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

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

A wind tunnel study of flows over idealised urban surfaces with roughness sublayer corrections

Variation of soil moisture during active and weak phases of summer monsoon JJAS (June, July, August, and September) is very important for sustenance of the crop and subsequent crop yield. As in situ observations of soil moisture are few or not available, researchers use data derived from remote sensing satellites or global reanalysis. This study documents the intercomparison of soil moisture from remotely sensed and reanalyses during dry spells within monsoon seasons in central India and central Myanmar. Soil moisture data from the European Space Agency (ESA)—Climate Change Initiative (CCI) has been treated as observed data and was compared against soil moisture data from the ECMWF reanalysis-Interim (ERA-I) and the climate forecast system reanalysis (CFSR) for the period of 2002–2011. The ESA soil moisture correlates rather well with observed gridded rainfall. The ESA data indicates that soil moisture increases over India from west to east and from north to south during monsoon season. The ERA-I overestimates the soil moisture over India, while the CFSR soil moisture agrees well with the remotely sensed observation (ESA). Over Myanmar, both the reanalysis overestimate soil moisture values and the ERA-I soil moisture does not show much variability from year to year. Day-to-day variations of soil moisture in central India and central Myanmar during weak monsoon conditions indicate that, because of the rainfall deficiency, the observed (ESA) and the CFSR soil moisture values are reduced up to 0.1 m³/m³ compared to climatological values of more than 0.35 m³/m³. This reduction is not seen in the ERA-I data. Therefore, soil moisture from the CFSR is closer to the ESA observed soil moisture than that from the ERA-I during weak phases of monsoon in the study region.

     

Sensitivity study on the role of Western Ghats in simulating the Asian summer monsoon characteristics

The Advanced Research Weather Research and Forecasting (AR-WRF) model is used to study the influence of Western Ghats situated along the west cost of peninsular India in the mean characteristics of the Asian summer monsoon (ASM) through numerical simulations. A control simulation (CTRL) is carried out using 11-year (2000–2010) mean initial and lateral boundary conditions from the ERA-Interim reanalysis to simulate the mean atmospheric features of the ASM. The Modern-Era retrospective analysis for research and applications (MERRA) data along with the Tropical Rainfall Measuring Mission (TRMM, 3B42 daily rainfall) data are used to validate the CTRL simulation. The simulated dynamical features and precipitation characteristics during the ASM period agree well with the MERRA reanalysis and TRMM observations. In order to examine the role of Western Ghats on the mean characteristics of the ASM, a sensitivity simulation (NoWG) is carried out with orography reduced to surface over a domain bound between 5°–28°N and 72°–90°E, keeping all other conditions unchanged. This sensitivity analysis showed an enhancement in the low level monsoon flow over the Indian Ocean and peninsular India in the absence of Western Ghats. The prominent up-draft over the west coast of peninsular India observed in the CTRL simulation also decrease in the absence of Western Ghats. The simulated rainfall show a considerable decrease over the west coast and an enhancement over the east coast of peninsular India in the absence of Western Ghats. These simulations clearly depict the importance of Western Ghats in the circulation dynamics and rainfall features during the ASM period.     

印度季风的年际变化与高原夏季旱涝

根据NCEP／NCAR再分析资料和海表面温度距平资料,分析了西藏高原夏季降水5个多、少雨年春、夏季印度洋850hPa、200hPa合成风场和合成海温场,发现多、少雨年前期与同期印度洋高、低空风场和海温场均存在明显差异,主要表现为高原夏季降水偏多(少)年印度夏季风偏强(弱),在850hPa合成风场上印度半岛维持西(东)风距平,西印度洋—东非沿岸为南(北)风距平,夏季阿拉伯海区和孟加拉湾出现反气旋(气旋)距平环流;200hPa合成风场上印度半岛维持东(西)风距平,南亚高压偏强(弱),索马里沿岸为南(北)风距平。印度夏季风异常与夏季印度洋海温距平的纬向分布型有密切联系。当夏季海温场出现西冷(暖)东暖(冷)的分布型时,季风偏强(弱),高原降水普遍偏多(少)。相关分析指出,索马里赤道海区的风场异常与高原夏季降水的关系最为密切,在此基础上我们定义了一个索马里急流越赤道气流指数,用它识别高原夏季旱涝的能力较之目前普遍使用的印度季风指数有了明显的提高。     

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.     

