A coupled model study on ENSO, MJO and Indian summer monsoon rainfall relationships

Summary In this paper, we have tried to understand the ENSO, MJO and Indian summer monsoon rainfall relationships from observation as well as from coupled model results. It was the general feeling that El-Niño years are the deficient in Indian monsoon rainfall and converse being the case for the La-Niña years. Recent papers by several authors noted the failure of this relationship. We find that the model output does confirm a breakdown of this relationship. In this study we have seen that a statistically defined modified Indian summer monsoon rainfall (MISMR) index, a linearly regressed ISMR index and dynamical Webster index (WBSI), shows an inverse relationship with ENSO index during the entire period of integration (1987 to 1999). It is also seen from this study that the amplification of the MJO signals were large and the ENSO signals were less pronounced during the years of above normal ISMR. The MJO signal amplitudes were small and ENSO signals were strong during the years of deficient ISMR. It has been noted that here is a time lag between the MJO and ENSO signal in terms of their modulation aspect. If time lag is added with the ENSO signal then both signals maintain the amplitude modulation theory. A hypothesis is being proposed here to define a relationship between MJO and ENSO signals for the entire period between 1987 and 1999.Received September 18, 2002; revised November 22, 2002; accepted December 20, 2002 Published online: May 8, 2003     

Lag-relationship between mid-tropospheric geopotential heights over the Northern Hemisphere and the Indian summer monsoon rainfall: Implications for forecasting

Summary In this study the relationship between mid-tropospheric geopotential heights over the Northern Hemisphere (20° N to 90° N, around the globe) and Indian summer monsoon rainfall (ISMR: June to September total rainfall) have been examined. For this purpose, the monthly 500 hPa geopotential heights in a 2.5° lat./lon. grid over the Northern Hemisphere and the ISMR data for the period 1958 to 2003 have been used.The analysis demonstrates a dipole structure in the correlation pattern over the East Pacific Ocean in the month of January which intensifies in February and weakens in March.The average 500 hPa geopotential height over the eastern tropical Pacific Ocean during February (index one), has a significant positive relationship (r = 0.72) with the ISMR. In addition, the surface air temperature (SAT) anomaly over North-west Eurasia during January (index two) is found to be strongly related with the subsequent summer monsoon rainfall. These relationships are found to be consistent and robust during the period of analysis and these indices are found to be independent of each other.Hence, using index one and index two, a multiple linear regression model is developed for the prediction of the ISMR and the empirical relationships are verified on independent data. The forecast of the ISMR, using the above model, is found to be satisfactory.The dipole structure in the correlation pattern over the East Pacific region during February weakens once the ENSO (El-Nino and Southern Oscillation) events are excluded from the analysis. This suggests that the dipole type relationship between mid-tropospheric geopotential heights over the East Pacific Ocean and the ISMR may be a manifestation of the ENSO cycle.     

A possible mechanism for the weakening of El Niño-monsoon relationship during the recent decade

Summary Observational data are used to explore the relationship between surface air temperature anomaly gradients and Indian summer monsoon rainfall (ISMR). The meridional temperature anomaly gradient across Eurasia during January directed towards equator (pole) is a very good precursor of subsequent excess (deficient) Indian summer monsoon rainfall (ISMR). This gradient directed towards equator (pole) indicates below (above) normal blocking activity over Eurasia, which leads to less (more) than normal southward penetration of dry and cold mid latitude westerlies over the Indian monsoon region, which ultimately strengthens (weakens) the normal monsoon circulation. These findings suggest a mechanism for the weakening of relationship between El Niño and ISMR.Though there is a strong fundamental association between El Niño (warm ENSO) and deficient Indian summer monsoon rainfall (ISMR), this relationship was weak during the period 1921–1940 and the recent decade (1991–1998). During the El Niño years of 1921–1940 and 1901–1998, the meridional temperature anomaly gradient across Eurasia (Eurasian forcing) during January was directed towards equator. On the other hand, during the El Niño years of 1901–1920 and 1941–1990 this gradient was directed towards pole. Thus during 1921–1940 and 1991–1998, the adverse impact of El Niño on Indian monsoon was reduced by the favorable Eurasian forcing resulting in the weak association between El Niño and ISMR. This finding disagrees with the hypothesis of winter warming over the Eurasian continent as the reason for the observed weakening of this relationship during recent decade.     

