Teleconnections in recent time and prediction of Indian summer monsoon rainfall

Summary The prediction of Indian Summer Monsoon Rainfall (ISMR) is vital for Indian economic policy and a challenge for meteorologists. It needs various predictors among which El Niño-Southern Oscillation (ENSO) is the most important. It has been established by various researchers that ENSO and ISMR relationship is weakening in recent years. It has been also argued that changes in ENSO-ISMR relationship may be due to decadal fluctuations, or it may be the indicative of longer-term trends related to anthropogenic-induced climate changes.In the present communication, an attempt is made to discuss the variability and predictability of ISMR in recent years. It is found that three different indices associated with different regions in the tropics and extra-tropics at different levels of the atmosphere-Asian land mass index represented by geopotential height at upper troposphere (A1), Caribbean-North Atlantic index represented by geopotential height at middle troposphere (A2) and tropical Pacific index at surface level (A3) – have different mechanisms to interact mutually and separately with ISMR in different periods. In recent years ISMR shows weak association with A1 and A3 while strong association with A2. Thus, if these three indices could be combined objectively, they can give rise to the predictability of ISMR. This objective combination is achieved here using Artificial Neural Network (ANN) and a model is developed to predict ISMR. This model has predicted reasonably well during the whole period of consideration (1958–2000) with a correlation coefficient of 0.92 in last 11 years (1990–2000) whereas most of the models fail to predict the variability in recent time.Current affiliation: Department of Physics, Federal University of Parana, Curitiba, Brazil.Received June 2002; revised October 1, 2002; accepted November 12, 2002 Published online: April 10, 2003     

Impact of Indian summer monsoon on the South Asian High and its influence on summer rainfall over China

By using the monthly ERA-40 reanalysis data and observed rainfall data, we investigated the effect of the Indian summer monsoon (ISM) on the South Asian High (SAH) at 200 hPa, and the role played by the SAH in summer rainfall variation over China. It is found that in the interannual timescale the east–west shift is a prominent feature of the SAH, with its center either over the Iranian Plateau or over the Tibetan Plateau. When the ISM is stronger (weaker) than normal, the SAH shifts westward (eastward) to the Iranian Plateau (Tibetan Plateau). The east–west position of SAH has close relation to the summer rainfall over China. A westward (eastward) location of SAH corresponds to less (more) rainfall in the Yangtze-Huai River Valley and more (less) rainfall in North China and South China. A possible physical process that the ISM affects the summer rainfall over China via the SAH is proposed. A stronger (weaker) ISM associated with more (less) rainfall over India corresponds to more (less) condensation heat release and anomalous heating (cooling) in the upper troposphere over the northern Indian peninsula. The anomalous heating (cooling) stimulates positive (negative) height anomalies to its northwest and negative (positive) height anomalies to its northeast in the upper troposphere, causing a westward (eastward) shift of the SAH with its center over the Iranian Plateau (Tibetan Plateau). As a result, an anomalous cyclone (anticyclone) is formed over the eastern Tibetan Plateau and eastern China in the upper troposphere. The anomalous vertical motions in association with the circulation anomalies are responsible for the rainfall anomalies over China. Our present study reveals that the SAH may play an important role in the effect of ISM on the East Asian summer monsoon.     

Probabilistic prediction of Indian summer monsoon rainfall using global climate models

Probabilistic seasonal predictions of rainfall that incorporate proper uncertainties are essential for climate risk management. In this study, three different multi-model ensemble (MME) approaches are used to generate probabilistic seasonal hindcasts of the Indian summer monsoon rainfall based on a set of eight global climate models for the 1982–2009 period. The three MME approaches differ in their calculation of spread of the forecast distribution, treated as a Gaussian, while all three use the simple multi-model subdivision average to define the mean of the forecast distribution. The first two approaches use the within-ensemble spread and error residuals of ensemble mean hindcasts, respectively, to compute the variance of the forecast distribution. The third approach makes use of the correlation between the ensemble mean hindcasts and the observations to define the spread using a signal-to-noise ratio. Hindcasts are verified against high-resolution gridded rainfall data from India Meteorological Department in terms of meteorological subdivision spatial averages. The use of correlation for calculating the spread provides better skill than the other two methods in terms of rank probability skill score. In order to further improve the skill, an additional method has been used to generate multi-model probabilistic predictions based on simple averaging of tercile category probabilities from individual models. It is also noted that when such a method is used, skill of probabilistic forecasts is improved as compared with using the multi-model ensemble mean to define the mean of the forecast distribution and then probabilities are estimated. However, skill of the probabilistic predictions of the Indian monsoon rainfall is too low.     