Dry spell characteristics over India based on IMD and APHRODITE datasets

Selected characteristics of dry spells and associated trends over India during the 1951–2007 period is studied using two gridded datasets: the Indian Meteorological Department (IMD) and the Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of the water resources (APHRODITE) datasets. Two precipitation thresholds, 1 and 3 mm, are used to define a dry day (and therefore dry spells) in this study. Comparison of the spatial patterns of the dry spell characteristics (mean number of dry days, mean number of dry spells, mean and maximum duration of dry spells) for the annual and summer monsoon period obtained with both datasets agree overall, except for the northernmost part of India. The number of dry days obtained with APHRODITE is larger for this region compared to IMD, which is consistent with the smaller precipitation for the region in APHRODITE. These differences are also visible in the spatial patterns of mean and maximum dry spell durations. Analysis of field significance associated with trends, at the level of 34 predefined meteorological subdivisions over the mainland, suggests better agreement between the two datasets in positive trends associated with number of dry days for the annual and summer monsoon period, for both thresholds. Important differences between the two datasets are noted in the field significance associated with the negative trends. While negative trends in annual maximum duration of dry spells appear field significant for the desert regions according to both datasets, they are found field significant for two regions (Punjab and South Interior Karnataka) for the monsoon period for both datasets. This study, in addition to providing information on the spatial and temporal patterns associated with dry spell characteristics, also allows identification of regions and characteristics where the two datasets agree/disagree.     

雅鲁藏布江流域夏季降水的年际变化及其原因

本文通过多套观测与再分析降水资料的比较,分析了雅鲁藏布江流域夏季降水的特征,从水汽含量与水汽输送的角度检验了雅鲁藏布江水汽通道的特点,研究了流域夏季降水的年际变化及其原因。分析表明:（1）该流域夏季降水大值位于雅鲁藏布江出海口至大峡谷一带,观测中流域平均降水可达5.8 mm d-1。不同资料表现的降水空间分布一致,但再分析降水普遍强于观测,平均为观测的2倍左右。（2）该流域夏季的水汽主要来自印度洋和孟加拉湾的偏南暖湿水汽输送,自孟加拉湾出海口沿布拉马普特拉河上溯至大峡谷,即雅鲁藏布江水汽通道。水汽收支诊断表明,夏季流域南部（即水汽通道所在处）是水汽辐合中心,流域平均的辐合约9.5 mm d-1,主要来自风场辐合与地形坡度的贡献。（3）不同再分析资料表现的流域降水和水汽分布特征总体一致,但量值差异较大。NCEP（美国国家环境预报中心）气候预报系统再分析资料CFSR、日本气象厅再分析资料JRA-25较欧洲中期天气预报中心再分析ERA-Interim资料更适于研究该流域（青藏高原东南部）的水汽特征,因为后者给出的流域降水和水汽偏强。（4）近30年该流域夏季降水无显著趋势,以年际变率为主。年际异常的水汽辐合（约为气候态的35.4%）源自异常西南风导致的局地水汽辐合（纬向、经向辐合分别贡献了16.5%、83.5%）,地形作用很小。流域夏季降水的年际变化是由印度夏季风活动导致的异常水汽输送造成的,其关键系统是印度季风区北部的异常气旋（反气旋）式水汽输送。     

Pattern characteristics of Indian monsoon rainfall using principal component analysis (PCA)

In the present study the Principal Component Analysis (PCA) is used to determine the dominant rainfall patterns from rainfall records over India. Pattern characteristics of seasonal monsoon rainfall (June–September) over India for the period 1940 to 1990 are studied for 68 stations. The stations have been chosen on the basis of their correlation with all India seasonal rainfall after taking the ‘t’ Student distribution test (5% level). The PCA is carried out on the rainfall data to find out the nature of rainfall distribution and percentage of variance is estimated. The first principal component explains 55.50% of the variance and exhibits factor of one positive value throughout the Indian subcontinent. It is characterized by an area of large positive variation between 10°N and 20°N extending through west coast of India. These types of patterns mostly occur due to the monsoon depression in the head Bay of Bengal and mid-tropospheric low over west coast of India. The analysis identifies the spatial and temporal characteristics of possible physical significance. The first eight principal component patterns explain for 96.70% of the total variance.     

