models outputs under World Climate Research Program Coupled Model Intercomparison Project (WCRP CMIP3) dataset. The response of South Asian summer monsoon to a transient increase in future anthropogenic radiative forcing is investigated for two time slices, middle (2031–2050) and end of the twenty-first century (2081–2100), in the non-mitigated Special Report on Emission Scenarios B1, A1B and A2 .There is large inter-model variability in the simulation of spatial characteristics of seasonal monsoon precipitation. Ten out of the 25 models are able to simulate space–time characteristics of the South Asian monsoon precipitation reasonably well. The response of these selected ten models has been examined for projected changes in seasonal monsoon rainfall. The multi-model ensemble of these ten models projects a significant increase in monsoon precipitation with global warming. The substantial increase in precipitation is observed over western equatorial Indian Ocean and southern parts of India. However, the monsoon circulation weakens significantly under all the three climate change experiments. Possible mechanisms for the projected increase in precipitation and for precipitation–wind paradox have been discussed. The surface temperature over Asian landmass increases in pre-monsoon months due to global warming and heat low over northwest India intensifies. The dipole snow configuration over Eurasian continent strengthens in warmer atmosphere, which is conducive for the enhancement in precipitation over Indian landmass. No notable changes have been projected in the El Niño–Monsoon relationship, which is useful for predicting interannual variations of the monsoon.  相似文献   

11.
Summary The behavior of the Indian summer monsoon during the period 1979–1985 is examined with surface rainfall and infrared satellite data in order to determine how well the satellite measurements mimic the episodic rainfall processes. It is shown that equivalent-black-body-temperatures derived from satellite measured outgoing longwave radiation (OLR) estimates are reliable indicators for reproducing the timevariant zonal structure of monsoon rainfall over the Indian sub-continent—but only at preferred frequencies. The Indian summer monsoon is found to exhibit a distinct three episode cycle of active-break periods along two north-south aligned cross-sections; the first along the west Indian coast, the second through central India up to the plains of west Uttar Pradesh.We use the triplex behavior of the monsoon as a framework to describe individual monsoons from 1979 to 1985. This is done in terms of the initiation or phase, amplitude, duration, and propagation of the individual episodes. Cospectrum calculations between the rainfall and satellite temperature show that significant coherence is only associate with the frequencies corresponding to specific sub-seasonal fluctuating modes of the monsoon, i.e. 30–50 day and 10–20 day modes. The 30–50 day mode exhibits particularly strong coherence. It is shown how the behavior of the rainfall normals can be used to aid the calculation of a synthetic satellite temperature normal. Coherance at the 30–50 day mode in the co-spectrum of the departure time series is also strong; coherence at the 10–20 day mode is weaker but significant. This suggests that although satellite derived temperature is not a universal for rainfall, it could be used as a variable for monitoring the inra-annual behavior of the fluctuating rainfall modes of the monsoon.With 12 Figures  相似文献   

12.
Summary The present study examines the long term trend in sea surface temperatures (SSTs) of the Arabian Sea, Bay of Bengal and Equatorial South India Ocean in the context of global warming for the period 1901–2002 and for a subset period 1971–2002. An attempt has also been made to identify the relationship between SST variations over three different ocean areas, and All-India and homogeneous region summer monsoon rainfall variability, including the role of El-Ni?o/Southern Oscillation (ENSO). Annual sea surface temperatures of the Arabian Sea, Bay of Bengal and Equatorial South India Ocean show a significant warming trend of 0.7 °C, 0.6 °C and 0.5 °C per hundred years, respectively, and a relatively accelerated warming of 0.16 °C, 0.14 °C and 0.14 °C per decade during the 1971–2002 period. There is a positive and statistically significant relationship between SSTs over the Arabian Sea from the preceding November to the current February, and Indian monsoon rainfall during the period 1901–2002. The correlation coefficient increases from October and peaks in December, decreasing from February to September. This significant relationship is also found in the recent period 1971–2002, whereas, during 1901–70, the relationship is not significant. On the seasonal scale, Arabian Sea winter SSTs are positively and significantly correlated with Indian monsoon rainfall, while spring SSTs have no significant positive relationship. Nino3 spring SSTs have a negative significant relationship with Indian monsoon rainfall and it is postulated that there is a combined effect of Nino3 and Arabian Sea SSTs on Indian monsoon. If the Nino3 SST effect is removed, the spring SSTs over the Arabian Sea also have a significant relationship with monsoon rainfall. Similarly, the Bay of Bengal and Equatorial South Indian Ocean spring SSTs are significantly and positively correlated with Indian monsoon rainfall after removing the Nino3 effect, and correlation values are more pronounced than for the Arabian Sea. Authors’ address: Dr. D. R. Kothawale, A. A. Munot, H. P. Borgaonkar, Climatology and Hydrometeorology divisions, Indian Institute of Tropical Meteorology, Pune 411008, India.  相似文献   

