Indian Monsoon Rainfall Research Articles

Inter‐annual variability of summer monsoon rainfall over Myanmar

ABSTRACTRainfall over Myanmar has large inter‐annual variability causing droughts and floods in many years. In this study, rainfall variability (in monthly scale) over Myanmar during summer monsoon has been examined using observed data. It is found that monthly rainfall in June, July and August months do not have any relation among each other, indicating that monthly rainfall received in Myanmar in these 3 months vary due to different mechanisms. In order to develop an effective drought monitoring and prediction system for the country, such mechanisms of rainfall variability have to be studied. Using composite wind analysis for excess and deficit rainfall years, it is found that deficiency of rainfall occurs when south‐westerly winds at 850 hPa are weaker over the region in June. During excess rainfall years, south‐westerly wind anomalies seen in June turn to stronger and milder westerly winds in July and August, respectively. However, a cyclonic anomaly is seen over North Bay of Bengal adjoining western coast of Myanmar in all the 3 months. It is found that the Myanmar rainfall is correlated positively with the sea surface temperature over central Pacific Ocean. An empirical orthogonal function (EOF) analysis of monthly and seasonal mean rainfall over the region has been carried out. The leading mode (EOF‐1) shows coherent spatial patterns between the Indian monsoon rainfall over east and central parts of the India and rainfall over the western Pacific. The second leading mode of seasonal rainfall shows a trend in rainfall during the study period.

Changing characteristics of extreme wet and dry spells of Indian monsoon rainfall

AbstractModeling of extreme events and its dynamic behavior have always been an intriguing topic. Increase in the magnitude and frequency of extreme events has widely been reported in recent decades, which is attributed to abrupt changes in climate. Numerous studies on extreme Indian monsoon characteristics, using a coarse‐resolution data set, have pointed out significant changes in heavy precipitation pattern over India. However, these studies differ in their conclusions, emphasizing the need for a fine‐resolution analysis. The present study aims to analyze the spatiotemporal variations and trends in the extreme (wet and dry) Indian monsoon precipitation, using 0.25° × 0.25° high‐resolution gridded data for a period of 113 years (1901–2013). Significant increase in the maximum intensity of rainfall and spatial heterogeneity is observed over the past half century. In addition, significant negative trends in wet spell durations and positive trends in dry spell durations are observed over wet regions; whereas contrasting trends are observed over dry regions. A shift in the frequency distribution of extreme events during the monsoon period is also noticed. The 50 year return level of maximum intensity clearly shows positive trends over the past century. Though characteristics of extremes are observed to be highly localized, apparent signs of wet regions turning drier and dry regions turning wetter are obtained. A comprehensive insight into different characteristics (intensity, spell, onset, and frequency) of Indian monsoon extremes is provided, which will help in effective water resources management and flood/drought hazard preparedness.

Spring “Predictability Barrier” and Indian Summer Monsoon

Monthly correlation of Indian monsoon rainfall (IMR) index with various monsoon indices changes predominantly and peaks within summer season (Ailikun and Yasunari, 2001). There is transition in this lead and lagged correlation during spring (March, April and May). This spring transition could not be captured in many general circulation models (GCMs) and is termed as “predictability barrier” (Latif and Graham, 1991). It has been less investigated and hence reasons for dampening/reversal of associated large scale fields during spring are intriguing. Present study illustrates dynamics of spring predictability barrier with Indian summer (June, July, August and September) monsoon (ISM). In this study, based on data from 1979 to 2008, an internal dynamics between various monsoon indices and corresponding IMR anomaly is diagnosed. It is found that secular behaviour of El Nino– Southern Oscillation (ENSO) during preceding spring of monsoon months (June, July, August and September) gets reversed in succeeding spring. Though correlation between various monsoon indices and ISM index remains similar during preceding and succeeding springs with peaks during monsoon (June, July, August and September), corresponding large scale fields show that strong significant convection dominates over the southern equatorial eastern Pacific Ocean, northern equatorial western Pacific Ocean, Indonesian throughflow and weaker significant convection dominates over the Head Bay of Arabian Sea and western to central Indian sub-continent during preceding spring. Such patterns reverse during succeeding spring.