Response of the Indian summer monsoon circulation and rainfall to seasonal snow depth anomaly over Eurasia

Several observational and modeling studies indicate that the Indian summer monsoon rainfall (ISMR) is inversely related to the Eurasian snow extent and depth. The other two important surface boundary conditions which influence the ISMR are the Pacific sea surface temperature (SST) to a large extent and the Indian Ocean SST to some extent. In the present study, observed Soviet snow depth data and Indian rainfall data for the period 1951–1994 have been statistically analyzed and results show that 57% of heavy snow events and 24% of light snow events over west Eurasia are followed by deficient and excess ISMR respectively. Out of all the extreme monsoon years, care has been taken to identify those when Eurasian snow was the most dominant surface forcing to influence ISMR. During the years of high(low) Eurasian snow amounts in spring/winter followed by deficient(excess) ISMR, atmospheric fields such as temperature, wind, geopotential height, velocity potential and stream function based on NCEP/NCAR reanalyses have been examined in detail to study the influence of Eurasian snow on the midlatitude circulation regime and hence on the monsoon circulation. Results show that because of the west Eurasian snow anomalies, the midlatitude circulations in winter through spring show significant changes in the upper and lower level wind, geopotential height, velocity potential and stream function fields. Such changes in the large-scale circulation pattern may be interpreted as precursors to weak/strong monsoon circulation and deficient/excess ISMR. The upper level velocity potential difference fields between the high and low snow years indicate that with the advent of spring, the winter anomalous convergence over the Indian region gradually becomes weaker and gives way to anomalous divergence that persists through the summer monsoon season. Also the upper level anomalous divergence centre shifts from over the Northern Hemisphere and equator to the Southern Hemisphere over the Indian Ocean and Australia.     

Impacts of large-scale teleconnections on climate variability over Southwest Asia

The atmospheric low frequency variability at a regional or global scale is represented by teleconnection. Using monthly dataset of the Climatic Research Unit (CRU) for the period 1971–2016, the impacts of four large-scale teleconnection patterns on the climate variability over Southwest Asia are investigated. The large-scale features include the El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) and the East Atlantic (EA) teleconnection patterns, as well as western tropical Indian Ocean (WTIO) sea surface temperature anomaly index. Results indicate that ENSO and EA are the first leading modes that explain variation of Southwest Asian precipitation, with positive (negative) anomalies during El Niño (La Niña) and the negative (positive) phase of EA. Variation of Southwest Asian near-surface temperature is most strongly related to WTIO index, with above-average (below-average) temperature during the positive (negative) phase of WTIO index, although the negative (positive) phase of NAO also favours the above-average (below-average) temperature. On the other hand, temperature (precipitation) over Southwest Asia shows the least response to ENSO (WTIO). ENSO and EA individually explain 13 percent annual variance of precipitation, while WTIO index explains 36 percent annual variance of near-surface temperature over Southwest Asia. Analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis Interim (ERA-Interim) data indicated establishments of negative (positive) geopotential height anomalies in the middle troposphere over Southwest Asia during El Niño (La Niña) or the negative (positive) phase of NAO, EA and WTIO. The response of precipitation variability over Southwest Asia to NAO is opposite to that expected from the geopotential height anomalies, but the correlation between precipitation and NAO is not statistically significant. Due to predictability of large-scale teleconnections, results of this study are encouraging for improvement of the state-of-the-art seasonal prediction of the climate over Southwest Asia.     