13.
Summary Based on observed rainfall data of India Meteorological Department (IMD), correlation coefficients (CCs) have been computed between Indian summer monsoon rainfall (ISMR) and sea surface temperature (SST) anomalies over different Nino regions and standardised pressure difference between Tahiti and Darwin. Significant positive CCs are found between the Southern Oscillation Index (SOI) in winter and subsequent June rainfall over India. Concurrent with and subsequent to Indian summer monsoon, SOI shows significant positive CC with the mean rainfall of July to September (JAS). Significant negative CCs are found between JAS mean rain and the concurrent and following SST anomalies over Nino-3.4 region. On the basis of these correlations, it is proposed that the entire period of summer monsoon from June to September could be divided into two sub-periods such as: early summer (June) and mid-late summer (July to September) monsoon for prediction of ISMR in the extended range.In order to examine the characteristics of atmospheric circulation during some El-Nino years, divergent flow at 200hPa and omega field at 500hPa based on NCEP/NCAR reanalysis have been studied in detail. Major significant southward shift of upper level divergent field from India are related to El-Nino and this shift may be responsible for causing droughts during several El-Nino years over India. Also vertical wind fields at 500hPa show sinking motion over large parts of India and west Pacific and ascending motion over southern Indian Ocean, central and eastern Pacific during major drought years.  相似文献   

14.
Peninsular India and Sri Lanka receive major part of their annual rainfall during the northeast monsoon season (October–December). The long-term trend in the northeast monsoon rainfall over the Indian Ocean and peninsular India is examined in the vicinity of global warming scenario using the Global Precipitation Climatology Project (GPCP) dataset available for the period 1979–2010. The result shows a significant increasing trend in rainfall rate of about 0.5 mm day?1 decade?1 over a large region bounded by 10 °S–10 °N and 55 °E–100 °E. The interannual variability of seasonal rainfall rate over peninsular India using conventional rain gauge data is also investigated in conjunction to the Indian Ocean dipole. The homogeneous rain gauge data developed by Indian Institute of Tropical Meteorology over peninsular India also exhibit the considerable upward rainfall trend of about 0.4 mm day?1 decade?1 during this period. The associated outgoing longwave radiation shows coherent decrease in the order of 2 W?m?2 decade?1 over the rainfall increase region.  相似文献   

15.
Rainfall over south peninsular India during the northeast (NE) monsoon season (Oct–Dec) shows significant interannual variation. In the present study, we relate the northeast monsoon rainfall (NEMR) over south peninsular India with the major oscillations like El Ni?o Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Equatorial Indian Ocean Oscillation (EQUINOO) in the Indian and Pacific Oceans. For establishing the teleconnections, sea surface temperature, outgoing long wave radiation, and circulation data have been used. The present study reveals that the positive phase of ENSO, IOD, and EQUINOO favor the NEMR to be normal or above normal over southern peninsular India. The study reveals that the variability of NEMR over south peninsula can be well explained by its relationship with positive phase of ENSO, IOD, and EQUINOO.  相似文献   

16.
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   

17.
Summary The global nature of the Madden-Julian Oscillations (MJOs) have been investigated by applying a frequency filter to daily data for the summer monsoon months (June to September) during two contrasting years—1987, a deficient monsoon year and 1988, an excess monsoon year. Several meteorological parameters at five levels in the troposphere have been examined. Regions with large amplitude of these oscillations are isolated for each year. The results indicate that the global spatial distribution of these oscillations is more in a deficient year than in an excess year, in particular over the Indian subcontinent and the EI Niño Southern Oscillation (ENSO) regions. The principal modes of variability during these two years have been investigated through Empirical Orthogonal Functions (EOFs). The first two eigenmodes of 850 hPa zonal wind explain nearly 50% of the variance. The dipole type of structure between the Indian and the Pacific region is more apparent in 1987 than in 1988. Time-longitude cross sections of the filtered zonal wind over the equatorial regions clearly show that eastward propagation is detected in 1987, but is virtually absent in 1988. It is also seen that the 30–60 day filtered winds are stronger during the monsoon of 1987 than in 1988.  相似文献   