CMIP5 Projected Changes in the Annual Cycle of Indian Monsoon Rainfall

The annual cycle of Indian monsoon rainfall plays a critical role in the agricultural as well as the industrial sector. Thus, it is necessary to evaluate the behaviour of the monsoon annual cycle in a warming climate. There are several studies on the variability and uncertainty of the Indian monsoon. This study, examines the impact of climate change on the annual cycle of monsoon rainfall in India from 1871–2100 by applying 20 model simulations designed by the World Climate Research Programme (WCRP) coupled with the model inter-comparison Project 5 (CMIP5). It is found that the models MPI-ESM-LR, INM-CM4 and MRI-CGCM3 best capture the spatial patterns of the monsoon rainfall peak month (MRPM) of the winter monsoon compared to observations, whereas HadGEM2-AO and MIROC-ESM-CHEM best capture the MRPM of the summer monsoon. The MIROC, MIROC-ESM, and MIROC-ESM-CHEM models best capture the average rainfall intensity as well as the MRPM of all-India rainfall. This paper examines the future spatial distribution of the MRPM for meteorological sub-divisions of India, that can have crucial implications for water resources and management. Although the future projections as per the CMIP5 models indicate no changes in the MRPM of the all-India rainfall, a reduction in average intensity can be expected. The projections indicate a shift in the MRPM in some meteorological sub-divisions, particularly with regard to the summer monsoon but no significant change has been projected for the winter monsoon. For example, the summer monsoon MRPM is projected to move from July to August in northern and central India.

Spatiotemporal patterns and trends of Indian monsoonal rainfall extremes

In this study, we provide a comprehensive analysis of trends in the extremes during the Indian summer monsoon (ISM) months (June to September) at different temporal and spatial scales. Our goal is to identify and quantify spatiotemporal patterns and trends that have emerged during the recent decades and may be associated with changing climatic conditions. Our analysis primarily relies on quantile regression that avoids making any subjective choices on spatial, temporal, or intensity pattern of extreme rainfall events. Our analysis divides the Indian monsoon region into climatic compartments that show different and partly opposing trends. These include strong trends towards intensified droughts in Northwest India, parts of Peninsular India, and Myanmar; in contrast, parts of Pakistan, Northwest Himalaya, and Central India show increased extreme daily rain intensity leading to higher flood vulnerability. Our analysis helps explain previously contradicting results of trends in average ISM rainfall.

Possible shift in the ENSO-Indian monsoon rainfall relationship under future global warming.

EI Nino-Southern Oscillation (ENSO) and Indian monsoon rainfall are known to have an inverse relationship, which we have observed in the rainfall spectrum exhibiting a spectral dip in 3–5 y period band. It is well documented that El Nino events are known to be associated with deficit rainfall. Our analysis reveals that this spectral dip (3–5 y) is likely to shift to shorter periods (2.5–3 y) in future, suggesting a possible shift in the relationship between ENSO and monsoon rainfall. Spectral analysis of future climate projections by 20 Coupled Model Intercomparison project 5 (CMIP5) models are employed in order to corroborate our findings. Change in spectral dip speculates early occurrence of drought events in future due to multiple factors of global warming.

Simulated Impact of Intensification of Irrigation on Indian Monsoon Rainfall and Surface Fluxes

Using Bio-sphere Atmosphere Transfer scheme (BATS) coupled regional climate model (RegCM4) the impact of intensification of irrigation on Indian monsoon atmospheric circulations and surface fluxes is being studied. Land use/land cover change is performed in the model to study the design or sensitivity experiments. This is implemented by changing the vegetation/landuse type in the model. Impact of increase in irrigation activity over Central India and Northwestern region of India is still an open question and hence it is attempted to answer them in this research work. In the first irrigation sensitivity experiment, vegetation/land-use types have been modified to “irrigated crop” type along districts of Central India, Indo-Gangetic plain and northern parts of India, in the RegCM4 model to test the hypothesis that whether-“increase in irrigation decreases monsoon (JJAS) precipitation over certain regions of India and increases pre-monsoon (MAM) precipitation”. Simulations suggest that increase in irrigation over Indian monsoon domain has altered the Indian summer (JJAS) monsoon by weakening it at regional scale over various regions due to probable weakening of the temperature contrast between land and sea. Increase in irrigation over the central India causes a decrease (increase) in sensible heat flux (latent heat flux, surface pressure) in summer monsoon season. To further test the hypothesis that the northwestern region of India is a hotspot for land atmosphere interactions and to test the impact of irrigation intensification over northwestern region of Indian subcontinent, on Indian summer monsoon another sensitivity experiment with irrigation intensification over northwestern regions of India is performed using RegCM4. This experiment suggests that irrigation impact or sensitivity on soil moisture; surface fluxes are limited to northwestern region of Indian subcontinent. Simulations performed at higher (50 km) resolution shows increase in precipitation during pre-monsoon season over northwestern regions of India, too. The Indian monsoon circulations are a part of global general atmospheric circulations periodic in nature and any form of vegetation impact study is a complex process. Thus, from the irrigation sensitivity experiments (using a regional climate model) it can be concluded that due to increase in irrigated land over India, pre-monsoon (MAM) precipitation increase particularly over Central and northwestern regions of India, with the development of anomalous cyclonic circulations.