Intrinsic problems in the seasonal prediction of the Indian summer monsoon rainfall

Summary The latest non-parametric statistical tool Singular Spectrum Analysis (SSA) has been shown to extract deterministic oscillations present in a nonlinear dynamical system. It has been hypothesized that the tropical ocean-atmosphere system consists of both deterministic and stochastic parts in the interannual time scales. In the present study SSA has been employed to extract the deterministic and random parts present in the Indian summer monsoon (ISM) and its predictors time series data sets.The dominant eigenmode pair of the ISM does not emerge as a pure and deterministic oscillation. However, about 34% variance is deterministically predictable in the inter-annual range. The second pair is significantly related to the first pair of Darwin pressure tendency and both emerge as deterministic parts. This relationship partially answers the questions raised by Webster and Yang (1992). The low frequency component of ENSO emerges as a deterministic oscillation in all the variables, except in Bombay pressure tendency. The presence of decadal-scale oscillations may possibly be responsible for the instability in the relationship between the ISM and its predictors. Some plausible explanations for the percent variance explained by the predictors in the existing empirical models have also been discussed. It has been proposed that empirical models can be constructed only with the deterministic parts which may help improve the predictive skill of existing models.With 12 Figures     

Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969–2005).     

Temperature variability over the Indian Ocean and its relationship with Indian summer monsoon rainfall

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.     

New regression model for Indian summer monsoon rainfall

Summary Based on the study of 45 years (1948–1992) data, the average lowest MSL pressure of heat low over central Pakistan and adjoining northwest India of the month of May is found to have potential as a parameter for predicting all India Summer monsoon seasonal rainfall. This new parameter is seen to have stable and significant correlation with monsoon rainfall. Its correlation coefficients for different periods are found significant at 0.1% to 1% level of significance. The stability of the correlation coefficients was tested using 10, 20 and 30 year sliding windows. This test revealed that it is the most dependable parameter in comparison with 7 of the well known parameters analysed in this study. Regression models have been developed considering this new parameter along with other circulation parameters. The regression models developed are seen to perform very well for the independent data. The Root Mean Square Error (RMSE) values of some of these models, for independent data, are smaller than those of similar regression models reported in literature.With 8 Figures     

Weakening of Indian summer monsoon rainfall in warming environment

Though over a century long period (1871–2010) the Indian summer monsoon rainfall (ISMR) series is stable, it does depict the decreasing tendency during the last three decades of the 20th century. Around mid-1970s, there was a major climate shift over the globe. The average all-India surface air temperature also shows consistent rise after 1975. This unequivocal warming may have some impact on the weakening of ISMR. The reduction in seasonal rainfall is mainly contributed by the deficit rainfall over core monsoon zone which happens to be the major contributor to seasonal rainfall amount. During the period 1976–2004, the deficit (excess) monsoons have become more (less) frequent. The monsoon circulation is observed to be weakened. The mid-tropospheric gradient responsible for the maintenance of monsoon circulation has been observed to be weakened significantly as compared to 1901–1975. The warming over western equatorial Indian Ocean as well as equatorial Pacific is more pronounced after mid-70s and the co-occurrence of positive Indian Ocean Dipole Mode events and El Nino events might have reinforced the large deficit anomalies of Indian summer monsoon rainfall during 1976–2004. All these factors may contribute to the weakening of ISMR.     

Empirical prediction of Indian summer monsoon rainfall with different lead periods based on global SST anomalies

Summary The main objective of this study was to develop empirical models with different seasonal lead time periods for the long range prediction of seasonal (June to September) Indian summer monsoon rainfall (ISMR). For this purpose, 13 predictors having significant and stable relationships with ISMR were derived by the correlation analysis of global grid point seasonal Sea-Surface Temperature (SST) anomalies and the tendency in the SST anomalies. The time lags of the seasonal SST anomalies were varied from 1 season to 4 years behind the reference monsoon season. The basic SST data set used was the monthly NOAA Extended Reconstructed Global SST (ERSST) data at 2° × 2° spatial grid for the period 1951–2003. The time lags of the 13 predictors derived from various areas of all three tropical ocean basins (Indian, Pacific and Atlantic Oceans) varied from 1 season to 3 years. Based on these inter-correlated predictors, 3 predictor sub sets A, B and C were formed with prediction lead time periods of 0, 1 and 2 seasons, respectively, from the beginning of the monsoon season. The selected principal components (PCs) of these predictor sets were used as the input parameters for the models A, B and C, respectively. The model development period was 1955–1984. The correct model size was derived using all-possible regressions procedure and Mallow’s “Cp” statistics. Various model statistics computed for the independent period (1985–2003) showed that model B had the best prediction skill among the three models. The root mean square error (RMSE) of model B during the independent test period (6.03% of Long Period Average (LPA)) was much less than that during the development period (7.49% of LPA). The performance of model B was reasonably good during both ENSO and non-ENSO years particularly when the magnitudes of actual ISMR were large. In general, the predicted ISMR during years following the El Ni?o (La Ni?a) years were above (below) LPA as were the actual ISMR. By including an NAO related predictor (WEPR) derived from the surface pressure anomalies over West Europe as an additional input parameter into model B, the skill of the predictions were found to be substantially improved (RMSE of 4.86% of LPA).     