The Variability of the Interannual Oscillations of the Indian Summer Monsoon Rainfall

A new method of analysis namely, Singular Spectrum Analysis (SSA) is applied to the Indian Summer Monsoon (June-September) Rainfall (ISMR) series. The method is efficient in extracting the statistically significant oscillations with periods 2.8 and 2.3 year from the white noise of the ISMR series. The study shows that 2.8 / 2.3 year cycle captures the variability of the ISMR related to Southern Oscillation / Quasi Biennial Oscillation. The temporal structure of these oscillations show that these are in phase in extreme (excess and drought) monsoon conditions as well as in El Nino Southern Oscillation (ENSO) years. Both these oscillations show minimum variability during the period 1920-1940 and there is an increasing trend in the variability of these oscillations in the recent decades. The study enables to obtain pure signal consisting of reconstructed time series using these two Oscillations, from the original white noise series.     

Indian summer monsoon rainfall predictability and variability associated with Northwest Pacific circulation in a suit of coupled model hindcasts

The Northwest Pacific (NWP) circulation (subtropical high) is an important component of the East Asian summer monsoon system. During summer (June–August), anomalous lower tropospheric anticyclonic (cyclonic) circulation appears over NWP in some years, which is an indicative of stronger (weaker) than normal subtropical high. The anomalous NWP cyclonic (anticyclonic) circulation years are associated with negative (positive) precipitation anomalies over most of Indian summer monsoon rainfall (ISMR) region. This indicates concurrent relationship between NWP circulation and convection over the ISMR region. Dry wind advection from subtropical land regions and moisture divergence over the southern peninsular India during the NWP cyclonic circulation years are mainly responsible for the negative rainfall anomalies over the ISMR region. In contrast, during anticyclonic years, warm north Indian Ocean and moisture divergence over the head Bay of Bengal-Gangetic Plain region support moisture instability and convergence in the southern flank of ridge region, which favors positive rainfall over most of the ISMR region. The interaction between NWP circulation (anticyclonic or cyclonic) and ISMR and their predictability during these anomalous years are examined in the present study. Seven coupled ocean–atmosphere general circulation models from the Asia-Pacific Economic Cooperation Climate Center and their multimodel ensemble mean skills in predicting the seasonal rainfall and circulation anomalies over the ISMR region and NWP for the period 1982–2004 are assessed. Analysis reveals that three (two) out of seven models are unable to predict negative (positive) precipitation anomalies over the Indian subcontinent during the NWP cyclonic (anticyclonic) circulation years at 1-month lead (model is initialized on 1 May). The limited westward extension of the NWP circulation and misrepresentation of SST anomalies over the north Indian Ocean are found to be the main reasons for the poor skill (of some models) in rainfall prediction over the Indian subcontinent. This study demonstrates the importance of the NWP circulation variability in predicting summer monsoon precipitation over South Asia. Considering the predictability of the NWP circulation, the current study provides an insight into the predictability of ISMR. Long lead prediction of the ISMR associated with anomalous NWP circulation is also discussed.     

Estimation of dependence of seasonal predictability of meteorological quantities in different regions of the Northern Hemisphere on the El Niño-Southern Oscillation phenomenon

Potential predictability and rms errors of ensemble forecasting of seasonal variability of the meteorological fields are estimated for different El Niño-Southern Oscillation (ENSO) episodes in the winter and summer of 1983–2002. By means of composite analysis, the rms errors and the potential predictability index are compared for different ENSO episodes in seven regions of the Northern Hemisphere midlatitudes. It is shown that the ENSO signals have a model-resolved response in the atmospheric circulation patterns in certain extratropical regions for some meteorological quantities. Geographic distribution of the potential predictability index shows that the maximum values occur near the centers of action of the main teleconnection systems.     