Statistical Selection of the Optimum Models in the CMIP5 Dataset for Climate Change Projections of Indian Monsoon Rainfall

Monsoons are the life and soul of India’s financial aspects, especially that of agribusiness in deciding cropping patterns. Around 80% of the yearly precipitation occurs from June to September amid monsoon season across India. Thus, its seasonal mean precipitation is crucial for agriculture and the national water supply. From the start of the 19th century, several studies have been conducted on the possible increments in Indian summer monsoon precipitation in the future. Unfortunately, none of them has endeavoured to discover the models whose yield give the best fit to the observed data. Here some statistical tests are performed to quantify the models of Coupled Model Inter-comparison Project 5 (CMIP5). Then, after, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to select optimum models. It shows that four models, CCSM4, CESM1-CAM5, GFDL-CM3, and GFDL-ESM2G, best capture the pattern in Indian summer monsoon rainfall over the historical period (1871–2005). Further, Student’s t-test is utilized to estimate the significant changes in meteorological subdivisions of selected optimum models. Also, our results reveal the Indian meteorological subdivisions which are liable to encounter significant changes in mean at confidence levels that differ from 80% to 99%.

Deciphering the desiccation trend of the South Asian monsoon hydroclimate in a warming world

Rising propensity of precipitation extremes and concomitant decline of summer-monsoon rains are amongst the most distinctive hydroclimatic signals that have emerged over South Asia since 1950s. A clear understanding of the underlying causes driving these monsoon hydroclimatic signals has remained elusive. Using a state-of-the-art global climate model with high-resolution zooming over South Asia, we demonstrate that a juxtaposition of regional land-use changes, anthropogenic-aerosol forcing and the rapid warming signal of the equatorial Indian Ocean is crucial to produce the observed monsoon weakening in recent decades. Our findings also show that this monsoonal weakening significantly enhances occurrence of localized intense precipitation events, as compared to the global-warming response. A 21st century climate projection using the same high-resolution model indicates persistent decrease of monsoonal rains and prolongation of soil drying. Critical value-additions from this study include (1) realistic simulation of the mean and long-term historical trends in the Indian monsoon rainfall (2) robust attributions of changes in moderate and heavy precipitation events over Central India (3) a 21st century projection of drying trend of the South Asian monsoon. The present findings have profound bearing on the regional water-security, which is already under severe hydrological-stress.

Unraveling the missing link of ENSO control over the Indian monsoon rainfall

AbstractUsing long daily rainfall (113 years) data, clear evidence of modulation of the statistics of subseasonal active and break spells of the Indian summer monsoon rainfall (ISMR) by the El Niño–Southern Oscillation (ENSO) is unraveled. We show that during the El Niño (La Nina) years, the frequency of longer break (active) spells and shorter active (break) spells increases substantially, while the frequency of shorter breaks (active) and longer active (break) spells decreases compared to ENSO neutral years. It is shown that the large‐scale teleconnection through which ENSO weakens (strengthens) the ISMR through shortening (lengthening) of the length of rainy season (LRS) also creates a background for modulation of the statistics of subseasonal spells leading to a further reduction (increase) in the ISMR during El Niño (La Niña) years. Our findings indicate that the “statistics of subseasonal spells” is predictable, brightening the prospect of seasonal prediction of the ISMR.

