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.     

The association of surface wind stresses over Indian Ocean with monsoon rainfall

Summary Variability of Indian summer monsoon rainfall is examined with respect to variability of surface wind stresses over Indian Ocean. The Indian Ocean region extending from 40°–120° E, and 30° S–25° N, has been divided into 8 homogeneous subregions, viz (1) Arabian Sea (AS), (2) Bay of Bengal (BB), (3) West-equatorial Indian Ocean (WEIO), (4) Central-equatorial Indian Ocean (CEIO), (5) East-equatorial Indian Ocean (EEIO), (6) South-west Indian Ocean (SWIO), (7) South-central Indian Ocean (SCIO), and (8) South-east Indian Ocean (SEIO). The period of study extends for 13 years from 1982–1994. Monthly NCEP surface wind stress data of five months – May through September, have been used in the study. The spatial variability of seasonal and monthly surface wind stresses shows very low values over CEIO and EEIO and very high values over AS, SWIO, and SEIO regions. On the seasonal scale, all India summer monsoon rainfall (AISMR) shows concurrent positive relationships with the surface wind stresses over AS, BB, WEIO, SWIO and SCIO and negative relationships with the surface wind stresses over EEIO and SEIO. The relationships of AISMR with the surface wind stresses over AS and WEIO are significant at 5% level. The concurrent relationships between monthly surface wind stresses over these 8 oceanic sub-regions and monthly subdivisional rainfalls over 29 sub-divisions have been studied. The rainfalls over the subdivisions in the central India and on the west coast of India are found to be significantly related with surface wind stresses over AS, SWIO, SCIO. Monthly subdivisional rainfalls of four subdivisions in the peninsular India show negative relationship with BB surface wind stresses. May surface wind stresses over AS, BB, WEIO, CEIO and SWIO have been found to be positively related with ensuing AISMR. The relationship with AS wind stresses is significant at 5% level and hence may be considered as a potential predictor of AISMR. Received May 21, 2001 Revised October 8, 2001     

Evolution of the relationship between near global and Atlantic SST modes and the rainy season in West Africa: statistical analyses and sensitivity experiments

 Monthly sea surface temperature anomalies (SSTA) at near-global scale (60 °N–40 °S) and May to October rainfall amounts in West Africa (16 °N–5 °N; 16 °W–16 °E) are first used to investigate the seasonal and interannual evolutions of their relationship. It is shown that West African rainfall variability is associated with two types of oceanic changes: (1) a large-scale evolution involving the two largest SSTA leading eigenmodes (16% of the total variance with stronger loadings in the equatorial and southern oceans) related to the long-term (multiannual) component of rainfall variability mainly expressed in the Sudan–Sahel region; and (2) a regional and seasonally coupled evolution of the meridional thermal gradient in the tropical Atlantic due to the linear combination of the two largest SSTA modes in the Atlantic (11% with strong inverse loadings over the northern and southern tropics) which is associated with the interannual and quasi-decadal components of regional rainfall in West Africa. Linear regression and discriminant analyses provide evidence that the main July–September rainfall anomalies in Sudan–Sahel can be detected with rather good skills using the leading (April–June) or synchronous (July–September) values of the four main oceanic modes. In particular, the driest conditions over Sahel, more marked since the beginning of the 1970s, are specifically linked to the warm phases of the two global modes and to cold/warm anomalies in the northern/southern tropical Atlantic. Idealized but realistic SSTA patterns, obtained from some basic linear combinations of the four main oceanic modes appear sufficient to generate quickly (from mid-July to the end of August) significant West African rainfall anomalies in model experiments, consistent with the statistical results. The recent negative impact on West African rainfall exerted by the global oceanic forcing is primarily due to the generation of subsidence anomalies in the mid-troposphere over West Africa. When an idealized north to south SSTA gradient is added in the tropical Atlantic, strong north to south height gradients in the middle levels appear. These limit the northward excursion of the rainbelt in West Africa: the Sahelian area experiences drier conditions due to the additive effect (subsidence anomalies+latitudinal blocking) while over the Guinea regions wet conditions do not significantly increase, since the subsidence anomalies and the blocking effect act here in opposite ways. Received: 26 June 1997 / Accepted: 3 October 1997     