Simple Multiple Regression Model for long range forecasting of Indian Summer Monsoon Rainfall

Summary The relationship between the Indian Ocean Sea-Surface Temperature Anomalies (SSTA) and the Indian Summer Monsoon Rainfall (ISMR) have been examined for the period, 1983–2006. High and positive correlation (0.51; significant at >99% level) is noticed between ISMR and SSTA over southeastern Arabian Sea (AS) in the preceding January. Significant and positive correlation (0.61: significant at >99% level) is also observed with the SSTA over northwest of Australia (NWA) in the preceding February. The combined SSTA index (AS + NWA) showed a very high correlation of 0.71 with the ISMR. The correlation between East Asia sea-level pressure (average during February and March in the region, 35° N–45° N; 120° E–130° E) and ISMR is found to be 0.62. The multiple correlation using the above two parameters is 0.85 which explains 72% variance in ISMR. Using the above two parameters a linear multiple regression model to predict ISMR is developed. Our results are comparable with those obtained from the power regression (developed with 16, 8 and 10 parameters) and ensemble models (using 3 to 6 parameters) of the Indian Meteorological Department (IMD) (Rajeevan et al. 2004; 2006). The rainfall during 2002 and 2004 could be predicted accurately from the present model. It is well known fact that most of the dynamical/statistical methods failed to predict the rainfall in 2002. However, as for associations between SST and ISMR, the index is quite susceptible to inter decadal fluctuations and markedly reduced skill is found in the decades preceding 1983. The RMS error for 24 years is 5.56 (% of long period average, LPA) and the correlation between the predicted and observed rainfall is 0.79. Correspondence: Y. Sadhuram, Regional Centre, National Institute of Oceanography, 176, Lawson’s Bay Colony, Visakhapatnam-530017, India     

Teleconnections: Northern hemisphere lower stratospheric geopotential heights and Indian monsoon rainfall

Summary In this study a search for teleconnection is made between the Northern Hemisphere lower stratospheric geopotential heights and Indian Monsoon Rainfall (IMR) through the correlation analysis approach. Monthly grid-point 50 hPa geopotential height data and the June to September IMR are used for the period 1958–1990.Analysis reveal that there are domains over the Northern Hemisphere where the variation of the geopotential heights during the preceding months of the monsoon period are related with the interannual behaviour of the IMR. During January and February significant positive correlations are seen along the lower latitudes (10°–20° N). However, the maximum relationship is seen during March, with high positive correlations over the Canadian sector and negative correlations over the east Asian sector. The correlation configuration weakens considerably, once the ENSO (El Niño Southern Oscillation) cases are excluded, suggesting that the correlation pattern obtained may be a manifestation of the ENSO cycle. Implications of these results in the long range forecasting of IMR are also discussed.With 5 Figures     

All India summer monsoon rainfall prediction using an artificial neural network

The prediction of Indian summer monsoon rainfall (ISMR) on a seasonal time scales has been attempted by various research groups using different techniques including artificial neural networks. The prediction of ISMR on monthly and seasonal time scales is not only scientifically challenging but is also important for planning and devising agricultural strategies. This article describes the artificial neural network (ANN) technique with error- back-propagation algorithm to provide prediction (hindcast) of ISMR on monthly and seasonal time scales. The ANN technique is applied to the five time series of June, July, August, September monthly means and seasonal mean (June + July + August + September) rainfall from 1871 to 1994 based on Parthasarathy data set. The previous five years values from all the five time-series were used to train the ANN to predict for the next year. The details of the models used are discussed. Various statistics are calculated to examine the performance of the models and it is found that the models could be used as a forecasting tool on seasonal and monthly time scales. It is observed by various researchers that with the passage of time the relationships between various predictors and Indian monsoon are changing, leading to changes in monsoon predictability. This issue is discussed and it is found that the monsoon system inherently has a decadal scale variation in predictability. Received: 13 March 1999 / Accepted: 31 August 1999     

Equatorial pacific SSTA-related decadal variations of potential predictability of ENSO and interannual climate