Relation between the upper ocean heat content in the equatorial Atlantic during boreal spring and the Indian monsoon rainfall during June–September

ABSTRACTEarlier studies have identified a teleconnection between the Atlantic zonal mode (AZM) and Indian summer monsoon rainfall (ISMR), both of which are active during the boreal summer (AZM: June–August; ISMR: June–September). It is known that El Niño‐Southern Oscillation (ENSO)‐like coupled dynamics are operational in the tropical Atlantic during the AZM events. Our goal here is to extend this process understanding to seek a predictive relation between the tropical Atlantic and the ISMR based on these known teleconnections. Monthly composite analysis of the zonal surface winds, heat content, and sea surface temperature (SST) in the equatorial Atlantic tells us that signatures of a warm or cold AZM event begin to emerge as early as January of that year. We found significant correlations between the ISMR and the low level zonal winds in the western equatorial Atlantic and heat content in the eastern equatorial Atlantic in the boreal spring season. Tracking coherent changes in these winds and the evolution of the heat content in the deep tropical Atlantic in the boreal spring may offer the potential for skillful predictions of the ensuing summer monsoon anomalies, especially during non‐ENSO years when the predictability of ISMR tends to be low.

Analysing Predictability in Indian Monsoon Rainfall: A Data Analytic Approach

This paper examines monthly and annual data to analyse predictability in the Indian monsoon rainfall. The periodic structure in the time series data is extracted using wavelets and the residual random part is separately modeled using artificial neural networks (ANN). Although wavelet and neural network based hybrid techniques have been widely applied in the recent years, the present approach has not been investigated so far. Our results show that the estimated periodic and random components comprise 30 and 15 %, respectively, variance of the total rainfall in case of annual data, whereas the model explains 93 % of variance in case of monthly data. It is shown that the prediction is more accurate when periodic and random parts are treated separately.

Teleconnections of Indian monsoon rainfall with AMO and Atlantic tripole

The teleconnections between the decadal modes in the Indian monsoon rainfall (IMR) and the North Atlantic sea surface temperature are investigated. The two decadal modes of variability in the North Atlantic, the Atlantic multidecadal oscillation (AMO) and the Atlantic tripole, have opposite relation with the two decadal modes of IMR. The AMO has positive correlation with the monsoon rainfall while the Atlantic tripole has negative correlation. This study has put forward hypotheses for the mechanisms involved in the teleconnections of the AMO and the Atlantic tripole with the IMR. The warm phase of AMO may influence the monsoon through the summer North Atlantic Oscillation (SNAO) and further through the equatorial zonal winds which increase the moisture flow over India by enhancing the southwesterly flow. The warm phase of Atlantic tripole may impact the monsoon through the all-season NAO, leading to decreased moisture flow over India through the equatorial wind pattern. The observed relations between the decadal modes in the North Atlantic and the Indian monsoon are explored in the simulations of National Center for Atmospheric Research Community Climate System Model version 4 (CCSM4) model. Although the model supports the observed decadal teleconnection between the Atlantic Ocean and Indian monsoon, it has limitations in capturing the details of the spatial pattern associated with the teleconnection. The teleconnections of AMO and Atlantic tripole with the Indian monsoon is further demonstrated through an experiment with CCSM4 by decoupling the North Atlantic Ocean. The hypotheses for the mechanisms of the Atlantic teleconnections are also explored in the CCSM4 simulation.

Seasonal-to-Interannual Time-Scale Dynamics of the Equatorial Undercurrent in the Indian Ocean

AbstractThis paper investigates the structure and dynamics of the Equatorial Undercurrent (EUC) of the Indian Ocean by analyzing in situ observations and reanalysis data and performing ocean model experiments using an ocean general circulation model and a linear continuously stratified ocean model. The results show that the EUC regularly occurs in each boreal winter and spring, particularly during February and April, consistent with existing studies. The EUC generally has a core depth near the 20°C isotherm and can be present across the equatorial basin. The EUC reappears during summer–fall of most years, with core depth located at different longitudes and depths. In the western basin, the EUC results primarily from equatorial Kelvin and Rossby waves directly forced by equatorial easterly winds. In the central and eastern basin, however, reflected Rossby waves from the eastern boundary play a crucial role. While the first two baroclinic modes make the largest contribution, intermediate modes 3–8 are also important. The summer–fall EUC tends to occur in the western basin but exhibits obvious interannual variability in the eastern basin. During positive Indian Ocean dipole (IOD) years, the eastern basin EUC results largely from Rossby waves reflected from the eastern boundary, with directly forced Kelvin and Rossby waves also having significant contributions. However, the eastern basin EUC disappears during negative IOD and normal years because westerly wind anomalies force a westward pressure gradient force and thus westward subsurface current, which cancels the eastward subsurface flow induced by eastern boundary–reflected Rossby waves. Interannual variability of zonal equatorial wind that drives the EUC variability is dominated by the zonal sea surface temperature (SST) gradients associated with IOD and is much less influenced by equatorial wind associated with Indian monsoon rainfall strength.