东亚夏季风异常大气环流遥相关及其对我国降水的影响

根据夏季东亚季风区内季风环流异常所反映行星尺度扰动的强弱,来定义东亚大气遥相关指数IEA.分析表明,它能较清楚地反映夏季西太平洋副高脊线和西伸脊点位置与东亚季风系统各支季风气流的变化.并揭示当IEA偏强(弱)时,东亚季风系统内的热带季风环流出现异常加强(减弱),副热带季风环流出现异常减弱(加强),而中高纬度季风环流又出现异常加强(减弱),三者之间的关系.分析还表明,IEA异常前期,具有明显ENSO循环位相特征,冬季热带太平洋SST、OLR异常,以及对流层高层风异常,可以作为前期征兆信号.该指数变化与我国夏季降水异常分布密切相关,并清楚地反映出东亚季风系统内热带季风环流与副热带季风环流及其各支季风气流异常对我国夏季降水的影响,为该指数在气候监测与预测中的应用提供一定的物理依据.     

Role of intra-seasonal oscillations in modulating Indian summer monsoon rainfall

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.     

The Interannual variability of rainfall over homogeneous regions of Indian summer monsoon

Theoretical and Applied Climatology - The Indian subcontinent, due to its enormous variety of geographical features, is associated with inhomogeneity. Hence, in the present study, we have...     

Simulation of Indian summer monsoon circulation and rainfall using RegCM3

Summary The Regional Climate Model RegCM3 has been used to examine its suitability in simulating the Indian summer monsoon circulation features and associated rainfall. The model is integrated at 55 km horizontal resolution over a South Asia domain for the period April–September of the years 1993 to 1996. The characteristics of wind at 850 hPa and 200 hPa, temperature at 500 hPa, surface pressure and rainfall simulated by the model over the Indian region are examined for two convective schemes (a Kuo-type and a mass flux scheme). The monsoon circulation features simulated by RegCM3 are compared with those of the NCEP/NCAR reanalysis and the simulated rainfall is validated against observations from the Global Precipitation Climatology Centre (GPCC) and the India Meteorological Department (IMD). Validation of the wind and temperature fields shows that the use of the Grell convection scheme yields results close to the NCEP/NCAR reanalysis. Similarly, the Indian Summer Monsoon Rainfall (ISMR) simulated by the model with the Grell convection scheme is close to the corresponding observed values. In order to test the model response to land surface changes such as the Tibetan snow depth, a sensitivity study has also been conducted. For such sensitivity experiment, NIMBUS-7 SMMR snow depth data in spring are used as initial conditions in the RegCM3. Preliminary results indicate that RegCM3 is very much sensitive to Tibetan snow. The model simulated Indian summer monsoon circulation becomes weaker and the associated rainfall is reduced by about 30% with the introduction of 10 cm of snow over the Tibetan region in the month of April.     

Pacific decadal oscillation and variability of the Indian summer monsoon rainfall

Recent studies have furnished evidence for interdecadal variability in the tropical Pacific Ocean. The importance of this phenomenon in causing persistent anomalies over different regions of the globe has drawn considerable attention in view of its relevance in climate assessment. Here, we examine multi-source climate records in order to identify possible signatures of this longer time scale variability on the Indian summer monsoon. The findings indicate a coherent inverse relationship between the inter-decadal fluctuations of Pacific Ocean sea surface temperature (SST) and the Indian monsoon rainfall during the last century. A warm (cold) phase of the Pacific interdecadal variability is characterized by a decrease (increase) in the monsoon rainfall and a corresponding increase (decrease) in the surface air temperature over the Indian subcontinent. This interdecadal relationship can also be confirmed from the teleconnection patterns evident from long-period sea level pressure (SLP) dataset. The SLP anomalies over South and Southeast Asia and the equatorial west Pacific are dynamically consistent in showing an out-of-phase pattern with the SLP anomalies over the tropical central-eastern Pacific. The remote influence of the Pacific interdecadal variability on the monsoon is shown to be associated with prominent signals in the tropical and southern Indian Ocean indicative of coherent inter-basin variability on decadal time scales. If indeed, the atmosphere–ocean coupling associated with the Pacific interdecadal variability is independent from that of the interannual El Niño-Southern Oscillation (ENSO), then the climate response should depend on the evolutionary characteristics of both the time scales. It is seen from our analysis that the Indian monsoon is more vulnerable to drought situations, when El Niño events occur during warm phases of the Pacific interdecadal variability. Conversely, wet monsoons are more likely to prevail, when La Niña events coincide during cold phases of the Pacific interdecadal variability.     