Summary Based on analysis of NCEP reanalysis data and SST indices of the recent 50 years, decadal changes of the potential predictability of ENSO and interannual climate anomalies were investigated. Autocorrelation of Nino3 SST anomalies (SSTA) and correlation between atmospheric anomalies fields and Nino3 SSTA exhibit obvious variation in different decades, which indicates that Nino3 SSTA-related potential predictability of ENSO and interannual climate anomalies has significant decadal changes. Time around 1977 is not only a shift point of climate on the interdecadal time scale but also a catastrophe point of potential predictability of ENSO and interannual climate. As a whole, ENSO and the PNA pattern in boreal winter are more predictable in 1980s than in 1960s and 1970s, while the Nino3 SSTA-related potential predictability of the Indian monsoon and the East Asian Monsoon is lower in 1980s than in 1960s and 1970s. Received October 19, 1999 Revised December 30, 1999     

Seasonal prediction of Indian summer monsoon in NCEP coupled and uncoupled model

This study has identified probable factors that govern ISMR predictability. Furthermore, extensive analysis has been performed to evaluate factors leading to the predictability aspect of Indian Summer Monsoon Rainfall (ISMR) using uncoupled and coupled version of National Centers for Environmental Prediction Coupled Forecast System (CFS). It has been found that the coupled version (CFS) has outperformed the uncoupled version [Global Forecast System (GFS)] of the model in terms of prediction of rainfall over Indian land points. Even the spatial distribution of rainfall is much better represented in the CFS as compared to that of GFS. Even though these model skills are inadequate for the reliable forecasting of monsoon, it imparts the capacious knowledge about the model fidelity. The mean monsoon features and its evolution in terms of rainfall and large-scale circulation along with the zonal and meridional shear of winds, which govern the strength of the monsoon, are relatively closer to the observation in the CFS as compared to the GFS. Furthermore, sea surface temperature–rainfall relation is fairly realistic and intense in the coupled version of the model (CFS). It is found that the CFS is able to capture El Niño Southern Oscillation ISMR (ENSO-ISMR) teleconnections much strongly as compared to GFS; however, in the case of Indian Ocean Dipole ISMR teleconnections, GFS has the larger say. Coupled models have to be fine-tuned for the prediction of the transition of El Niño as well as the strength of the mature phase has to be improved. Thus, to sum up, CFS tends to have better predictive skill on account of following three factors: (a) better ability to replicate mean features, (b) comparatively better representation of air–sea interactions, and (c) much better portrayal of ENSO-ISMR teleconnections. This study clearly brings out that coupled model is the only way forward for improving the ISMR prediction skill. However, coupled model’s spurious representation of SST variability and mean model bias are detrimental in seasonal prediction.     

Role of the southern Indian Ocean in the transitions of the monsoon-ENSO system during recent decades