The Relationship Between some Large-scale Atmospheric Parameters and Rainfall over Southeast Asia: A Comparison with Features over India

Summary Monthly rainfall data for 135 stations for periods varying from 25 to 125 years are utilised to investigate the rainfall climatology over the southeast Asian monsoon regime. Monthly rainfall patterns for the regions north of equator show that maximum rainfall along the west coasts occurs during the summer monsoon period, while the maximum along the east coasts is observed during the northeast monsoon period. Over the Indonesian region (south of the equator) maximum rainfall is observed west of 125 °E during northern winter and east of 125 °E during northern summer. The spatial relationships of the seasonal rainfall (June to September) with the large scale parameters – the Subtropical Ridge (STR) position over the Indian and the west Pacific regions, the Darwin Pressure Tendency (DPT) and the Northern Hemisphere Surface Temperature (NHST) – reveal that within the Asian monsoon regime, not only are there any regions which are in-phase with Indian monsoon rainfall, but there are also regions which are out-of-phase. The spatial patterns of correlation coefficients with all the parameters are similar, with in-phase relationships occurring over the Indian region, some inland regions of Thailand, central parts of Brunei and the Indonesian region lying between 120° to 140 °E. However, northwest Philippines and some southern parts of Kampuchea and Vietnam show an out-of-phase relationship. Even the first Empirical Orthogonal Function of seasonal rainfall shows similar spatial configuration, suggesting that the spatial correlation patterns depict the most dominant mode of interannual rainfall variability. The influence of STR and DPT (NHST) penetrates (does not penetrate) upto the equatorial regions. Possible dynamic causes leading to the observed correlation structure are also discussed. Received October 10, 1996 Revised February 25, 1997     

Evolution of geophysical parameters over the Indian Ocean region during contrasting monsoon years of 2002 and 2003 using TRMM/TMI data

Summary The evolution of geophysical parameters over Indian Ocean during two contrasting monsoon years 2002 (drought) and 2003 (normal) were studied using TRMM/TMI satellite data. Analysis indicates that there was a lack of total water vapour (TWV) build up over Western Indian Ocean (WIO) during May 2002 (drought) when compared to 2003 (normal). Negative (positive) TWV anomalies were found over the WIO in May 2002 (2003). In 2002, negative SST anomaly of ∼1.5 °C is found over entire WIO when compared to 2003. Anomalously high sea surface wind speed (SWS) anomaly over the South West Indian Ocean (SWIO) and WIO would have resulted in cooling of the sea surface in May 2002 in comparison to 2003. In 2003 the wind speed anomaly over entire WIO and Arabian Sea (AS) was negative, whereas sea surface temperature (SST) anomaly was positive over the same region, which would have resulted in higher moisture availability over these regions. A negative (positive) TWV anomaly over Eastern Arabian Sea (EAS) and positive (negative) anomaly over WIO forms a dipole structure. In the month of June no major difference is seen in all these parameters over the Indian Ocean. In July 2002 the entire WIO and AS was drier by 10–15 mm as compared to 2003. The pentad (5 day) average TWV values shows high (>55 mm) TWV convergence over EAS and Bay of Bengal (BoB) during active periods of 2003, which gives high rainfall over these regions. However, during 2002 although TWV over BoB was >55 mm but it was ∼45–55 mm over EAS during entire July and hence less rainfall. The evaporation has been calculated from the bulk aerodynamic formula using TRMM/TMI geophysical products. It has been seen that the major portion of evaporative moisture flux is coming from southern Indian Ocean (SIO) between 15 and 25° S. Evaporation in June was more over AS and SIO in 2003 when compared to 2002 which may lead to reduce moisture supply in July 2002 and hence less rainfall compared to July 2003.     