Indian summer monsoon rainfall variability in global coupled ocean-atmospheric models

Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensemble system for seasonal-to-inter-annual prediction (DEMETER). Dependency of the model simulated Indian summer monsoon rainfall and global sea surface temperatures on model formulation and initial conditions have been studied in detail using the nine ensemble member simulations of the seven different coupled ocean–atmosphere models participated in the DEMETER program. It was found that the skills of the monsoon predictions in these hindcasts are generally positive though they are very modest. Model simulations of India summer monsoon rainfall for the earlier period (1959–1979) are closer to the ‘perfect model’ (attainable) score but, large differences are observed between ‘actual’ skill and ‘perfect model’ skill in the recent period (1980–2001). Spread among the ensemble members are found to be large in simulations of India summer monsoon rainfall (ISMR) and Indian ocean dipole mode (IODM), indicating strong dependency of model simulated Indian summer monsoon on initial conditions. Multi-model ensemble performs better than the individual models in simulating ENSO indices, but does not perform better than the individual models in simulating ISMR and IODM. Decreased skill of multi-model ensemble over the region indicates amplification of errors due to existence of similar errors in the individual models. It appears that large biases in predicted SSTs over Indian Ocean region and the not so perfect ENSO-monsoon (IODM-monsoon) tele-connections are some of the possible reasons for such lower than expected skills in the recent period. The low skill of multi-model ensemble, large spread among the ensemble members of individual models and the not so perfect monsoon tele-connection with global SSTs points towards the importance of improving individual models for better simulation of the Indian monsoon.     

A study on the decreasing trend in tropical easterly jet stream (TEJ) and its impact on Indian summer monsoon rainfall

Using the NCEP/NCAR reanalysis wind and temperature data (1948–2011) and India Meteorological Department (IMD) rainfall data, a long-term trend in the tropical easterly jet stream and its effect on Indian summer monsoon rainfall has been explained in the present study. A decreasing trend in zonal wind speed at 100 mb (maximum decrease), 150 mb, and 200 mb (minimum) is observed. The upper-level (100, 150, and 200 mb) zonal wind speed has been correlated with the surface air temperature anomaly index (ATAI) in the month of May, which is taken as the difference in temperature anomaly over land (22.5°N–27.5°N, 80°E–90°E) and Ocean (5°S–0°S, 75°E–85°E). Significant high correlation is observed between May ATAI and tropical easterly jet stream (TEJ) which suggests that the decreasing land–sea temperature contrast could be one major reason behind the decreasing trend in TEJ. The analysis of spatial distribution of rainfall over India shows a decreasing trend in rainfall over Jammu and Kashmir, Arunachal Pradesh, central Indian region, and western coast of India. Increasing trend in rainfall is observed over south peninsular and northeastern part of India. From the spatial correlation analysis of zonal wind with gridded rainfall, it is observed that the correlation of rainfall is found to be high with the TEJ speed over the regions where the decreasing trend in rainfall is observed. Similarly, from the analysis of spatial correlation between rainfall and May ATAI, positive spatial correlation is observed between May ATAI and summer monsoon rainfall over the regions such as south peninsular India where the rainfall trend is positive, and negative correlation is observed over the places such as Jammu and Kashmir where negative rainfall trend is observed. The decreased land–sea temperature contrast in the pre-monsoon month could be one major reason behind the decreased trend in TEJ as well as the observed spatial variation in the summer monsoon rainfall trend. Thus, the study explained the long-term trend in TEJ and its relation with May month temperature over the Indian Ocean and land region and its effect on the trend and spatial distribution of Indian summer monsoon rainfall.     

Global effect of irrigation and its impact on the onset of the Indian summer monsoon

In a context of increased demand for food and of climate change, the water consumptions associated with the agricultural practice of irrigation focuses attention. In order to analyze the global influence of irrigation on the water cycle, the land surface model ORCHIDEE is coupled to the GCM LMDZ to simulate the impact of irrigation on climate. A 30-year simulation which takes into account irrigation is compared with a simulation which does not. Differences are usually not significant on average over all land surfaces but hydrological variables are significantly affected by irrigation over some of the main irrigated river basins. Significant impacts over the Mississippi river basin are shown to be contrasted between eastern and western regions. An increase in summer precipitation is simulated over the arid western region in association with enhanced evapotranspiration whereas a decrease in precipitation occurs over the wet eastern part of the basin. Over the Indian peninsula where irrigation is high during winter and spring, a delay of 6?days is found for the mean monsoon onset date when irrigation is activated, leading to a significant decrease in precipitation during May to July. Moreover, the higher decrease occurs in June when the water requirements by crops are maximum, exacerbating water scarcity in this region. A significant cooling of the land surfaces occurs during the period of high irrigation leading to a decrease of the land-sea heat contrast in June, which delays the monsoon onset.