Interannual and long-term variability of Indian summer monsoon rainfall

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.     

Spatial monsoon variability with respect to NAO and SO

In this paper, the simultaneous effect of North Atlantic Oscillation (NAO) and Southern Oscillation (SO) on monsoon rainfall over different homogeneous regions/subdivisions of India is studied. The simultaneous effect of both NAO and SO on Indian summer monsoon rainfall (ISMR) is more important than their individual impact because both the oscillations exist simultaneously throughout the year. To represent the simultaneous impact of NAO and SO, an index called effective strength index (ESI) has been defined on the basis of monthly NAO and SO indices. The variation in the tendency of ESI from January through April has been analyzed and reveals that when this tendency is decreasing, then the ESI value throughout the monsoon season (June–September) of the year remains negative andvice versa. This study further suggests that during the negative phase of ESI tendency, almost all subdivisions of India show above-normal rainfall andvice versa. The correlation analysis indicates that the ESI-tendency is showing an inverse and statistically significant relationship with rainfall over 14 subdivisions of India. Area wise, about 50% of the total area of India shows statistically significant association. Moreover, the ESI-tendency shows a significant relationship with rainfall over north west India, west central India, central north east India, peninsular India and India as a whole. Thus, ESI-tendency can be used as a precursor for the prediction of Indian summer monsoon rainfall on a smaller spatial scale.     

Variation in the relationship of the Indian summer monsoon with global factors

Utilizing data for the long period 1871–1990, variation in the relationships between Indian monsoon rainfall (IMR) and tendencies of the global factors. Southern Oscillation Index (SOI) and the sea surface temperature (SST) over eastern equatorial Pacific Ocean has been explored. The periods for which relationships exist have been identified. Tendencies from the season SON (Sept-Oct-Nov) to season DJF (Dec-Jan-Feb) and from DJF to MAM (Mar-Apr-May) before the Indian summer monsoon are indicated respectively by SOIT-2/SSTT-2 and SOIT-l/SSTT-1, current tendency from JJA (June-July-Aug) to SON, by SOIT0/SSTT0, tendencies from SON to DJF and DJF to MAM following monsoon, by SOIT1/SSTT1 and SOIT2/SSTT2 respectively. It is observed that while the relationships of IMR with SSTT-1, SSTT0 and SSTT2 exist almost throughout the whole period, that with SOIT-1 exists for 1942–1990, with SOIT0 for 1871–1921 and 1957–1990 and with SOIT2, for 1871–1921 only. The relationships that exist with SOIT-1, SOIT2, SSTT-1, SSTT2 and with SSTT0 (for period 1931–1990) are found to be very good and those that exist with SOIT0 for periods 1871–1921 and 1957–90 and for SSTT0 for the period 1871–1930 are good. It is thus seen that the relationships of SOIT-1, SOIT0 and SOIT2 with IMR do not correspond well with those of SSTT-1, SSTT0 and SSTT2 with IMR respectively, even though SOI and SST are closely related to each other for all the seasons. SOIT-1 and SSTT-1 can continue to be used as predictors for IMRDuring the whole period, IMR is found to play a passive, i.e. of being influenced or anticipated by SSTT-1 as well as an active role, i.e. of influencing or anticipating SSTT2. This implies a complex and perhaps non-linear interaction between IMR and SST tendency from DJF to MAM. Possibly, this is a part of the larger interaction between Asian monsoon rainfall and the tropical Pacific. A possible physical mechanism for the interaction is indicated.     

Indian monsoon variability in relation to Regional Pressure Index

In this paper Regional Pressure Index (RPI) over the Indian region (20‡N—40‡N and 70‡0E—85‡E) has been constructed for 101 years (1899-1999) on a monthly scale. The relationship of these indices was carried out with the Indian Summer Monsoon Rainfall (June–September) (ISMR) over the various homogeneous regions, for all the time scales. From the analysis it has been seen that RPI in the month of May is significantly associated with ISMR over various regions on all the scales. The relationship is statistically significant at 1% level. The study reveals that RPI in the month of May and January will be a new precursor for the long range forecasting of ISMR on the smaller spatial scale. On the decadal and climatological scale, winter and spring time RPI show a significant inverse relationship with the rainfall over the regions Peninsular India (PI) and North West India (NWI), while the association is direct with Central North East India (CNEI) and North East India (NEI). The relationship is significant at 0.1 and 1% level respectively.     

