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

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

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.     

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.     

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     

Intraseasonal SST-precipitation relationship and its spatial variability over the tropical summer monsoon region

The SST-precipitation relationship in the intraseasonal variability (ISV) over the Asian monsoon region is examined using recent high quality satellite data and simulations from a state of the art coupled model, the climate forecast system version 2 (CFSv2). CFSv2 demonstrates high skill in reproducing the spatial distribution of the observed climatological mean summer monsoon precipitation along with its interannual variability, a task which has been a conundrum for many recent climate coupled models. The model also exhibits reasonable skill in simulating coherent northward propagating monsoon intraseasonal anomalies including SST and precipitation, which are generally consistent with observed ISV characteristics. Results from the observations and the model establish the existence of spatial variability in the atmospheric convective response to SST anomalies, over the Asian monsoon domain on intraseasonal timescales. The response is fast over the Arabian Sea, where precipitation lags SST by ~5 days; whereas it is slow over the Bay of Bengal and South China Sea, with a lag of ~12 days. The intraseasonal SST anomalies result in a similar atmospheric response across the basins, which consists of a destabilization of the bottom of the atmospheric column, as observed from the equivalent potential temperature anomalies near the surface. However, the presence of a relatively strong surface convergence over the Arabian Sea, due to the presence of a strong zonal gradient in SST, which accelerates the upward motion of the moist air, results in a relatively faster response in terms of the local precipitation anomalies over the Arabian Sea than over the Bay of Bengal and South China Sea. With respect to the observations, the ocean–atmosphere coupling is well simulated in the model, though with an overestimation of the intraseasonal SST anomalies, leading to an exaggerated SST-precipitation relationship. A detailed examination points to a systematic bias in the thickness of the mixed layer of the ocean model, which needs to be rectified. A too shallow (deep) mixed layer enhances (suppress) the amplitude of the intraseasonal SST anomalies, thereby amplifying (lessening) the ISV and the active-break phases of the monsoon in the model.     

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     

Influence of ENSO and of the Indian Ocean Dipole on the Indian summer monsoon variability

Indian summer monsoon (ISM) variability is forced from external factors (like the El Niño Southern Oscillation, ENSO) but it contains also an internal component that tends to reduce its potential for predictability. Large-scale and local monsoon indices based on precipitation and atmospheric circulation parameters are used as a measure of ISM variability. In a 9-members ensemble of AMIP-type experiments (with same boundary SST forcing and different initial conditions) their potential predictability is comparable using both local and large-scale monsoon indices. In the sample analyzed, about half of more predictable monsoon years coincide with El Niño and/or positive Indian Ocean Dipole (IOD) events. Summer monsoon characteristics during ENSO and IOD years are analyzed through composites computed over a three years period (i.e. one year before and one year after the event peak) to investigate the mutual relationship between the events lagged in time. The connection between ISM and IOD is mostly confined in the summer and autumn, while that with ENSO is stronger and extends more in time. In the coupled model results the IOD influence on the monsoon is large, even because in the model IOD events are intense and easily reproduced due to a strong air-sea feedback in the eastern side of the basin. Monsoon seasons preceding or following an El Niño or a La Niña event are not exactly symmetric, even in terms of their biennial character. In most of the cases, both in reanalysis and model, El Niño and positive IOD events tend to co-occur with larger anomalies either in the Indo-Pacific ocean sector or over India, while La Niña and negative IOD do not. From the observed record, the ENSO-IOD correlation is positive strong and significant since mid-60s and it may correspond with either strong or weak ENSO-monsoon relationship and with strong or weak IOD-monsoon relationship. A main difference between those periods is the relationship between Indian monsoon rainfall and SST in other ocean basins rather than the Indo-Pacific sector alone.     

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

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

Pacific Ocean sea-surface temperature variability and predictability of rainfall in the early and late parts of the Indian summer monsoon season

For central India and its west coast, rainfall in the early (15 May–20 June) and late (15 September–20 October) monsoon season correlates with Pacific Ocean sea-surface temperature (SST) anomalies in the preceding month (April and August, respectively) sufficiently well, that those SST anomalies can be used to predict such rainfall. The patterns of SST anomalies that correlate best include the equatorial region near the dateline, and for the early monsoon season (especially since ~1980), a band of opposite correlation stretching from near the equator at 120°E to ~25°N at the dateline. Such correlations for both early and late monsoon rainfall and for both regions approach, if not exceed, 0.5. Although correlations between All India Summer Monsoon Rainfall and typical indices for the El Ni?o-Southern Oscillation (ENSO) commonly are stronger for the period before than since 1980, these correlations with early and late monsoon seasons suggest that ENSO continues to affect the monsoon in these seasons. We exploit these patterns to assess predictability, and we find that SSTs averages in specified regions of the Pacific Ocean in April (August) offer predictors that can forecast rainfall amounts in the early (late) monsoon season period with a ~25% improvement in skill relative to climatology. The same predictors offer somewhat less skill (~20% better than climatology) for predicting the number of days in these periods with rainfall greater than 2.5?mm. These results demonstrate that although the correlation of ENSO indices with All India Rainfall has decreased during the past few decades, the connections with ENSO in the early and late parts have not declined; that for the early monsoon season, in fact, has grown stronger in recent decades.     