Comparing two high-resolution gauge-adjusted multisatellite rainfall products over India for the southwest monsoon period

Reliable high-resolution rainfall estimates are vital for hydrological and weather/climate-related applications and evaluation of high-resolution numerical model outputs. Multisatellite rainfall products provide immense opportunities to analyse rainfall at regular spatial and temporal scales, but suffer from large region- and season-dependent biases. Direct calibration or merging of ground-based observations with multisatellite rainfall estimates essentially provides more accurate rainfall estimates as it benefits from the relative merits of both the sources. In this study, two popular gauge-adjusted multisatellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research monitoring 3B42 version 7 (3B42V7) and Climate Prediction Center (CPC) Rainfall Estimation Algorithm version 2 (RFE2.0) are compared with the recently released and improved gridded India Meteorological Department (IMD) gauge-based rainfall estimates over India. The comparison is done for a 13 year southwest monsoon season ranging from 2001 to 2013 at 0.25° latitude/longitude resolution. A number of skill metrics such as mean, bias, co-efficient of variation, correlation co-efficient, anomaly correlation, pattern correlation and root-mean-square error (RMSE) are computed to assess the accuracy of both the merged satellite-gauge rainfall products. The prominent Indian monsoon rainfall features are well captured by both 3B42V7 and RFE2.0 products, in general. However, they overestimate mean rainfall at the all-India scale and the overestimation is comparatively larger for RFE2.0 than for 3B42V7. Even though the interannual variability of the Indian monsoon rainfall from both the gauge-adjusted multisatellite data sets is comparable with the gauge-based estimates for the study period, RFE2.0 overestimates light rainfall and underestimates heavy rainfall. Moreover, the comparison at sub-regional scales shows that 3B42V7 overestimates rainfall over eastern India and the foothills of the Himalayas and underestimates along the west coast and over the northeast, whereas RFE2.0 underestimates monsoon rainfall over the three sub-regions except over eastern India where it overestimates rainfall by about 25%. Both the gauge-adjusted multisatellite rainfall products show larger RMSE of the order of 100% along the west coast of India, which is a cause of concern. Overall analysis suggests that 3B42V7 is superior to RFE2.0 at synoptic scale over the Indian monsoon region.

Rethinking Indian monsoon rainfall prediction in the context of recent global warming.

Prediction of Indian summer monsoon rainfall (ISMR) is at the heart of tropical climate prediction. Despite enormous progress having been made in predicting ISMR since 1886, the operational forecasts during recent decades (1989–2012) have little skill. Here we show, with both dynamical and physical–empirical models, that this recent failure is largely due to the models' inability to capture new predictability sources emerging during recent global warming, that is, the development of the central-Pacific El Nino-Southern Oscillation (CP–ENSO), the rapid deepening of the Asian Low and the strengthening of North and South Pacific Highs during boreal spring. A physical–empirical model that captures these new predictors can produce an independent forecast skill of 0.51 for 1989–2012 and a 92-year retrospective forecast skill of 0.64 for 1921–2012. The recent low skills of the dynamical models are attributed to deficiencies in capturing the developing CP–ENSO and anomalous Asian Low. The results reveal a considerable gap between ISMR prediction skill and predictability.

Possible roles of regional SST anomalies in long-term changes in the relationship between the Indian and Australian summer monsoon rainfall

The present study investigates long-term changes in the relationship between interannual variations of the Indian monsoon rainfall (IMR) and the Australian monsoon rainfall (AMR) during the period 1900–2010. It is found that the relationship between austral summer AMR and the following boreal summer IMR (denoted as the AMR-IMR relationship) is negative during 1900–1930 and 1960–1990, but weak positive during 1930–1960. This long-term change in the AMR-IMR relationship is more prominent than the change in the relationship between boreal summer IMR and the succeeding austral summer AMR (denoted as the IMR-AMR relationship). The impact of regional sea surface temperature (SST) anomalies north of Australia on the IMR to AMR transition has experienced obvious changes during the analysis period. The long-term change in the IMR-AMR relationship is attributed to the change in impacts of regional SST anomalies north of Australia and their coherence with equatorial Pacific and tropical Indian Ocean SST anomalies. It is found that the east-west SST anomaly gradient in the North Indian Ocean is an important factor in the IMR variations. The impact of the North Indian Ocean zonal SST anomaly gradient on the AMR to IMR transition has changed largely during the analysis period. This appears to be a major reason for the long-term change in the AMR-IMR relationship. The changes in the impacts of regional SST anomaly or SST anomaly gradient are associated with changes in the amplitude of regional SST anomalies that are likely due to the change in the El Nino-Southern Oscillation (ENSO)-related SST anomaly pattern.