Interdecadal mode and its propagating characteristics of SSTA in the South Pacific

Summary This paper is to promote a further understanding of the interdecadal mode of the South Pacific. With this focus, we will specifically aim at better understanding the difference between interannual and interdecadal SSTA modes over South Pacific. We define the difference of the normalization area-averaged SSTA in the southern extratropical Pacific (160° W–110° W, 40° S–25° S) and the south subpolar Pacific (150° W–110° W, 60° S–45° S) as the South Pacific interdecadal index (I _spd). It is found that the interannual mode is more coherent than the interdecadal mode in the central and eastern tropical Pacific, and the interdecadal mode is significant only during boreal winter (DJF). The interdecadal variation of SSTA firstly occurring in the extratropic South Pacific propagates to the western boundary of the South Pacific, then moves northeast to cross the equator, and finally reaches the central tropic Pacific. It takes about 8 years to propagate from southeast subtropical Pacific to the north hemisphere. The previous studies have suggested the mechanism of waves in the subsurface in the South Pacific. Our study also highlights the Rossby waves play important roles in linkage between the extratropics-tropics South Pacific SSTA on interdecadal time scales. Moreover, the paper shows that the interdecadal variability originated in the extrotropic southeast Pacific is mainly induced by interannual variability in the tropic Pacific.     

Intense rainfall events over the west coast of India

Summary The west coast of the Indian peninsula receives very heavy rainfall during the summer Monsoon (June–September) season with average rainfall over some parts exceeding 250 cm. Heavy rainfall events with rainfall more than 15 cm day⁻¹ at one or more stations along the west coast of India occur frequently and cause considerable damage. A special observational programme, Arabian Sea Monsoon Experiment, was carried out during the monsoon season of 2002 to study these events. The spatial and temporal distributions of intense rainfall events, presented here, were used for the planning of this observational campaign. The present study using daily rainfall data for summer monsoon season of 37 years (1951–1987) shows that the probability of getting intense rainfall is the maximum between 14° N–16° N and near 19° N. The probability of occurrence of these intense rainfall events is high from mid June to mid August, with a dip in early July. It has been believed for a long time that offshore troughs and vortices are responsible for these intense rainfall events. However, analysis of the characteristics of cloud systems associated with the intense rainfall events during 1985–1988 using very high resolution brightness temperature data from INSAT-IB satellite shows that the cloud systems during these events are characterized by large spatial scales and high cloud tops. Further study using daily satellite derived outgoing longwave radiation (OLR) data over a longer period (1975–1998) shows that, most of these events (about 62%) are associated with systems organized on synoptic and larger scales. We find that most of the offshore convective systems responsible for intense rainfall along the west coast of India are linked to the atmospheric conditions over equatorial Indian Ocean.     

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).     

Forecasting the equatorial Pacific sea surface temperatures by neural network models

We used neural network models to seasonally forecast the tropical Pacific sea surface temperature anomalies (SSTA) in the Ni?o 3.4 region (6 ^°S–6 ^°N, 120 ^°W–170 ^°W). The inputs to the neural networks (i.e., the predictors) were the first seven wind stress empirical orthogonal function (EOF) modes of the tropical Pacific (20 ^°S–20 ^°N, 120 ^°E–70 ^°W) for four seasons and the Ni?o 3.4 SSTA itself for the final season. The period of 1952–1981 was used for training the neural network models, and the period 1982–1992 for forecast validation. At 6-month lead time, neural networks attained forecast skills comparable to the other El Ni?o-Southern Oscillation (ENSO) models. Our results suggested that neural network models were viable for ENSO forecasting even at longer lead times of 9 to 12 months. We hypothesized that at these longer leads, the underlying relationship between the wind stress and Ni?o 3.4 SSTA became increasingly nonlinear. The neural network results were interpreted in light of current theories, e.g., the role of the “off-equatorial” Rossby waves in triggering the onset of an ENSO event and the delayed-oscillator theory in the development and termination of an ENSO event. Received: 31 October 1995 / Accepted: 25 July 1996     

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     

Significant changes in the ENSO-monsoon relationship and associated circulation features on multidecadal timescale

Climate Dynamics - We observe significant changes in the ENSO–Indian summer monsoon rainfall (ISMR) relationship in past three multidecadal epochs (early epoch: 1931–1960, middle epoch:...     

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.     

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.     