Simulation of the variability and extremes of daily rainfall during the Indian summer monsoon for present and future times in a global time-slice experiment

In this study the simulation of the variability and extremes of daily rainfall during the Indian summer monsoon for the present-day and the future climate is investigated. This is done on the basis of a global time-slice experiment (TSL) with the ECHAM4 atmospheric general circulation model (GCM) at a high horizontal resolution of T106. The first time-slice (period: 1970–1999) represents the present-day climate and the second (2060–2089) the future climate. Moreover, observational rainfall data from the Global Precipitation Climatology Project (GPCP, 1997–2002) and rainfall data from the ECMWF re-analysis (ERA, 1958–2001) are considered. ERA reveals serious deficiencies in its representation of the variability and extremes of daily rainfall during the Indian summer monsoon. These are mainly a severe overestimation of the frequency of wet days over the oceans and in the Himalayas, where also the rainfall intensity is overestimated. Further, ERA shows unrealistically heavy rainfall events over the tropical Indian Ocean. The ECHAM4 atmospheric GCM at a horizontal resolution of T106, on the other hand, simulates the variability and extremes of daily rainfall in good agreement with the observations. The only marked deficiencies are an underestimation of the rainfall intensity on the west coast of the Indian peninsula and in Bangladesh, an overestimation over the tropical Indian Ocean, due to an erroneous northwestward extension of the tropical convergence zone, and an overestimation of the frequency of wet days in Tibet. Further, heavy rainfall events are relatively strong in the centre of the Indian peninsula. For the future, TSL predicts large increases in the rainfall intensity over the tropical Indian Ocean as well as in northern Pakistan and northwest India, but decreases in southern Pakistan, in the centre of the Indian peninsula, and over the western part of the Bay of Bengal. The frequency of wet days is markedly increased over the tropical Indian Ocean and decreased over the northern part of the Arabian Sea and in Tibet. The intensity of heavy rainfall events is generally increased in the future, with large increases over the Arabian Sea and the tropical Indian Ocean, in northern Pakistan and northwest India as well as in northeast India, Bangladesh, and Myanmar.     

Atmospheric circulation characteristics during some El-Nino years in relation to Indian summer monsoon rainfall

Summary Based on observed rainfall data of India Meteorological Department (IMD), correlation coefficients (CCs) have been computed between Indian summer monsoon rainfall (ISMR) and sea surface temperature (SST) anomalies over different Nino regions and standardised pressure difference between Tahiti and Darwin. Significant positive CCs are found between the Southern Oscillation Index (SOI) in winter and subsequent June rainfall over India. Concurrent with and subsequent to Indian summer monsoon, SOI shows significant positive CC with the mean rainfall of July to September (JAS). Significant negative CCs are found between JAS mean rain and the concurrent and following SST anomalies over Nino-3.4 region. On the basis of these correlations, it is proposed that the entire period of summer monsoon from June to September could be divided into two sub-periods such as: early summer (June) and mid-late summer (July to September) monsoon for prediction of ISMR in the extended range.In order to examine the characteristics of atmospheric circulation during some El-Nino years, divergent flow at 200hPa and omega field at 500hPa based on NCEP/NCAR reanalysis have been studied in detail. Major significant southward shift of upper level divergent field from India are related to El-Nino and this shift may be responsible for causing droughts during several El-Nino years over India. Also vertical wind fields at 500hPa show sinking motion over large parts of India and west Pacific and ascending motion over southern Indian Ocean, central and eastern Pacific during major drought years.     

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.     

Intercomparison of CRA-Interim Precipitation Products with ERA5 and JRA-55

By using the hourly data from surface meteorological stations in China, the 3-hour precipitation data from CRA-Interim (Chinese Reanalysis-Interim), ERA5 (ECMWF Reanalysis 5) and JRA-55 (Japanese Reanalysis-55) are compared, both on the spatial-temporal distributions and on bias with observation precipitation in China. The results show that: (1) The three sets of reanalysis datasets can all reflect the basic spatial distribution characteristics of annual average precipitation in China. The simulation of topographic forced precipitation in complex terrain by CRA-interim is more detailed, while CRA-interim has larger negative bias in central and East China, and larger positive bias in southwest China. (2) In terms of seasonal precipitation, the three sets of reanalysis datasets overestimate the precipitation in the heavy rainfall zone of spring and summer, especially in southwest China. CRA interim’s location of the rain belt in the First Rainy Season in South China is west by south, the summer precipitation has positive bias in southwest and South China. (3) All of the reanalysis datasets can basically reflect the distribution difference of inter-annual variation of drought and flood, but the overall the CRA-Interim generally shows negative bias, while the ERA5 and JRA-55 exhibit positive bias. (4) For the diurnal variation of precipitation in summer, all the reanalysis datasets perform better in simulating the daytime precipitation than in the night, and bias of CRA-interim is less in southeast and northeast than elsewhere. (5) ERA5 generally performs the best on the evaluation of quantitative precipitation forecast, the JRA-55 is the next, followed by the CRA-Interim. CRA-Interim has higher missing rate and lower threat score for heavy rains; however, at the level of downpour, the CRA-Interim performs slightly better.     