Decoupling of the East Asian summer monsoon and Indian summer monsoon between 20 and 17 ka

Marine Oxygen Isotope Stage (MIS) 2, with its profound environmental and climatic changes from before the last glacial maximum (LGM) to the last deglaciation, is an ideal period for understanding the evolution of the East Asian summer monsoon (EASM) and Indian summer monsoon (ISM), two Asian monsoon sub-systems. With 875 stable oxygen isotope ratios and 43 ²³⁰Th dates from stalagmites in Sanxing Cave, southwestern China, we construct and interpret a new, replicated, Asian summer monsoon (ASM) record covering 30.9–9.7 ka with decadal resolution. δ¹⁸O records from this site and other reported Chinese caves display similar long-term orbitally dominated trends and synchronous millennial-scale strong and weak monsoonal events associated with climate changes in high northern latitudes. Interestingly, Sanxing δ¹⁸O and Arabian Sea records show a weakening ISM from 22 to 17 ka, while the Hulu and Qingtian records from East and Central China express a 3-ka intensifying EASM from 20 to 17 ka. This decoupling between EASM and ISM may be due to different sensitivities of the two ASM sub-systems in response to internal feedback mechanisms associated with the complex geographical or land-ocean configurations.     

Long range prediction of Indian summer monsoon rainfall

The search for new parameters for predicting the all India summer monsoon rainfall (AISMR) has been an important aspect of long range prediction of AISMR. In recent years NCEP/NCAR reanalysis has improved the geographical coverage and availability of the data and this can be easily updated. In this study using NCEP/NCAR reanalysis data on temperature, zonal and meridional wind at different pressure levels, few predictors are identified and a prediction scheme is developed for predicting AISMR. The regression coefficients are computed by stepwise multiple regression procedure. The final equation explained 87% of the variance with multiple correlation coefficient (MCC), 0.934. The estimated rainfall in the El-Niño year of 1997 was ?1.7% as against actual of 4.4%. The estimated rainfall deficiency in both the recent deficient years of 2002 and 2004 were ?19.5% and ?8.5% as against observed ?20.4% and ?11.5% respectively.     

On the impacts of ENSO and Indian Ocean dipole events on sub-regional Indian summer monsoon rainfall

The relative impacts of the ENSO and Indian Ocean dipole (IOD) events on Indian summer (June–September) monsoon rainfall at sub-regional scales have been examined in this study. GISST datasets from 1958 to 1998, along with Willmott and Matsuura gridded rainfall data, all India summer monsoon rainfall data, and homogeneous and sub-regional Indian rainfall datasets were used. The spatial distribution of partial correlations between the IOD and summer rainfall over India indicates a significant impact on rainfall along the monsoon trough regions, parts of the southwest coastal regions of India, and also over Pakistan, Afghanistan, and Iran. ENSO events have a wider impact, although opposite in nature over the monsoon trough region to that of IOD events. The ENSO (IOD) index is negatively (positively) correlated (significant at the 95% confidence level from a two-tailed Student t-test) with summer monsoon rainfall over seven (four) of the eight homogeneous rainfall zones of India. During summer, ENSO events also cause drought over northern Sri Lanka, whereas the IOD events cause surplus rainfall in its south. On monthly scales, the ENSO and IOD events have significant impacts on many parts of India. In general, the magnitude of ENSO-related correlations is greater than those related to the IOD. The monthly-stratified IOD variability during each of the months from July to September has a significant impact on Indian summer monsoon rainfall variability over different parts of India, confirming that strong IOD events indeed affect the Indian summer monsoon.