影响江南春雨年际变化的前期海洋信号及可能机理

基于诊断,本文计算了1982~2014年江南春雨的开始时间、结束时间和总降水量,分析了江南春雨的气候特征和年际变化,探讨了前冬Nino3.4区域海温异常与江南春雨的联系及可能机理。结果表明,江南春雨的起止时间和总降水量都具有显著的年际变化,前冬赤道东太平洋海温与江南春雨总量存在显著的正相关。前冬Nino3.4指数为正时,一方面通过Walker环流在赤道120°E附近区域激发出异常下沉运动以及低层异常反气旋,增强了南海地区低层西南气流以及水汽输送,另一方面与东太平洋海温变化相联系的印度洋增暖在赤道印度洋引发低层东风和孟加拉湾北部反气旋环流异常,进一步增强了江南地区的水汽输送;高层南亚地区则存在西风异常,对应江南上空辐散和抽吸作用加强,导致上升运动进一步增强,使得江南春雨总量增加;前冬Nino3.4指数为负时则次年春雨偏少;并且前冬El Ni?o事件的强度对春雨异常也有影响,前冬El Ni?o强（弱）的年份,海温异常的信号能（不能）持续到春季,江南春雨总量通常偏多（偏少）。另外,加入了前冬南极涛动指数和印度洋海盆一致模所建立的江南春雨总量的多元线性回归方程,其回归结果比基于单独的Nino3.4指数能更好地反映江南春雨的异常,可用于季节预测。     

Principal component analysis of satellite-observed outgoing long-wave radiation during the monsoon period (June–September) over India

Summary In this study, Principal Component Analysis (PCA) has been used to identify the major modes of the outgoing long-wave radiation data for the period (1979–2002) during the Indian monsoon period (June–September), using seasonal mean values over the Indian region covering 143 grid points (5° N–35° N and 70° E–95° E at 2.5° Longitude–Latitude intervals. The five principal components explain up to 98.0% of the total variance. The first principal component explains 60% of the total variance with a pronounced variation in the outgoing long-wave radiation over the region 10° N to 25° N. It appears that the major reason for the monsoon variability is the intensity and associated fluctuations in the two major semi-permanent seasonal systems. This is largely indicative of strong seasonal shift of the major area of cloudiness associated with convergence zone. The second principal component explaining 20% of the total variance exhibits higher positive component loadings along 25° N and east of 80° E. The possible reason for this could be the synoptic systems such as monsoon depression/lows over the north bay and trough/vortices off the west-coast in the Arabian sea.     

Anomalous warming over Indian Ocean during 1997 El-Niño

Summary  The year 1997 witnessed one of the most severe El-Ni?o events of the century. However, the All-India Summer Monsoon Rainfall (AISMR) was 102% of its long period average. In view of recent studies (Tourre and White, 1995, 1997) of detection of ENSO signal over Indian Ocean, the Sea-Surface Temperature (SST) variation over Indian Ocean (20° N–10° S/50° E–100° E), concurrent to El-Ni?o event of 1997 is examined. It is observed that during the developing, mature and decaying stages of El-Ni?o, the North Indian Ocean was abnormally warm. This anomalous warming may be one of the factors responsible for anomalous precipitation over India during October to December of 1997. Received August 24, 1999/Revised February 15, 2000     

The Characteristics of Cold Air Outbreaks over the Eastern Highlands of Kenya

Summary Climatological statistics of extreme temperature events over Kenya are established from the analysis of daily and monthly maximum temperatures for a representative station (Nairobi Dagoretti Corner) over the period 1956–1997. The months of June to August were shown to be the coldest with a mean monthly maximum temperature of less than 22 °C. Seasonal (June to August) mean maximum temperature was 21.5 °C. Using this seasonal mean temperature for the period 1967–1997 delineated 1968 as the coldest year in this series and 1983 as the warmest year. Spectral analysis of the seasonal data, for both the coldest and the warmest years, revealed that the major periods were the quasi-biweekly (10 days) and the Intraseasonal Oscillations (23 days). Secondary peaks occurred at periods of 4–6 and 2.5–3.5 days. A temperature threshold of 16.7 °C during July was used to define cold air outbreaks over Nairobi. This threshold temperature of 16.7 °C was obtained from the mean July maximum temperature (20.9 °C) minus two standard deviations. Notable trends include a decrease in the frequency of station-days, between 1956 and 1997, with temperatures less than 16.7 °C during July. Surface pressure patterns indicate that the origin of the cold air is near latitude 25° S and to the east of mainland South Africa. The cold air near 25° S is advected northwards ahead of the surface pressure ridge. Received July 19, 1999 Revised January 11, 2000     