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     

Impact of MJO on the intraseasonal variation of summer monsoon rainfall over India

The summer monsoon rainfall over India exhibits strong intraseasonal variability. Earlier studies have identified Madden Julian Oscillation (MJO) as one of the most influencing factors of the intraseasonal variability of the monsoon rainfall. In this study, using India Meteorological Department (IMD) high resolution daily gridded rainfall data and Wheeler?CHendon MJO indices, the intra-seasonal variation of daily rainfall distribution over India associated with various Phases of eastward propagating MJO life cycle was examined to understand the mechanism linking the MJO to the intraseasonal variability. During MJO Phases of 1 and 2, formation of MJO associated positive convective anomaly over the equatorial Indian Ocean activated the oceanic tropical convergence zone (OTCZ) and the resultant changes in the monsoon circulation caused break monsoon type rainfall distribution. Associated with this, negative convective anomalies over monsoon trough zone region extended eastwards to date line indicating weaker than normal northern hemisphere inter tropical convergence zone (ITCZ). The positive convective anomalies over OTCZ and negative convective anomalies over ITCZ formed a dipole like pattern. Subsequently, as the MJO propagated eastwards to west equatorial Pacific through the maritime continent, a gradual northward shift of the OTCZ was observed and negative convective anomalies started appearing over equatorial Indian Ocean. During Phase 4, while the eastwards propagating MJO linked positive convective anomalies activated the eastern part of the ITCZ, the northward propagating OTCZ merged with monsoon trough (western part of the ITCZ) and induced positive convective anomalies over the region. During Phases 5 and 6, the dipole pattern in convective anomalies was reversed compared to that during Phases 1 and 2. This resulted active monsoon type rainfall distribution over India. During the subsequent Phases (7 and 8), the convective and lower tropospheric anomaly patterns were very similar to that during Phase 1 and 2 except for above normal convective anomalies over equatorial Indian Ocean. A general decrease in the rainfall was also observed over most parts of the country. The associated dry conditions extended up to northwest Pacific. Thus the impact of the MJO on the monsoon was not limited to the Indian region. The impact was rather felt over larger spatial scale extending up to Pacific. This study also revealed that the onset of break and active events over India and the duration of these events are strongly related to the Phase and strength of the MJO. The break events were relatively better associated with the strong MJO Phases than the active events. About 83% of the break events were found to be set in during the Phases 7, 8, 1 and 2 of MJO with maximum during Phase 1 (40%). On the other hand, about 70% of the active events were set in during the MJO Phases of 3 to 6 with maximum during Phase 4 (21%). The results of this study indicate an opportunity for using the real time information and skillful prediction of MJO Phases for the prediction of break and active conditions which are very crucial for agriculture decisions.     

Role of cumulus parameterization schemes in simulating heavy rainfall episodes off the coast of Maharashtra state during 28 June–4 July 2007

Indian summer monsoon gives on an average 250 cm of rainfall due to mesoscale/synoptic scale systems over west coast of India; now-a-days, MM5 model plays a very crucial role in simulating such heavy rainfall episodes like Mumbai (India) on 26 July 2005, which caused devastation through flash floods. The main aim of this study is to simulate such heavy rainfall episodes using three different cumulus parameterization schemes (CPS) namely Kain–Fritsch-1, Anthes–Kuo and Grell and to compare their relative merits in identifying the characteristics of mesoscale systems over 14 stations in coastal Maharashtra state during 28 June–4 July 2007. MM5 control experiment results are analysed for the fields of mean sea level pressure, wind, geopotential height at 850 hPa and rainfall with the above schemes. It is interesting to note that Kain–Fritsch-1 scheme simulates heavy rainfall amount of 48 cm for an observed rainfall of 51 cm in 24 h. The Grell scheme underestimates heavy rainfall episodes, while the Anthes–Kuo scheme is found to over predict rainfall on both temporal and spatial scales. The reason for better performance of KF-1 scheme may be due to inclusion of updrafts and downdrafts. Later the simulated rainfall quantities at 14 stations over study region are validated with both 3B42RT and observed rain gauge data of India Meteorological Department (IMD) and the results are promising. Finally, for the heavy rainfall prediction cases, the best threat score is at 0.25 mm threshold for three CPSs. Thus, this study is a breakthrough in pointing out that the KF-1 experiment has the best skill in predicting heavy rainfall episodes.     