Influence of different land-surface processes on Indian summer monsoon circulation

The impact of different land-surface parameterisation schemes for the simulation of monsoon circulation during a normal monsoon year over India has been analysed. For this purpose, three land-surface parameterisation schemes, the NoaH, the Multi-layer soil model and the Pleim-Xiu were tested using the latest version of the regional model (MM5) of the Pennsylvania State University (PSU)/National Center for Atmospheric Research (NCAR) over the Indian summer monsoon region. With respect to different land-surface parameterisation schemes, latent and sensible heat fluxes and rainfall were estimated over the Indian region. The sensitivity of some monsoon features, such as Somali jet, tropical easterly jet and mean sea level pressure, is discussed. Although some features of the Indian summer monsoon, such as wind and mean sea level pressure, were fairly well-simulated by all three schemes, many differences were seen in the simulation of the typical characteristics of the Indian summer monsoon. It was noticed from the results that the features of the Indian summer monsoon, such as strength of the low-level westerly jet, the cross-equatorial flow and the tropical easterly jet were better simulated by NoaH compared with verification analysis than other land-surface schemes. It was also observed that the distribution of precipitation over India during the peak period of monsoon (July) was better represented with the use of the NoaH scheme than by other schemes.

Spatio-temporal variability of summer monsoon rainfall over Orissa in relation to low pressure systems

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     

Large-scale interannual variation of the summer monsoon over India and its empirical prediction

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.     

Intraseasonal oscillations and interannual variability of surface winds over the Indian monsoon region

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.     

The role of low-frequency intraseasonal oscillations in the anomalous Indian summer monsoon rainfall of 2002

We analyze the dynamical features and responsible factors of the low-frequency intraseasonal time scales which influenced the nature of onset, intensity and duration of active/break phases and withdrawal of the monsoon during the anomalous Indian summer monsoon of 2002 — the most severe drought recorded in recent times. During that season, persistent warm sea surface temperature anomalies over the equatorial Indian Ocean played a significant role in modulating the strength of the monsoon Hadley circulation. This in turn affected the onset and intense break spells especially the long break during the peak monsoon month of July. Strong low-frequency intraseasonal modulations with significant impact on the onset and active/break phases occurred in 2002 which were manifested as a good association between low-frequency intraseasonal oscillations and the onset and active/break spells. Further, SST anomalies over the equatorial Indo-Pacific region on low-frequency intraseasonal time scales were found to affect the equatorial eastward and thereby off-equatorial northward propagations of enhanced convection over the Indian region. These propagations in turn modulated the active/break cycle deciding the consequent severity of the 2002 drought.     

基于统计-动力反演的近千年印度夏季风驱动机制探讨

过去1000年的气候变化是最近数十年人类活动影响加强情况下全球气候变化的自然背景, 其变化规律和驱动机制的研究对预测未来气候变化有着重要意义。非线性统计-动力反演方法结合了统计模型和动力模型的优点, 能充分利用观测数据反演系统各因子之间的相互关系。本文尝试应用非线性统计-动力反演方法建立印度夏季风的动力方程, 为研究印度夏季风的驱动机制提供量化参考。经研究发现:近千年印度夏季风系统是复杂非线性动力系统; 工业革命前印度夏季风变化的主要驱动力是北大西洋海表温, 其次是温室气体(N2O和CO2)浓度与阿拉伯海海表温、ENSO及太阳辐照度等的相互作用; 在工业革命后期, 温室气体(CH4、N2O和CO2)浓度及其与北大西洋海表温、太阳辐照度、ENSO及北极温度等的相互作用成为印度夏季风的主要驱动力; 单因子甲烷和N2O是印度夏季风的驱动力, 而它们的非线性相互作用(两个因子的交叉项)却是稳定作用力。总体来说, 工业革命前, 北大西洋海表温度是印度夏季风的主要驱动因子; 工业革命后, 温室气体则成为主要的驱动因子。     

Interannual and long-term variability of the summer monsoon and its possible link with northern hemispheric surface air temperature

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.     

