Spatial and temporal relationships between global land surface air temperature anomalies and Indian summer monsoon rainfall

Summary Using the 60 year period (1931–1990) gridded land surface air temperature anomalies data, the spatial and temporal relationships between Indian summer monsoon rainfall and temperature anomalies were examined. Composite temperature anomalies were prepared in respect of 11 deficient monsoon years and 9 excess monsoon years. Statistical tests were carried out to examine the significance of the composites. In addition, correlation coefficients between the temperature anomalies and Indian summer monsoon rainfall were also calculated to examine the teleconnection patterns.There were statistically significant differences in the composite of temperature anomaly patterns between excess and deficient monsoon years over north Europe, central Asia and north America during January and May, over NW India during May, over central parts of Africa during May and July and over Indian sub-continent and eastern parts of Asia during July. It has been also found that temperature anomalies over NW Europe, central parts of Africa and NW India during January and May were positively correlated with Indian summer monsoon rainfall. Similarly temperature anomalies over central Asia during January and temperature anomalies over central Africa and Indian region during July were negatively correlated. There were secular variations in the strength of relationships between temperature anomalies and Indian summer monsoon rainfall. In general, temperature anomalies over NW Europe and NW India showed stronger correlations during the recent years. It has been also found that during excess (deficient) monsoon years temperature gradient over Eurasian land mass from sub-tropics to higher latitudes was directed equatowards (polewards) indicating strong (weak) zonal flow. This temperature anomaly gradient index was found to be a useful predictor for long range forecasting of Indian summer monsoon rainfall.With 12 Figures     

Modulation of Indian summer monsoon through northern and southern hemispheric extra-tropical oscillations

The Indian summer monsoon is a highly energetic global atmospheric circulation system. Although the El Nino Southern Oscillation (ENSO) has been statistically effective in explaining several past droughts in India, in recent decades the ENSO-monsoon relationship has weakened over the Indian subcontinent. In this context, a teleconnection with other dominant modes is of interest. The present study focuses on the mutual impact of the North Atlantic Oscillation (NAO) and Southern Annular Mode (SAM) on the regional variability of the Indian summer monsoon. Strong El Nino and La Nina years are excluded to find the interaction between extratropics and Indian summer monsoon. During the synchronous effect of these extratropical modes, the intensity as well as the spatial distribution of rainfall anomalies varies significantly in the western coastal region, eastern part of central and northeast India. The decrease in rainfall along the southwest coastal regions is related to the reduced zonal moisture transport. Significant reduction in moisture transport occurs in the positive phase of SAM and the negative phase of the NAO. The thermal gradient developed between the Indian landmass and southern tropical ocean differs significantly during the simultaneous impact of these modes. Moreover, the spatial variation and change in intensity of summer monsoon (July–August) parameters associated with SAM depend on the respective phase of the NAO. These results will help to open new areas of research on the simultaneous teleconnection of the two hemispheric modes on circulation features and weather systems.     

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     

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     

Observed lead-lag relationships between Indian summer monsoon and some meteorological variables

Lagged relationships between the Indian summer monsoon and several climate variables are investigated. The variables examined are gridded fields of snow cover (14 years), sea surface temperature (41 years) and 500 hPa geopotential height north of 20 °N (42 years). We also used series of global air temperature (108 years) and Southern Oscillation index (112 years). Precipitation over all India during June–September over a 112 year period are used as Indian monsoon index. Emphasis is put on early monsoon precursors. In agreement with the tendency for a low frequency oscillation in the ocean-atmosphere system, several precursor patterns are identified as early as the year preceding the monsoon. The most important key regions and seasons of largest correlations are selected and the corresponding series are used to perform a monsoon prediction. The prediction shows however a relatively moderate score mainly due to the not highly significant correlations. To improve the predictions we filtered the variables into their biennial (1.5–3.5 years) and low frequency (3.5–7.5 years) modes. Correlations between the monsoon and the filtered variables are higher than those obtained without filtering especially for the biennial mode. The two modes are out-of-phase before the monsoon and in-phase during and after. This phasing is found in all variables except for snow cover for which the two modes are in-phase before the monsoon and out-of-phase during and after. It is suggested that such phasing may be important for the formation of snow and could explain the higher correlations when variables are concomitant or are lagging the monsoon. Early predictions of the monsoon based on those two modes show improved scores with highly significant correlations with the actual monsoon. Received: 19 June 1996 / Accepted: 11 April 1997     

Relationships between interannual variability in the Arabian Sea and Indian summer monsoon rainfall