Excitation of low-level jet as seen by GOES (I-O) satellite off the Somali coast

The intensification of a low-level jet off the Somali coast, as observed through GOES (I-O) satellite during In-dian summer monsoon 1979 has been studied. Excitation of Low-level cross-equatorial flow in the western Indian ocean results from an interaction between extratropical perturbations moving eastward across the South African-Malgassy region of the Southern Hemisphere. This excitation occurs 2-3 days after the first appearance of a northward propagation cold front across the South African-Malgassy region. Intensification of cross-equatorial flow is followed by an increase in rainfall activity along the west coast of India after 3-4 days. The study reveals that this association can be used to forecast an increase in rainfall activity along the west coast of India 5-7 days in advance.     

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     

Interannual and long-term variability in the North Atlantic Oscillation and Indian Summer monsoon rainfall

Summary The interannual and decadal scale variability in the North Atlantic Oscillation (NAO) and its relationship with Indian Summer monsoon rainfall has been investigated using 108 years (1881–1988) of data. The analysis is carried out for two homogeneous regions in India, (Peninsular India and Northwest India) and the whole of India. The analysis reveals that the NAO of the preceding year in January has a statistically significant inverse relationship with the summer monsoon rainfall for the whole of India and Peninsular India, but not with the rainfall of Northwest India. The decadal scale analysis reveals that the NAO during winter (December–January–February) and spring (March–April–May) has a statistically significant inverse relationship with the summer monsoon rainfall of Northwest India, Peninsular India and the whole of India. The highest correlation is observed with the winter NAO. The NAO and Northwest India rainfall relationship is stronger than that for the Peninsular and whole of India rainfall on climatological and sub-climatological scales.Trend analysis of summer monsoon rainfall over the three regions has also been carried out. From the early 1930s the Peninsular India and whole of India rainfall show a significant decreasing trend (1% level) whereas the Northwest India rainfall shows an increasing trend from 1896 onwards.Interestingly, the NAO on both climatological and subclimatological scales during winter, reveals periods of trends very similar to that of Northwest Indian summer monsoon rainfall but with opposite phases.The decadal scale variability in ridge position at 500 hPa over India in April at 75° E (an important parameter used for the long-range forecast of monsoon) and NAO is also investigated.With 4 Figures     

Impact of domain size on the simulation of Indian summer monsoon in RegCM4 using mixed convection scheme and driven by HadGEM2

In this study, a smaller domain over India alone and a larger South Asia (SA) domain have been used in the Regional Climate Model version 4.2 (RegCM4.2) to examine the effect of the domain size on the Indian summer monsoon simulations. These simulations were carried out over a period of 36 years at 50 km horizontal resolution with the lateral boundary forcings of the UK Met Office Hadley Centre Global Circulation Model Version 2.0. Results show that the Indian summer monsoon rainfall is significantly reduced when the domain size for the model integration is reduced from SA to the Indian domain. In case of SA domain simulation, the Equitable Threat Scores have higher values in case of very light, light and moderate rainfall events than those in case of the Indian domain simulation. It is also found that the domain size of model integration has dominant impact on the simulated convective precipitation. The cross-equatorial flow and the Somali Jet are better represented in the SA simulation than those in the Indian domain simulation. The vertically integrated moisture flux over the Arabian Sea in the SA domain simulation is close to that in the NCEP/NCAR reanalysis while it is underestimated in the Indian domain simulation. It is important to note that when RegCM4.2 is integrated over the smaller Indian domain, the effects of the Himalayas and the moisture advection from the Indian seas are not properly represented in the model simulation and hence the monsoon circulation and associated rainfall are underestimated over India.     

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