The focus of this study is to document the possible role of the southern subtropical Indian Ocean in the transitions of the monsoon-ENSO system during recent decades. Composite analyses of sea surface temperature (SST) fields prior to El Niño-Southern Oscillation (ENSO), Indian summer monsoon (ISM), Australian summer monsoon (AUSM), tropical Indian Ocean dipole (TIOD) and Maritime Continent rainfall (MCR) indices reveal the southeast Indian Ocean (SEIO) SSTs during late boreal winter as the unique common SST precursor of these various phenomena after the 1976–1977 regime shift. Weak (strong) ISMs and AUSMs, El Niños (La Niñas) and positive (negative) TIOD events are preceded by significant negative (positive) SST anomalies in the SEIO, off Australia during boreal winter. These SST anomalies are mainly linked to subtropical Indian Ocean dipole events, recently studied by Behera and Yamagata (Geophys Res Lett 28:327–330, 2001). A wavelet analysis of a February–March SEIO SST time series shows significant spectral peaks at 2 and 4–8 years time scales as for ENSO, ISM or AUSM indices. A composite analysis with respect to February–March SEIO SSTs shows that cold (warm) SEIO SST anomalies are highly persistent and affect the westward translation of the Mascarene high from austral to boreal summer, inducing a weakening (strengthening) of the whole ISM circulation through a modulation of the local Hadley cell during late boreal summer. At the same time, these subtropical SST anomalies and the associated SEIO anomalous anticyclone may be a trigger for both the wind-evaporation-SST and wind-thermocline-SST positive feedbacks between Australia and Sumatra during boreal spring and early summer. These positive feedbacks explain the extraordinary persistence of the SEIO anomalous anticyclone from boreal spring to fall. Meanwhile, the SEIO anomalous anticyclone favors persistent southeasterly wind anomalies along the west coast of Sumatra and westerly wind anomalies over the western Pacific, which are well-known key factors for the evolution of positive TIOD and El Niño events, respectively. A correlation analysis supports these results and shows that SEIO SSTs in February–March has higher predictive skill than other well-established ENSO predictors for forecasting Niño3.4 SST at the end of the year. This suggests again that SEIO SST anomalies exert a fundamental influence on the transitions of the whole monsoon-ENSO system during recent decades.     

Outgoing long-wave radiation over the Tropical Pacific and Atlantic Ocean and Indian summer monsoon rainfall

Summary In this paper, the interannual variability of satellite derived outgoing longwave radiation (OLR) is examined in relation to the Indian summer monsoon rainfall (June to September total rainfall; ISMR). Monthly grid point OLR field over the domain i.e. the tropical Pacific and Atlantic region (30°N to 30°S, 110°E to 10°W) and the ISMR for the period 1974–2001 are used for the study. A strong and significant north–south dipole structure in the correlation pattern is found between the ISMR and the OLR field over the domain during January. This dipole is located over the west Pacific region with highly significant negative (positive) correlations over the South China Sea and surrounding region (around north-east Australia). The dipole weakens and moves northwestward during February and disappears in March. During the month of May, the OLR over the central Atlantic Ocean shows a significant positive relationship with the ISMR. These relationships are found to be consistent and robust during the period of analysis and can be used in the prediction of the ISMR.A multiple regression equation is developed, using the above results, for prediction of the ISMR and the empirical relationships are verified using an independent data set. The results are encouraging for the prediction of the ISMR. The composite annual cycle of the OLR, over the west Pacific regions during extreme ISMR is found to be useful in the prediction of extreme summer monsoon rainfall conditions over the Indian subcontinent.     

夏季印度洋海盆模与MC区域降水异常联系的进一步分析

利用英国哈德莱中心的逐月海表温度资料及NCEP/NCAR月平均再分析资料等,通过在印度洋海盆模IOBM指数(IIOB)中扣除长期趋势和两类ENSO的同期信号后,得到了修正的IOBM指数(Im IOB),并由此分析了IOBM的变化及与海洋性大陆区域降水异常的联系。结果表明:印度洋IOBM为暖位相时,不同季节的印度洋地区均呈现异常偏暖,但大气是上升还是下沉运动则在印度洋不同季节和不同区域存在很大变化。就夏季而言,印度洋大部分地区存在上升运动,这与海温异常偏暖有关。在北半球夏季,指数Im IOB存在3~5 a的周期变化。当IOBM处于正位相时,印度洋至我国东海地区大范围海温偏暖。MC(Maritime Continent,海洋性大陆)区域西部降水正异常,而MC区域东北部降水为负异常。造成这种降水分布的原因是:当指数为正时,在MC区域的西部对流层低层辐合、高层辐散,上升运动增强,且水汽辐合,而MC区域的东北部对流层低层辐散、高层辐合,上升运动不明显,水汽辐散,不易形成降水。而在对流层低层与西太平洋辐散中心对应,南北半球出现关于赤道对称的反气旋对,赤道印度洋上的异常加热激发东传的Kelvin波,加强东风异常,同时加强了KMC(海洋性大陆的核心区域)之外南北半球热带地区的这对Rossby波型。以上这些结果有利于深刻理解MC降水异常成因及热带海陆气相互作用过程。     

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).     