Probabilistic multi-model ensemble prediction of Indian summer monsoon rainfall using general circulation models: A non-parametric approach

Probabilistic prediction has the ability to convey the intrinsic uncertainty of forecast that helps the decision makers to manage the climate risk more efficiently than deterministic forecasts. In recent times, probabilistic predictions obtained from the products from General Circulation Models (GCMs) have gained considerable attention. The probabilistic forecast can be generated in parametric (assuming Gaussian distribution) as well as non-parametric (counting method) ways. The present study deals with the non-parametric approach that requires no assumption about the form of the forecast distribution for the prediction of Indian summer monsoon rainfall (ISMR) based on the hindcast run of seven general circulation models from 1982 to 2008. Probabilistic prediction from each of the GCM products has been generated by non-parametric methods for tercile categories (viz. below normal (BN), near-normal (NN), and above normal (AN)) and evaluation of their skill is assessed against observed data. Five different types of PMME schemes have been used for combining probabilities from each GCM to improve the forecast skill as compared to the individual GCMs. These schemes are different in nature of assigning the weights for combining probabilities. After a rigorous analysis through Rank Probability Skill Score (RPSS) and relative operating characteristic (ROC) curve, the superiority of PMME has been established over climatological probability. It is also found that, the performances of PMME1 and PMME3 are better than all the other methods whereas PMME3 has showed more improvement over PMME1.     

地球轨道对北大西洋淡水注入影响印度夏季风的调节作用：以8.2 ka和4.2 ka事件为例

北大西洋淡水注入触发的千年尺度气候突变事件发生在不同地球轨道背景下, 理解地球轨道参数对印度夏季风千年尺度变率特征的调节作用, 对理解未来印度夏季风对北大西洋淡水注入的响应具有重要的科学意义。本研究利用通用地球系统模式CESM, 探讨印度夏季风在8.2 ka B.P. 和4.2 ka B.P. 对相同北大西洋淡水注入的响应差异。模拟结果显示, 北大西洋淡水注入使得印度夏季风强度显著减弱, 其中夏季风降水变化在这两次事件中没有显著的空间差异, 但变化幅度在4.2 ka B.P. 要显著大于其在8.2 ka B.P., 表明地球轨道参数对印度夏季风千年尺度变率特征具有重要的调节作用。进一步分析显示, 地球轨道并非通过影响温盐环流强度进行调节, 而与夏季太阳辐射的高低有关。在4.2 ka B.P. 时, 在相同的淡水注入下, 由于夏季太阳辐射较低, 加剧了北大西洋的降温, 同时也增强了其对下游大气的冷却作用, 使得欧亚大陆南部对流层中上层大气具有更大的降温幅度, 这进一步削弱了欧亚大陆南部与赤道印度洋对流层中上层大气的经向温度梯度, 从而导致印度夏季风相较于8.2 ka B.P. 具有更大的衰退幅度。因此, 在较低夏季太阳辐射背景下, 印度夏季风对北大西洋淡水注入的响应更为敏感。

     

Meteorological fields variability over the Indian seas in pre and summer monsoon months during extreme monsoon seasons

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.     

Interannual variability of onset of the summer monsoon over India and its prediction

In this article, the interannual variability of certain dynamic and thermodynamic characteristics of various sectors in the Asian summer monsoon domain was examined during the onset phase over the south Indian peninsula (Kerala Coast). Daily average (0000 and 1200 UTC) reanalysis data sets of the National Centre for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) for the period 1948–1999 were used. Based on 52 years onset date of the Indian summer monsoon, we categorized the pre-onset, onset, and post-onset periods (each an average of 5 days) to investigate the interannual variability of significant budget terms over the Arabian Sea, Bay of Bengal, and the Indian peninsula. A higher difference was noticed in low-level kinetic energy (850 hPa) and the vertically integrated generation of kinetic energy over the Arabian Sea from the pre-onset, onset, and post-onset periods. Also, significant changes were noticed in the net tropospheric moisture and diabatic heating over the Arabian Sea and Indian peninsula from the pre-onset to the post-onset period. It appears that attaining the magnitude of 40 m² s⁻² and then a sharp rise in kinetic energy at 850 hPa is an appropriate time to declare the onset of the summer monsoon over India. In addition to a sufficient level of net tropospheric moisture (40 mm), a minimum strength of low-level flow is needed to trigger convective activity over the Arabian Sea and the Bay of Bengal. An attempt was also made to develop a location-specific prediction of onset dates of the summer monsoon over India based on energetics and basic meteorological parameters using multivariate statistical techniques. The regression technique was developed with the data of May and June for 42 years (1948–1989) and validated with 10 years NCEP reanalysis from 1990 to 1999. It was found that the predicted onset dates from the regression model are fairly in agreement with the observed onset dates obtained from the Indian Meteorology Department.     