18.
The performance of the new multi-model seasonal prediction system developed in the frame work of the ENSEMBLES EU project for the seasonal forecasts of India summer monsoon variability is compared with the results from the previous EU project, DEMETER. We have considered the results of six participating ocean-atmosphere coupled models with 9 ensemble members each for the common period of 1960–2005 with May initial conditions. The ENSEMBLES multi-model ensemble (MME) results show systematic biases in the representation of mean monsoon seasonal rainfall over the Indian region, which are similar to that of DEMETER. The ENSEMBLES coupled models are characterized by an excessive oceanic forcing on the atmosphere over the equatorial Indian Ocean. The skill of the seasonal forecasts of Indian summer monsoon rainfall by the ENSEMBLES MME has however improved significantly compared to the DEMETER MME. Its performance in the drought years like 1972, 1974, 1982 and the excess year of 1961 was in particular better than the DEMETER MME. The ENSEMBLES MME could not capture the recent weakening of the ENSO-Indian monsoon relationship resulting in a decrease in the prediction skill compared to the “perfect model” skill during the recent years. The ENSEMBLES MME however correctly captures the north Atlantic-Indian monsoon teleconnections, which are independent of ENSO.  相似文献   

19.
Summary Variability of Indian summer monsoon rainfall is examined with respect to variability of surface wind stresses over Indian Ocean. The Indian Ocean region extending from 40°–120° E, and 30° S–25° N, has been divided into 8 homogeneous subregions, viz (1) Arabian Sea (AS), (2) Bay of Bengal (BB), (3) West-equatorial Indian Ocean (WEIO), (4) Central-equatorial Indian Ocean (CEIO), (5) East-equatorial Indian Ocean (EEIO), (6) South-west Indian Ocean (SWIO), (7) South-central Indian Ocean (SCIO), and (8) South-east Indian Ocean (SEIO). The period of study extends for 13 years from 1982–1994. Monthly NCEP surface wind stress data of five months – May through September, have been used in the study. The spatial variability of seasonal and monthly surface wind stresses shows very low values over CEIO and EEIO and very high values over AS, SWIO, and SEIO regions. On the seasonal scale, all India summer monsoon rainfall (AISMR) shows concurrent positive relationships with the surface wind stresses over AS, BB, WEIO, SWIO and SCIO and negative relationships with the surface wind stresses over EEIO and SEIO. The relationships of AISMR with the surface wind stresses over AS and WEIO are significant at 5% level. The concurrent relationships between monthly surface wind stresses over these 8 oceanic sub-regions and monthly subdivisional rainfalls over 29 sub-divisions have been studied. The rainfalls over the subdivisions in the central India and on the west coast of India are found to be significantly related with surface wind stresses over AS, SWIO, SCIO. Monthly subdivisional rainfalls of four subdivisions in the peninsular India show negative relationship with BB surface wind stresses. May surface wind stresses over AS, BB, WEIO, CEIO and SWIO have been found to be positively related with ensuing AISMR. The relationship with AS wind stresses is significant at 5% level and hence may be considered as a potential predictor of AISMR. Received May 21, 2001 Revised October 8, 2001  相似文献   

20.
500 hPa ridge positions over the Indian and the West Pacific regions during April are related with the summer monsoon rainfall over India. The ridge position over the Indian region shows better relation with monsoon rainfall than that shown by the ridge over the Pacific region. The multiple correlation of these ridge positions with monsoon rainfall exceeds 0.7. These predictive relationships are better than those shown by other parameters, viz. (1) Northern Hemispheric surface temperature; (2) East-Pacific sea surface tempera-ture; (3) El-Nino events and (4) Tahiti-Darwin pressure difference, and index of southern oscillation, over the 30-year samples analysed.  相似文献   

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