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.     

Four-dimensional structure and sub-seasonal regulation of the Indian summer monsoon multi-decadal mode

A better understanding of the drivers and teleconnection mechanisms responsible for the multi decadal mode (MDM) of variability of the Indian summer monsoon rainfall (ISMR) with major socio-economic impacts in the region through clustering of large-scale floods or droughts is key to improving the poor simulation of ISMR MDM by most climate models. Here, using the longest instrumental record of ISMR available (1813–2006) and longest atmospheric and oceanic re-analyses, the global four dimensional (space–time) structures of atmospheric and oceanic fields of the multi-decadal mode of ISMR and sub-seasonal evolution of the teleconnection mechanism are brought out, essential for understanding underlying drivers but lacking so far. The relationships between the spatial structure of winds, Sea Surface Temperature (SST) and thermocline depth with the ISMR MDM indicate that the tropical ocean over the Indo-Pacific domain is passive responding primarily to the surface winds associated with the mode. A close association between the Atlantic Meridional Overturning Circulation (AMOC), north Atlantic (NA) SST, NA sea surface salinity (SSS) and the ISMR MDM indicate a slow oceanic pathway linking NA SST and the ISMR. In addition to strong correlation (~ 0.9) between global spatial patterns of JJAS SST associated with the MDMs of ISMR, NA SST and AMOC, strong temporal coherence (correlations ~ 0.9) between them is suggestive of regulation of the ISMR MDM (T ~ 65-years) by the NA SST associated with the Atlantic Multidecadal Oscillation (AMO) through a ‘fast’ atmospheric bridge. On a seasonal time scale, the atmospheric bridge manifests in the form of a stationary Rossby wave train generated by an anticyclonic (cyclonic) barotropic vorticity located above positive (negative) SST anomaly over NA in two phases of the AMO. That the AMO SST is the driver of the ISMR MDM is further supported when we unravel the sub-seasonal face of the teleconnection between the two. We show that phase locking of active (break) spells with annual cycle during positive (negative) phases of the ISMR MDM are forced by a similar phase locking of barotropic anticyclonic (cyclonic) vorticity over the NA SST with the annual cycle through the generation of a quasi-stationary Rossby wave train with an anticyclonic (cyclonic) vorticity at upper level over the Indian region with the NA columnar vorticity leading Indian monsoon rainfall by about a week. Our findings provide a basis for enhanced predictability of tropical climate through slow modulation by extra-tropical SST.

     

Respective influences of IOD and ENSO on the Tibetan snow cover in early winter

Using reanalysis data and snow cover data derived from satellite observations, respective influences of Indian Ocean Dipole (IOD) and El Niño/Southern Oscillation (ENSO) on the Tibetan snow cover in early winter are investigated. It is found that the snow cover shows a significant positive partial correlation with IOD. In the pure positive IOD years with no co-occurrences of El Niño, negative geopotential height anomalies north of India are associated with warm and humid southwesterlies to enter the plateau from the Bay of Bengal after rounding cyclonically and supply more moisture. This leads to more precipitation, more snow cover, and resultant lower surface temperature over the plateau. These negative geopotential height anomalies north of India are related to the equivalent barotropic stationary Rossby waves in the South Asian wave guide. The waves can be generated by the IOD-related convection anomalies over the western/central Indian Ocean. In contrast, in the pure El Niño years with no co-occurrences of the positive IOD, the anomalies of moisture supply and surface temperature over the plateau are insignificant, suggesting negligible influences of ENSO on the early winter Tibetan snow cover. Further analyses show that ENSO is irrelevant to the spring/early summer Tibetan snow cover either, whereas the IOD-induced snow cover anomalies can persist long from the early winter to the subsequent early summer.