The Indian summer monsoon as revealed by the NCMRWF system

In this study, we present the mean seasonal features of the Indian summer monsoon circulation in the National Centre for Medium Range Weather Forecasting (NCMRWF) global data assimilation and forecast system. The large-scale budgets of heat and moisture are examined in the analyzed and model atmosphere. The daily operational analyses and forecasts (day 1 through day 5) produced for the summer seasons comprising June, July and August of 1995 and 1993 have been considered for the purpose. The principal aim of the study is two-fold. Primarily, to comprehend the influence of the systematic errors over the Indian summer monsoon, secondarily, to analyze the performance of the model in capturing the interseasonal variability. The heat and moisture balances show reduction in the influx of heat and moisture in the model forecasts compared to the analyzed atmosphere over the monsoon domain. Consequently, the diabatic heating also indicates reducing trend with increase in the forecast period. In effect, the strength of Indian summer monsoon, which essentially depends on these parameters, weakens considerably in the model forecasts. Despite producing feeble monsoon circulation, the model captures interseasonal variability realistically. Although, 1995 and 1993 are fairly normal monsoon seasons, the former received more rainfall compared to the latter in certain pockets of the monsoon domain. This is clearly indicated by the analyzed and model atmosphere in terms of energetics.     

On breaks of the Indian monsoon

For over a century, the term break has been used for spells in which the rainfall over the Indian monsoon zone is interrupted. The phenomenon of ’break monsoon’ is of great interest because long intense breaks are often associated with poor monsoon seasons. Such breaks have distinct circulation characteristics (heat trough type circulation) and have a large impact on rainfed agriculture. Although interruption of the monsoon rainfall is considered to be the most important feature of the break monsoon, traditionally breaks have been identified on the basis of the surface pressure and wind patterns over the Indian region. We have defined breaks (and active spells) on the basis of rainfall over the monsoon zone. The rainfall criteria are chosen so as to ensure a large overlap with the traditional breaks documented by Ramamurthy (1969) and Deet al (1998). We have identified these rainbreaks for 1901-89. We have also identified active spells on the basis of rainfall over the Indian monsoon zone. We have shown that the all-India summer monsoon rainfall is significantly negatively correlated with the number of rainbreak days (correlation coefficient -0.56) and significantly positively correlated with the number of active days (correlation coefficient 0.47). Thus the interannual variation of the all-India summer monsoon rainfall is shown to be related to the number of days of rainbreaks and active spells identified here. There have been several studies of breaks (and also active spells in several cases) identified on the basis of different criteria over regions differing in spatial scales (e.g., Websteret al 1998; Krishnanet al it 2000; Goswami and Mohan 2000; and Annamalai and Slingo 2001). We find that there is considerable overlap between the rainbreaks we have identified and breaks based on the traditional definition. There is some overlap with the breaks identified by Krishnanet al (2000) but little overlap with breaks identified by Websteret al (1998). Further, there are three or four active-break cycles in a season according to Websteret al (1998) which implies a time scale of about 40 days for which Goswami and Mohan (2000), and Annamalai and Slingo (2001) have studied breaks and active minus break fluctuations. On the other hand, neither the traditional breaks (Ramamurthy 1969; and Deet al 1998) nor the rainbreaks occur every year. This suggests that the `breaks’ in these studies are weak spells of the intraseasonal variation of the monsoon, which occur every year. We have derived the OLR and circulation patterns associated with rainbreaks and active spells and compared them with the patterns associated with breaks/active minus break spells from these studies. Inspite of differences in the patterns over the Indian region, there is one feature which is seen in the OLR anomaly patterns of breaks identified on the basis of different criteria as well as the rainbreaks identified in this paper viz., a quadrapole over the Asia-west Pacific region arising from anomalies opposite (same) in sign to those over the Indian region occurring over the equatorial Indian Ocean and northern tropical (equatorial) parts of the west Pacific. Thus it appears that this quadrapole is a basic feature of weak spells of the intraseasonal variation over the Asia-west Pacific region. Since the rainbreaks are intense weak spells, this basic feature is also seen in the composite patterns of these breaks. We find that rainbreaks (active spells) are also associated with negative