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。     

Increasing trend of northeast monsoon rainfall over the equatorial Indian Ocean and peninsular India

Peninsular India and Sri Lanka receive major part of their annual rainfall during the northeast monsoon season (October–December). The long-term trend in the northeast monsoon rainfall over the Indian Ocean and peninsular India is examined in the vicinity of global warming scenario using the Global Precipitation Climatology Project (GPCP) dataset available for the period 1979–2010. The result shows a significant increasing trend in rainfall rate of about 0.5 mm day^?1 decade^?1 over a large region bounded by 10 °S–10 °N and 55 °E–100 °E. The interannual variability of seasonal rainfall rate over peninsular India using conventional rain gauge data is also investigated in conjunction to the Indian Ocean dipole. The homogeneous rain gauge data developed by Indian Institute of Tropical Meteorology over peninsular India also exhibit the considerable upward rainfall trend of about 0.4 mm day^?1 decade^?1 during this period. The associated outgoing longwave radiation shows coherent decrease in the order of 2 W?m^?2 decade^?1 over the rainfall increase region.     

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     

The Summer Monsoon Onset over the Tropical Eastern Indian Ocean： The Earliest Onset Process of the Asian Summer Monsoon

The onset process of the tropical eastern Indian Ocean (TEIO) summer monsoon (TEIOSM) and its relationship with the cross-equatorial flows are investigated via climatological analysis. Climatologically, results indicate that the earliest onset process of the Asian summer monsoon occurs over the TEIO at pentad 22 (April 15–20). Unlike the abrupt onset of the South China Sea (SCS) summer monsoon, the TEIOSM onset process displays a stepwise advance. Moreover, a close relationship between the TEIOSM development and the northward push of the cross-equatorial flows over 80–90E is revealed. A difference vorticity center, together with the counterpart over the southern Indian Ocean, constitutes a pair of difference cyclonic vortices, which strengthens the southwesterly wind over the TEIO and the northerly wind to the west of the Indian Peninsula from the end of March to late May. Therefore, the occurrence of the southwesterly wind over the TEIO is earlier than its counterpart over the tropical western Indian Ocean, and the cross-equatorial flows emerge firstly over the TEIO rather than over the Somali area. The former increases in intensity during its northward propagation, which provides a precondition for the TEIOSM onset and its northward advance.     

印度洋偶极子与中国东部夏季降水的年代际变化关系

采用1951—2012年GPCP、中国160站台站降水资料及NOAA海表温度资料,分析了中国东部夏季降水及热带印度洋偶极子(IOD)的年际变化特征,以及两者的年代际变化关系。结果表明,中国东部夏季降水主要呈现两种模态分布,即"+-+"三极型和"-+"偶极型。并且在1953—1973年和2002—2012年中国东部夏季降水分别存在准2 a和4 a的震荡周期,年际变化明显。相关性分析发现,夏季IOD时间序列与中国东部夏季降水场的第三模态所对应的时间序列场呈负相关关系,且通过了信度为0.05的显著性检验,说明夏季IOD与中国东部夏季降水第三模态相关性较好。     

江淮夏季降水异常与西印度洋地区大气环流异常的关系

运用NCEP/NCAR再分析资料和中国气候中心整编的160站月平均降水资料应用经验正交函数、线性相关分析等,分析了江淮地区夏季降水异常特征及其与西印度洋区域大气环流年际异常关系的变化及其可能的机理。结果表明:当500 hPa中纬度低槽活动偏多(少),西太平洋副热带高压偏强(弱),东亚夏季风偏强(弱)时,江淮地区降水偏多(少)。进一步分析还发现西印度洋上空的垂直环流与江淮夏季降水存在较好的关系,但这种年际异常之间的联系受到背景场的影响明显:1979—1993年西印度洋垂直上升运动与江淮夏季降水的变化趋势基本相反,两者线性相关系数为-0.43;1994—2010年两者的变化趋势基本一致,相关系数达0.71。即当西印度洋地区存在环流异常下沉(上升)时,西太平洋副热带高压通常异常减弱东退(增强西伸),副热带季风减弱(增强),有利于雨带偏南(北)。因此,在西太平洋副热带高压和副热带季风年代际偏强(弱)阶段,西印度洋环流与江淮夏季降水呈负(正)相关。