A New Metric for Indian Monsoon Rainfall Extremes*

AbstractExtreme monsoon rainfall in India has disastrous consequences, including significant socioeconomic impacts. However, little is known about the overall trends and climate factors associated with extreme rainfall because rainfall greatly varies across India and because few appropriate methods are available to measure extreme rainfall in the context of such heterogeneity. To provide a comprehensive assessment of extreme monsoon rainfall, the authors developed a metric using record rainfall data to measure the changes in the likelihood of extreme high and extreme low rainfall over time; this metric is independent of the characteristics of the underlying rainfall distributions. Hence, the metric is ideally suited to aggregate extreme rainfall information across heterogeneous regions covering India. The authors found that from 1930 to 2013, the likelihood of extreme high and extreme low rainfall increases 2-fold and 4-fold, respectively. These overall trend increases are driven by anomalous increases, particularly in the early 2000s; the likelihood of extreme high and extreme low rainfall increases 5-fold and 18-fold in 2005 and 2002, respectively. These findings imply a broadening of the underlying monsoon rainfall distribution over the past century. The authors also show that the time patterns of the likelihood of extreme rainfall in recent decades are correlated with El Niño–Southern Oscillation, especially when it is in the same phase with the Pacific decadal oscillation and Indian Ocean dipole.

Trends and oscillations in the Indian summer monsoon rainfall over the last two millennia

Observations show that summer rainfall over large parts of South Asia has declined over the past five to six decades. It remains unclear, however, whether this trend is due to natural variability or increased anthropogenic aerosol loading over South Asia. Here we use stable oxygen isotopes in speleothems from northern India to reconstruct variations in Indian monsoon rainfall over the last two millennia. We find that within the long-term context of our record, the current drying trend is not outside the envelope of monsoon's oscillatory variability, albeit at the lower edge of this variance. Furthermore, the magnitude of multi-decadal oscillatory variability in monsoon rainfall inferred from our proxy record is comparable to model estimates of anthropogenic-forced trends of mean monsoon rainfall in the 21st century under various emission scenarios. Our results suggest that anthropogenic-forced changes in monsoon rainfall will remain difficult to detect against a backdrop of large natural variability.

Effect of Global Temperature Changes on Rainfall Fluctuations over River Basins Across Eastern Indo-GangeticPlains

Annual weather cycle of India comprises mainly wet and dry periods with monsoonal rains as one of the significant wet periods. All India monsoon rainfall shows strong spatio-temporal variations and large departures from its normal values. It is proposed in this study to document climatological characteristics, fluctuation features and periodic cycles in annual, seasonal and monthly rainfall series of seven river basins across eastern Indo-Gangetic plains (EIGP) using longest possible instrumental area-averaged monthly rainfall series (sometimes goes back up to 1829) up to 2007. Understanding its relationships with the global tropospheric temperature changes and El Nino-La-Nina events are also attempted. Climatologically mean annual rainfall vary from 1070.5mm (±216.8mm) over Tons to 1508.6mm (±205.2mm) over Subarnarekha river basin. The highest rainfall over EIGP occurs during monsoon (1188±115.4mm) and that is during month of July (372.6±56.3mm). The annual and monsoonal rainfall of all river basins is normally distributed, except post-monsoon and winter. Over the period of available records, rainfall fluctuations showed 2-to-3 tendencies in the combination of increase, decrease and normal. Annual rainfall of none of the river basins show significant long term trend however, monsoonal rainfall of Brahmani, Sons, Mahanadi and EIGP does show significant decreasing long-term trend. In recent 20 years all river basins show declining tendency in monsoonal rainfall. Power spectra of all rainfall series are characterized by consistent significant peaks at 3-5 years, 10-20 years, 40 years and >80 years of wavelength. Short-term fluctuations of period <10 years is the major contributor of total variance of annual/monsoon rainfall (77.6%), followed by decadal variations of period 10-30 years (13.1%) and long-term trend of period >30 years (9.3%). The short term variations can be attributed to the variability in intensity and duration of rain producing weather systems, decadal variability is seems to be in relation with the different climatic signal and long-term changes are the manifestation of asymmetry in whole tropospheric warming across globe.