江西省冬季气温异常与区域海温的关联

利用1960-2010年江西省81个台站月平均气温观测资料和NOAA全球月平均海表温度资料(ERSST-V3),分析了江西省冬季气温异常与海温异常的相互联系,并运用超前-滞后相关分析和奇异值分解(SVD)方法初步探讨了关键区海温异常之间的相互作用.结果表明:①影响江西省冬季气温异常的海温关键区和关键时段分别为同期印度洋(10°S～20°N,54°～90°E)、同期西北太平洋(20°～40°N,120°～180°E)和前期8-9月北大西洋中部(24°～44°N,20°～60°W)海域;②西北太平洋关键区暖水年预示暖冬年好于印度洋区,而印度洋区冷水年预示冷冬年稍好于西北太平洋区,冬季西北太平洋与印度洋海温异常可以修正前期8-9月北大西洋中部海温异常对江西省冬季气温的影响.     

Mid-Holocene to present-day evolution of the Indian monsoon in transient global simulations

The low-frequency evolution of Indian rainfall mean-state and associated interannual-to-decadal variability is discussed for the last 6000 years from a multi-configuration ensemble of fully coupled global transient simulations. This period is marked by a shift of Indian Summer Monsoon Rainfall (ISMR) distribution towards drier conditions, including extremes, and a contraction of the rainy season. The drying is larger in simulations with higher horizontal resolution of the atmosphere and revised land surface hydrology. Vegetation–climate interactions and the way runoff is routed to ocean modulate the timing of the monsoon onset but have negligible effects on the evolution of seasonal rainfall amounts in our modeling framework in which carbon cycling is always active. This drying trend is accompanied by changes in ISMR interannual-to-decadal variability decreasing over north and south India but increasing over central India (20°–25° N). The ISMR interannual-to-decadal variability is decomposed into six physically consistent regimes using a clustering technique to further characterize its changes and associated teleconnections. From 6 to 3.8 kyr bp, the century-to-century modulations in the frequency of occurrence associated to the regimes are asynchronous between the simulations. Orbitally-driven trends can only be detected for two regimes over the whole 6–0 kyr bp period. These two regimes reflect increased influence of ENSO on both ISMR and Indian Ocean Dipole as the inter-hemispheric energy gradient weakens. Severe long-term droughts are also shown to be a combination of long-term drying and internally generated low-frequency modulations of the interannual-to-decadal variability.

     

Stratospheric zonal wind and temperature in relation to summer monsoon rainfall over India

Summary  The interannual variability of the Indian summer monsoon (June–September) rainfall is examined in relation to the stratospheric zonal wind and temperature fluctuations at three stations, widely spaced apart. The data analyzed are for Balboa, Ascension and Singapore, equatorial stations using recent period (1964–1994) data, at each of the 10, 30 and 50 hPa levels. The 10 hPa zonal wind for Balboa and Ascension during January and the 30 hPa zonal wind for Balboa during April are found to be positively correlated with the subsequent Indian summer monsoon rainfall, whereas the temperature at 10 hPa for Ascension during May is negatively correlated with Indian summer monsoon rainfall. The relationship with stratospheric temperatures appears to be the best, and is found to be stable over the period of analysis. Stratospheric temperature is also significantly correlated with the summer monsoon rainfall over a large and coherent region, in the north-west of India. Thus, the 10 hPa temperature for Ascension in May appears to be useful for forecasting summer monsoon rainfall for not only the whole of India, but also for a smaller region lying to the north-west of India. Received July 30, 1999 Revised March 17, 2000