Summary The interannual variability of the monthly mean upper layer thickness for the central Arabian Sea (5°N-15° N and 60° E-70° E) from a numerical model of the Indian Ocean during the period 1954–1976 is investigated in relation to Indian monsoon rainfall variability. The variability in the surface structure of the Somali Current in the western Arabian Sea is also briefly discussed. It is found that these fields show a great deal of interannual variability that is correlated with variability in Indian monsoon rainfall. Model upper layer thickness (H) is taken as a surrogate variable for thermocline depth, which is assumed to be correlated with sea surface temperature. In general, during the period 1967 to 1974, which is a period of lower than normal monsoon rainfall, the upper ocean warm water sphere is thicker (deeper thermocline which implies warmer surface water); in contrast, during the period 1954–1966, which is a period of higher than normal monsoon rainfall, the upper warm water sphere is thinner (shallower thermocline which implies cooler surface water). The filtered time series of uppper layer thickness indieates the presence of a quasi-biennial oscillation (QBO) during the wet monsoon period, but this QBO signal is conspicuously absent during the dry monsoon period.Since model H primarily responds to wind stress curl, the interannual variability of the stress curl is investigated by means of an empirical orthogonal function (EOF) analysis. The first three EOF modes represent more than 72% of the curl variance. The spatial patterns for these modes exhibit many elements of central Arabian Sea climatology. Features observed include the annual variation in the intensity of the summer monsoon ridge in the Arabian Sea and the annual zonal oscillation of the ridge during pre- and post-monsoon seasons. The time coefficients for the first EOF amplitude indicate the presence of a QBO during the wet monsoon period only, as seen in the ocean upper layer thickness.The variability in the model upper layer thickness is a passive response to variability in the wind field, or more specifically to variability in the Findlater Jet. When the winds are stronger, they drive stronger currents in the ocean and have stronger curl fields associated with them, driving stronger Ekman pumping. They transport more moisture from the southern hemisphere toward the Indian subcontinent, and they also drive a greater evaporative heat flux beneath the Findlater Jet in the Arabian Sea. It has been suggested that variability in the heat content of the Arabian Sea drives variability in Indian monsoon rainfall. The results of this study suggest that the opposite is true, that the northern Arabian Sea responds passively to variability in the monsoon system.With 10 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.     

欧亚遥相关型对印度夏季风与华北夏季降水间关系的影响

利用国家气候中心160站月平均降水资料、印度热带气象研究所的全印度月平均降水资料和NCEP/NCAR的再分析资料,从年际和年代际角度分别研究了欧亚遥相关型（Eurasian teleconnection,EU）对印度夏季风与华北夏季降水关系的影响,并探究其物理机制。结果表明,EU与印度夏季风之间的相关系数只有-0.078,二者相互独立。印度夏季风与华北夏季降水有正相关关系（Indian Summer Monsoon and North China Summer Rainfall,ISM-NCSR）,且在正EU位相时,ISM-NCSR关系较弱;负EU位相时,ISM-NCSR关系较强。这是由于EU负位相时,贝加尔湖右侧存在反气旋环流,有利于北风及冷空气南下。因此,强印度季风时北上的暖湿气流在华北地区与偏北风相遇形成锋面,有利于华北降水;弱印度季风时华北地区完全被强北风控制,水汽输送通道被阻断,不利于降水,从而导致ISM-NCSR关系强。正EU位相时与此相反,相关关系弱。     

The coherence of satellite infrared temperatures with monsoon rainfall at preferred frequencies and the triplex behavior of the Indian summer monsoon

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

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.     

Pre-monsoon surface pressure and summer monsoon rainfall over India

Summary The relationship between the surface air pressure field during the pre-monsoon months and the Indian summer monsoon rainfall is analysed using climate data from 105 stations situated in Eurasia between 0°–60° N and 20°–100° E. Moreover, grid-point data for the whole northern hemisphere are used. Pressure during April over an area around 50° N and 35° E is found to show a significant negative correlation with the subsequent monsoon rainfall. During May the pressure over a large part of the study area south of 40° N shows a significant correlation with its highest value in the heat low region over Pakistan. It is assumed that monitoring of pressure variations over this region may be useful in predicting monsoon rainfall, particularly the rainfall during the first half of the season. Certain limitations of the climate data in this region are also discussed.With 5 Figures     

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     

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 role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall

Many climate models have problems simulating Indian summer monsoon rainfall and its variability, resulting in considerable uncertainty in future projections. Problems may relate to many factors, such as local effects of the formulation of physical parametrisation schemes, while common model biases that develop elsewhere within the climate system may also be important. Here we examine the extent and impact of cold sea surface temperature (SST) biases developing in the northern Arabian Sea in the CMIP5 multi-model ensemble, where such SST biases are shown to be common. Such biases have previously been shown to reduce monsoon rainfall in the Met Office Unified Model (MetUM) by weakening moisture fluxes incident upon India. The Arabian Sea SST biases in CMIP5 models consistently develop in winter, via strengthening of the winter monsoon circulation, and persist into spring and summer. A clear relationship exists between Arabian Sea cold SST bias and weak monsoon rainfall in CMIP5 models, similar to effects in the MetUM. Part of this effect may also relate to other factors, such as forcing of the early monsoon by spring-time excessive equatorial precipitation. Atmosphere-only future time-slice experiments show that Arabian Sea cold SST biases have potential to weaken future monsoon rainfall increases by limiting moisture flux acceleration through non-linearity of the Clausius–Clapeyron relationship. Analysis of CMIP5 model future scenario simulations suggests that such effects are small compared to other sources of uncertainty, although models with large Arabian Sea cold SST biases may suppress the range of potential outcomes for changes to future early monsoon rainfall.     

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.     

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.